Search Results (8,146)

Background: Childhood obesity is a critical public health challenge with a rising prevalence worldwide, contributing to numerous health risks and long-term societal burdens. Concurrently, climate change and environmental degradation demand sustainable approaches to dietary patterns. The Planetary Health Diet (PHD), initially designed for adults, emphasizes plant-based foods and sustainable practices. Objectives: This review explores the suitability of the PHD for addressing childhood obesity by assessing its nutritional adequacy and proposing necessary adaptations for pediatric populations. Methods: A narrative review methodology was employed, examining data from global and regional nutritional guidelines and evaluating the PHD’s bromatological composition against age-specific requirements. Results: The findings indicate that while the PHD aligns with environmental goals, it may not fully meet the energy and specific nutrient needs of children and adolescents without modifications. Key challenges include ensuring adequate intake of bioavailable protein, iron, calcium, vitamin B12, and vitamin D. Strategies such as incorporating fortified foods, optimizing food pairings, and gradual adaptation to high-fiber diets are critical for successful implementation. This review also highlights the importance of cultural adaptability, family involvement, and regional food systems in promoting adherence. Tailored interventions, such as school meal programs and educational initiatives, can bridge gaps in nutrition while fostering sustainable dietary behaviors. Conclusions: Adapting the PHD for pediatric needs presents an opportunity to integrate nutritional health with environmental stewardship, contributing to obesity prevention and a sustainable future. Further research is required to validate these adaptations and develop comprehensive frameworks for global implementation. Full article

The deprivation of historical and cultural testimony has a direct impact on a territory and its local communities, leading to the loss of social cohesiveness, identity values, and resources that come from sustainable tourism. Even though international action frameworks (Hyogo Framework for Action, Sendai Framework for Action, and 2030 Sustainable Development Goals) emphasise how important it is to recognise the relationship between heritage, society, and territory, a strategic and sustainable vision of participatory conservation and safeguarding is still required on a local level. Through the activities implemented within the SIRIUS and RESTART projects, led by the Department of Cultural Heritage, University of Bologna, this paper aims to stimulate a reflection on how the cultural heritage of a place might constitute an effective resilience tool for the impacted populations, with a focus on young citizens. As a transversal element in achieving the 17 Sustainable Development Goals, cultural heritage can play a significant role in the establishment of a “risk culture” among residents and visitors, promoting the adoption of responsible behaviours for one’s own safety in an emergency and for the better preservation of cultural assets. In a broader perspective, this strategy will support “climate-sensitive” tourism and citizenship, which can facilitate adaptation to local climate change impacts. Full article

In our interconnected society, prioritizing the resilience and sustainability of road infrastructure has never been more critical, especially in light of growing environmental and climatic challenges. By harnessing data from various sources, we can proactively enhance our ability to detect road damage. This approach will enable us to make well-informed decisions for timely maintenance and implement effective mitigation strategies, ultimately leading to safer and more durable road systems. This paper presents a new method for detecting road potholes during low-light conditions, particularly at night when influenced by street and traffic lighting. We examined and assessed various advanced machine learning and computer vision models, placing a strong emphasis on deep learning algorithms such as YOLO, as well as the combination of Grad-CAM++ with feature pyramid networks for feature extraction. Our approach utilized innovative data augmentation techniques, which enhanced the diversity and robustness of the training dataset, ultimately leading to significant improvements in model performance. The study results reveal that the proposed YOLOv11+FPN+Grad-CAM model achieved a mean average precision (mAP) score of 0.72 for the 50–95 IoU thresholds, outperforming other tested models, including YOLOv8 Medium with a score of 0.611. The proposed model also demonstrated notable improvements in key metrics, with mAP50 and mAP75 values of 0.88 and 0.791, reflecting enhancements of 1.5% and 5.7%, respectively, compared to YOLOv11. These results highlight the model’s superior performance in detecting potholes under low-light conditions. By leveraging a specialized dataset for nighttime scenarios, the approach offers significant advancements in hazard detection, paving the way for more effective and timely driver alerts and ultimately contributing to improved road safety. This paper makes several key contributions, including implementing advanced data augmentation methods and a thorough comparative analysis of various YOLO-based models. Future plans involve developing a real-time driver warning application, introducing enhanced evaluation metrics, and demonstrating the model’s adaptability in diverse environmental conditions, such as snow and rain. The contributions significantly advance the field of road maintenance and safety by offering a robust and scalable solution for pothole detection, particularly in developing countries. Full article

Forest ecosystems are increasingly facing challenges related to overexploitation and climate and land-use change, thereby posing a threat to the myriad benefits they provide. Forest management is the only tool for ensuring that adaptation, mitigation, and biodiversity conservation in forest ecosystems are maintained and further enhanced over time. However, forest managers might not have clear guidance on how to ensure these goals are achieved through their practices, which is why a goal-driven management framework is proposed and discussed in this study. The proposed framework provides an overview of the possible effects of alternative forest management practices on climate services, biodiversity conservation, and wood extraction and production. Based on this framework, the following “should-haves” for forest management towards achieving multiple goals are outlined: consideration of the trade-offs between biodiversity and other benefits; the need to reflect on time and space variability; and incorporation of climate sensitivity. The suggested actions are as follows: improve the monitoring framework; implement more robust modeling tools; and further consider policy trajectories. Full article

Aerosol optical and microphysical properties determine their radiative capabilities, climatic impacts, and health effects. Satellite remote sensing is a crucial tool for obtaining aerosol parameters on a global scale. However, traditional physical and statistical retrieval methods face bottlenecks in data mining capacity as the volume of satellite observation information increases rapidly. Artificial intelligence methods are increasingly applied to aerosol parameter retrieval, yet most current approaches focus on end-to-end single-parameter retrieval without considering the inherent relationships among multiple aerosol properties. In this study, we propose a sequence-to-sequence aerosol parameter joint retrieval algorithm based on the transformer model S2STM. Unlike conventional end-to-end single-parameter retrieval methods, this algorithm leverages the encoding–decoding capabilities of the transformer model, coupling multi-source data such as polarized satellite, meteorological, model, and surface characteristics, and incorporates a physically coherent consistency loss function. This approach transforms traditional single-parameter numerical regression into a sequence-to-sequence relationship mapping. We applied this algorithm to global observations from the Chinese polarimetric satellite (the Particulate Observing Scanning Polarimeter, POSP) and simultaneously retrieved multiple key aerosol optical and microphysical parameters. Event analyses, including dust and pollution episodes, demonstrate the method’s responsiveness in hotspot regions and events. The retrieval results show good agreement with ground-based observation products. This method is also adaptable to satellite instruments with various configurations (e.g., multi-wavelength, multi-angle, and multi-dimensional polarization) and can further improve its spatiotemporal generalization performance by enhancing the spatial balance of ground station training datasets. Full article

Climate change and human interventions have exerted a long-term influence on variations in continental streamflow. Despite this, the precise mechanisms by which these factors regulate the change in streamflow remain inadequately understood, especially in arid alpine regions, due to the limited number of observations which exacerbates difficulties in comprehensively assessing streamflow alterations. Consequently, assessing the impacts of climate change and human interventions on streamflow is a challenge in data-scarce regions. Here, using the Zamu River as an example, we analyzed streamflow changes in arid alpine regions using a method that integrates the Patch-generated Land Use Simulation model, the Soil and Water Assessment Tool, and the Coupled Model Intercomparison Project Phase 6. Our analysis highlighted that climate change primarily drove streamflow variations in the Zamu River, accounting for over 80% of the observed contributions. This influence was further amplified by the effects of future climate and changes in land use and land cover, resulting in increased streamflow. Additionally, precipitation emerged as the main factor driving the rise in streamflow. These findings emphasize the significant impact of climate change on water cycles in arid alpine regions and underscore the necessity for tailored water resource management strategies to ensure sustainable regional development and effective climate change adaptation. Full article

This study examines the trends in heatwave characteristics across mainland Portugal from 1980/1981 to 2022/2023, utilising ERA5-Land reanalysis data. To achieve this, the study applies the Heatwave Magnitude Index (HWMI) to identify heatwave days for minimum (T_min) and maximum (T_max) temperatures across 15 grid-points representing Portugal’s diverse geography and climate. Three key annual parameters are analysed: the number of heatwave days (ANDH), the average temperature during heatwaves (AATW), and the intensity of heatwave events (AIHD). Results reveal a consistent increase in heatwave persistence throughout mainland Portugal, with more pronounced trends observed for T_max compared to T_min. ANDH T_min shows upward trends across all grid-points, with increases ranging from 0.8 to 4.2 days per decade. ANDH T_max exhibits even more significant increases, with 11 out of 15 grid-points showing statistically significant rises, ranging from 2.2 to 4.4 days per decade. Coastal areas, particularly in the south, demonstrate the most substantial increases in heatwave persistence. The intensity of heatwaves, as measured by AIHD, also shows positive trends across all grid-points for both T_min and T_max, with southern locations experiencing the most significant increases. The study also discusses decadal trends in annual averages of T_min and T_max, as well as extreme measures such as annual minimum (AMIN) and annual maximum (AMAX), daily temperatures spatially represented across mainland Portugal. These analyses reveal widespread warming trends, with more pronounced increases in T_max compared to T_min. The AMIN and AMAX trends further corroborate the overall warming pattern from the heatwave analyses, with notable spatial variations observed. The findings indicate a substantial worsening in the occurrence, duration, and intensity of heatwave events. This increased persistence of heatwaves, especially evident from the early 2000s onwards, suggests a potential climate regime shift in mainland Portugal. The results underscore the need for adaptive strategies to address the growing challenges posed by more frequent and intense heatwaves in the region. Full article

In the context of climate change, characterized by an increase in average precipitation, agricultural pests have demonstrated enhanced adaptability to high humidity and other challenging environmental conditions, thereby intensifying the need for effective prevention and control measures. Among these pests, Megoura crassicauda (Hemiptera: Aphididae) represents a significant threat to both crop yield and quality. The aim of this study was to investigate the physiological behavioral changes and the regulatory mechanisms of trehalose metabolism in M. crassicauda under conditions of high-humidity stress. Additionally, we sought to explore the survival strategies and water regulation mechanisms employed by this insect, with the goal of identifying new biological targets for its management. The findings indicated that, despite an increase in environmental humidity, there was no significant difference in the survival rate of M. crassicauda. However, a reduction in developmental duration and reproductive capacity was observed. Increased humidity correlated with elevated trehalose levels and decreased glycogen content. Notably, although the relative expression levels of trehalase (TRE) and Trehalose-6-phosphate synthase (TPS) were downregulated, Trehalose-6-phosphate phosphatase (TPP) expression was upregulated. These results suggest that high humidity environments significantly influence the growth, development, and trehalose metabolism of M. crassicauda. It appears that adaptations to high-humidity conditions in M. crassicauda are facilitated by modulations in the types and distribution of sugars within their bodies, achieved through alterations in the expression of genes associated with trehalose metabolism. In summary, the results of this study indicate that high humidity significantly affects the development and sugar metabolism of M. crassicauda. These changes may represent one of the potential mechanisms underlying its environmental adaptation and migration. This insight provides valuable assistance for predicting the occurrence and migration of the pest M. crassicauda. Full article

Plant sterols (STs) are essential for the regulation of fluidity and permeability of cell membranes, which have a wide structural diversity. The dynamics of changes in sterol molecular species in leaves of a valuable cereal crop, spring oat (Avena sativa L.), as a function of different sowing dates were studied. In particular, 11 molecular species of sterols (STs) and triterpenoids in A. sativa leaves were identified by GC-MS. Triterpenoids Ψ-taraxasterol, cyclolaudenol, and betulin were identified in A. sativa leaves for the first time, which may be related to adaptation to extreme climatic conditions of the cryolithozone. The dynamics of STs and triterpenoids changes were revealed during growth and development of the standard term and late summer sowing term during A. sativa hardening to low ambient temperatures. The ratio of β-sitosterol to campesterol was found to increase in response to low positive air temperatures, while the ratio of stigmasterol to β-sitosterol remained constant from mid-September to the end of October. Overall, leaves of standard-seeded A. sativa plants maintained higher levels of absolute STs and triterpenoids by 1.9-fold than leaves of late-seeded A. sativa plants. It is suggested that the ability of A. sativa plants to synthesize β-sitosterol and stigmasterol may be part of an evolutionary adaptation process to cope with wide temperature fluctuations and to maintain important membrane-bound metabolic processes. Full article

Rice is the staple diet for most of the world’s population and is considered a major staple crop in China. Anhui province of China is among the leading provinces for rice production, consumption, and commodities; it is well-known as the “land of fish and rice”. Japonica rice cultivation in Anhui Province is mainly categorized into late-maturing medium, early-maturing medium, and early-maturing late japonica. This review explores the suitable ecological zone distribution and corresponding climate characteristics of the three types of japonica rice in Anhui Province. Data on japonica rice varieties approved in the province over the past twenty years were collected, illustrating the development process of japonica rice varieties in the province and their quality and resistance to rice blast disease. The review shows that the yield is positively and significantly correlated with agronomic traits, such as the number of effective panicles and the total number of grains per panicle, plant height, etc. In addition, it elucidates the major problems faced by Anhui’s japonica rice breeding and cultivation, such as frequent events of high temperatures, rice blast disease, and medium to low soil fertility levels. Considering the existing issues in breeding japonica rice varieties in Anhui Province, this review proposes a strategy for breeding high-yield and disease-resistant japonica rice varieties, particularly varieties adaptable to medium and low fertility soil conditions. In brief, this article provides a theoretical basis and practical recommendations for the sustainable development of japonica rice in the Anhui Province of China. Full article

Bud dormancy is a critical adaptive trait in woody plants, essential for enduring harsh winter conditions. The relationship between bud break timing and cold resistance is complex and has been a subject of debate. This study utilizes a Genome-Wide Association Study (GWAS) on 201 natural mulberry populations to identify the MaFAD2 gene, which shows the strongest association with bud break timing. Known for its role in cold resistance, MaFAD2′s link to bud break timing suggests a direct correlation between these traits. Expression analysis of MaFAD2 in mulberry trees indicates peak activity in dormant buds, declining as dormancy ends. Selective sweep analysis on germplasms from contrasting climates reveals positive selection in MaFAD2 in cold-resistant Uzbek germplasms. Overexpression of MaFAD2 in early-budding germplasms significantly delays bud break, confirming its regulatory role. These findings highlight MaFAD2 as a key determinant of cold tolerance variability among mulberry germplasms, with its expression directly correlated with bud break timing. This provides a molecular basis for selecting cold-resistant mulberry germplasms based on bud break timing in breeding programs. Full article

Wildfires pose a serious threat to ecosystems and human safety, and with the backdrop of global climate change, the prediction of forest fires has become increasingly important. Traditional machine learning methods face challenges in forest fire prediction, such as difficulty identifying feature parameters, manual intervention in model selection, and hyperparameter tuning, which affect prediction accuracy and efficiency. This study proposes an analytical framework for forest fire prediction based on Automated Machine Learning (AutoML) technology to address the challenges traditional machine learning methods face in forest fire prediction. We collected meteorological, topographical, and vegetation data from Guangxi Province, with meteorological data covering 1994 to 2023, providing comprehensive background information for our prediction model. Using the prediction model, which was constructed with the AutoGluon framework, the experimental results indicate that models under the AutoGluon framework (e.g., KNeighborsDist classifier) significantly outperform traditional machine learning models in terms of accuracy, precision, recall, and F1-Score, with the highest accuracy rate reaching 0.960. Model error analysis shows that models under the AutoGluon framework perform better in error control. This study provides an efficient and accurate method for forest fire prediction, which is of great significance for decision-making in forest fire management and for protecting forest resources and ecological security. Full article

This study examines the impacts of climate-induced externalities on the stability of agroecosystems and the ecosystem services they provide. Using the PRISMA approach, we review literature published from 2015 to 2024. The study identifies how extreme weather events such as droughts, floods, heatwaves, and altered precipitation patterns disrupt the provisioning, regulating, and supporting services critical to food security, soil fertility, water purification, and biodiversity. Our findings show a continued increase in climate extremes, raising concerns about food security, environmental resilience, and socio-economic stability. It also reveals that regions dependent on rain-fed agriculture, such as parts of Africa, Asia, and the Mediterranean, are particularly vulnerable to these stressors. Adaptation strategies, including conservation agriculture, crop diversification, agroforestry, and improved water management, are identified as crucial for mitigating these impacts. This study emphasises the importance of proactive, policy-driven approaches to foster climate resilience, support agroecosystem productivity, and secure ecosystem services critical to human well-being and environmental health. Full article

Non-satisfactory bread-making quality in wheat, a Tajik staple, hampers food security in Tajikistan and calls for plant breeding efforts. Here, methods were searched for to study grain protein composition, which is of use for Tajik plant breeding to improve bread-making quality. Size-exclusion high-performance liquid chromatography (SE-HPLC) was used to determine protein composition in 22 wheat varieties and breeding lines grown in two locations, which were then compared with the specific protein composition evaluated using electrophoresis and previous results from Tajik breeding and farmer-grown wheat. As Tajik wheat generally showed a large variation in high-molecular-weight glutenin subunit (HMW-GS) composition, with several allelic variants in the same line, single-seed selection was required when using this methodology in breeding for improved bread-making quality, and such an evaluation willalso result in more homogenous lines for protein composition. SE-HPLC was found to be a suitable tool to evaluate protein composition in the current Tajik wheat material with a heterogeneous protein composition, which might be advantageous for adaptation to the local and future climate. However, more easy-to-handle and high-throughput methods, e.g., marker-assisted selection, could be preferable alternatives for studying protein composition in wheat and for use in breeding for increased bread-making quality to increase food security in Tajikistan. Full article

Screen systems are often neglected in practice. This can lead to local flooding, pollution of receiving watercourses, blockages of channels by debris, and safety problems for children playing. The aim of this case study is therefore to protect below-ground channels and people, prevent flooding, improve water quality, and save personnel costs through a new screen system maintenance, repair, and upgrade methodology. The results show that repairing or enlarging the screens optimizes their functionality and reduces the risk of flooding. A particular focus is on increasing the screen dimension from one- and two-dimensional to three-dimensional screens. The new variable safety priority and the bar spacing increase with the passage area. Screens at large discharges should therefore be prioritized. Cleaning sand traps reduces the risk of pipe blockages and improves the water quality of receiving waters. Fine particles often have too high nutrient and oxygen demand values. The installation of pre-screens can increase the efficiency of the main screens. Optimization of travel routes for maintenance teams can be achieved by better planning maintenance routes. Adapting and maintaining screens to climate change by applying the novel prioritization method is likely to be successful. This should include prioritized inspections, repairs, and adjustments to screen structures. Full article