Search Results (2,794)

Cold chain logistics possesses unique characteristics, particularly the necessity to maintain low temperatures within containers throughout the distribution process. Real-world traffic conditions, such as congestion, significantly impact the efficiency of cold chain logistics and contribute to increased carbon emissions. To foster green and sustainable development in this sector, a carbon emission trading mechanism has been established, incentivizing companies to invest in energy conservation and emission reduction through economic transactions. This study introduces a multi-objective optimization model for route planning in port seafood logistics, integrating considerations of traffic congestion and zero-carbon transportation. To accurately reflect real-world traffic conditions, a time-dependent function is utilized to model traffic congestion within actual road networks. The road segments are divided, and the travel time for vehicles in each segment is computed. Additionally, the costs associated with the distribution process are analyzed, leading to the development of a multi-objective optimization model aimed at minimizing both distribution costs and zero-carbon transportation costs. The proposed model demonstrates significant economic savings and environmental advantages, providing a theoretical foundation for decision-making processes that support the green and sustainable development of port seafood logistics. Full article

Effective tunnel construction and demolition (C&D) waste management is a critical issue in the context of sustainable development, and C&D waste management measures guided by 3R principles (Reduce, Reuse, and Recycle) comply with the circular economy. In this study, an extended theory of planned behavior model based on the existing literature was proposed to identify the drivers of tunnel construction managers’ intention to implement effective waste management measures; then, the respondents were classified into four groups according to personality traits to explore the effects of personality profile on the heterogeneity in relationships between psychological drivers and C&D waste management intention and behaviors. The results show that all TPB constructs, policies, and environmental concern are significant predictors of managers’ intention to manage C&D waste properly. Then, considerable variance in the driving effects of various psychological drivers across different groups is witnessed. For the positive and temperate participants, subjective norms and policies are the most effective driving factors. However, PBC and environmental concern show a stronger relationship with the conservative and introverted participants’ intentions to adopt effective waste management measures. The findings are beneficial to developing corresponding management measures to promote effective C&D waste management. Full article

As the global population ages, so too does the prevalence of older people with chronic kidney disease (CKD). Helping people age well with CKD and supporting older people with end-stage kidney disease (ESKD) to make personalized decisions regarding kidney replacement therapy (KRT) or conservative care (CC) are an essential component of care. However, these factors are relatively underreported in both the fields of nephrology and geriatric medicine, and prospective, randomized evidence is lacking. This narrative review article, authored by both nephrologists and geriatricians, discusses specific geriatric issues that arise in older people with CKD and why they matter. The available evidence for KRT or CC in older people with frailty is outlined. The importance of performing a comprehensive geriatric assessment, or a modified nephrogeriatric assessment, to ensure a systematic evaluation of the person’s medical problems and life needs, goals, and values is described. We consider different models of nephrogeriatric care and how they may be implemented. Kidney supportive care—addressing an individual’s symptoms and overall well-being alongside the more traditional nephrological principles of preventing disease progression and optimizing risk—is highlighted throughout the article. We outline ways of identifying the later stages of a person’s disease journey, when transition to palliative care is indicated, and elaborate methods of preparing patients for this through multidisciplinary advance care planning. Finally, we discuss practice and systems for nephrogeriatric care in five different European countries and consider future directions, challenges, and highlights in this rapidly evolving, increasingly relevant field. Full article

Land use conflicts represent an increasing challenge to sustainable development, particularly in regions undergoing rapid urbanization. This study investigated the spatiotemporal dynamics of land use conflicts and their ecological implications in Tianshui City from 1980 to 2020. The main objectives were to identify patterns of spatial heterogeneity, explore the driving factors behind these conflicts, and analyze their relationship with the ecological risks. The results indicate the following findings. In terms of spatiotemporal heterogeneity, early land use changes were primarily driven by structural factors, such as topography and climate, with a Nugget/Still ratio of <0.30 observed from 1980 to 2000. After 2000, however, stochastic factors, including an average annual urbanization rate increase of 5.2% and a GDP growth rate of 9.1%, emerged as the dominant drivers, as reflected in a Nugget/Still ratio > 0.36. Regarding conflict intensity, high-conflict areas expanded by approximately 1110 square kilometers between 1980 and 2020, predominantly concentrated in fertile agricultural regions such as the Weihe River Basin and urban core areas. Conversely, non-conflict zones decreased by 38.7%. In terms of ecological risk correlation, bivariate LISA cluster analysis revealed a significant spatial autocorrelation between severe land use conflicts and ecological risks (Moran’s I = 0.62, p < 0.01). High-risk clusters in areas transitioning from arable land to built-up land increased by 23% after 2000. Predictions based on the future land-use simulation (FLUS) model suggest that by 2030, high-intensity conflict areas will expand by an additional 16%, leading to intensified competition for land resources. Therefore, incorporating ecological safety thresholds into land spatial planning policies is essential for reconciling the conflicts between development and conservation, thereby promoting sustainable land use transitions. Full article

The urbanization and the expansion of human settlements led to the adaptation of many animal species to living close to humans, often using buildings for roosting. Panel buildings are particularly attractive to rock-dwelling animals such as swifts, swallows, pigeons, and bats due to their numerous cracks and crevices. The abundance of these structures in Eastern Europe has led to the establishment of numerous bird and bat colonies in the cities. However, the recent renovation and insulation of these buildings, while beneficial to residents, threatens the roosts. Construction workers are sometimes unaware of animal presence and inadvertently destroy nests or colonies. Rapid assessments before renovation are essential to rescue individuals and ensure the planning of alternative roosts for bats and birds. We conducted a pilot survey of 61 residential buildings in five municipalities in Bulgaria: Razgrad, Popovo, Haskovo, Dimitrovgrad, and Bobov Dol, to assess bird and bat biodiversity. We performed field assessments using direct observation, thermal cameras, ultrasonic detection, sunset counts, and endoscopic cameras. The most commonly detected bird species were the house martin, barn swallow, common swifts, the Eurasian jackdaw, pigeons, and sparrows. The most commonly detected bat species were the common pipistrelle, noctule, and Kuhl’s pipistrelle. Additionally, we discuss the specifics of the “soviet-type” buildings as nesting facilities for pigeons and the impact of the pigeons on the “micro ecology” of the blocks. Our study aimed to guide conservation actions and awareness during the expanding renovation efforts of old buildings in Bulgaria. Full article

Mycoplasma pneumoniae (MP) is the main culprit of community-acquired pneumonia. Commonly used laboratory testing methods have many shortcomings. Serological diagnosis has low sensitivity, causing false negatives, while a quantitative real-time polymerase chain reaction (qPCR) requires large equipment and professional staff. To make up for these shortcomings, we proposed a label-free, low-cost, and small-sized ion-sensitive field-effect transistor (ISFET) array based on a low-buffered loop-mediated isothermal amplification (LAMP) assay. A complementary metal oxide semiconductor (CMOS)-based ISFET array with 512 × 512 sensors was used in this system, which responds specifically to H⁺ with a sensitivity of 365.7 mV/pH. For on-chip amplification, a low-buffered LAMP system designed for the conserved sequences of two genes, CARDS and gyrB, was applied. The rapid release of large amounts of H⁺ in the low-buffered LAMP solution led to a speedy increase in electrical signals captured by the ISFET array, eliminating the need for a sophisticated temperature cycling and optical system. The on-chip results showed that the device can accurately complete MP detection with a detection limit of about 10³ copies/mL (approximately 1 copy per reaction). In the final clinical validation, the detection results of eight throat swab samples using the ISFET sensors were fully consistent with the clinical laboratory diagnostic outcomes, confirming the accuracy and reliability of the ISFET sensors for use in clinical settings. And the entire process from sample lysis to result interpretation takes about 60 min. This platform has potential to be used for the point-of-care testing (POCT) of pathogen infections, providing a basis for the timely adjustment of diagnosis and treatment plans. Full article

Understanding the changes in ecosystem quality caused by land use changes is critical for sustainable urban development and environmental management. This study investigates the spatial-temporal evolution of ecosystem quality in Wuhan from 2000 to 2020 and forecasts future trends under multiple land use scenarios for 2030. Using a “foundation-function-structure” assessment framework, we integrate system dynamics (SD), the Patch-generating Land Use Simulation (PLUS) model, and a neural network-based ecosystem quality inversion model to analyze land use transitions and their ecological impacts. The results indicate that rapid urban expansion has significantly contributed to the decline of cropland and forest areas, while impervious surfaces have increased, leading to notable ecological degradation. Simulations for 2030 under three scenarios—ecological protection, natural development, and economic priority—demonstrate that the ecological protection scenario yields the highest ecosystem quality, preserving landscape connectivity and mitigating degradation risks. In contrast, the economic priority scenario results in extensive urban expansion, exacerbating ecological stress. Under the ecological protection scenario from 2020 to 2023, the decline in ecosystem quality was primarily due to the expansion of urban fringes and the erosion of forest and grassland areas. The increase in ecosystem quality was mainly attributed to the transformation of early urban edge conflict zones into stable urban edge interior areas and the integration of fragmented ecological land patches. These findings highlight the need for strategic land use planning to balance economic growth and environmental conservation. This study provides a robust methodological framework for assessing and predicting ecosystem quality changes, offering valuable insights for policymakers and urban planners striving for sustainable development. Full article

Background/Objectives: The integration of Augmented Reality (AR) and Artificial Intelligence (AI) in educational applications presents an opportunity to enhance learning outcomes in young users. This study focuses on ARFood, a serious game designed to teach Generation Alpha about nutritional health and environmental sustainability. The objective is to evaluate and improve the effectiveness of the app’s AI-driven feedback mechanisms in achieving specific educational goals in these domains. Methods: ARFood features two AI-powered Non-Player Characters (NPCs), each programmed to evaluate virtual shopping carts created by users. The nutritional NPC provides feedback on dietary choices, while the sustainability NPC assesses environmental impacts. Ninety-three participants were involved, generating 83 virtual carts that were evaluated by both NPCs. Each NPC’s feedback was assessed for alignment with five predefined educational objectives per theme using a zero-shot RoBERTa classifier. An iterative process was employed to refine the NPC prompts, increase the weight of underrepresented objectives, and re-evaluate virtual carts until all objectives were satisfactorily addressed. Results: Initial evaluations revealed uneven alignment across educational objectives, particularly in areas such as resource conservation and balanced diet planning. Prompt refinement led to a significant improvement in feedback quality, with the final iterations demonstrating comprehensive coverage of all educational objectives. Conclusions: This study highlights the potential of AR and AI in creating adaptive educational tools. Iterative prompt optimization, supported by zero-shot classification, was effective in enhancing the app’s ability to deliver balanced, goal-oriented feedback. Future applications can leverage this approach to improve educational outcomes across various domains. Full article

The hydraulic model serves as an effective tool for operational simulation, dispatch decision-making, and engineering planning in water distribution systems (WDSs). The increasing complexity of large-scale networks and the growing number of monitoring devices present both challenges and opportunities for the online calibration of WDSs in terms of efficiency and accuracy. To address these issues, this paper introduces a novel strategy, Flowmeter-Monitoring Path-Partitioning (FMPP), for nodal demand calibration of hydraulic models. FMPP partitions nodes based on the monitoring paths of flowmeters, which include all downstream nodes of a given flowmeter. Then, a system of equations is formulated from the mass and energy conservation, and an iterative optimization process is employed to calibrate the nodal demands. This method enables the partitioning of nodes to achieve the optimal granularity, enabling each flowmeter to be calibrated individually and also reducing the calibration parameters through node grouping. The performance of the proposed method has been validated through two comprehensive case studies, demonstrating its superiority to conventional calibration techniques in terms of accuracy, computational efficiency, and practical applicability in real-time nodal demand estimation. This approach meets the requirements for the real-time calibration of nodal demand in complex large-scale pipe networks. Full article

In recent years, global warming has become a major driver of biodiversity loss, significantly impacting various vertebrate species, including mammals. Consequently, numerous smaller species face extinction risks due to anthropogenic factors as well as inadequate assessments and conservation planning. Thus, this study focuses on two recently described endemic giant flying squirrel species under the Petaurista genus—Petaurista mishmiensis and Petaurista mechukaensis—found in Arunachal Pradesh, India. Using an ensemble species distribution model (SDM), this research delineates suitable habitats for these lesser-known species and evaluates the effects of climate change and habitat fragmentation on these areas. This analysis aims to inform a comprehensive management plan for their conservation. The ensemble model identified suitable habitat patches for the two species, extending beyond their current IUCN-designated ranges in Arunachal Pradesh. Under present conditions, P. mishmiensis has the largest predicted suitable area (9213 sq. km), followed by P. mechukaensis (6754 sq. km). However, future projections reveal alarming habitat losses ranging from 13.45% to 55.86% across the study area. This study also highlights severe habitat fragmentation throughout the state as viable patches for P. mishmiensis are drastically reduced in size, resulting in many being completely lost and the remaining areas being closer together. However, the P. mechukaensis experiences significant disintegration, resulting in numerous smaller, more dispersed patches within Arunachal Pradesh. Hence, to address these challenges, this study recommends several actions such as genetic assessments to confirm evolutionary relationships, evaluations of corridor connectivity, and comprehensive field studies. Furthermore, establishing joint forest conservation committees involving local communities, forest personnel, defense forces, naturalists, and scientists are also encouraged. Ultimately, this research provides critical insights for guiding future field studies across Arunachal Pradesh’s vast landscapes and supports the development of detailed species management plans to protect these endemic flying squirrels. Full article

Understanding global patterns of tree canopy height and density is essential for effective forest management and conservation planning. This study examines how these attributes vary along latitudinal gradients and identifies key climatic drivers influencing them. We utilized high-resolution remote sensing datasets, including a 10 m resolution canopy height dataset aggregated to 1 km for computational efficiency, and a 1 km resolution tree density dataset derived from ground-based measurements. To quantify the relationships between forest structure and environmental factors, we applied nonlinear regression models and climate dependency analyses, incorporating bioclimatic variables from the WorldClim dataset. Our key finding is that latitude exerts a dominant but asymmetric control on tree height and density, with tropical regions exhibiting the strongest correlations. Tree height follows a quadratic latitudinal pattern, explaining 29.3% of global variation, but this relationship is most pronounced in the tropics (−10° to 10° latitude, R² = 91.3%), where warm and humid conditions promote taller forests. Importantly, this effect differs by hemisphere, with the Southern Hemisphere (R² = 67.1%) showing stronger latitudinal dependence than the Northern Hemisphere (R² = 35.3%), indicating climatic asymmetry in forest growth dynamics. Tree density exhibits a similar quadratic trend but with weaker global predictive power (R² = 7%); however, within the tropics, latitude explains 90.6% of tree density variation, underscoring strong environmental constraints in biodiverse ecosystems. Among climatic factors, isothermality (Bio 3) is identified as the strongest determinant of tree height (R² = 50.8%), suggesting that regions with stable temperature fluctuations foster taller forests. Tree density is most strongly influenced by the mean diurnal temperature range (Bio 2, R² = 36.3%), emphasizing the role of daily thermal variability in tree distribution. Precipitation-related factors (Bio 14 and Bio 19) moderately explain tree height (~33%) and tree density (~25%), reinforcing the role of moisture availability in structuring forests. This study advances forest ecology research by integrating high-resolution canopy structure data with robust climate-driven modeling, revealing previously undocumented hemispheric asymmetries and biome-specific climate dependencies. These findings improve global forest predictive models and offer new insights for conservation strategies, particularly in tropical regions vulnerable to climate change. Full article

In sub-Saharan Africa, protected areas are located in close proximity to communities, leading to frequent negative encounters between humans and wildlife. This is coupled with increased pressure from communities seeking park resources to support their livelihoods. To address this, land use plans have been designed around protected areas. For example, in Kenya, wildlife conservancies have been created out of private and community lands. The aim of these conservancies is to contribute to improved livelihoods, reduce human–wildlife conflicts, and increase support for conservation. However, limited research exists on how the conservancies have achieved their aims among local communities. This study focuses on the Maasai Mara region in Kenya and examines how livelihoods and human–wildlife conflicts influence support for conservation among conservancy members. Data were gathered from 411 households adjacent to the reserve through a survey conducted in June and July 2024. The findings indicate a high incidence of human–wildlife conflict and improved security in health and education only. Despite this, there is high satisfaction with the conservancy model and strong support for conservation. Although these findings highlight the significance of conservancies in mitigating human–wildlife conflict, enhancing livelihoods, and garnering conservation support, more attention is needed for food and financial security. Full article

The contribution aims to summarize the huge amount of work carried out by CEN TC 346, the European committee for standardization of cultural heritage, from its establishment in 2004 to the present. A specific European standardization activity in the field of cultural heritage conservation was proposed to ensure a shared, science-based approach in order to guarantee best practices, more effective planning and implementation, and obtaining the best results. The work program was initially based on five working groups which had the responsibility to manage a few standardization projects according to the human resources initially available. Over time, the work program was implemented thanks to the active contributions of European member countries. Notwithstanding, standards were developed according to a need-based approach; it is possible to individuate a certain coherence in their development, very similar to a matrix approach. As a consequence, eight topics were presented and discussed, and four of them were strictly related to the issues discussed in the general document related to the conservation process. The remaining topics dealt with building management for storage heritage collections, monitoring of archaeological deposits for preservation in situ, handling of movable objects and finally the procurement of conservation services and works. The potential direct impact on the environment and also benefits to the sustainability of cultural heritage have been taken into account for each standard proposed. Full article

Flood risks are escalating globally due to unplanned urban expansion and the impacts of climate change, posing significant challenges for urban areas and necessitating effective mitigation strategies. Nature-based solutions (NBSs) have emerged as innovative and sustainable approaches for managing flood risks. The International Union for Conservation of Nature (IUCN) defines NBSs as actions that conserve, manage, and restore natural and modified ecosystems to address societal concerns while benefiting both people and the environment. This research focuses on developing NBS strategies for the most flood-prone area within Kochi, a city highly vulnerable to flooding. The study begins with a comprehensive site examination to identify flood sources and causes in Kochi, aiding in selecting flood vulnerability indicators. An analytical framework incorporating flood risk assessment and exposure studies using physical and social indicators, alongside GIS mapping techniques, revealed that approximately half of Kochi is affected. The study identified key vulnerability hotspots, particularly within the Central Business District (CBD), where high population density and inadequate infrastructure exacerbate flood risks. Proposed NBS interventions include restoring natural floodplains, enhancing canal capacities, creating urban forests, and establishing green infrastructure like permeable pavements and rainwater harvesting systems. Key findings emphasize the effectiveness of integrating NBSs with traditional flood management strategies, forming a mixed flood control system. These interventions mitigate flood risks, improve biodiversity, reduce the urban heat island effect, and enhance community well-being. Importantly, the research underscores the role of public participation and community-driven maintenance plans in ensuring the sustainability of NBS interventions. Aligning these strategies with Kochi’s Master Plan 2040 ensures coherence with broader urban planning and climate resilience goals. The research anticipates changes in climate, land use patterns, and urban dynamics to inform NBS suitability in Kochi. Ultimately, the research demonstrates how implementing NBSs can deliver a range of socio-environmental benefits, significantly influencing urban development in vulnerable zones. By advocating for the integration of NBSs into urban infrastructure planning, this study offers a blueprint for resilient and sustainable flood management strategies that are applicable to other coastal cities facing similar challenges. Full article

This study addresses the urgent need for effective methods to monitor and conserve Araucaria angustifolia, a critically endangered species of immense ecological and cultural significance in southern Brazil. Using high-resolution satellite images from Google Earth, we apply the YOLOv7x deep learning model to detect this species in two distinct urban contexts in Curitiba, Paraná: isolated trees across the urban landscape and A. angustifolia individuals within forest remnants. Data augmentation techniques, including image rotation, hue and saturation adjustments, and mosaic augmentation, were employed to increase the model’s accuracy and robustness. Through a 5-fold cross-validation, the model achieved a mean Average Precision (AP) of 90.79% and an F1-score of 88.68%. Results show higher detection accuracy in forest remnants, where the homogeneous background of natural landscapes facilitated the identification of trees, compared to urban areas where complex visual elements like building shadows presented challenges. To reduce false positives, especially misclassifications involving palm species, additional annotations were introduced, significantly enhancing performance in urban environments. These findings highlight the potential of integrating remote sensing with deep learning to automate large-scale forest inventories. Furthermore, the study highlights the broader applicability of the YOLOv7x model for urban forestry planning, offering a cost-effective solution for biodiversity monitoring. The integration of predictive data with urban forest maps reveals a spatial correlation between A. angustifolia density and the presence of forest fragments, suggesting that the preservation of these areas is vital for the species’ sustainability. The model’s scalability also opens the door for future applications in ecological monitoring across larger urban areas. As urban environments continue to expand, understanding and conserving key species like A. angustifolia is critical for enhancing biodiversity, resilience, and addressing climate change. Full article