In order to establish the formation patterns of the Co–Mg oxide system, samples with different Co:Mg ratios and heat treatment temperatures were synthesized and studied. Study of the sam-ples confirmed the phase transition of MgxCo2–xO4 spinels into corresponding solid solutions at 800–900 °C. The similarity of formation patterns for different compositions is shown. The rock-salt oxide in low-temperature samples is an anion-modified paracrystalline phase that forms a “true” solid solution only upon spinel decomposition. TPR profiles of decomposed Co3O4 spinel show surface Co3O4 peaks and a wide peak corresponding to well-crystallized CoO, while par-tial Co3O4 TPR up to 380 °C results in dispersed and amorphous CoO. High-temperature non-stoichiometric samples are poorly reduced, indicating their low oxygen reactivity. Spinel reoxidation after heat treatment to 1100 °C by calcination at 750 °C showed complete regenera-tion for MgCo2O4–Co3O4 samples and its absence in case of an excess of MgO relative to stoi-chiometry. Based on the data obtained, it can be concluded that the processes governing the formation of Co–Mg oxide systems are determined by both Co:Mg ratio and the heat treatment conditions, potentially providing the possibility of fine tuning for specific catalytic processes.

A techno-economic model was developed to investigate the influence of components on the system costs of redox flow batteries. Sensitivity analyses were carried out based on a example of a 10 kW/120 kWh vanadium redox flow battery system and the costs of the individual components were analyzed. Particular consideration was given to the influence of material costs and resistances of bipolar plates and energy storage media as well as voltages and electric currents. Based on the developed model it was possible to formulate statements about the targeted optimization of existing battery systems and general aspects for future developments of redox flow batteries.

The electrical percolation of alternating current through two-phase polyethylene/graphite composite electrodes with different contents of graphite microparticles immersed in aqueous KCl solutions has been studied. Above the graphite content of the first percolation threshold, the electrochemical impedance response of this electrode is associated with an equivalent circuit of resistance Ru in series with a constant phase element CPE. An insulator material+conductive filler model is proposed in which the electroactive surface is considered as the intersection of the percolation cluster through the solid and the cluster associated with the interfacial region. CPE is analyzed assuming a distribution of micro-capacitors of the graphite particles in contact with the dielectric solution and inside the dielectric polymeric phase.

Demand for environmentally friendly types of energy is growing all over the world, which naturally increases the intensity of work on the production of hydrogen-containing fuel mixtures. Steam reforming of methanol is one of the most effective areas of research, as it is a process with low energy consumption. The results of steam reforming of methanol on the catalysts prepared by solution combustion synthesis (SCS) and impregnation by moisture capacity are presented. Investigation of the activity of Cu-Ce-Al catalysts of different composition was carried out for production of hydrogen and comparison of SCS with traditional impregnation method. Methanol conversion reaches 99%, while the selectivity of H2 was 88%, at 500 °C. It was found that CuAl2O4 spinel formation is due to substitution of Al3+ with Cu2+ Ce3+ cations. A consequence CuAl2O4 and CeAlO3 lattice parameters increase because of difference in ionic radius of Al3+ (0.53 Å) and Cu2+ (0.73 Å), Ce3+ (1.07 Å). Advantages of SCS catalysts in steam reforming of methanol were shown. The aim of this research is to develop a new catalyst for conversion of methanol into hydrogen containing fuel mixtures, which will further promote the organization of a new era of environmentally friendly energy-saving production methods.

The current state-of-the-art does not provide a universal and rapid method of determining the state of health (SOH) of a battery or a supercapacitor without carefully examining the degradation of hundreds of full charge/discharge cycles. Lithium-ion batteries, sodium-ion batteries and supercapacitors of different cell chemistries were studied by impedance spectroscopy during lifetime tests. Faradaic and capacitive charge storage are distinguished by the relationships between stored electric charge and capacitance. For batteries, impedance spectroscopy is best applicable in the flat region of the voltage-charge curve. An approximately linear correlation between pseudocapacitance and Ah capacity is observed as long as overcharge and deep discharge are avoided. The correct calculation of quantities related to complex impedance and differential capacitance is outlined – which may also be useful as an introductory text and tutorial for newcomers to the field. Novel diagram types are proposed for the purpose of instant performance and failure diagnosis of batteries and supercapacitors.

Two ferrocene derivatives, namely, 1,2-(tetramethylene)-ferrocene and 1,2,1’,2’-bis(tetramethylene)-ferrocene, were synthesized in a four-step reaction sequence starting from ferrocene. Friedel-Craft acylation of ferrocene with succinic anhydride gave mono- or bis(3-carboxypropinoyl)ferrocene depending on the stoichiometry of succinic anhydride. The reduction of the keto groups to methylene, followed by ring-closing using trifluoroacetic anhydride gave 1,2-(α-ketotetramethylene)-ferrocene or 1,2,1’,2’-bis(α-ketotetramethylene)ferrocene. The diastereomeric mixture of the latter diketones was separated by column chromatography, characterized by single-crystal X-ray analysis, and assigned their stereochemistry. Reduction of the keto groups to methylene under Clemmensen conditions gave homoannular mono- or bis(tetramethylene) ferrocene derivatives. The molecular structure of 1,2-(tetramethylene)-ferrocene revealed that the ipso carbon atoms of the cyclopentadienyl group are 0.023(3) Å farther away from Fe(II) compared to the remaining three carbon atoms. Both complexes exhibit lower half-wave oxidation potentials than ferrocene, possibly due to the electron-releasing effects of the tetramethylene bridges.

An electrochemical bioassay based on the rotating droplet electrochemistry by using electron transfer mediator was developed for the evaluation of a wide variety of pollutants such as antibiotics, heavy metals and pesticides in the water environment. Ferricyanide was used as electron transfer mediator for obtaining the catalytic response of Escherichia coli. The electrochemical response of E.coli was measured via hydrodynamic chronoamperometry in a microdroplet on a screen-printed carbon electrode (SPCE). The constructed electrode system successfully evaluate the catalytic response of E.coli solution in presence of ferricyanide. The assay for antibiotic toxicity on E.coli was carried out. The EC50 for ampicillin, sulfamonomethoxine, chlorotetracycline, tetracycline and oxytetracycline valuated by the pre-incubation method were 0.26, 0.77, 5.25, 18.5, 19.0 µM, respectively. The toxicity order was ampicillin > sulfamonomethoxine > chlorotetracycline > tetracycline>oxytetracycline. The proposed method can be used to evaluate the antibiotic toxicities in different real sample, such as pond water, powder and raw milk. Recoveries were found in the range 90 and 99%. The developed methods do not require additional incubation time to evaluate toxicity.

A novel catechol (CA) biosensor was developed by the immobilization of tyrosinase (Tyr) onto in situ electrochemical reduction graphene (EGR) on choline functionalized gold nanoparticals (AuNPs–Ch) film. The results of UV–visible spectra indicated that Tyr retained its original structure in the film. And electrochemical investigation of the biosensor showed a pair of well–defined, quasi–reversible redox peaks with E_pa= –0.0744V and E_pc= –0.114 V (vs. SCE) in 0.1 M, pH 7.0 sodium phosphate buffered saline at the scan rate of 100 mV/s. The transfer rate constant k_s was 0.66 s^–1. The Tyr–EGR/AuNPs–Ch showed a good electrochemical catalytic response for the reduction of CA, with the linear range from 0.2 to 270 μM and a detection limit of 0.1 μM (S/N= 3). The apparent Michaelis–Menten constant was estimated to be 109 μM.

8-Hydroxydeoxyguanosine (8-OHdG) was the most widely used oxidative stress biomarker of the free radical-induced oxidative damage product of DNA, which may allow a premature assessment of various diseases. This paper designed a label-free, portable biosensor device to direct detect 8-OHdG by plasma coupled electrochemistry on transparent and conductive indium tin oxide (ITO) electrode. We reported a flexible printed ITO electrode made from particle-free silver and carbon inks. After inkjet printing, the working electrode was sequentially assembled by gold nanotriangles (AuNTAs) and platinum nanoparticles (PtNPs). This nanomaterial-modified portable biosensor showed excellent electrochemical performance for 8-OHdG detection from 10 μg/mL to 100 μg/mL by our self-developed constant voltage source integrated circuit system. This work demonstrated a portable biosensor for simultaneously integrating nanostructure, electroconductivity, and biocompatibility to construct advanced biosensors for oxidative damage biomarkers. The proposed nanomaterial modified ITO-based electrochemical portable device was a potential biosensor to approach 8-OHdG point-of-care testing (POCT) in various biological fluid samples, such as saliva and urine samples.

Recent trends concerning hydrogen as a fuel of the future and problems related to its production, storage and utilization increase the demand for efficient technologies related to these problems. A large part of such technologies is related to application of advanced materials based on various complex oxides which are used as efficient catalysts for fuel transformation into hydrogen and syngas, materials for membranes with selective permeability for hydrogen and syngas production, components of solid oxide fuel cells/electrolyzers as well as many other applications in energy, electrochemistry and catalysis. Such materials are typically based on oxides and solid solutions with perovskite and fluorite structures or their derivatives. Attention is also paid to the materials based on spinel, apatite, mayenite, sheelite, fergusonite structures. The above-mentioned materials are continuously studied in order to modify and optimize their functional properties. On the other hand, other classes of materials (weberites, monazites, etc.) are recently discovered and considered as candidate materials for the aforementioned applications due to their specific functional properties or a great potential of their improvement. In this review, some of these materials are considered.

Multifunctional coatings based on Sn-Ni materials with and without titanium oxide nanoparticles (TiO2NPs) incorporation were prepared using the electrochemical deposition technique at 70°C. TiO2NPs were dispersed in the electrolyte bath, and their influence on both surface texture, crystalline phase, and properties was investigated. Various techniques such as X-ray phase analysis (XRD), scanning electron microscopy (SEM), and energy dispersive X-ray microanalysis (EDX) were used to characterize the prepared coatings. The anti-corrosion effectiveness of the coatings was assessed using potentiodynamic polarization curves and electrochemical impedance spectroscopy in an artificial sweat medium, while the bactericidal activity of the composite coatings (the ability to induce cell death) was evaluated in accordance with ISO 27447:2009 test. The influence of the TiO2NPs on the composition, structure and properties of the deposited coatings was established. Particular attention was paid to the relationship between the anticorrosive and bactericidal properties of the coatings and their structure and composition. The synergistic effect of the various properties was investigated and discussed.

This study employed High-Performance Liquid Chromatography coupled with Diode Array De-tector and Mass Spectrometry (HPLC-DAD-MS) to characterize bioactive compounds in olive leaf extracts. The analysis revealed a diverse metabolic profile, predominantly composed of tyrosol, flavonoids, and hydroxycinnamic acid. The antioxidant activity of the extracts demonstrated their efficacy, with variations observed between neutral and acidic pH conditions. Encapsulation was explored as a preservation method, successfully maintaining the integrity of phenolic compounds in both liquid and powdered forms. All four extracts have an undeniable antimicrobial effect. Moreover, the antibacterial activity tested on E. coli ATCC 25922 and S. aureus ATCC 25923 strains significantly improved post-encapsulation, particularly for the acidic pH extract. The findings suggest that encapsulation can potentially conserve and/or enhance the antimicrobial activity of olive leaf extract, paving the way for developing functional products with improved shelf life and nutritional properties. Further investigations are recommended to elucidate underlying mecha-nisms and optimize encapsulation processes to maximize the benefits of olive leaf extract in di-verse applications.

Materials based on platinum metals with very good catalytic activity were tested in the reduction of p–nitrophenol (pNP) to p–aminophenol (pAP). The majority of presented catalytic materials are based on the adsorption of p–nitrophenol on the surface of the catalyst simultaneously with molecular hydrogen, coming from sodium borohydride in an aqueous medium, which reduces it. In the present paper, a catalytic material based on osmium dispersed in n–decanol or n–dodecanol is presented, which also works as an emulsion membrane, for the absorption of p–nitrophenol and molecular hydrogen at the n–alcohol aqueous solution interface. The hydrogenation of p–nitrophenol is carried out in a reaction and separation column in which the acid receiving phase emulsion is dispersed in the osmium nanodispersion, in n–alcohols. This emulsion circulates from the base of the column to its upper part in co-current or counter-current with the source phase consisting of p–nitrophenol and sodium borohydride. Experiments show that the circulation of counter-current phases is superior to that in co-current, and the emulsion based on n–decanol is more efficient than the one based on n–dodecanol. The increase in the pH difference between the source and receiving phases leads to the increase in the conversion of p–nitrophenol to p–aminophenol. The efficiency of separation of the reaction product in the receiving phase is lower than the conversion at the same operating time. The apparent catalytic rate constant (kapp) of the new catalytic material based on the emulsion membrane with nanodispersion of osmium nanoparticles (0.1×10−3 for n–dodecanol and 0.9×10−3 for n-decanol) is lower by an order of magnitude compared to those based on adsorption on catalysts from platinum metal group. The advantage of the tested membrane catalytic material is that it extracts p–aminophenol in the acid receiving phase. The paper proposes a mechanism of the studied reduction system.

Some glucagon-like peptide-1 receptor agonists (GLP-1 RAs), first used in the treat-ment of type 2 diabetes mellitus (T2DM), have been approved for the treatment of obe-sity in patients with or without T2DM (liraglutide – LIR, semaglutide - SEM, and tir-zepatide - TIR). Social media had an important influence on the off-label use of GLP-1 RAs for obesity, especially for SEM. We analysed the Google queries related to SEM to assess people's interest in this drug. We also investigated the occurrence of adverse drug reactions (ADRs) by searching the EudraVigilance database (EV) for Individual Case Safety Reports (ICSRs) that reported SEM as the suspected drug and performed a descriptive and a disproportionality analysis. Data obtained for SEM were compared to other GLP-1 RAs. SEM had the highest proportions of searches on Google associated with the term “weight loss” and presented the lowest number of severe ADRs, but it also had the highest number of ICSRs reported in EV. Even though no unexpected safety issues have been reported for it until now, SEM has a high tendency for overdose reports. The most frequent off-label use was reported for SEM and TIR. In order to lower the ADRs’ risks, the off-label use should be reduced and carefully monitored.

This review aims to describe the role of Limbic System-Associated Membrane Protein (LSAMP) in normal and pathophysiology and its potential implications in oncogenesis. We have summarized research articles reporting the role of LSAMP in the development of a variety of malignancies such as clear cell renal cell carcinoma, prostatic adenocarcinoma, lung adenocarcinoma, osteosarcoma, neuroblastoma, acute myeloid leukemia, and epithelial ovarian cancer. We also examine current understandings of how defects in LSAMP gene function may contribute to oncogenesis. Finally, this review discuss-es the implications of future LSAMP research and clinical applications. Recent Findings LSAMP has been originally described as a surface adhesion glycoprotein expressed on cortical and subcortical neuronal somas and dendrites during the development of the limbic system. It is categorized as part of the IgLON immunoglobulin superfamily of cell-adhesion molecules and is involved in regulating neurite outgrowth and neural synapse generation. LSAMP is both aberrantly expressed and implicated in the development of neuropsychiatric disorders due to its role in the formation of specific neuronal connections within the brain. Additionally, LSAMP has been shown to support brain plasticity via the formation of neuronal synapses and is involved in modulating the hypothalamus in anxiogenic environments. In murine studies, loss of LSAMP expression was associated with decreased sensitivity to amphetamine, increased sensitivity to benzodiazepines, increased hyperactivity in new environments, abnormal social behavior, decreased aggressive behavior, and decreased anxiety. Findings have suggest-ed that LSAMP plays a role in attuning serotonergic activity as well as GABA activity. Given its importance to limbic system development, LSAMP has also been studied in the context of suicide. In malignancies, LSAMP plays a significant role as a putative tumor suppressor, the loss of which leads to more aggressive phenotypes and mortality from metastatic disease. Loss of the LSAMP gene facilitates epithelial-mesenchymal transition, or EMT, where epithelial cells lose adhesion and gain the motile properties associated with mesenchymal cells. Additionally, LSAMP and the function of the RTK pathway have been implicated in tumorigenesis through the modulation of RTK expression in cell membranes and the activation of second messenger pathways and β-catenin.

Cisplatin (CDDP) remains a key drug for patients with advanced bladder cancer (BC), despite the emergence of new therapeutic agents. Identifying factors contributing to treatment resistance to CDDP is crucial. The acidity of the tumor microenvironment has been reported to be associated with treatment resistance and poor prognosis across various cancer types. Our objective was to investigate the effects of an acidic environment on BC cells and elucidate the mechanisms behind CDDP resistance. Our findings show that BC cells cultured in acidic conditions developed resistance to cisplatin as acidity increased. Notably, CDDP administered to BC cells in a pH 6.0 environment required twice the concentration compared to pH 7.5 to achieve equivalent toxicity. Using chloroquine and navitoclax, we identified the involvement of Bcl-2 and LC3B pathways in the acquisition of CDDP resistance under acidic conditions. Western blot analysis revealed that the activation of Bcl-2 and XIAP expression appears to inhibit both apoptotic and autophagic cell death. These results suggest that alleviating the acidity of the tumor microenvironment in clinical settings might enhance BC sensitivity to CDDP.

A novel approach to enhance Additive Friction Stir Deposition (AFSD) is presented through the integration of Multimodal Retrieval Augmented Generation (RAG). AFSD which is a solid-state metal additive manufacturing process characterized by its complexity, necessitating advanced analytical tools. A multimodal RAG system is implemented, integrating textual, and visual data. The methodology involves text extraction using LangChain's PyPDFLoader, followed by chunking and embedding generation via Google's Generative AI model. ChromaDB is utilized for vector storage and efficient information retrieval. The system, powered by Google's Gemini large language model, demonstrates proficiency in generating detailed explanations of friction-based deposition processes, identifying manufacturing techniques from visual data, and evaluating material microstructures. Information from multiple sources is synthesized to produce context-aware responses. Process control, quality assurance, and decision-making in AFSD are significantly enhanced by this approach. The system's capabilities are illustrated through the analysis of various friction-based deposition techniques and microstructure evaluation.

We present a novel derivation of fundamental physical laws by solving a maximization problem on the Shannon entropy of all possible measurements relative to a system's initial state, subject to specific linear constraints. By introducing appropriate linear constraints, we create probability measures that adhere to particular underlying mathematical structures, enabling us to recover various physical theories within a unified framework. Specifically, imposing a U(1) group constraint leads to the emergence of quantum mechanics by incorporating complex probability amplitudes and interference effects. Extending this approach, we apply a Spinc(3,1) group constraint to derive a relativistic quantum theory that naturally includes Lorentz symmetry. Remarkably, in 3+1 dimensions, this method uniquely results in the metric tensor of general relativity through a double-copy mechanism applied to the Dirac current. Furthermore, it inherently incorporates the SU(3)xSU(2)xU(1) gauge symmetries of the Standard Model, providing a unified description of fundamental interactions. These findings highlight the power of entropy maximization under linear constraints to reveal the deep connections between probability theory and the mathematical structures underlying fundamental physics, offering new insights into the emergence of spacetime dimensions and symmetry structures in our universe.

Batched network coding (BNC) is a practical realization of random linear network coding (RLNC) designed for reliable network transmission in multi-hop networks with packet loss. By grouping coded packets into batches and restricting the use of RLNC within the same batch, BNC resolves the issue of RLNC that has high computational and storage costs at the intermediate nodes. A simple and common way to apply BNC is to fire and forget the recoded packets at the intermediate nodes, as BNC can act as an erasure code for data recovery. Due to the finiteness of batch size, recoding strategy is a critical design that affects the throughput, the storage requirements and the computational cost of BNC. The gain of the recoding strategy can be enhanced with the aid of a feedback mechanism, however the utilization and development of this mechanism is not yet standardized. In this paper, we investigate a multi-phase recoding mechanism for BNC. In each phase, recoding depends on the amount of innovative information remained at the current node after the transmission of the previous phases was completed. Relevant information can be obtained via hop-by-hop feedback, then a more precise recoding scheme that allocates networking resources can be established. Unlike hop-by-hop retransmission schemes, the reception status of individual packets does not need to be known, and packets to be sent in the next phase may not be the lost packets in the previous phase. Further, due to the loss-tolerance feature of BNC, it is unnecessary to pass all innovative information to the next node. This study illustrates that multi-phase recoding can significantly boost the throughput and reduce the decoding time as compared with the traditional single-phase recoding approach. This opens new window in developing better strategies for designing BNC, rather than sending more batches in a blind manner.

This paper investigates a Local Strategy-Driven Multi-Agent Deep Deterministic Policy Gradient (LSD-MADDPG) method for demand-side energy management systems (EMS) in smart communities. Addressing critical challenges in EMS solutions such as data overhead, single-point failures, nonstationary environments, and scalability, the proposed LSD-MADDPG effectively harmonizes individual building needs with entire community energy management goals. By leveraging and sharing only strategic information among agents, the proposed approach demonstrates to optimize the EMS decision-making processes, while enhancing training efficiency and safeguarding data privacy - a critical concern in the community setting. The proposed LSD-MADDPG has proven to be capable of reducing energy costs and flattening community demand curve by coordinating indoor temperature control and electric vehicle charging schedules across multiple buildings. Comparative case studies reveal that LSD-MADDPG excels in both cooperative and competitive settings, aligning individual buildings’ energy management actions with overall community goals in a fair manner, highlighting its potential for future smart community energy management advancements.

Simulations of the pump response time refer to the determination of the time constant of the transient process when the flow and pressure change. The changes mentioned in the standards are precisely defined and prescribed by the "MIL-P-19692E" norms. The simulation showed that the time constants are within the permissible limits prescribed by these norms. The diagram shows the responses for the considered pump and for the case when the flow changes from Qn to Qmin and changes from Qmin to Qn. The time constants t1 and t2 are defined on the diagrams, with the parameters that the pump has. In addition, the standards define the pressure jump that occurs during the transient process as well as time constants. From the flow change diagram, it can be seen that the flow change is also very fast and takes place in time intervals shorter than 0.1 s. By evaluating the size of the time constants, t1 and t2, it can be concluded that they have a value below 0.05 s, which meets the regulations in that area. Also, the size of the jump pressure meets the regulations because it is only 1.2 M Pa above the nominal pressure.

The impact of climate change is undeniable: considering the significant carbon footprint of surgical activity, there is an urgent need to pursue sustainability in the operating room as well. At the Breast Surgery Clinic of the IRCCS Ospedale Policlinico San Martino in Genoa, a prospective study was conducted from September 2023 to May 2024 to evaluate the effectiveness of a series of measures aimed at reducing the environmental impact in the operating room. 34 women affected by invasive breast cancer T1-2, cN0 underwent quadrantectomy and sentinel lymph node biopsy (SNLB): 17 according to a standard, high environmental impact approach; 17 according to a green approach based on the "5 R rule" (reduce, reuse, recycle, rethink, research). The implementation of measures such as the use of indocyanine green (ICG) for SNLB, the use of local anesthesia and intravenous sedation, the minimization of waste production, the use of reusable gowns, drapes and surgical instruments and the separate collection of non-infectious plastic waste resulted not only in a reduced environmental impact, but also in benefits for patients, who were spared a hospital admission the day before surgery, the administration of a radiotracer, and, in 58.8% of cases, an overnight stay. Considering the alarming data regarding the threat to our health, it is both possible and necessary to adopt virtuous behaviors in the operating room that reverse the current trend of emitting greenhouse gases.

Demand for livestock products in East Africa is anticipated to triple by 2050. Therefore, sustainable intensification of livestock production systems for increased productivity is necessary in line with minimal negative environmental consequences. An agronomic field experiment was set up at the International Livestock Research Institute in Nairobi, Kenya, and the effects of organic and inorganic soil amendments on greenhouse gas emissions (particularly N2O) from a Humic Nitisol planted with Brachiaria brizantha cv. xaraes were evaluated between October 2018 and August 2019. The treatments comprised mineral NPK fertilizer, Lablab intercrop, FYM, FYM-BC, Bioslurry, and control. Fertilizer treatments were applied at a rate of 45 kg N ha-1 following each harvest. GHG emissions were measured using the static vented chamber technique. Treatment and season significantly influenced daily N2O emissions. The lowest (4.51±3.30 µg N m-2 h-1) and highest (27.16±3.61 µg N m-2 h-1) mean N2O emissions were recorded under NPK and Control treatments during the short rains and dry seasons, respectively. Cumulative N2O emissions and the corresponding yield-scaled emissions were similar across all the treatments but varied significantly (p < 0.001) between the wet and dry seasons. Cumulative N2O emissions were 0.31±1.49, 0.33±1.47, 0.33±1.74, and 0.37±1.74, 0.38±2.3 and 0.42±1.81 Kg N ha-1 under FYM-BC, Lablab, NPK fertilizer, and FYM, Bioslurry and control treatments respectively. The corresponding yield-scaled emissions were also higher during the wet (0.23±1.16 g N kg-1 DM) than in the dry seasons (0.16±0.50 g N kg-1 DM). Higher (-21.86±4.47 mg CH4-Ch-1) CH4 uptake was recorded under the control treatment whereas the lowest (-2.69±17.97 mg CH4-Ch-1) uptake was recorded under Bioslurry (P < 0.01). Treatment and season exhibited individual effects on daily CO2 emissions (P < 0.001), with a significant interaction effect (P < 0.001). The highest (157.5±28.76 mg CO2-C m-2h-1) and lowest (44.33±8.37 mg CO2-C m-2h-1) CO2 emissions were recorded under Control and FYM treatments during the October 2018-January 2019 and January-March 2019 HD. Since the experiment was newly established via ploughing a field which had been used as a permanent pasture during previous years, did not expect considerable yield differences between treatments. Yet, it is interesting to see first effects of fertilizer amendments, pointing to their potential as climate-smart forage intensification strategies. The study established that Manure + biochar is a better strategy for forage soil amendments in mitigating soil N2O emissions.

Interferons (IFNs) are cytokines involved in the immune response with synergistic regulatory action. They are therapeutics for various viral and proliferative conditions, with proven safety and efficacy. Their clinical application presents difficulties due to the molecules' size, degradation, and pharmacokinetics. We developed a controlled release system for viral respiratory tract infections. A core-shell nanoparticle was prototyped, which hydrolyzed the shell (polyvinylpyrrolidone), releasing the active ingredients IFN-α and IFN-γ. The core (chitosan) degraded slowly, with a controlled release of IFN-α. The primary and rapid effect of the combination of interferons ensured an antiviral and immunoregulatory response from day one, induced by IFN-α and enhanced by IFN-γ. The multilayer design demonstrated an optimal toxicity profile. This formulation is an inhaled dry powder targeted for the non-invasive intranasal route. This prototype would ensure greater bioavailability, controlled release, fewer adverse effects, and robust biological action thanks to the simultaneous impact of both molecules.

Lidar and camera sensors are widely utilized in autonomous vehicles (AVs) and robotics due to their complementary sensing capabilities—lidar provides accurate depth information, while cameras capture rich visual data. However, effective fusion of these sensors requires precise calibration, which is often challenging due to the differences in sensing modalities. This paper presents a self-calibration algorithm based on Singular Value Decomposition (SVD) to address this problem. Singular Value Decomposition is a powerful matrix factorization technique that helps identify key calibration parameters by decomposing matrices into singular vectors and values, representing essential calibration data. Our method not only automates the calibration process but also provides a reliable mechanism for detecting calibration errors, ensuring long-term accuracy and robustness in sensor fusion. The algorithm simplifies deployment in real-world applications by eliminating the need for manual calibration or external targets. Experimental results show that our approach improves sensor alignment and fusion accuracy, making it particularly useful for AV and robotic systems where maintaining precise calibration is critical.

(1)Background: Evidence on the association between air pollution and the risk of exacerbations of chronic obstructive pulmonary disease (COPD) is scarce and inconsistent. We aimed to analyze the association between long-term exposure to particulate matter with a diameter of less than 2.5 µm (PM2.5) and nitrogen dioxide (NO2) and exacerbation of COPD (COPD-E) in Bogotá, Colombia; (2) Methods: Retrospective cohort study of 722 COPD patients in the AIREPOC program of the Colombian Pneumological Foundation between 2018 and 2021. Exposure to PM2.5 and NO2 was estimated for residential locations using the inverse squared distance weighted regression (IDWR) method. Hazard Ratios (HR) were calculated for the first COPD-E during follow-up using Cox models, adjusted for meteorological, demographic, and clinical variables; (3) Results: COPD-E was associated with long-term exposure to PM2.5 (HR:1.03, 95%CI: 1.02-1.05) and NO2 (HR:1.05, 95%CI: 1.03-1.07) controlling for the effect of quality of life, history of COPD-E, Forced Expiratory Volume in One Second (FEV1) pre-bronchodilator and exposure to solar radiation. An association was found between COPD-E and concentrations ≥ 25µg/m3 of NO2 (HR:1.49, 95%CI: 1.12-1.98) but not with concentrations ≥15 µg/m3 of PM2.5; (4) Conclusions: This study suggests that people with COPD exposed to higher concentrations of PM2.5 and NO2 had an increased risk of COPD-E. Solar radiation was also associated with an increased risk of COPD-E. The results highlight the importance of continuing efforts to reduce air pollution.

Neuropsychiatric disorders are worldwide public-health concern. Schizophrenia is one of the well-known neuropsychiatric disorders, which may affect millions globally. Maternal immune activation might be one of the key factor for the development of neuropsychiatric disorders. Previously, a mouse model of neuropsychiatric disorders has originally been made, in which poly-I:C, sodium dextran sulfate (DSS) and κ-carrageenan (CGN) were used for the maternal immune activation of mice. In the neuropsychiatric disorder mice, a significant link between biochemical changes of p62 and/or GLAST in the mouse brain and the alteration of experimental behaviors. Therefore, potential therapeutic study has been achieved for the development of effective treatment against neuropsychiatric disorders with using butyric acid, trehalose, piceid, and biochanin A. As a result, some of the combination with these orally available molecules could be effective for the improvement of behavioral alterations as well as biochemical changes of p62 and/or GLAST in the mouse brain. Importantly, the correlation between behavioral score and p62/GLAST protein expression has been again recognized. The significant correlation between pathological behavior and the biochemical alterations would contribute to develop further innovative therapeutics for vaious psychiatric disorders.

Chemosensory proteins (CSP) are found in the olfactory sensory organs (antennae and maxillary palps) and/or gustatory sensory organs (labellum and legs) and long been accepted to function through binding ‘odorants’. Yet, the same CSPs are also expressed in many tissues other than olfactory and gustatory organs, such as gut, brain, fat body, wing, epidermis, corpora allata, pheromone gland, prothoracic gland, etc. In this review, we suggested the rename “chemosensory protein (CSP)” to “4 Cysteines Soluble Protein (4CSP). To support our idea, we reviewed CSPs from several aspects: their primary sequences, existence of CSP in insects, hexapods, and bacteria, expression during development and in other tissues, evolution of CSP genes, genomic mining, their ancestral functions and lipoid binding, function outside the chemosensory/binding aspect, their intracellular function, and from structure to function. The scope of the review per se is broad, and this is especially true given the volume of data that has been gathered on CSP expressed in ways that are not consistent with the olfactory paradigm. We discuss the Mp10 story in aphids, our research on insecticide resistance, and other lipid transport and immunity-related processes. There is substantial evidence to support the non-chemosensory aspects of CSPs, which is where the majority of discussions lean. There are still very few, if any, statements outlining the aspects of CSPs’ chemosensory properties, specifically how they activate olfactory receptor neurons (ORNs). We present an analysis showing a stronger correlation between them and the actin complex family proteins, mucins, and translation initiation factors. An additional argument is the existence of CSPs outside of insects. Therefore, strong arguments in favor of renaming chemosensory proteins are becoming evident here, outweighing the drawbacks.

Objectives: To assess the role of soluble PD-L1 and PD-1 in combination with mRNA transcripts of PCA3, PSMA, AR genes in diagnostics of clinically significant prostate cancer (PCa). Methods: For 68 PCa patients, plasma sPD-L1 and sPD-1 were measured by ELISA method and the urinary PSMA, PCA3 and AR were tested using RT-qPCR. Results: PSMA and AR were iden-tified as the most reliable biomarkers for predicting clinically significant prostate cancer, with AUCs of 0.81 and 0.78, respectively. Additionally, the expression levels of PSMA and PCA3 were associated with the pT3 stage. Despite the diagnostic potential of mRNA transcripts alone, the ad-dition of sPD-L1 and sPD-1 significantly enhanced diagnostic accuracy. Combination doubled the specificity of PCA3 from 44.1% to 88.0%, compared to PCA3 alone. sPD-L1, sPD-1 and AR resulted in the best distinction between clinically significant and insignificant prostate cancer, achieving an AUC of 0.97, an accuracy of 0.95, a sensitivity of 100%, a specificity of 95%, revealing the potential of AR in distinguishing clinically significant PCa, more effectively than PSMA and PCA3. Our find-ings highlight the significant potential of sPD-1 in enhancing diagnostic accuracy when added to a triple gene panel, achieving an AUC of 0.90 compared to an AUC of 0.78 without sPD-1. This un-derscores the value of sPD-1, which has been less explored than sPD-L1 in cancer diagnostics. Con-clusions: sPD-L1 and sPD-1 has a potential to significantly enhance the accuracy of PCa diagnostics when added to the diagnostic panel, alongside PSMA, PCA3, and AR mRNA transcripts.

Background: Falls in older adults are prevalent and can result in an injury affecting their quality of life. Whether a fall is fatal or not, it has a high financial impact. Older adults with dementia are more likely to fall than their cognitively healthy counterparts, increasing their risk of serious injury or even death. This quality improvement project developed, implemented, and evaluated an evidence-based fall prevention bundle to reduce preventable falls in a long-term memory care unit.; Methods: The interventions that were implemented includes fall risk screening, physical exercise, vitamin D supplementation, purposeful hourly rounds, and post-fall huddles. Kurt Lewin’s force field analysis guided the project’s implementation. Nurses, healthcare providers, certified nursing assistants, restorative aides, and life enrichment staff from all shifts at a long-term memory care unit participated in the project. The participants implemented the evidence-based fall prevention bundle based on their scope of practice. They participated for 12 weeks. The frequency of falls was compared three months before, during, and after implementation. Paired t-test and independent samples t-test were used to analyze statistically significant differences between variables.; Results: Thirty staff members attended educational sessions, and 22 residents received interventions. Fall rates dropped 50% during the project's implementation but increased subsequently. The difference in the number of falls before, during, and after implementation was not statistically significant.; Conclusions: Staff working in a long-term care facility may help reduce fall rates using evidence-based interventions, but measures should be taken to sustain the initiative's implementation.

The use of probiotics has been gaining popularity in terms of inclusion into human diets over recent years. Based on properties exerted by these living organisms, several benefits have been elucidated and conferred to the host. Bacteria has been more commonly used in probiotic preparations, in comparison to yeast candidates, however, yeast exhibit several beneficial properties such as the prevention and treatment of diarrhoea, production of antimicrobial agents, prevention of pathogen adherence to intestinal sites, maintain microbial balance, modulation of the immune system, resistant to some antibiotics, amongst others. This review details the use of yeast organisms as biotherapeutics and has a special focus on production considerations and their formulation into different delivery formats.

Recent clinical trials using synthetic incretin hormones, glucagon-like peptide 1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP) receptor agonists have demonstrated that these treatments ameliorated many complications related to obesity, emphasizing the significant impact of body weight on overall health. Incretins are enteroendocrine hormones secreted by gut endothelial cells triggered by nutrient ingestion. The phenomenon that oral ingestion of glucose elicited much higher insulin secretion than intra-venous injection of equimolar glucose is known as incretin effect. This also alludes to the thesis that food intake is the root cause of insulin resistance. Amylin is co-expressed with insulin from the pancreas β-cells but does not have insulinotropic function. Amylin suppresses glucagon secretion, slowing gastric emptying, and suppressing the central nervous system (CNS) reward center leading to weight loss. However, amylin can self-aggregate and cause serious cytotoxicity and may cause β-cell apoptosis. Glucagon is secreted by the pancreatic α-cells and participates in glucose homeostasis in glucose-dependent manner. In hypoglycemia, glucagon increases blood glucose level by glycogenolysis and gluconeogenesis and inhibits glycogenesis in the liver. Some triple agonists in combination with glucagon and dual incretins are already being developed. These advances bring to the question “Are the benefits of these anti-obesity treatments sustainable?” Chronic agonism may decrease the number of receptors. Also, long-term stimulation may cause β-cell exhaustion and failure. Additionally, instead of endogenous control of the appetite, exogenous control of satiety and food intake may hinder the long-term sustainability of these treatments. We will discuss the incretins’ mechanism of action, challenges, and future directions.

Water desalination technology has emerged as a critical area of research, particularly with the advent of more cost-effective alternatives to conventional methods such as reverse osmosis and thermal evaporation. Given the vital importance of water for life and the scarcity of potable water for agriculture and livestock—especially in the Kingdom of Saudi Arabia—the capacitative deionization (CDI) method for removing salt from water is highlighted as the most economical choice compared to other techniques. CDI applies a voltage difference across two porous electrodes to extract salt ions from saline water. This study will investigate water desalination using CDI, utilizing a compact D.C. power source under 5 volts and a standard current of 2 amperes. We will convert waste materials like sunflower seeds, peanut shells, and rice husks into activated carbon through carbonization and chemical activation to improve its pore structure. Critical parameters for desalination, including voltage, flow rate, and total dissolved solids (TDS) concentration, have been established. The initial TDS levels are set at 2000, 1500, 1000, and 500 ppm, with flow rates of 38.2, 16.8, and 9.5 mL/min across various voltage settings of 1.5, 2, and 2.5 volts, applicable to both direct and inverse desalination methods. Results indicate that desalination processes function effectively at a flow rate of 9.5 mL/min, achieving a performance efficiency of 65%, while a voltage of 2.5 volts yields a performance level of 44%.

This study delves into the significant impact of Houthi insurgent activities on maritime traffic within the strategic Red Sea and Suez Canal routes, crucial conduits for global trade. It explores the correlation between regional instability, as exemplified by Houthi actions from 1st attack to a merchant vessel (November 19, 2023) to February 5, 2024, and alterations in maritime traffic patterns, alongside the operational efficiency of these vital maritime arteries. Employing descriptive statistics, qualitative, and geospatial analytical methods, the research examines recent trends in maritime traffic and incident reports, shedding light on the spatial and geopolitical challenges faced by one of the world's most critical trade routes. The findings reveal a marked decline in maritime activity in the Gulf of Aden and Suez Canal, attributed to security concerns stemming from Houthi attacks, with a significant shift towards alternative routes, notably around the Cape of Good Hope. This shift underscores the broader implications of regional instability on global trade dynamics and the critical nature of maintaining uninterrupted maritime flow. The study also highlights the economic ramifications, including increased operational costs and freight rates due to longer transit times and enhanced security measures. It concludes with a call for improved maritime security protocols and international cooperation to safeguard these strategic maritime pathways. This research contributes to the discourse on transport geography by quantifying the direct impacts of regional conflicts on maritime logistics and proposing strategies for future resilience, emphasizing the intertwined nature of global trade, security, and the urgent need for collective action in the face of evolving geopolitical challenges.

High-accuracy geolocation is crucial for high-resolution spaceborne SAR images. Most advanced SAR satellites have better theoretical geolocation accuracy than 1 meter but maybe unrealizable with less accurate external data, including the atmospheric parameters and the ground elevations. To investigate the actual SAR geolocation accuracy in common applications, we analyze the properties of different geolocation errors, propose a set of geolocation procedures, and conduct experiments on TerraSAR-X images and a pair of Tianhui-2 images. The results show that based on GNSS elevations, the geolocation accuracy is better than 1 meter for TerraSAR-X and 2 meters / 4 meters for the Tianhui-2 reference / secondary satellite. Based on the WorldDEM and the SRTM, an extra geolocation error of 2 and 4 meters will be introduced, respectively. By comparing the effectiveness of different tropospheric correction methods, we find that the GACOS mapping method has advantages in terms of resolution and computational efficiency. We conclude that the tropospheric error and the ground elevation error are the primary factors influencing the geolocation accuracy, and the key to improving accuracy is to use higher-accuracy DEMs. Additionally, we propose and validate a geolocation model for the Tianhui-2 secondary satellite.

The adversarial vulnerability of deep learning models is a critical issue that must be addressed to ensure the safe commercialization of AI technologies. Although numerous studies on adversarial defense methods are actively being conducted from various perspectives, most of them still provide limited robustness, and even the relatively trusted adversarial training is no exception. To develop more reliable defense methods, ongoing research exploring the properties and causes of adversarial vulnerabilities is essential. In this study, we focus on a hypothesis regarding the existence of adversarial examples: The adversarial examples represent low-probability “pockets” in the manifold. Assuming that the hypothesis holds true, we propose a method for generating perturbation: “mixed perturbation (MP)”, which aims at discovering diverse pocket samples in a defensive perspective. The proposed method generates perturbations by leveraging information from both the main task and auxiliary tasks in multi-task learning scenarios, combining them through random weighted summation. The generated mixed perturbation intends to maintain the primary directionality of the main task perturbation to improve the model’s main task recognition performance while introducing variability in the perturbation directions. We then utilize them for adversarial training to form more robust decision boundary. Through experiments and analyses conducted on five benchmark datasets, we validated the effectiveness of our proposed method.

Background/Objectives: Pulmonary diseases are common in patients with thoracic aortic aneurysm (TAA) and abdominal aortic aneurysm (AAA). Although high prevalences of chronic obstructive pulmonary disease and lung cancer (LC) are known, the prevalence of these and other pulmonary diseases regarding their relation to outcome of TAA and/or AAA are not determined. Methods: Pulmonary diseases present at aortic aneurysm (AA) diagnosis and follow-up periods and cause of death of 952 patients with TAA, AAA, or TAA+AAA (including thoracoabdominal AA) treated at our institution in Japan, were retrospectively analyzed. Cox regression analysis was used to investigate potential risk factors of mortality. Results: Mean patient age was 72.4 years, and median follow-up was 4.92 years. At diagnosis, 528 (55.5%) patients had pulmonary diseases, including emphysema without interstitial lung disease (ILD) or LC, LC, idiopathic pulmonary fibrosis (IPF) without LC, non-IPF ILD without LC, and interstitial lung abnormalities (ILAs) without LC in 250, 85, 65, 15, and 58 patients, respectively. During follow-up, LC and acute exacerbation (AE) of IPF developed in 50 and 12 patients, respectively. In 213 patients who died, there were 45 (21.1%) aortic disease-related deaths. Other causes of death included LC (27.7%), cardiovascular event (9.4%), pneumonia (5.6%), and interstitial lung disease (4.7%). In a multivariate Cox regression hazard model, age, larger maximum aneurysm diameter, and coexisting LC, IPF, or concomitant cancer were associated with poor prognosis. Conclusions: In patients with AA, not only age and aneurysm diameter but also coexisting LC and IPF were prognostic factors for mortality.

Cardiovascular disease (CVD) is the primary cause of mortality globally with a multifactorial etiology that involves epigenetics. Chromobox 3 (CBX3), the major isoform of heterochromatin protein 1, is involved in intricate epigenetic mechanisms affecting congestive heart failure. In patients with CVD affected by lung cancer risk, CBX3 exerts a sophisticated mechanism of action, suppressing the proliferation, migration, and formation of neointima in vascular smooth muscle cells (VSMCs) by affecting the Notch3 pathway, indicating a potential protective function against vascular remodeling and atherosclerosis. However, the broader impact of CBX3 on endothelial function, as well as its effects on monocyte/macrophage and lymphocyte infiltration and function within the arterial wall, remain poorly understood. Since very little is known so far, more definite research would be needed to reveal the fine mechanisms of CBX3 action, along with its relationship in molecular processes and prospects as a biomarker. Specifically, CBX3 biological features could be examined to gain a greater insight into CVD risks. This review outlines the role of CBX3 in mechanisms associated with CVD and feasibility for optimizing pre-existing therapy and developing new therapeutic strategies based on personalized medi-cine.

Accurate determination of an individual’s unique human leukocyte antigen (HLA) allele holds important significance in evaluating the risk associated with autoimmune and infectious diseases, such as human immunodeficiency virus (HIV) infection. Several allelic variants within the HLA system have been linked to either increased protection or susceptibility in the context of infectious and autoimmune diseases. This study aimed to determine the frequency and association of HLA alleles between people living with HIV (PLHIV) as the case group and HIV-uninfected Peruvian individuals with high-risk behavior of sexual transmission diseases as the control group. Whole exome sequencing (WES) was used to determine high-resolution HLA allelotypes using OptiType and arcasHLA tools. The HLA alleles present in HLA classes I (A, B, and C loci) and II (DPA1, DPB1, DQA1, DQB1 and DRB1 loci) were determined in a cohort of 59 PLHIV (cases) and 44 HIV-uninfected individuals (controls). The most frequent HLA alleles were A*02:01, DPB1*04:02 and DQB1*03:419 at 36%, 30% and 28% prevalence in general population. We found that C*07:01 (p = 0.0101; OR = 10.222, 95% IC: 1.40–74.55), DQA1*03:02 (p = 0.0051; OR = 5.297, 95% IC: 1.48–19.02) and DRB1*09:01 (p = 0.0119; OR = 4.788, 95% IC: 1.39–16.44) showed an association with susceptibility to HIV infection, while DQB1*03:419 (p = 0.0478; OR = 0.327, 95% IC: 0.11–0.96) was associated with protection from HIV infection. Our findings contribute to the knowledge of HLA allele diversity in the Peruvian population (around 70% South American indigenous ancestry), lay the groundwork for further valuable large-scale use of HLA typing and offer a novel association of HIV infection that is relevant to vaccine studies.

Wearing masks to protect against communicable diseases is an effective tool used in many coun-tries affected by the COVID-19 pandemic. Antibacterial activity, antibacterial efficiency, micro-bial purity and breathability properties of medical disposable masks are very important. Ag is most commonly applied to antimicrobial textiles, but several studies are known about Ag nano-particles. In this work three antimicrobial additives were used. One of them Rudolf GmBH's RUCO-BAC AGP with silver chloride (AgCl) active ingredient also has antimicrobial activity. Four compositions of the binders with antimicrobial additives were prepared and applied to one-layer nonwoven PP material using screen printing, knife over roll coating and laminating machine methods. The influence of the binder antimicrobial polymer coating on the breathabil-ity and antibacterial activity of the nonwoven PP material was evaluated. Results had showed that the composition of the polyacrylic acid binder Tubicoat Thickener LP had the least effect on their breathability and samples with the RUCO-BAC AGP formulation had showed the best an-timicrobial response. Therefore, further studies of the antimicrobial coating composition were performed using the binder Tubicoat Thickener LP and antimicrobial additives of different chemical nature and concentration - RUCO-BAC AGP, BI-OME AM10 and Nano Ag aqueous dis-persion. Based on the microbiological and air permeability results of the samples of the one-layer nonwoven material with coating, the samples of two-layers and three-layers of medical mask model were prepared. Microbiological studies have shown that three-layered medical mask model with RUCO-BAC AGP composition in the middle layer, in both sides of the model has antibacterial efficiency against three pathogens (E. Coli, K. Pneumoniae, an S. Aureus). The performance of this medical mask model has been found to meet requirements for type I medi-cal masks according to the EN 14863 standard. Study have shown that the microbial purity of the mask model is CFU/g

Forensic speaker recognition plays a key role in criminal investigations, providing important conclusions for the justice system. The mandatory use of protection masks during the COVID-19 pandemic has posed a challenge for forensic speaker recognition, as they act as voice barriers or filters. Although the pandemic has been declared over, analyzing their impact in forensic speaker recognition contributes to a better understanding of the use of coverings as a voice disguise technique. This study aims to evaluate the impact of two types of face masks on an automatic forensic speech recognition system. For this purpose, the Multilingual Forensic Voice Database (FMVD), developed under the CERTAIN-FORS project, funded by the European Union, was used. Comparisons were made between dialog speech samples and reading samples collected without a mask, with a surgical mask, and with an FFP2 mask for both sexes in eight different languages. The performance metrics equal error rate (EER) and cost of likelihood ratio (Cllr) were calculated and analyzed. The results show that the presence of face masks has an impact on the performance metrics. The effect observed varies according to the language spoken, the gender of the speaker, and the type of mask.

This review explores the intricate relationship between the microbiome and cancer metabolism, focusing on the Warburg effect—a shift where cancer cells rely on glycolysis for energy even in oxygen-rich environments. This metabolic reprogramming fuels tumor growth and alters the tumor microenvironment. Recent studies highlight the microbiome's influence on cancer metabolism, suggesting that microbial imbalances can either promote or hinder the Warburg effect. Microbiome alterations impact metabolic pathways, immune responses, and gene expression, which can accelerate or mitigate cancer progression. We examine how dysbiosis affects the Warburg effect and its implications for tumor growth, metastasis, and treatment resistance. Additionally, we discuss the potential of microbiome-targeted therapies, such as probiotics and fecal microbiota transplants, to modulate cancer metabolism. These interventions offer the possibility of reversing or controlling the metabolic shifts in cancer cells, enhancing the efficacy of traditional treatments like chemotherapy and immunotherapy. Despite promising developments, challenges remain in identifying key microbial species and pathways, as well as in validating microbiome-targeted therapies through large-scale clinical trials. Nonetheless, the intersection of microbiome research and cancer metabolism presents an exciting frontier for innovative therapies. This review offers a fresh perspective on cancer metabolism by integrating microbiome insights, highlighting the potential for interdisciplinary research to enhance our understanding of cancer progression and treatment strategies.

This scoping review explores the development and application of sustainability competence frameworks in secondary education globally, identifying key trends and challenges within the field. An initial sample of 2,659 peer-reviewed publications from 2003 to 2023 was subjected to a rigorous multi-stage screening process, refining the selection for in-depth analysis. Through qualitative clustering, the review identifies two primary perspectives on sustainability competencies. The first emphasizes transversal competencies, relevant across diverse educational settings, including national policies, global educational guidelines, various subject domains, and innovative teaching-learning approaches. The second perspective focuses on specific frameworks that address the cognitive, affective, and behavioral dimensions of sustainability. The review highlights a global consensus on the importance of key competencies such as critical thinking, systems thinking, and action competence, which are essential for preparing secondary students to tackle sustainability challenges. Additionally, it stresses the need for a holistic approach to competence development that integrates cognitive, affective, and behavioral aspects. Despite this consensus, the review reveals a research bias, with a predominance of studies from Europe, particularly Germany and Sweden, and calls for increased regional diversity and collaboration in future research.

Diabetic foot ulcers (DFUs) are a multifactorial pathophysiologic condition that occurs in patients with diabetes mellitus (DM). Approximately 9.1 to 26.1 million people are affected by DFUs annually. This condition can lead to progressive foot infections and, ultimately, foot amputation. Various microbes contribute to DFUs, including methicillin-resistant Staphylococcus. aureus, Pseudomonas aeruginosa, and Escherichia coli can form biofilms composed of complex matrices that create a protective shield around the microorganisms, enhancing their survival and resistance to treatment. Biofilm formation is a critical virulence factor directly associated with the onset and persistence of DFUs. It not only complicates the clinical management of these ulcers but also facilitates antibiotic resistance, necessitating a comprehensive approach to treatment. Effective management strategies must therefore target biofilm formation and the virulence factors associated with these pathogens. By addressing these elements, conventional antibiotics can be rendered more effective in treating diabetic foot ulcers. This approach aims not only to promote wound healing but also to address underlying causes and prevent further complications. This article seeks to highlight the significance of biofilm formation in DFUs, explore methodologies for studying this condition, as well as discuss demographic considerations and treatment options.

Avoiding global dependence on fossil oils, as well as improving the environmental impact during energy production, are factors that drive research into renewable energies. Considering lignocellulosic biomass residues as a raw material for gasification, a thermochemical process that converts lignocellulosic resources into synthesis gas (H2, CO, CH4 and CO2) is an alternative under study, due to its relatively low costs, high efficiency and the wide variety of applications of synthesis gas. Fortunately, there are still fields for its improvement and technological development. Gasification, for example: Different types of lignocellulosic biomass, such as sugarcane bagasse, wheat straw, pine sawdust or corn cob, differ in their physical, chemical and morphological properties, which can affect the characteristics of the gasification process. This work uses the methodology of generalized stoichiometry and mass and atomic balances in the gasification reactor, to predict the composition of syngas produced by gasification of both individual substrates and mixtures. The results provide useful information for the design and operation of gasification reactors, with their operating region between 2.0 bar and 4.5 bar, and 1024 K and 1224 K, understanding the effects of different types of biomasses, its humidity and molecular weight on the operation and performance of the process.

Posterior retroperitoneal laparoscopic adrenalectomy (PRLA) has emerged as a revolutionary minimally invasive technique for adrenal gland surgery, offering significant advantages over traditional open approaches. This narrative review aims to provide a comprehensive update on PRLA, focusing on its anatomical foundations, surgical technique, and clinical implications. We conducted an extensive review of the current literature and surgical practices to elucidate the key aspects of PRLA. The procedure leverages a unique "backdoor" approach, accessing the adrenal glands through the retroperitoneum, which necessitates a thorough understanding of posterior abdominal wall and retroperitoneal anatomy. Proper patient selection, meticulous surgical planning, and adherence to key technical principles are paramount for successful outcomes. The surgical technique is described step-by-step, emphasizing critical aspects such as patient positioning, trocar placement, and adrenal dissection. PRLA demonstrates reduced postoperative pain, shorter hospital stays, and faster recovery times compared to open surgery, while maintaining comparable oncological outcomes for appropriately selected cases. However, the technique presents unique challenges, including a confined working space and the need for surgeons to adapt to a posterior anatomical perspective. We conclude that PRLA, in the right clinical setting, offers a safe and effective alternative to traditional adrenalectomy approaches. Future research should focus on expanding indications and refining techniques to further improve patient outcomes.

Background: Somatic tinnitus (ST) is a type of tinnitus that is influenced by changes in somatosensory input from the cervical spine or temporomandibular area. Although traditional physiotherapy has been shown to reduce ST symptoms, in-clinic treatment is not always available, and adherence to home exercise programs is often low. This study aims to investigate the effectiveness of an app-based physiotherapy program to enhance compliance and availability of treatment for ST patients. Methods: This pilot randomized controlled trial included 38 adult patients with chronic somatic tinnitus. Participants were randomly assigned to a treatment group receiving a 9-week app-based cervical spine exercise program or a control group. The primary outcome was tinnitus distress measured using the Tinnitus Handicap Inventory (THI). As a secondary outcome we the Mini-Tinnitus Questionnaire (Mini-TQ). Results: Participants in the treatment group showed significant reductions in tinnitus distress, with a large effect size for both the THI and Mini-TQ (Cohen’s d = 1.71 and 1.02, respectively). The control group showed no significant changes. Conclusion: This study provides evidence that an app-based physiotherapy intervention is a feasible and effective treatment for ST. Further research with larger sample sizes, comparisons to traditional in-clinic treatments is needed to confirm these findings. Additional studies on personalized treatment might further improve the treatment.

Geography has been a fundamental determinant of economic development throughout history, influencing resource distribution, trade routes, climate conditions, and the spatial organization of economic activity. This essay delves into the multifaceted role of geography in shaping economic outcomes, drawing upon historical analyses and contemporary economic theories. By examining the historical origins of economic growth, the impact of geographical barriers and advantages, the influence of climate and natural resources, and the spatial distribution of industries, we explore how geographical factors contribute to international inequality and the divergent development trajectories of nations and regions. The discussion incorporates insights from seminal works, including Koyama and Rubin's "How the World Became Rich," Davis and Weinstein's analysis of the geography of economic activity, and Redding and Venables' exploration of economic geography and international inequality, among others. We also consider the roles of institutions, governance, and technology as mediating factors that can amplify or mitigate the influence of geography on economic development. By highlighting the interplay between geography and these mediating factors, the essay underscores the importance of tailored policy interventions that consider geographical realities. Understanding this complex relationship is essential for addressing global and regional disparities and formulating effective development strategies that leverage geographical advantages while mitigating disadvantages.

Arbutus unedo (strawberry tree) is a small Mediterranean tree capable of vigorous regrowth after disturbances like fire. Traditionally used for biomass fuel, its bark and branches hold potential for higher-value products through ecovalorisation into liquid mixtures that could replace petro-leum-based materials. This study aimed to explore the chemical composition of various compo-nents of Arbutus unedo and to produce a liquefied material from its internal (IB) and external bark (EB). Chemical compositions of internal and external bark were determined using TAPPI standards including ash, extractive content, lignin, and cellulose. Metal cations were analyzed by ICP. Liquefaction of bark was optimized in a PARR reactor, evaluating factors such as particle size, temperature, and time and the best polyols were monitored by FTIR-ATR. Polyurethane foams were made with internal and external bark liquefied materials by polymerization with isocyanate, a catalyst and water as blowing agent. Results showed that EB has a higher extractive and lignin content, while IB contains more cellu-lose. Liquefaction yields were higher for IB (74%) than EB (68%), with IB yielding polyols that produced stronger and more resilient foams. Mechanical properties of the foams were influenced by the NCO/OH ratio and catalyst levels. Overall, the internal bark demonstrated superior performance for foam production, highlighting its potential as an eco-friendly alternative to petroleum-derived materials.

In this study, we address key challenges in enhancing ruminant productivity across Ethiopia, Tanzania, Kenya, Uganda, Rwanda, and Burundi in eastern Africa. A critical focus is on improving access to forage seeds essential for cattle systems. Key factors such as ruminant population, feed deficits, and governmental priorities are examined. The primary challenge lies in inadequate access to affordable forage seeds, compounded by reluctance to invest in perceived expensive elite varieties. Many farmers rely on outdated planting materials, lacking purity and vigor. To overcome these barriers, our analysis stresses the urgency of transitioning to recently improved seed varieties through rigorous selection and breeding. Promoting domestic seed production within Africa is crucial to mitigate high import costs and logistical complexities like variety registration. A coordinated regional approach to seed production could enhance economic viability and foster widespread adoption of improved forages. Such initiatives align with governmental agendas for sector development, offering triple benefits: increased productivity, environmental gains through reduced methane emissions, and regional economic growth.

The present paper focuses on the practical application of software tools for calculating and verifying trusses systems. It covers externally and internally statically indeterminate trusses systems and compares results from two software tools. The MATLAB Simscape – Multibody simulation tool, specially designed for mechanical systems, is utilized to calculate the trusses system. The model is optimized to minimize errors compared to theoretical calculations. By using blocks, it is possible to build a system, including repeating parts quickly.

Optical communication systems pose significant challenges, including the effects of nonlinear noises. The nonlinearities, including Kerr-induced phase noise, become more problematic in m-QAM as the orden of the format increases becoming a highly densed set of data-symbols and therefore, requiring advanced signal processing for successful separation of symbols at the demodulation stage. Machine learning techniques have recently been applied to improve signal integrity in such scenarios. This paper explores the application of a spectral clustering algorithm adapted to deal with data streaming to mitigate nonlinear noise in long-haul optical channels dominated by nonlinear phase noise, offering a promising solution to a pressing issue. We demonstrate that the spectral clustering algorithm outperforms the k-means algorithm in the face of nonlinear phase noise in -90, -100, and -110 dBc/Hz scenarios at 1 MHz in a simulated 10 GHz symbol rate channel.

In the context of high frequency and intensity forest fires driven by future warming and drying climate, early detection and effective control of fires are extremely important to reduce losses. Satellite remote sensing, characterized by its broad observational scope and strong repeat observation capability, has become an important method for rapid monitoring of forest fires, replacing traditional means such as manual measurement and aerial photography. This paper addresses the misjudgments caused by solely relying on changes in infrared band brightness values and single-band separation in forest fire discrimination. It constructs the angle slope index ANIR based on the red band, near-infrared band and short-wave infrared band, Angle slope index AMIR based on the short-wave infrared band, mid-infrared band and far-infrared band, and angle slope index AMNIR based on the difference between the AMIR and ANIR, integrating the strong inter-band correlations and the reflectance characteristics of visible and short-wave infrared bands to simultaneously monitor smoke and fuel biomass changes in forest fires. To address the omissions caused by single-image fire discrimination algorithms, the paper constructs time-series Angle slope difference indices ∆ANIR and ∆AMIR. To address the different fire point discrimination thresholds caused by background difference in different time and space, the paper uses the decomposed three-dimensional OTSU(Maximum inter-class variance method) algorithm to calculate the segmentation threshold of the sub-regions constructed from the AMNIR data. The methods were validated using high temporal resolution meteorological satellite Himawari-8 and ground truth fire data from Hunan Province, China, from 2018-2019. The results show that the discrimination method based on the ASITR(Angle slope indices thresholds) method exhibits an accuracy of 0.88, a missed detection rate of 0.17, and an overall evaluation value of 0.85, which is 0.09 higher in accuracy and 0.03 higher in overall evaluation than the discrimination method based on infrared bands brightness values proposed by Feng et al. [1] (accuracy 0.79, missed detection rate 0.14, overall evaluation value 0.82); the method based on the FAMN_OTSU_ASITR (Fusion of Angle slope difference index (false) data, Decomposed three-dimensional OTSU adaptive threshold segmentation Algorithm and ASITR) exhibits an accuracy of 0.85, a missed detection rate of 0.08, and an overall evaluation value of 0.88, which is 0.09 lower in missed detection rate and 0.03 higher in overall evaluation as compared to the ASITR. The results demonstrate that the forest fire discrimination method based on Angle slope indices, Himawari-8 satellite data, and the decomposed OTSU adaptive threshold segmentation algorithm can improve the accuracy of forest fire discrimination and reduce errors in missed detections.

This study aimed to investigate the prevalence of cardiovascular disease (CVD) risk factors among Algerian aircrew, a population exposed to unique environmental and occupational stressors. By comparing these rates to the general population, we sought to identify specific health challenges faced by aircrew. Methods: A cross-sectional study was conducted on 154 Algerian aircrew participants. Prevalence rates for current smoking, hypertension, diabetes, and dyslipidemia were compared between the aircrew and a general population control group. Results: Our findings revealed significantly higher rates of current smoking among aircrew compared to the general population. Additionally, smoking, dyslipidemia, hypertension, and diabetes emerged as the most prevalent risk factors within the aircrew population. Conclusions: Despite the rigorous selection process for aircrew recruitment, our study confirms findings from previous literature, highlighting the high rate of normal qualifying examinations. The substantial sample size and homogeneous nature of the aircrew population enhance the reliability and generalizability of our conclusions. These findings underscore the importance of targeted interventions to mitigate CVD risk factors within this specific population, given the unique environmental and occupational factors associated with aircrew.

Secure Secret Sharing Single-Source Shortest Distance (SSSD) protocols, built on the Secure Multi-Party Computation (SMC) foundation, have emerged as a promising solution to address the secure distribution and management of sensitive secrets among multiple parties. This paper focuses on the crucial aspect of security proof within SSSD protocols based on SMC, aiming to provide a scientifically rigorous understanding of the formal verification process and the robust guarantees they offer. Through a comprehensive examination of the fundamental principles underpinning SMC and the specific design considerations unique to SSSD protocols, this paper meticulously explores the key components and intricate steps involved in constructing a rigorous security proof. Furthermore, it discusses the adversarial model, precise security definitions, cryptographic assumptions utilized within the proof, and sophisticated techniques and reductions to establish its validity. By means of a meticulous analysis of the security proof for SSSD protocols, this paper critically evaluates both the strengths and limitations of the proposed approach, offering valuable insights to inform future research and development within this significant domain of study.

The research identified challenges faced by teachers, suggested effective pedagogical strategies, and proposed practical recommendations to mitigate the negative impacts of ChatGPT in higher education. These strategies promote the ethical and responsible use of artificial intelligence, ensuring academic integrity. The article deeply analyzes pedagogical strategies to prevent plagiarism and promote academic integrity, offering a practical guide for educators on how to ethically integrate AI into their pedagogical practices. By filling a gap in the literature, the study contributes to the discussion on the ethical use of AI in education, offering evidence-based recommendations and fostering critical reflection on the impact of emerging technologies in the academic environment. The research highlights effective pedagogical strategies to mitigate the negative effects of ChatGPT, promoting an educational approach that prevents plagiarism and encourages the ethical use of AI. Through documentary analysis of scientific articles and data coding according to Bardin's methodology, patterns and trends were identified for the development of innovative pedagogical practices. The qualitative approach included a literature review and content analysis of articles published in the last five years. The results indicated that, although ChatGPT can personalize teaching and support content development, it also increases the risk of plagiarism and reduces students’ critical engagement. To combat these challenges, it is suggested to create personalized assessments, promote critical thinking, and use plagiarism detection tools. Continuous teacher training and the development of clear policies on the ethical use of AI are essential to ensure academic integrity and quality of learning.

The study examines the effects of transitioning to hydrogen production in the National Capital Region (NCR) and Palawan Province, Philippines, focusing on technology, environment, and stakeholder impact. The research, conducted through a July 2022 survey, aimed to assess public awareness, knowledge, risk perception, and acceptance of hydrogen and its environmentally friendly variant, green hydrogen, infrastructure. Disparities were found between urban NCR and rural Palawan, with lower awareness in Palawan. Safety concerns were highlighted, with NCR respondents generally considering hydrogen production safe, while Palawan respondents had mixed feelings, particularly regarding nuclear-based hydrogen generation. The report emphasizes the potential ecological advantages of hydrogen technology but highlights potential issues concerning water usage and land impacts. It suggests targeted public awareness campaigns, robust safety assurance programs, regional pilot projects, and integrated environmental plans to facilitate the seamless integration of hydrogen technology into the Philippines' energy portfolio. This collective effort aims to help the country meet climate action obligations, foster sustainable development, and enhance energy resilience.

Habitat fragmentation is often assumed to negatively impact species diversity because smaller, more isolated populations on smaller habitat patches are at a higher extinction risk. However, some empirical and theoretical studies suggest that landscapes with numerous small habitat patches may support higher species richness, although the circumstances remain elusive. We used an agent-based metacommunity model to investigate this and simulate landscapes of the same total area but diverse patch sizes. Our model, as generic and unbiased by specific assumptions as possible, aimed to explore which circumstances may be more conducive to supporting higher biodiversity. To this end, most parameters and behaviors were random. The model included generalized species traits, dispersal, and interactions to explore species richness dynamics in fragmented landscapes of distinct patch sizes. Our results show that landscapes with many small patches maintain higher species richness than those with fewer large patches. Also, the relationship between patch connectivity and species richness is more pronounced in landscapes with smaller patches. High connectivity in these landscapes may support species diversity by preventing local extinctions and facilitating recolonization. In contrast, connectivity is less significant in large-patch landscapes, where generalist species dominate. The findings highlight the complex interplay between patch size quality, connectivity, species traits, and diverse interactions among species in determining species richness. We suggest the patterns produced by the model represent null predictions and may be useful as a reference for a diversity of more specialized questions and predictions. These insights may also have specific implications for conservation strategies, suggesting that maintaining a mosaic of small, well-connected patches could enhance biodiversity in fragmented landscapes.

In this article, the diversity of mangrove and associate species with anticancer properties are reviewed. Information included their scientific names, synonyms, common names, families and life-forms. Their anticancer properties are documented with description on cancer cell types, effects and mechanisms. Mangroves are exclusive species confined to the mangrove habitat. Plants that occur in the coastal environment and also in mangroves are associates or non-exclusive species. In this article, species with anticancer properties are 25 mangrove species belonging to 17 genera and 11 families, and 31 associate species belonging to 28 genera and 20 families possess. Most reported mangrove species are Avicennia marina and Ceriops tagal with five and four studies, respectively. Associate species most reported are Talipariti tiliaceum or Hibiscus tiliaceus with five studies, followed by Anacardium occidentale, Artocarpus altilis, Ceriops manghas, Pluchea indica and Pongamia pinnata with four studies each. In the conservation of mangrove and associate species with anticancer properties, in in-situ conservation, species are protected in their natural surroundings as ecosystems (e.g., virgin jungle reserves and Ramsar sites) while in ex-situ conservation, species are protected outside their natural habitats (e.g., arboreta and botanical gardens).

Chronic mountain sickness (CMS) poses a significant health risk to individuals who rapidly ascend to high altitudes, potentially endangering their lives. Inorganic nanoparticles offer an effective means of transporting and delivering drugs, protecting nucleic acids from nuclease degradation, and mediating the expression of target genes in specific cells. These nanoparticles are almost non-toxic, easy to prepare and store, possess a large surface area, exhibit good biocompatibility and degradability, and maintain good stability. They can be utilized in the treatment of CMS to enhance the therapeutic efficacy of drugs. This paper provides an overview of the impact of inorganic nanomaterials on CMS, discussing their roles as nanocarriers and their potential in CMS treatment. It aims to present novel therapeutic strategies for the clinical management of CMS and summarizes the relevant pathways through which nanomaterials contribute to plateau disease treatment, providing a theoretical foundation for future clinical research.

The application of machine learning (ML) and remote sensing (RS) in soil and water conserva-tion has become a powerful tool. As analytical tools continue to advance, the variety of ML al-gorithms and RS sources has expanded, providing opportunities for more sophisticated analyses. At the same time, researchers are required to select appropriate technologies based on research objectives, topic, and scope of the study area. In this paper, we present a comprehensive review on the application of ML algorithms and RS that has been implemented to advance research in soil and water conservation. The key contribution of this review paper is that it provides an overview of current research areas within soil and water conservation and their effectiveness in improving prediction accuracy and resource management in categorized subfields, including biomass-vegetation, soil properties, hydrology and water resources, and wildfire management. We also highlight challenges and future directions based on limitations of ML and RS applica-tions in soil and water conservation. This review aims to serve as a reference for researchers and decision-makers by offering insights into the effectiveness of ML and RS applications in the field of soil and water conservation.

The interaction between gut-residing microorganisms plays a critical role in the pathogenesis of Crohn’s disease (CD), where microbiome dysregulation can alter immune responses leading to unresolved local inflammation. The aim of this study is to analyze the immunomodulatory properties of our recently developed probiotic+amylase blend in the SAMP1/YitFc (SAMP) mouse model of CD-like ileitis. Four groups of SAMP mice were gavaged for 56 days with: 1) probiotic strains + amylase (concentration: 0.25 mg/100 uL PBS); 2) only probiotics; 3) only amylase; PBS (vehicle-treated controls). Ilea were collected for GeoMx Digital Spatial Profiler (DSP) analysis and histological evaluation. Histology assessment for inflammation indicated a significantly reduced level of ileitis in mice administered probiotics+amylase blend. DSP analysis showed decreased abundance of neutrophils and increased abundance of dendritic cells, innate lymphoid cells and macrophages, with a significant enrichment of five intracellular pathways related to apoptosis, in probiotics+amylase treated mice. Increased apoptosis occurrence was confirmed by TUNEL assay. Our data demonstrate a beneficial role of the probiotic and amylase blend, highlighting an increased apoptosis of innate immunity-associated cell subsets, thus promoting the resolution of inflammation. Hence, we suggest that our recently developed probiotic blend may be a therapeutic tool to manage CD and therefore could be a candidate compound to be tested in clinical trials.

Customized wrist splints, particularly for upper extremity orthoses like wrist support braces, are commonly used across numerous clinical scenarios. However, the traditional process for producing personalized wrist splints is largely manual and highly dependent on the expertise of orthopedic specialists. This experience-based approach often leads to suboptimal outcomes, necessitating further refinement of the designs. Recent advancements in Additive Manufacturing (AM) have brought significant innovation to various industries, including orthopedics. This study aims to present a comprehensive methodology that integrates advanced design tools ,like 3D Scanning, with digital manufacturing techniques to produce tailored wrist splints. The produced hand brace aims to offer enhanced mechanical performance and comfort by precisely fitting an individual’s anatomy while minimizing material usage and weight. To achieve optimal design efficiency, the study explores the application of a Topology Optimization (TO) approach for design, while the manufacturing process utilizes Fused Deposition Modeling (FDM), an evolving technology within the Additive Manufacturing (AM) sector.

In this study, we successfully reproduced the PSB with laddered patterning, showcasing the predictive capability of the framework of Field Theory of Multiscale Plasticity (FTMP), without relying on ad hoc models, intricate mathematical models, or elaborate finite element discretization. The FTMP-incorporated CP-FEM simulation not only reasonably replicates the experimentally observed laddered morphology and PSB but also effectively simulates surface roughening and grooving, independent of vacancy formation and diffusion. These results highlight the significance of laddered morphology and set the stage for further investigations into the effects of vacancy formation in future studies in Part II. Leveraging incompatibility tensor-based degrees of freedom, the FTMP framework offers exceptional capabilities for natural modeling dislocation substructures typically overlooked in conventional approaches, positioning it as a transformative tool for advancing our understanding of the mechanism that dictate slip band-fatigue crack transitions.

Graph neural networks and graph convolutional networks are effective at representing complex relationships. We attempt to apply them to sports analytics by reviewing existing applications in sports. These methodologies leverage the inherent graph structure of sports data, capturing interactions among players, teams, and game events. By systematically examining various studies, we highlight how GNNs and GCNs can enhance performance prediction, player evaluation, and tactical analysis in sports. Our review emphasizes the unique advantages these models offer over traditional analytical approaches, particularly in their ability to account for the dynamic and interconnected nature of sports activities. We conclude by identifying potential areas for future research and application, suggesting that the integration of advanced graph-based techniques could significantly advance the field of sports analytics.

Magnetorheological elastomers (MREs) are in demand in the field of high-tech micro- and nano-industries such as biomedical applications and soft robotics due to their exquisite magneto-sensitive response. Among various MRE applications, programmable actuators are emerging as promising soft robots because of their combined advantages of excellent flexibility and precise controllability in a magnetic system. Here, we present the development of a magnetically programmable soft magnetic microarray actuators through field-induced injection molding using MREs, which consist of styrene-ethylene/butylene styrene (SEBS) elastomer and carbonyl iron powder (CIP). The ratio of the CIP/SEBS matrix is designed to maximize the CIP fraction based on a critical solids loading. Further, as part of the design of the magnetization distribution in micropillar arrays, the magnetorheological response of the molten composites is analyzed using the static and dynamic viscosity results for both the on- and off- magnetic states, which reflect the particle dipole interaction and subsequent particle alignment during field-induced injection molding process. To develop high aspect ratio soft magnetic microarray, X-ray lithography is applied to prepare the sacrificial molds with a height-to-width ratio of 10. The alignment of CIP is designed to achieve a parallel magnetic direction along the micropillar columns, and consequently, the micropillar arrays successfully achieve the uniform and large bending actuation of up to approximately 81˚ with an applied magnetic field. This study suggests that the injection molding process offers a promising manufacturing approach to build a programmable soft magnetic microarray actuator.

Clear cell renal cell carcinoma (ccRCC) is a highly aggressive subtype of renal cancer, often associated with poor prognosis and high mortality rates. In this study, we identified Nicotinamide N-methyltransferase (NNMT) as a key gene involved in the pathogenesis of ccRCC through RNA sequencing analysis of tumor and normal tissues from 14 patients. NNMT was among the top five upregulated genes, and its high expression was significantly correlated with reduced overall, progression-free, and disease-specific survival in patients, as well as advanced pathological stages and higher histologic grades. Gene ontology (GO) enrichment analysis revealed NNMT's role in biological processes such as signal transduction and immune response. Immune cell infiltration analysis indicated that high NNMT expression was associated with increased infiltration of activated NK cells and macrophages, while low expression correlated with a higher presence of regulatory T cells. Functional studies using siRNA-mediated NNMT knockdown in ccRCC cell lines demonstrated a significant reduction in cell proliferation, with further analysis revealing altered gene expression profiles related to cell adhesion and calcium ion binding. These findings suggest that NNMT not only plays a pivotal role in ccRCC aggressiveness but also may serve as a valuable prognostic biomarker and a potential therapeutic target for improving clinical outcomes in patients with this malignancy.

Objectives: The male urethra is a complex structure that plays a critical role in genitourinary health and function. Despite its importance, histological descriptions of the penile urethra, par-ticularly its epithelial components, remain incomplete. This study offers a comprehensive his-tological analysis of the penile urethra, focusing on the epithelium across distinct anatomical regions, including the glans, distal and proximal fossa navicularis, and spongy urethra. Meth-ods: Utilizing four human penile specimens, we employed various staining techniques to eluci-date the structural characteristics of these epithelial tissues. Results: Our findings reveal notable variations in epithelial composition, such as the presence of glycogen-rich cells in the distal fos-sa navicularis and the presence of mucous glands in the spongy urethra and proximal fossa na-vicularis. Additionally, we identified a previously underreported valvule-like structure in the distal fossa navicularis in two of the specimens. Conclusions: This study provides new insights into the histological organization of the penile urethra, offering critical reference data that can enhance our understanding of urethral pathologies and improve the outcomes of surgical inter-ventions, particularly in the context of tissue engineering and reconstructive surgery.

Introduction: The COVID-19 pandemic has triggered several challenges to mental health worldwide. Undergraduate medical students face considerable stress in their academic routines. Thus, there is a need to explore the implications of the mental health of undergraduate medical students during the COVID-19 pandemic. Objective: To review the global literature about anxiety and depression disorders in undergraduate medical students during the COVID-19 pandemic. Method: we developed an integrative literature review on the occurrence of anxiety and depression symptoms in undergraduate medical students during the COVID-19 pandemic. We assessed the results on the occurrence of anxiety and depression and the severity of symptoms in medical students during the COVID-19 pandemic using quantitative studies applying the GAD-7 questionnaire for anxiety or PHQ-9 for depression. Results: We reviewed 85 selected studies, and the results showed a significant prevalence of moderate and severe symptoms of anxiety and depression, with 28.2% of participants presenting scores ≥ 10 on the GAD-7 and 38.9% on the PHQ-9. Statistical analyses revealed associations between higher rates of anxiety symptoms in developing countries and data collected after the lockdown period in 2020, at the Pandemic lockdown. Conclusion: Our findings highlight the need for specific interventions to support the mental health of undergraduate medical students, critically in female students from developing countries during a Pandemic crisis.

The incremental sheet forming is born as an excellent alternative to other material forming pro-cedures to deform incrementally flat metal sheets into the preferred complex three-dimensional profile. The main characteristics of this process are its versatility and cost-effectiveness; in addition, it allows for reaching greater formability, compared to conventional sheet forming processes. Re-cently, its use has been extended to polymers and composites. The following review aims to present the current state of the art of the incremental sheet forming of polycarbonate, an outstanding en-gineering plastic, starting from the first studies on the feasibility of this process applied to polymers. Attention is given to the advantages, drawbacks and main applications of the incrementally formed polycarbonate sheets, as well as the influence of the process parameters and the toolpath strategies on features like formability, forming forces, deformation and failure mechanisms, geometric accu-racy, surface quality, etc. Moreover, new hybrid forming methods for process optimization are presented. Finally, a discussion is provided on the technical challenges and research directions for incremental sheet forming of polycarbonate, and more generally thermoplastics, in the future. Therefore, this review aims to offer an extensive overview of the incremental forming of polycar-bonate sheets, useful to academic and industrial researchers who work on this topic.

In the transition from traditional electrical energy generation with mainly linear sources to increasing inverter-based distributed generation, electrical power systems’ power quality requires new monitoring methods. Integrating a high penetration of distributed generation, which is typically located in medium- or low-voltage grids, shifts the monitoring tasks from the transmission to distribution layers. Compared to high-voltage grids, distribution grids feature a higher level of complexity. Monitoring all relevant buses is operationally infeasible and costly. State estimation methods provide knowledge about unmeasured locations by learning a physical system’s non-linear relationships. This article examines a new flexible, close-to-real-time concept of harmonic state estimation using synchronized measurements processed in a neural network. A physics-aware approach enhances a data-driven model, taking into account the structure of the electrical network. An OpenDSS simulation generates data for model training and validation. Different load profiles for both training and testing were utilized to increase the variance in the data. The results of the presented concept demonstrate high accuracy compared to other methods for harmonic orders 1 to 20.

The physiological impact of walking in nature was quantified via continuous heart rate variabil-ity (HRV), pre- and post-walk saliva cortisol measures, and self-reported mood and mindfulness scores for N=17 participants who walked “The Green Road” at Walter Reed National Military Medical Center in Bethesda, Maryland. For N=15 of the participants, HRV analysis revealed two main groups: group 1 individuals who had a 104% increase (mean) in root mean square standard deviation (RMSSD) and 47% increase (mean) in standard deviation of NN values (SDNN) indi-cating an overall reduction in physiological stress from walking the Green Road, and group 2 in-dividuals who had a decrease (mean) of 42% and 31% in these respective HRV metrics signaling an increase in physiological stresses. Post-walk self-reported scores for vigor and mood disturb-ance were more robust for the Green Road than for a comparable urban road corridor and showed that higher HRV during the walk was associated with improved overall mood. Saliva cortisol was lower after taking a walk for all participants and showed that walking the Green Road elicited a significantly larger reduction in cortisol of 53% on average when compared with 37% of walking along an urban road. It is also observed that the order in which individuals walked the green road, and urban road also impacted their cortisol response with those walking the urban road before the green showing a substantial reduction in cortisol, suggesting a possible attenuation effect of walking the green road first. These findings provide quantitative data demonstrating the stress-reducing effects of being in nature, thus supporting the health benefit value of providing access to nature more broadly in many settings.

This article examines empirically the research on digital strategy, addressing its temporal evolution, sources of scientific production, countries and organizations generating knowledge, and the topics investigated. It highlights key authors and journals from 1991 to 2023, contributing to Sustainable Development Goal (SDG) 9. Methodologically, traditional bibliometric laws and computational tools (VOSviewer software) were applied for data processing. The results show an exponential increase in publications from 2005 to 2022 with a critical mass in digital strategy studies, concentrated in 11 journals and 83 authors with 2 or more publications. The main organizations leading scientific production in this field are in the USA. Finally, the primary Web of Science categories for the leading journals are Business, Management, and Psychology. The research examines the use and adoption of digital strategies in marketing, the impact of digital transformation on business models, and the challenges it poses for human resources. In addition, the challenges arising from the impact of COVID-19, the rise of artificial intelligence, and the integration of digital strategies in public administration should continue to be addressed. Finally, industrial digital transformation and the challenges of Big Data in higher education have less connection with other key concepts analyzed.

The detection of microplastics (MPs) in drinking water has emerged as a critical environmental concern, with significant implications for public health. However, the variability in identification methods across studies has made it difficult to compare results, underscoring the urgent need for standardized protocols. This study presents a comprehensive meta-analysis and practical ap-proach to standardizing Fourier Transform Infrared Spectroscopy (FTIR)-based methodologies for detecting MPs in drinking water. By systematically reviewing studies from 2019 to 2023, this research identifies the most effective techniques for MP quantification, with an emphasis on the use of 0.45 μm cellulose nitrate filters and Nile red staining for fluorescence detection. The me-ta-analysis demonstrates consistent results across studies, supported by statistical analysis con-firming the reproducibility and reliability of the methodologies employed. Experimental findings highlight that the cellulose nitrate filter offers superior microplastic retention with low back-ground fluorescence, making it ideal for FTIR analysis. Moreover, the Nile red spray method is recommended for its efficiency and uniformity in staining, and random counting proves to be a rapid and reliable quantification technique. This study advocates for the adoption of standard-ized protocols, particularly in filter selection and staining methods, to ensure accurate and com-parable MP detection. The findings contribute valuable insights for optimizing water treatment processes and provide a solid foundation for future research and regulatory frameworks aimed at mitigating microplastic contamination in water resources.

The potential of technical lignins slow pyrolysis is briefly summarized. The pyrolysis process, which can be self-sustained by burning the co-produced gas, can primarily produce high-quality biochar in significant amounts, to be used as a fuel and as a reductant in metallurgy. Together, significant amounts of bio-oil can be produced, rich in guaiacols, which are commercial and expensive chemicals produced today via petrochemical routes and used in pharmacology, food chemistry, polymer chemistry, etc. Such compounds or bio-oil itself can also be converted by hydrodeoxygenation into biofuels.

Conclusions: The findings provide a first-time study on nanotechnology curricula within medical specialty programs in Colombia, with potential extrapolation to similar situations in other medical schools.

Through the integration of genomic information, transcriptome sequencing data, and bioinformatics methods, we conducted a comprehensive identification of the ALDH gene family in melon. We explored the impact of this gene family on melon growth, development, and their expression patterns in various tissues and under different stress conditions. Our study discovered a total of 17 ALDH genes spread across chromosomes 1, 2, 3, 4, 5, 7, 8, 11, and 12 in the melon genome. Through a phylogenetic analysis, these genes were classified into 10 distinct subfamilies. Notably, genes within the same subfamily exhibited consistent gene structures and conserved motifs. Our study discovered a pair of fragment repeats within the melon ALDH gene. Furthermore, there was a noticeable collinearity relationship between the melon's ALDH gene and that of Arabidopsis (12 times), and rice (3 times). Transcriptome data reanalysis revealed that some ALDH genes consistently expressed highly across all tissues and developmental stages, while others were tissue or stage-specific. We analysed the ALDH gene's expression patterns under six stress types, namely salt, chilling, waterlogged, powdery mildew, fusarium wilt, and gummy stem blight. The results showed differential expression of MELO3C024328 and MELO3C004430 under all stress conditions, signifying their crucial roles in melon growth and stress response. RT-qPCR analysis further corroborated these findings. This study paves the way for future genetic improvements in melon molecular breeding.

The modulation of vocal elements such as pitch, loudness, and duration plays a crucial role in conveying both linguistic information and the speaker’s emotional state. While acoustic features like fundamental frequency (F0) variability have been widely studied in emotional speech analysis, challenges remain in accurately classifying emotions due to the complex and dynamic nature of vocal expressions. Traditional analytical methods often oversimplify these dynamics, potentially overlooking intricate patterns indicative of specific emotions. This study aims to enhance emotion classification in speech by directly incorporating dynamic F0 contours into the analytical framework using Generalized Additive Mixed Models (GAMMs). We utilized the Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS), focusing on eight distinct emotional states expressed by 24 professional actors. Sonorant segments were extracted, and F0 measurements were converted into semitones relative to a 100 Hz baseline to standardize pitch variations. By employing GAMMs, we modeled non-linear trajectories of F0 contours over time, accounting for both fixed effects (emotions) and random effects (individual speaker variability). Our analysis revealed that incorporating emotion-specific non-linear time effects and individual speaker differences significantly improved the model’s explanatory power, ultimately explaining up to 66.5% of the variance in F0. The inclusion of random smooths for time within speakers captured individual temporal modulation patterns, providing a more accurate representation of emotional speech dynamics. The results demonstrate that dynamic modeling of F0 contours using GAMMs enhances the accuracy of emotion classification in speech. This approach captures the nuanced pitch patterns associated with different emotions and accounts for individual variability among speakers. The findings contribute to a deeper understanding of the vocal expression of emotions and offer valuable insights for advancing speech emotion recognition systems.

Cassava (Manihot esculenta Crantz) is used as biomass energy materials and an effective supplement for food and feed. Cinnamyl alcohol dehydrogenase (CAD) catalyzes the final step of lignin biosynthesis and is responsible for various stresses. However, systematic investigation of CAD gene family in cassava has been poorly understood. In this study, we performed a genome-wide survey and identified 36 MeCADs genes that were unevenly harbored in 12 chromosomes. Through phylogenetic analyses along with Arabidopsis counterparts, these MeCADs were divided into four groups, each gene contains a similar structure and conserved motifs. Interestingly, transcriptome data analyses unveiled 32 MeCAD genes during the postharvest physiological deterioration (PPD) process of cassava tuberous roots, whereas 27 MeCAD genes significantly changed. Meanwhile, the relative quantitative analysis of 6 MeCAD genes demonstrated that they were sensitive to PPD, suggesting they may involve in PPD regulation. Silencing MeCAD13 and MeCAD28 further showed that lignin content significantly decreased in the leaves. The wound-stress tolerance of transgenic yeast cells was enhanced after transformation with MeCAD13 and MeCAD28. In conclusion, MeCAD13 and MeCAD28 may play positive roles in lignin biosynthesis and PPD response, respectively. These results provided a systematic functional analysis of MeCADs in cassava and paved a new way to genetically modify of lignin biosynthesis and PPD tolerance.

The aim of the present review is to investigate the role of a toothpastes containing enzymes and proteins in supplementing natural salivary defenses. A systematic review was conducted using PRISMA with PROSPERO ID code CRD42024558854. An exhaustive search of PubMed, Web Of Science, and Scopus, using the PICO format was carried out. The used MeSH were enzymes; AND proteins; AND toothpaste. In vivo studies on humans analyzing the gum effects of a toothpaste containing enzymes and proteins, in the English language, published in the last 10 years were included. The search period started on 04 June 2024 and ended on 20 July 2024. The risk of bias was evaluated according to the Revised Cochrane risk-of-bias tool for randomized trials (RoB 2.0) while non-randomized studies were evaluated with the Cochrane risk-of-bias tool in Non-Randomized Studies (ROBINS-I). From a total of 62 studies, 3 were included. Two RCTs and had low and medium risk of bias, the N-RCT had low risk of bias. With the limitations of the present study, a toothpaste containing enzymes and proteins can improve gum health after 12 week and after 12 months, the role against black stains seemed not to be confirmed.

(1) Background: Arrhythmia, or irregular heart rhythms, are a prevalent cardiovascular condition and can be diagnosed using electrocardiogram (ECG) signals. Advances in deep learning have enabled automated analysis of these signals. However, the effectiveness of deep learning models depends heavily on the quality of signal preprocessing. This study evaluates the impact of different windowing techniques applied to Fourier Transform-preprocessed ECG signals on the classification accuracy of deep learning models. (2) Methods: We applied three windowing techniques—Hamming, Hann, and Blackman—to transform ECG signals into the frequency domain. A 1D Convolutional Neural Network (CNN) was employed to classify the ECG signals into five arrhythmia categories based on features extracted from each windowed signal.(3) Results: The Blackman window yielded the highest classification accuracy, with improved signal-to-noise ratio and reduced spectral leakage compared to the Hamming and Hann windows. (4) Conclusions: The choice of windowing technique significantly influences the effectiveness of deep learning models in ECG classification. Future studies should explore additional preprocessing methods and their clinical applications.

The study aimed to determine the protein content and amino acid profile of the longissimus lumborum and the semiomembranosus muscles of fallow deer originating from an organic feeding ground (OFG) and a conventional feeding ground (CFG). The amino acid content was determined using the ion-exchange chromatography method in accordance with AOAC. The present study provides the first published data on the nutritional value of fallow deer meat proteins. An analysis of the results revealed significant differences between the essential (EAA) and non-essential amino acid (NEAA) contents, depending on the feeding ground. A higher nutritional value was noted for the OFG fallow deer muscles, as indicated by the higher EAA and NEAA amino acid contents, a higher EAA proportion, a higher chemical score (CS) value, and the calculated expected protein efficiency ratio (PER) and biological value (BV). A significant effect of the muscle type on the histidine content and the feeding ground x muscle interaction for glycine was noted. All fallow deer muscle samples exhibited a complete profile of essential amino acids and a high-quality protein profile. The data presented in this overview show that the nutritional value of fallow deer meat represents an excellent source of proteins for humans.

Background/Objectives: The COVID-19 pandemic has had a profound impact on mental health worldwide, especially exacerbating Eating Disorders (EDs). This study aims to evaluate changes in the presentation and severity of EDs before and after the pandemic at the Regional Residential Center "Mariconda" in Salerno. Methods: This retrospective cohort study analyzed data from 162 patients admitted to the Regional Residential Center "Mariconda" between December 2018 and December 2023. The onset of pandemic restrictions in mid-2020 was the dividing line for the pre-COVID and post-COVID groups. Demographic and clinical data were collected, including age, gender, education level, previous hospital admissions, admission diagnosis, body mass index (BMI), and comorbidity with other psychiatric illnesses. Results: Of the 162 subjects, 115 were admitted post-pandemic. The post-pandemic group was significantly younger, had lower education levels, more frequent previous hospitalizations, and a higher frequency of severe comorbidity with other mental illnesses compared to the pre-COVID group. No significant differences were found between the groups regarding gender distribution, initial diagnosis upon admission, average and length of hospital stay. Conclusion: The COVID-19 pandemic has exacerbated the presentation and severity of EDs, particularly among younger individuals with lower educational attainment. These findings underscore the urgent need for targeted, integrated treatment approaches for EDs, especially global crises. Further research is essential to understand the long-term effects of the pandemic on EDs and to refine treatment strategies to better support affected individuals.

This study investigated the optimal treatment conditions to improve the quality of white pan bread by applying high-voltage pulsed electric fields (PEF) technology with varying electric field treatment times to bread dough. The treatment was conducted at an electric field strength of 2 kV/cm, frequency of 10 Hz, and a pulse width of 100 µs, with varying treatment time of 10, 20, and 30 min. When PEF was applied for 10 min, the treatment dough’s fermentation expansion rate was significantly higher. Bread made with the 10 min treated dough also exhibited higher weight, volume, specific volume, and moisture content, along with lower oven spring and baking loss rate. During storage, the 10 min treated samples maintained higher moisture content, while the 20 and 30 min treated samples showed no significant difference. In terms of texture profile analysis, the treated samples had lower hardness and chewiness compared to the control, while springiness, cohesiveness, and resilience tended to be slightly higher. In terms of texture, the treated samples had lower hardness and chewiness, but higher springiness, cohesiveness, and resilience compared to the control group.

In the context of enhanced decision-making related to Industry 4.0 and 5.0, this work examines the first step to implement a Digital Twin (DT) in a discrete manufacturing firm. The DT will be required to be adequately integrated with the information systems, especially the Manufacturing Execution System (MES), because the virtual counterpart of the DT itself, a Discrete Event Simulator (DES) model, will exploit MES data for the validation and the monitoring. The objective of the DT is to enhance the decision-making related to production planning, in particular, achieving better on-time delivery to customers. Therefore, the DT intends to depict material flows within the production department to enhance monitoring and control, facilitating the prompt identification of deviations from the plan, and supporting the decision-makers, enabling a more responsive and informed management of delay alerts. The first goal to achieve the DT implementation and integration is to establish a conceptual framework that improves material flow data synchronization. A conceptual integration and implementation framework for the DT will be proposed and discussed, underlying the technical decisions chosen to achieve the functional and integration requirements.

Additive manufacturing (AM) is a cutting-edge manufacturing technique that allows for the direct creation of complicated objects from digital desktop designs. Among the several AM techniques, the material extrusion technique has gained more attention because of its ability to manufacture complicated objects and customizes profiles at a reasonable costin a shortertime period. The main advantages of this technique are its easier fabrication process and low cost when compared to other well-known AM techniques. Enhancement in mechanical properties plays the key role in the AM objects. So, Incorporating nanofillers or nanoparticles into the basic materials like polymers, carbon ceramic and metal based materials is one of the most promising alternatives. This review attempts to enlighten and inform readers about the basic working principle of material extrusion technique and the many forms of polymer-based additives reported in the literature. This review can guide the readers to compare and assess the uses of polymer based raw materials before on choosing the kind of material be used, as well as it provides a view point on the application of AM by the material extrusion method in different disciplines. Finally, the challenges and upcoming prospects of the material extrusion process are discussed.

Antibiotic-loaded bone cement has been traditionally advocated as a key step for the success of one-stage hip revision surgery, while cementless techniques have been re-cently proposed with and without the use of local antibacterials as an equally suc-cessful alternative. Aim of this review is to investigate the effective role of local anti-microbial protection for one-stage cemented and cementless hip revision surgery. Twelve studies reporting the results of cemented single-stage procedure at a minimum two years follow-up were reviewed. When pooling together the data, no infection re-currence was observed on average in 83.3% of the patients (range 75.0% to 100%). Only two papers, both from the same French group, included patients treated without the use of antibiotic-loaded bone cement, with an average infection control of 95.9% in a total of 195 patients. This figure appears better that the 80.7% infection control ob-tained by pooling together all the remaining studies. Concerning cementless one-stage revision, a total of 17 studies, reporting on 521 patients, showed an average 90.0% (range 56.8% to 100%) no infection recurrence, at a minimum two years follow-up. Eight papers reported the outcomes of cementless implants without any local antibac-terial protection and nine more described four different techniques for local antimi-crobial implant protection. No comparative study investigated cementless revision with or without local antibacterial protection. Pooled data showed an average infection control of 86.7%, without the application of local antibacterials, compared to 90.1% to 100% with local antimicrobial protection, depending on the technology used. Howev-er, due to the relatively low number of patients treated with each local antimicrobial protection, no statistical difference could be found, either considering local antibacte-rial strategies alone or pooled together. No side effect had been reported by any local antibacterial technique. This review points out that local antibacterial protection for one-stage hip revision surgery, although safe and largely performed in the clinical set-ting, appears still to rely mainly on experts’ opinion and on observational series with no prospective or comparative trial, hence no definitive conclusion can be drawn con-cerning its effective role in one-stage hip revision surgery.

We introduce succinct and objective definitions of the various classes of objects in the solar system. Unlike in the formal definitions adopted by the International Astronomical Union in 2006, group separation is obtained from measured physical properties of the objects. Thus, this classification scheme does not rely on orbital/environmental factors subject to debate—the physical parameters are intrinsic properties of the objects themselves. Surface gravity g is the property that single-handedly differentiates (a) planets from all other objects (and it leaves no room for questioning the demotion of Pluto); and (b) the six largest (g&gt;1 m s−2) of the large satellites from dwarf planets. Large satellites are separated from small satellites by their sizes and masses/densities, which may serve as higher-order qualifiers of class membership. Size considerations are also sufficient for the classification of (i) main-belt asteroids (except possibly Ceres) as small solar-system bodies similar in physical properties to the small satellites; and (ii) a group of large Kuiper-belt objects as dwarf planets similar in physical properties to the large (but not the largest) satellites in our solar system. The selection criteria are simple and clear and reinforce the argument that body shape and environmental factors need not be considered in stipulating class membership of solar as well as extrasolar bodies.

Currently, NiFe-LDH exhibits excellent oxygen evolution reaction (OER) due to the interaction of the two metal elements on the LDH platform. However, such interaction is still insufficient to compensate for its poor electrical conductivity, limited active sites and sluggish dynamics. Herein, a feasible two-step hydrothermal strategy is proposed by coupling low-conductivity NiFe-LDH with 3D porous graphene aerogel (GA). Consequently, the optimized NiFe-LDH/GA (1:1) possess a 257 mV (10 mA cm-2) overpotential and could continuously operate for 56 h in OER. Our investigation validates that the NiFe-LDH/GA has a three-dimensional mesoporous structure, synergistic interaction between LDH and GA, and interfacial reconstruction of NiOOH. Such interface synergistic coupling effect promotes fast mass transfer and facilitates OER kinetics, and this work offers new sights into designing efficient and stable GA-based electrocatalysts.

It is challenging to apply the receiver function method to teleseisms recorded by ocean bottom seismographs (OBS) due to a specific working environment that differs from land stations. Tele-seismic incident waveforms reaching the vicinity beneath stations are contaminated by multiple reflections generated by seawater and sediments and noise resulting from currents. Furthermore, inadequate coupling between OBS and seabed reduces the signal-to-noise ratio (SNR) of seismograms, leading to poor quality of extracted receiver functions or even wrong deconvolution results. For instance, the poor results cause strong ambiguities regarding Moho depth. This study uses numerical modelling to analyze the influences of multiple reflections generated by seawater and sediments on H-kappa stacking and neighborhood algorithm. Numerical modellings show that seawater multiple reflections are mixed with coda waves of direct P-wave and slightly impact extracted receiver functions, thus can be ignored in subsequent inversion processing. However, synthetic seismograms have strong responses to the sediments. Compared to waveforms of horizontal and vertical components, sedimentary responses are too strong to identify the converted waves clearly. The extracted RFs correspond to the above influences, resulting in divergent results of H-kappa stacking (i.e., Moho depth and crustal average VP/VS ratio are unstable and have great uncertainties). Fortunately, waveform inversion approaches (e.g., neighborhood algorithm) is available and valid for obtaining S-wave velocity structure of the crust-upper mantle beneath the station with sediments varying in thickness and velocity.

Remote sensing (RS) and Geographic Information Systems (GIS) provide significant opportunities for monitoring and managing natural resources across various temporal, spectral, and spatial resolutions. There is a critical need for natural resource managers to understand the expanding capabilities of image sources, analysis techniques, and in-situ validation methods. This article reviews a range of image analysis tools applicable to natural resource management, including agriculture, water, forests, soil, and natural hazards, and compares their functionalities. Our study highlights that Google Earth Engine (GEE) is favored for wide-area analysis due to its extensive coverage and free access. Global Mapper excels in 3D and light detection and ranging (LIDAR) data, environment for visualizing images (ENVI) specializes in multi- and hyperspectral image processing, ERDAS IMAGINE is optimal for radar data, and eCognition is used for object-based image analysis. The article emphasizes the importance of in-situ validation data, which provides essential ground truth information to calibrate and validate RS models, thereby enhancing accuracy. Understanding these tools and integrating them with in-situ validation techniques enables natural resource managers to improve their monitoring and decision-making processes, facilitating effective collaboration with RS researchers.

Introduction: Patients receiving biological and targeted synthetic disease-modifying antirheumatic drugs (b/tsDMARDs) for rheumatological conditions are at an increased risk of serious, potentially life-threatening, infection. However, the incidence, aetiology and clinical course of serious infection in patients receiving b/tsDMARDs in tropical settings are incompletely defined. Methods: We retrospectively reviewed all patients with rheumatoid arthritis receiving b/tsDMARDs between October 2012 and October 2021, at Cairns Hospital in tropical Australia. The incidence, aetiology, and clinical course of serious infections (those requiring admission to hospital or parenteral antibiotics) was determined. Results: 310 patients had 1468 patient-years of b/tsDMARD therapy during the study period; 74/310 (24%) had 147 serious infections translating to an overall risk of 10.0 episodes of serious infection per 100-patient-years. The respiratory tract (50/147, 34%) and skin (37/147, 25%) were the most frequently affected sites. A pathogen was identified in 59/147 (40%) episodes and was most commonly Staphylococcus aureus (24/147, 16%). Only 2/147 (1%) were confirmed “tropical infections”: 1 case of Burkholderia pseudomallei and 1 case of mixed B. pseudomallei and community-acquired Acinetobacter baumannii infection. Overall, 13/147 (9%) episodes of serious infection required Intensive Care Unit admission (0.9 per 100-patient-years of b/tsDMARD therapy) and 4/147 (3%) died from their infection (0.3 per 100-patient-years of b/tsDMARD therapy). The burden of comorbidity and co-administration of prednisone were the strongest predictors of death or a requirement for ICU admission. Conclusion: The risk of serious infection in patients taking b/tsDMARDs in tropical Australia is higher than in temperate settings, but this is not explained by an increased incidence of traditional tropical pathogens.

Purpose/Objective: Frequent consumption of fermented carbohydrates and bottle feeding contribute to the development of early childhood caries (ECC). There are no substantial findings on the effects of breastfeeding patterns on oral health conditions in children in the United States. We aimed to assess the nexus between exclusive breastfeeding during the first 6 months and oral health disorders, namely toothache, decayed teeth, or unfilled cavities in early childhood. Materials and Methods: Design: Cross-sectional epidemiologic design of nationally representative data collected via telephone surveys in the United States was utilized. Setting: National Survey of Children’s Health, 2012 Participants: Population-based random sample of parents/guardians of 24,655 children aged 6 months to 5 years. Main Outcome and Measure: Parent-reported oral health condition including toothache, decayed teeth or unfilled cavity in the past 12 months. Results: A total of 2,392 (9.7%) children aged 6 months to 5 years experienced an oral health disorder, mainly toothache, decayed teeth, or unfilled cavity in the previous 12 months. Relative to non-Hispanic White children (7.7%), a greater proportion of non-Hispanic Black (12.9%) and multi-racial children (12.6%) experienced oral health disorders (OHD). In the univariable model, relative to children who never breastfed, those who were breastfed exclusively for 6 months were 28% less likely to present with OHD, Odds Ratio (OR) = 0.72, 95% CI, 0.52-0.98. After adjustment, the protective nature of exclusive breastfeeding against OHD did not remain, adjusted OR (aOR) =1.11, 99% CI 0.79-1.57. Children of mothers with fair/poor health were almost twice as likely to have poor OHD compared with children of mothers with excellent/very good health (aOR = 1.79, 99% CI 1.08-2.69). Conclusions and Relevance: Exclusive breastfeeding for the first six months of life improved pediatric OHD and remains mutually beneficial for mothers and children. These findings suggest the importance of exclusive breastfeeding and maternal health in relation to dental hygiene in children.

In recent years, digital transformation has become a pivotal factor for Small and Medium-sized Enterprises (SMEs), empowering them to adopt emerging technologies for competitive advantage. This systematic literature review examines 60 research papers published between 2014 and 2024, using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework to explore the impact of digital technologies such as artificial intelligence, cloud computing, blockchain, and the Internet of Things (IoT) on SME performance. The review focuses on key drivers and barriers, including operational efficiency, customer engagement, and market expansion. Methodologies employed in the analyzed studies include quantitative approaches (60%), such as surveys and structural equation modelling, qualitative methods (25%), including interviews and case studies, and mixed methods approaches (15%) that combine both. A geographic distribution analysis highlights contributions from various countries, revealing regional research gaps. The results show that digital technologies have significantly improved SME operations, but challenges like limited resources and strategic focus persist. Additionally, the dominance of quantitative methods indicates a potential bias, suggesting the need for more diverse methodological approaches to fully understand the transformative potential of digital technologies for SMEs.

The EcoFlora Project was launched at the New York Botanical Garden and expanded to other botanical gardens across the United States to enhance our understanding of urban plant biodiversity through community science iNaturalist observations. This study evaluates the strengths and limitations of using iNaturalist observations and herbarium specimen records in biodiversity research, demonstrating their complementary roles. iNaturalist engages community scientists and provides real-time data but may suffer from biases and inconsistent identification accuracy. Conversely, herbarium specimens offer verified, historical records but require significant resources for collection and upkeep. Through case studies in five U.S. metro areas, EcoFloras highlight the effectiveness of combining these data sources for comprehensive biodiversity assessments. The project reveals how leveraging both digital tools and traditional specimen collections can provide a more complete picture of biodiversity, informing conservation strategies and biodiversity management. Integrating community science with established scientific methods fosters greater public involvement in conservation and offers a robust framework for addressing biodiversity challenges. Rigorous data cleaning is essential, and future efforts should focus on linking both data sources to enhance plant conservation strategies. By leveraging the strengths of both iNaturalist and herbarium data, researchers can greatly enhance the effectiveness of conservation strategies.

The fishery biology of the invasive Atlantic blue crab Callinectes sapidus in the Mediterranean Sea outside the eastern sectors of the basin has been only recently investigated. Here we studied the population of C. sapidus in the Lesina Lagoon (Adriatic Sea, SE Italy). In total, 838 crabs were captured monthly between February 2021 and January 2022 using fyke nets. Abundances varied seasonally with catches per unit effort ranging between 0 and 1.76 crabs fyke nets-1 d-1 in winter and summer. Spatial abundances estimated in summer by a Carle-Strub procedure ranged between 0.06 and 0.64 crabs m-2. Sex ratio (♂/♀) was close to 1:1; males prevailed only in August and September; ovigerous females occurred from April to August. Males’ size at morphological maturity was smaller than females (110.6-112.3 mm vs. 122.1-123.1 mm). Seasonal von Bertalanffy growth parameters indicated that, compared with males, females showed a shorter maximum lifespan (5 vs. 8 years), a higher growth coefficient K (0.6 vs. 0.4 y-1) and growth performance index ' (4.6 vs. 4.3), while maximum sizes CW∞ (237.8 vs. 232.6 mm) and seasonality indices C (0.62 vs. 0.57) were similar. Furthermore, females showed higher natural and fishing mortalities and exploitation rate. We discussed the results of the present study in the context of the available literature to provide a valuable basis for the implementation of standardised Mediterranean-scale management plans, matching exploitation of C. sapidus with sustainable conservation of coastal ecosystems.

Parkinson’s disease (PD) is a prevalent neurodegenerative disorder characterized by symptoms such as tremors, dementia, and bradykinesia. Early non-motor signs, including constipation and hyposmia, suggest a potential connection between PD and the gut. The loss of dopaminergic neurons in the substantia nigra is a hallmark of PD, with unknown causes. While current treatments provide symptom relief, there are no therapies to slow the progression of the disease. The gut microbiota plays a role in inflammatory and immune responses and has been implicated in neurological disorders. The connection between gut microbiota and neurodegenerative disease remains unclear. In this paper, we aim to explore the potential link between gut microbiome dysbiosis in PD, focusing on constipation, which is an early symptom of the disease. Our review will examine the evidence that suggests the possibility of chronic intestinal inflammation that may contribute to the development of Parkinson’s disease and implicate further connections with other neurodegenerative diseases.

Canine Multiple System Degeneration (CMSD) is an early onset, progressive movement disorder affecting Kerry Blue Terriers and Chinese Crested dogs. The associated pathologic lesions include degeneration of the cerebellum, caudate nucleus and substantia nigra. CMSD is inherited as an autosomal recessive trait in both dog breeds. Previous linkage mapping localized the CMSD locus to a 15 MB region on canine chromosome 1 (CFA1). Next generation sequencing was used to generate whole genome sequences from DNA of an affected dog from each breed. The resulting sequence reads were aligned to the NCBI canine reference genome (build 3.1). Among the homozygous sequence variants within the CFA1 target region, a nonsense variant in exon 15 of SERAC1 was identified in the affected Kerry Blue Terrier, while in the Chinese Crested dog, a 4 bp deletion in the SERAC1 exon 4 acceptor splice site was found. RT-PCR showed that this deletion resulted in exon 4 skipping. Genotyping of large cohorts of Kerry Blue Terriers and Chinese Crested dogs for the respective breed-specific SERAC1 variants showed complete concordance between genotype and disease phenotype. Genotype-phenotype concordance was also observed in offspring generated by cross breeding between SERAC1-heterozygous Kerry Blue Terrier and Chinese Crested dogs, with only the compound heterozygotes exhibiting the disease phenotype, further confirming the recessive inheritance of CMSD. Variants in human SERAC1 are associated with disorders with a range of ages of disease onset and patterns of clinical signs, but that are all characterized by movement abnormalities similar to those of the dogs with CMSD. Canine CMSD could serve as a valuable model to elucidate the mechanisms underlying SERAC1-deficiency disorders and to evaluate potential therapeutic interventions.

Introduction: Cartilage injuries and osteoarthritis are very prevalent and considered a public health problem, as they are highly disabling and represent an economic burden. Mesenchymal Stromal Cells (MSCs) can be isolated from different tissues and have the immunomodulatory capacity to regulate local articular joint environment. This translational study aims to compare the cartilage restoration from MSCs from the synovial membrane (SM) and dental pulp (DP), by tissue engineered treatment in a Good Manufacturing Practices. Materials and Methods: A controlled experimental study in fourteen miniature pigs was performed, using scaffold-free Tissue Engineering Construct (TEC) from DP and SM MSCs, with 6 months follow-up. Total thickness cartilage defects were performed in both posterior knees. The defect was left empty on one side, and the other received TEC from DP (n=7) or from SM (n=7). MRI assessed morphology with the MOCART scoring system. T2 mapping assessed water and collagen fiber composition. Histology evaluated cartilage repair using the ICRS-2 score. Results: The mean MOCART value in the untreated group was 46.2 ± 13.4, while the group treated with TEC from SM was 65.7 ± 15.5 (p

Background/Objectives: Heart failure (HF) is a chronic disease with a steadily increasing prevalence, high mortality, social and economic costs. Furthermore, every hospitalisation for acute HF is associated with worsening prognosis and reduced life expectancy. In order to prevent hospitalisations, it would be useful to have instruments that can predict them well in advance. Methods: We performed a review on remote monitoring of heart failure through implantable devices.; Results: Precise multi-parameter algorithms, available for ICD and CRT-D patients, have been created, which also use artificial intelligence and are able to predict a new heart failure event more than 30 days in advance. There are also implantable pulmonary artery devices that can predict hospitalisations and reduce the impact of heart failure. proper organisation of transmission and alerts management is crucial for clinical success in using these tools. Conclusions: The full implementation of remote monitoring of implantable devices and in particular the use of new algorithms for the prediction of acute heart failure episodes represents a huge challenge but also a huge opportunity.