Search Results (10,996)

This research uses advanced statistical methods to examine climate change mitigation policies’ economic and environmental impacts. The primary objective is to assess the effectiveness of carbon pricing, renewable energy subsidies, emission trading schemes, and regulatory standards in reducing CO₂ emissions, fostering economic growth, and promoting employment. A mixed-methods approach was employed, combining regression analysis, cost–benefit analysis (CBA), and computable general equilibrium (CGE) models. Data were collected from national and global databases, and sensitivity analyses were conducted to ensure the robustness of the findings. Key findings revealed a statistically significant reduction in CO₂ emissions by 0.45% for each unit increase in carbon pricing (p < 0.01). Renewable energy subsidies were positively correlated with a 3.5% increase in employment in the green sector (p < 0.05). Emission trading schemes were projected to increase GDP by 1.2% over a decade (p < 0.05). However, chi-square tests indicated that carbon pricing disproportionately affects low-income households (p < 0.05), highlighting the need for compensatory policies. The study concluded that a balanced policy mix, tailored to national contexts, can optimise economic and environmental outcomes while addressing social equity concerns. Error margins in GDP projections remained below ±0.3%, confirming the models’ reliability. Full article

Microbial contamination during seafood processing can often lead to a reduction in shelf life and the possibility of food-borne illnesses. Sanitisation with chlorine-based products during seafood processing is therefore sometimes undertaken. This study compared the effects of two sanitisers, chlorine dioxide (ClO₂) and hypochlorous acid (HOCl) at their suggested concentration (5 ppm and 10 ppm; 50 ppm and 100 ppm respectively), on physical, chemical, and microbial qualities of Atlantic salmon (Salmo salar) fillets throughout 7 days of simulated retail display refrigeration. Parameters used for assessment included quality index (QI), drip loss, colour, texture, histology, total volatile base nitrogen (TVB-N), lipid oxidation (malonaldehyde, MDA), pH, and total viable count changes. Results indicated that whilst drip loss increased over the storage time, day 4 and 7 drip loss in both sanitisers decreased significantly compared with the control. There was a linear relationship (R > 0.70) between QI and storage time in all treatments, particularly in regard to skin brightness, flesh odour, and gaping parameters, but treatment differences were not present. Texture parameters including gumminess, chewiness, and hardness increased over time in the control whilst both sanitiser treatments seemed to provide protective effects against texture hardening during storage. The observed softening effects from the sanitiser treatments were aligned with microstructural and cytological changes in the histology results, as evidenced by a reduced fibre–fibre adhesion, myodigeneration, and an increase in interfibrillar space over storage time. Colour, especially chroma (C*), was shown to decrease over time in control, whereas insignificant protective effects were observed in both sanitiser treatments at day 7. Irrespective of treatment and storage time, MDA levels exceeded the acceptable limit on all days, whilst TVB-N levels were below the critical limit. Although pH was influenced by treatment and storage time, the pH was within the normal range. Microbiological results showed that with sanitiser addition, TVC was below the permissible level (10⁶ CFU/g) until day 4 but ClO₂ ice (5 ppm), ClO₂ (10 ppm), and HOCl (100 ppm) treated fillets all exceeded the limit on day 7. The mixed results on the effect of sanitiser addition on fillet quality and shelf life suggested that further investigation on pathogen reduction, sanitiser introductory method, as well as testing the same treatments in low-fat fish models would be recommended. Full article

SCOBY (symbiotic culture of bacteria and yeasts) is an artificially created mixed culture containing selected strains of acetic acid and lactic acid bacteria and yeast which are present in the cellulose membrane. The growing popularity of kombucha consumption and high popularity of coffee creates the possibility of developing coffee-based kombucha production on an industrial scale, which currently does not differ in method from production on a laboratory scale and at home. Therefore, the aim of this work was to determine the possibility of using an alternative method of coffee fermentation using SCOBY, in which the fermentation was carried out in a bioreactor with a constant air flow (rate 2L/min). This study determined the effect of the fermentation method on the processing time, SCOBY mass gain, and selected properties of the fermented coffee beverage. The alternative fermentation method did not negatively affect the properties of the fermented coffee beverage, i.e., caffeine content, colour, polyphenol content, and antioxidant properties, in comparison with the traditional fermentation method. Additionally, it accelerated the fermentation process, shortening it from 8 to 4 days, and in some cases caused an increase in the total polyphenol content and antioxidant activity, almost 10% and over 40%, respectively. The results of this study show a possibility to use alternative methods for coffee fermentation, which can be easily adapted for industrial scale. Variants of fermented and aerated beverages with 4% coffee, and 4 and 5% sugar concentrations stood out among the others as having the best properties and might be introduced to the industry. Full article

Parents’ contributions to their children’s emotion regulation during adolescence has been a relatively understudied interpersonal context of development, even though parents’ roles as sources of social and emotional learning persist from childhood into adolescence and the complexity of teens’ lives grows during this time. This study aims to investigate the differential predictive utility of qualities and behaviors in interparental and parent–teen relationships during adolescence for predicting youths’ development of intra- and interpersonal emotion regulation over a 13-year period. To assess these hypotheses, data were obtained from a longitudinal, multi-method, multi-informant study of 184 adolescents (107 Caucasian, 53 African American, and 24 mixed/other ethnicity; median family income of USD 40,000–60,000/year in 1999, equivalent to about USD 75,000–112,000/year when accounting for inflation) and their parents. The results provide support for a differential pattern of prediction; qualities of interparental relationships in early adolescence were significant predictors of young adult interpersonal emotion regulation, whereas behaviors in interparental and parent–teen relationships in late adolescence were significant predictors of both young adult positive intra- and interpersonal emotion regulation. Notably, some father-reported relationship predictors during late adolescence had unexpected relations with later intrapersonal emotion regulation. The results are discussed in terms of the helpfulness of these specific relationship factors during each part of adolescence for supporting positive intra- and interpersonal emotional regulation development. Full article

This paper presents a static output feedback controller for a semi-active suspension system that provides improved ride comfort under various road roughness conditions. Previous studies on feedback control for semi-active suspension systems have primarily focused on rejecting low-frequency disturbances, such as bumps, because the feedback controller is generally vulnerable to high-frequency disturbances, which can cause unintended large inputs. However, since most roads feature a mix of both low- and high-frequency disturbances, there is a need to develop a controller capable of responding effectively to both disturbances. In this work, road roughness is classified using the Burg method to select the optimal damping coefficient to respond to the high-frequency disturbance. The optimal control gain for the feedback controller is determined using the linear quadratic static output feedback (LQSOF) method, incorporating the optimal damping coefficient. The proposed algorithm was evaluated through simulations under bump scenarios with differing road roughness conditions. The simulation results demonstrated that the proposed algorithm significantly improved ride comfort compared to baseline algorithms under mixed disturbances. Full article

Accurate carbon intensity forecasts enable consumers to adjust their electricity use, reducing it during high fossil-fuel generation and increasing it when renewables dominate. Existing methods for carbon intensity forecasting can be categorized into a source-disaggregated approach (SDA), focused on delivering individual generation forecasts for each potential source (e.g., wind, brown-coal, etc.), and a source-aggregated approach (SAA), attempting to produce a single carbon intensity forecast for the entire system. This research aims to conduct a thorough comparison between SDA and SAA for carbon intensity forecasting, investigating the factors that contribute to variations in performance across two distinct real-world generation scenarios. By employing contemporary machine learning time-series forecasting models, and analyzing data from representative locations with varying fuel mixes and renewable penetration levels, this study provides insights into the key factors that differentiate the performance of each approach in a real-world setting. The results indicate the SAA proves to be more advantageous in scenarios involving increased renewable energy generation, with greater proportions and instances when renewable energy generation faces curtailment or atypical/peaking generation is brought online. While the SDA offers better model interpretability and outperforms in scenarios with increased niche energy generation types, in our experiments, it struggles to produce accurate forecasts when renewable outputs approach zero. Full article

Background: Diabetic retinopathy (DR) is a leading cause of blindness in patients with type 2 diabetes mellitus (T2DM). Cardiovascular risk factors, such as hypertension, obesity, and dyslipidemia, may play a crucial role in the development and progression of DR, though the evidence remains mixed. This study aimed to assess cardiovascular risk factors as independent predictors of DR and to develop a predictive model for DR progression in T2DM patients. Methods: A retrospective cross-sectional study was conducted on 377 patients with T2DM who underwent a comprehensive eye exam. Clinical data, including blood pressure, lipid profile, BMI, and smoking status, were collected. DR staging was determined through fundus photography and classified as No DR, Non-Proliferative DR (NPDR), and Mild, Moderate, Severe, or Proliferative DR (PDR). A Multivariate Logistic Regression was used to evaluate the association between cardiovascular risk factors and DR presence. Several machine learning models, including Random Forest, XGBoost, and Support Vector Machines, were applied to assess the predictive value of cardiovascular risk factors and identify key predictors. Model performance was evaluated using accuracy, precision, recall, and ROC-AUC. Results: The prevalence of DR in the cohort was 41.6%, with 34.5% having NPDR and 7.1% having PDR. A multivariate analysis identified systolic blood pressure (SBP), LDL cholesterol, and body mass index (BMI) as independent predictors of DR progression (p < 0.05). The Random Forest model showed a moderate predictive ability, with an AUC of 0.62 for distinguishing between the presence and absence of DR XGBoost showing a better performance, featuring a ROC-AUC of 0.68, while SBP, HDL cholesterol, and BMI were consistently identified as the most important predictors across models. After tuning, the XGBoost model showed a notable improvement, with an ROC-AUC of 0.72. Conclusions: Cardiovascular risk factors, particularly BP and BMI, play a significant role in the progression of DR in patients with T2DM. The predictive models, especially XGBoost, showed moderate accuracy in identifying DR stages, suggesting that integrating these risk factors into clinical practice may improve early detection and intervention strategies for DR. Full article

This study addresses the set orienteering problem with mandatory visits (SOPMV), a variant of the team orienteering problem (SOP). In SOPMV, certain critical sets must be visited. The study began by formulating the mathematical model for SOPMV. To tackle the challenge of obtaining a feasible route within time constraints using the original MILP approach, a two-stage mixed-integer linear programming (MILP) model is proposed. Subsequently, a simulated annealing (SA) algorithm and a dynamic programming method were employed to identify the optimal route. The proposed SA algorithm was used to solve the SOP and was compared to other algorithms, demonstrating its effectiveness. The SA was then applied to solve the SOPMV problem. The results indicate that the solutions obtained using SA are superior and more efficient compared to those derived from the original MILP and the two-stage MILP. Additionally, the results reveal that the solution quality deteriorates as the ratio of the set of mandatory visits increases or the maximum allowable travel time decreases. This study represents the first attempt to integrate mandatory visits into SOP, thereby establishing a new research direction in this area. The potential impact of this research is significant, as it introduces new possibilities for addressing complex combinatorial optimization problems. Full article

Introduction. The COVID-19 pandemic has significantly impacted global health, with Eastern Europe experiencing notable excess morbidity and mortality and vaccine hesitancy. This study utilized the Behavior Integration (BI) framework to identify barriers and motivators for COVID-19 vaccination and develop strategies to increase vaccine demand and confidence in Moldova, North Macedonia, and Serbia. Methods. A mixed-methods approach was employed, including qualitative interviews and quantitative surveys. The BI framework was used to integrate human behaviors with technical and operational considerations throughout the project. Results. A total of 2742 online surveys were collected in Moldova and Serbia, revealing significant barriers such as vaccine safety concerns (OR = 1.839, 95% CI: 1.328–2.547 in urban Moldova; OR = 1.990, 95% CI: 1.351–2.931 in urban Serbia), logistical challenges, and lack of institutional trust. Conversely, motivators included personal health concerns, recommendations from health care providers, and the desire to travel. The proposed social and behavior change strategy included a continuing medical education course that trained 2403 medical providers, with post-test results showing a 99% improvement in knowledge and confidence in applying the information, and collective engagement workshops for 3260 chronic disease patients and 842 pregnant women, of which 7% were vaccinated against COVID-19. Conclusions. The BI approach effectively identified and addressed vaccination barriers and motivators, leading to tailored strategies that increased vaccine uptake. Continuous stakeholder engagement, adaptive learning processes, and local organizations are crucial for refining program implementation, ensuring sustainability, and promoting public health. Full article

This sequential explanatory mixed-methods study investigated the differences in persistence between students from the Sherman STEM Teacher Scholars Program (STEP), a STEM teacher scholarship and career preparation program, and STEM majors not in the program. Quantitative results indicated that STEP participants had higher levels of academic integration, women scored higher on persistence factors than men, and White students had a higher degree commitment than students of color. Qualitative findings indicated that STEP provided a family atmosphere and connected their coursework to their career aspirations. Women of color felt stereotyped by White classmates in STEM courses, which impacted their degree of commitment, and students of color in STEP relied on the program as a counterspace to racially insensitive STEM classrooms. Full article

Desert grasslands are a crucial component of terrestrial ecosystems that play vital roles in regional and global hydrological cycling, climate change, and ecosystem balance through variations in their soil moisture content (SMC). Despite this, current research on the SMC of desert grasslands remains insufficient, with many areas remaining underexplored. In this study, we focused on a typical desert grassland located in the northern foothills of the Yinshan Mountains. Ground-penetrating radar (GPR) exploration and soil sampling were used to test existing mixed-media models, and a new mixed-media model was calibrated using cross-validation methods. Among the three general mixed-media models, the Topp and Roth models yielded more accurate SMC estimates for the study area, with root mean square errors of 0.0091 g/cm³ and 0.0054 g/cm³, respectively, and mean absolute percentage errors of 25.86% and 19.01%, respectively, demonstrating their high precision. A comparison of the calibrated and original mixed-media models revealed that the estimation accuracy was significantly improved after parameter calibration. After parameter calibration, the Ferre model achieved an accuracy comparable to that of the Topp model. Parameter-calibrated models can be used to estimate the SMC using GPR data, offering a higher precision than general models and possessing greater suitability for the study area. The soil in the study area is primarily composed of sand particles and is therefore more compatible with the parameters of the Topp model, whereas the Ferre model requires further parameter calibration to achieve effective application. Full article

Metal screw extrusion (MSE) is a continuous, solid-state forming method utilizing an inherently high degree of deformation to consolidate fragmented input materials into a solid bulk by breaking their oxide skins. Severe plastic deformation with equivalent strain in the range of 10–20 can be achieved depending on set process parameters. Rigorous mixing can be employed to form sophisticated materials like bulk composites, nanocomposites, particle-reinforced metals, and fine-grained materials. Furthermore, the inherent solid-state processing is well suited for recovery of difficult-to-recycle materials. A range of non-ferrous materials has been manufactured by MSE and further characterized in terms of microstructural evolution and mechanical and functional properties. Furthermore, MSE has been studied in terms of flow, accumulated strain, and environmental impact. The following review aims to critically highlight the existing work performed on MSE, compare it to existing and emerging technologies as well as explore future development and possible applications. MSE has the potential to be utilized for numerous commercial applications. To realize industrial use of MSE, key aspects of the process and the influence of processing parameters on the resulting product must be understood. Full article

With the rapid pace of global urbanization, the urbanization of resettlement communities in China has garnered increasing attention from scholars. This study, grounded in experiential value theory, delves into the relationship between public spaces in resettlement communities and their social cohesion. Focusing on resettlement communities in the central urban area of Fuzhou, this study employs a mixed-method approach to analyze the functional characteristics of public spaces using geospatial data, including their green coverage ratio, spatial accessibility, facility configuration, and neighborhood density. A correlation analysis and multiple linear regression were employed to identify the key elements influencing social cohesion. The results indicate significant disparities in the green coverage, accessibility, facility configuration, and neighborhood density of public spaces. These differences are evident in the quantitative metrics used and also reflect imbalances in spatial layout and resource distribution, highlighting potential pathways for optimizing the quality of public spaces. Further data analyses revealed that both emotional value (β = 0.602, p < 0.01) and functional value (β = 0.136, p < 0.01) have significant positive impacts on social cohesion, with emotional value being particularly influential. This study offers insights for urban planners and policymakers by providing scientific evidence for the optimization of public space design in resettlement communities, with implications for community governance and urban sustainability. Full article

The detection of lipopolysaccharide (LPS) has important value for the monitoring of diseases such as sepsis and the impurity control of drugs. In this work, we prepared guanidinylated carbon dots (GQ-CDs) and used them to adsorb 5-carboxyfluorescein (FAM)-labeled single-stranded DNA (ssDNA) to become GQ-CDs/FAM-DNA, resulting in quenched FAM. The quenching efficiency of the FAM-DNA by GQ-CDs in the GQ-CDs/FAM-DNA system was 91.95%, and this quenching was stable over the long term. Upon the addition of LPS, the quenched FAM-DNA in the GQ-CDs/FAM-DNA system regained fluorescence at 520 nm. The mechanism studies found that the addition of LPS promoted the dissociation of FAM-DNA adsorbed on GQ-CDs, thereby restoring fluorescence. The degree of fluorescence recovery was closely related to the content of LPS. Under optimized conditions, the fluorescence recovery was linearly related to LPS concentrations ranging from 5 to 90 μg/mL, with a detection limit of 0.75 μg/mL. The application of this method to plasma samples and trastuzumab injections demonstrated good spiked recoveries and reproducibility. This platform, based on GQ-CDs for the adsorption and quenching of FAM-DNA, enables the detection of LPS through relatively simple mixing operations, showing excellent competitiveness for the determination of actual samples under various conditions. Full article

Despite the availability of COVID-19 vaccines, Nigeria still faces significant COVID-19 vaccine hesitancy, with only 60.7% of the eligible population fully vaccinated as of 20 March 2023. Our study, part of a community-based effort to improve knowledge and uptake of the COVID-19 vaccine in the Gwagwalada Area Council of Abuja, the Federal Capital Territory (FCT) of Nigeria, utilized the WHO’s Behavioral and Social Drivers (BeSDs)-of-vaccination framework to examine the drivers of COVID-19 vaccination among eligible adults. This was a mixed-method study with focus group discussions (FGDs) and in-depth interviews (IDIs) involving 40 purposively sampled participants. We triangulate qualitative findings with data from a household survey of 1512 eligible adults identified using a two-stage systematic cluster sampling approach. All data were collected from the 1–18 November 2022. The household survey showed 46% COVID-19 vaccine uptake, with Pearson chi-square and Fisher’s exact test showing significant associations between vaccine uptake and gender, religion, and education. Multivariate logistic regression showed that confidence in vaccine safety, knowing vaccination sites and family/friends’ endorsement of COVID-19 vaccination were the strongest items associated with vaccine uptake in the thinking-and-feeling, practical-issue, and social-process domains, respectively. Multiple items measuring these domains aligned with BeSD priority question, demonstrating the robustness of the pared-down framework. Qualitative data corroborated these findings. To address vaccine hesitancy and increase uptake, community-driven approaches to improve trust in vaccine safety and benefits and promote positive vaccination norms are needed. In addition, service delivery strategies to make vaccination services easily accessible and identifiable should be developed and tailored to community needs. Full article