Adaptive Management Strategies Research Articles

Immediate Effect of Floating Solar Energy Deployment on Greenhouse Gas Dynamics in Ponds.

Floating photovoltaic (FPV) solar energy offers promise for renewable electricity production that spares land for other societal benefits. FPV deployment may alter greenhouse gas (GHG) production and emissions from waterbodies by changing physical, chemical, and biological processes, which can have implications for the carbon cost of energy production with FPV. Here, we use an ecosystem-scale experiment to assess how GHG dynamics in ponds respond to installation of operationally representative FPV. Following FPV deployments of 70% array coverage, daily whole-pond GHG emissions increased by 26.8% on a carbon dioxide-equivalent (CO2-eq) basis, and dissolved oxygen availability rapidly decreased. Despite increased emissions following FPV deployment, FPV-derived GHG emissions from waterbodies are likely lower than landscape GHG emissions associated with terrestrial solar and hydropower production on a CO2-eq kWh-1 basis. Adaptive management strategies like bubbler installation may reduce the magnitude of FPV impacts on GHG and dissolved oxygen dynamics.

Investigating the potential of ICEYE-SAR data in storm damage detection in a coniferous forest with rugged terrain

ABSTRACT Adaptive forest management strategies require accurate detection of forest disturbance, in various spatial scales. Synthetic Aperture Radar (SAR) data can provide information about the forest attributes, penetrating the canopy at different levels under any weather and lighting conditions. ICEYE consists of the largest constellation of SAR satellites, enabling very high spatial and temporal resolution. In this study, ICEYE data were investigated in the detection of storm damage, in a fir forest with complex topography which was recently hit by the Daniel storm, resulting in severe damage to the forest structure (FS) and alluvium depositions (AD). To identify the best potential for storm damage detection using ICEYE data, an unsupervised change detection approach was employed combining wavelet transform and adaptive thresholds at spatial scales of 0.5 m (R05), 1 m (R1), 2 m (R2) and 3 m (R3). Additionally, two morphological filters were applied in best-performing resolutions to assess the impact of post-processing on the detection accuracy. Finally, FS and AD damage were investigated separately in order to provide detailed information about the detection capabilities of ICEYE. The results showcased that R1 (UA = 32.35, PA = 18.34 and K = 0.31) provided the best detection performance, followed by R05 (UA = 20.62, PA = 20.12 and K = 0.19). Furthermore, the employment of morphological filters slightly increased UA and Kappa metrics in both R1(UA = 33.40 and K = 0.32) and R05 (UA = 25.60 and K = 0.24), suggesting that post-processing is necessary to mitigate false detections. Regarding the investigation of AD and FS damage, it was revealed that post-processed ICEYE data in both R05 and R1 are capable of identifying AD with satisfying accuracy (UA = 47.41, PA = 22.36, K = 0.47), while FS damage detection is more challenging (UA = 10.15%-14.40%, PA = 14.55%-15.11%, and Kappa = 0.10-0.17). Overall, this study demonstrated that ICEYE can be used to detect storm-affected areas in mountainous forest ecosystems, especially in cases where detection with other methods is not feasible.

Adaptive Deep Reinforcement Learning Energy Management for Hybrid Electric Vehicles Considering Driving Condition Recognition

Adaptive energy management strategy (EMS) can adjust the underlying control scheme of hybrid electric vehicles (HEVs) according to different external conditions, thus maintaining high performance consistently. For this reason, this study designs a double-layer EMS for a power-split HEV, which combines deep reinforcement learning (DRL) with driving condition recognition (DCR) to achieve efficient operation of powertrain under different driving conditions. At the upper layer, the long-term dependencies in velocity sequences are captured through the sequential networks to enhance the accuracy of DCR. At the lower layer, multi-objective reward functions are formulated, and the optimal weight parameters are identified for different driving conditions. Furthermore, the deep deterministic policy gradient (DDPG) algorithm is employed to dynamically optimize power flow. The simulation experiments are conducted to verify the feasibility and the energy-saving effects of the proposed strategy. The results indicate that integrating variations in driving conditions into the energy allocation of HEVs can further improve the fuel economy and maintain battery health. Specifically, the method enhances the fuel economy by an average of 10.76%, compared to a number of traditional benchmark strategies.

Policy Proposals for Mitigating Intensive Care Unit Strain: Insights from the COVID-19 Pandemic.

Intensive care unit (ICU) strain, characterized by a discrepancy between perceived or actual intensive care resources and demand, significantly impacts patient outcomes and healthcare worker well-being. The coronavirus disease (COVID-19) pandemic exacerbated ICU strain, leading to increased mortality and extended hospital stays, affecting both critically ill patients with and without COVID-19. A systematic review identified 16 leading and lagging indicators of ICU capacity strain, including queuing, premature and after-hours ICU discharge, use of temporary space, length of stay, burnout, staffing and nurse-to-patient ratio, ICU census, acuity and turnover, standardized mortality ratio, readmissions, availability of critical supplies, ventilator use, and surgery cancellation. However, variability in operational definitions and limited evidence regarding the reliability, validity, usability, and feasibility limit the value of single indicators for informed strategic planning and policy guidance. Regional and national policies and programs are essential to enhance real-time monitoring for effective management of critical care resources, and they mitigate the impact of ICU strain, facilitating complex interhospital transfers to reduce strain and ensuring comprehensive strategies for enhancing ICU resilience. Proactive regional cooperation is advocated for policy formulation, knowledge exchange, and resource allocation to anticipate and mitigate ICU strain, ensuring equitable healthcare access during global health crises. The policy implications for future preparedness emphasize the importance of evidence-based triage and adaptable patient management strategies alongside ethical considerations in resource allocation and the role of behavioral economic insights in optimizing resource utilization and collaborative healthcare practices. This multifaceted approach for addressing ICU strain comprehensively and effectively during a pandemic would promote health equity and enhance healthcare system resilience under both routine operations and crisis conditions.

Adapted RCP 4.5 and 8.5 climate change scenarios for invasive Sus scrofa in Mexico

Climate change is a common factor that contributes to the growth or decline of animal populations. The present study, conducted using the Species Distribution Model, highlights the fact that despite the recognized negative impact of wild boar (Sus scrofa) on semi-natural areas and agricultural systems worldwide, the species remains poorly studied. According to projections for Representative Concentration Pathways (RCP) 4.5 and 8.5, increased clusters of wild boar abundance are expected to emerge around fragmented species assemblages by 2070. Sus scrofa is an extremely destructive and rapidly spreading invasive species whose movement appears to be facilitated by humans. As a consequence, many endemic plants are threatened with extinction. Biological corridors between fragments with poor conservation status should be linked to priority areas for adequate protection. The creation of preserved landscapes in territories separated from semi-natural ecosystems is recommended. Additionally, these measures can help mitigate the negative impact of S. scrofa on local biodiversity. Continuous monitoring and adaptive management strategies will be crucial for long-term conservation of the affected areas. Environmental protection efforts must prioritize the restoration of natural habitats and the implementation of strict regulations to control the spread of this invasive species. Collaborations between conservation organizations, governments, farmers, and local communities are essential to ensure effective wild boar management and the preservation of arable land and forests. Moreover, public awareness campaigns about the environmental impact of wild boar and the importance of conservation efforts are critical for garnering broader support.

Changes in Distribution Ranges of Abies Species Dominating in the Forests of Northeast Asia Since the Last Glacial Maximum

ABSTRACTAimClimate variations within the stadial–interstadial cycles drive shifts in the distribution of forest dominants. This study examines how climate dynamic alters the distribution ranges of two boreal and one cold‐temperate Abies species dominating in Northeast Asia.LocationNortheast Asia: China, Japan, Korea and Russia.TaxonAbies nephrolepis, A. sachalinensis (sect. Balsamea) and A. holophylla (sect. Pseudopicea).MethodsWe developed climate envelope species distribution models (SDMs) using warmth and coldness indices, the continentality index, and proxies of rain and snow precipitation indices. We interpolated SDMs on reconstructed climates for the Last Glacial Maximum (LGM) and the Holocene Climatic Optimum (HCO) and to predicted climates for 2070 under global warming scenarios RCP2.6 and RCP8.5.ResultsDuring the LGM, the climatic optimum for all species covered extensive areas on the shelves of the Japanese and Yellow Seas, facilitated by the global sea level drop. The interglacial climatic optimum supports the expansion of A. nephrolepis and A. sachalinensis compared to the LGM, whereas the range of A. holophylla climatic niche range experiences a reduction.Main ConclusionsOur findings highlight the significant impact of climatic oscillations on the spatial distribution and ecological dynamics of Abies species in Northeast Asia. The contrasting responses of boreal and temperate fir species to glacial and interglacial periods underscore the complex interplay between climate change and the distribution of forest dominants. Projections under future warming scenarios suggest that Abies species will face further range shifts, emphasising the need for adaptive forest management and conservation strategies, especially in the southern part of their distribution.

Coral gardening in a changing climate: Rapid assessment of the 4th recorded bleaching event at the Anantara Lagoon and reef system, South Male Atoll, Maldives

Coral reefs are crucial to marine biodiversity and provide essential ecosystem services, but they face severe threats from climate change, particularly through coral bleaching events. The Maldives, renowned for its diverse coral reefs, has experienced increasing coral bleaching incidents, impacting both marine biodiversity and the tourism-dependent economy. This study investigates the effects of the 2024 coral bleaching event on coral nurseries within the Anantara Lagoon and reef system, South Male Atoll, Maldives. Monitoring was conducted across two coral nurseries in the lagoon and one coral nursery on the natural reef, focusing on species-specific responses to bleaching, predation, and survival rate. Results revealed variability in bleaching impacts among species and locations. Acropora aspera and Acropora muricata exhibited high mortality rates and increased predation, particularly at greater depths (~5 m), while Montipora digitata, Pocillopora damicornis, and Porites cylindrica showed greater resilience. The findings highlight the importance of adaptive management strategies for coral nurseries, emphasizing real-time environmental monitoring and strategic nursery placement to bolster coral reef resilience. This study underscores the need for integrated approaches combining coral restoration with broader reef management practices to enhance ecosystem recovery and sustainability

Pacific Water Security and Drought. Fostering Traditional Knowledge Concerns in the South Pacific amidst a Climate Crisis

The Pacific region faces increasing challenges of water security and drought due to a current and irreversible climate crisis. This paper examines the impacts of rising temperatures, changing weather patterns, and extreme weather events on freshwater resources across Pacific Island communities. These challenges are exacerbating water scarcity and threatening the basic needs of these vulnerable populations. Traditional knowledge and community-based adaptation strategies have long played a vital role in mitigating water-related risks. However, the severity of the current climate crisis demands an integrative approach that combines scientific research, policy action, and traditional ecological knowledge. This study explores how the integration of Indigenous practices with modern scientific approaches can enhance resilience to drought and freshwater scarcity. It underscores the importance of traditional knowledge systems in sustainable water management, while also recognizing the need for greater focus on how Pacific communities experience climate impacts and respond through local community-based adaptation. By combining local knowledge with scientific data, it is possible to develop culturally appropriate, adaptive water management strategies. This approach aims to build long-term resilience in the Pacific, ensuring communities' access to clean water and safeguarding their overall well-being.

The role of rehabilitating and restoration the green dam in managing the impact of invasive forest pests in Algeria

The rehabilitation of Algeria’s "Green Dam" project, a large-scale reforestation initiative, represents a key strategy for mitigating climate change, especially in semi-arid regions. This study, conducted between 2021 to 2024 in the semi-arid region of Djelfa (Algeria), evaluates the impact of defoliators in three different stands. Our findings reveal that infestation levels were significantly lower in mixed-species stands compared to monoculture stands, with monoculture plantations showing the highest infestation rates. Seasonal analysis revealed consistent stability in rehabilitated zones, with lower infestation indices throughout the year. The study highlights the role of species diversity in enhancing forest resilience to pest outbreaks, as mixed-species plantations naturally disrupt pest population dynamics and support healthier ecosystems. These results highlight the effectiveness of Green Dam’s rehabilitation in enhancing ecosystem health, increasing biodiversity, and reducing vulnerability to climate-induced disturbances, positioning it as a critical tool for ecological restoration and climate mitigation in northern Algeria. Furthermore, the project exemplifies a scientifically driven approach to combating desertification and climate change in semi-arid ecosystems. By integrating tritrophic analyses examining forest species, pest insects, and their antagonists—along with spatiotemporal monitoring, the study provides valuable insights into ecological interactions under changing climatic conditions. As expanding defoliators and xylophages pose increasing challenges, adaptive management strategies tailored to semi-arid regions are necessary. The rehabilitation of the Green Dam project emerges as a model for large-scale ecological restoration, combining reforestation efforts with scientific innovation to bolster ecosystem resilience, enhance sustainable land management, and address global issues such as biodiversity loss, desertification, and climate instability. Continued monitoring and adaptive management are essential to ensure the long-term success of reforested landscapes.

Integrating Water Evaluation and Planning Modeling into Integrated Water Resource Management: Assessing Climate Change Impacts on Future Surface Water Supply in the Irawan Watershed of Puerto Princesa, Philippines

The Irawan Watershed in Puerto Princesa, Philippines, is an important resource that supports domestic, agricultural, and industrial water needs. This study applies the Water Evaluation and Planning (WEAP) model to project the impacts of climate change on future surface water availability, integrating the findings into an Integrated Water Resource Management (IWRM) framework. Using bias-corrected General Circulation Models (GCMs) under four shared socioeconomic pathways (SSPs), this study examines scenarios from low to high emissions (SSP126, SSP245, SSP370, and SSP585) for the assessment of potential variations in water supply. The results indicate a significant vulnerability to water availability, especially under SSP370 and SSP585, where climate warming is pronounced, leading to significant reductions in streamflow. Conversely, SSP126 suggests relatively stable conditions with less pronounced hydrological changes. The study also explores the socioeconomic drivers that affect water demand, including population growth and land use changes that influence agricultural water needs. The findings underscore the urgency of using adaptive management strategies to conserve water resources in the face of these anticipated challenges. Key recommendations include optimizing water use efficiency in all sectors, establishing protective zones around natural ecosystems, implementing climate-resilient infrastructure, and promoting community engagement in water management. These measures are critical for enhancing water security and promoting sustainable development within the watershed, contributing to the broader goals of Sustainable Development Goal (SDG) 6. This study offers decision-makers and resource managers an evidence-based framework for integrating hydrological modeling into IWRM, providing valuable insights to navigate the complexities of climate change and ensure the long- term sustainability of water resources in the Philippines.

Human Resource Planning Strategy to Improve the Quality of Online Library Management Information Systems (E-Libraries) of Higher Education in the Industrial Era 5.0

Library management information systems in universities are essential for managing e-libraries in universities. The world of education will face one of the challenges after 2030: the use of information technology or robotics in various sectors of human life, one of which is university libraries. This research was conducted using a literature approach by collecting data from various relevant theoretical sources about human resource management and higher education management information systems in the context of university library human resource planning strategies. This article delves into the practical application of library human resource planning strategies in universities. It discusses the formulation of university library human resource planning and the development of human resources in the era of Society 5.0. Furthermore, it explores the challenges and opportunities in implementing these strategies, such as change management, adaptive higher education management information system policies, and the development of librarians' professionalism in the era of society 5.0. This study uses a literature approach by collecting data from relevant theoretical sources about library human resource management and higher education management information systems in the educational context of university library human resource planning strategies. Data is analyzed through systematic literature synthesis to identify university library human resource planning strategies that can improve the quality of management e-library in the era of Society 5.0. In this era, adaptive and technology-oriented human resource management strategies are the key to improving the quality of university e-library management.

Climate Change and Urban Flooding: Assessing Remote Sensing Data and Flood Modeling Techniques: A Comprehensive Review

This review critically examines the current understanding of climate change impacts on urban flooding, synthesizing recent findings to provide a comprehensive overview of how rising temperatures, sea-level rise, and increased extreme weather events influence urban floods. Additionally, it discusses various flood modeling techniques, outlining their advantages and disadvantages. Covering a broad spectrum of studies published between 2007 and 2024, selected for their relevance and methodology, this review highlights several key findings. Climate change significantly exacerbates urban flood disasters, with remote sensing emerging as an indispensable tool for climate change and flood monitoring and prediction. Despite these advancements, notable gaps remain in the literature. There is a conspicuous lack of long-term impact studies and limited discourse on the efficacy of existing mitigation strategies. Additionally, the review underscores the deficiency of real-time flood monitoring systems specifically designed for urban areas. These gaps highlight an urgent need for targeted research and the development of adaptive management practices to enhance flood prediction and management in urban settings. Future research must focus on advancing real-time monitoring systems, integrating remote sensing technologies more effectively, and developing comprehensive flood models. The review also emphasizes the importance of interdisciplinary approaches that merge hydrology, climatology, urban planning, and technology. By consolidating existing research, this review serves as a valuable resource for researchers and policymakers. It underscores the critical need for innovative flood modeling techniques and adaptive management strategies to tackle the challenges posed by climate change. This synthesis not only enriches the current body of knowledge, but also provides clear directions for future investigations, emphasizing the imperative for improved prediction, preparedness, and response mechanisms in urban flood management.

Analysis of Water Dynamics at the Effluent Treatment Station of Cooperoque: Evaluation of Precipitation, Evaporation, and Infiltration of Effluent from a Milk Refrigeration Station

Purpose: The study aims to analyze water dynamics at the Cooperoque Effluent Treatment Station, focusing on the interactions between precipitation, evaporation, and effluent infiltration to enhance water resource management. Theoretical reference: The research references various studies and methodologies related to the quantification of evaporation from lakes and reservoirs, particularly in semi-arid regions, utilizing the Jensen-Haise Method for evaporation estimation. The research aligns with previous studies, such as Mallmann (2014), on water infiltration in soil management, emphasizing the importance of understanding water dynamics for sustainable resource management. Method: The study employs the Jensen-Haise Method to calculate evaporation rates, covering the period from January 2023 to October 2024. It examines the effects of precipitation, evaporation, and effluent infiltration on tank levels. Results and conclusion: The results reveal that tank levels are influenced by precipitation, evaporation, and effluent infiltration, with more significant declines during dry months and smaller reductions during periods of high precipitation. Evaporation rates, calculated using the Jensen-Haise Method, are higher in warmer months, contributing to lower tank levels, while these rates decrease in colder months. A notable anomaly occurred in May 2024 when effluent infiltration exceeded the volume of generated effluents and rainfall due to the activation of an irrigation system. Key findings indicate that lake levels drop more during dry months, with a significant negative water balance observed in May 2024 due to excessive infiltration during heavy rainfall. The study concludes that adaptive water management strategies are necessary to address climatic variations and improve the efficiency of the effluent treatment system. Implications of research: The research provides valuable insights for developing adaptive water management strategies to address climatic variations and improve the efficiency of effluent treatment systems. Continuous monitoring is emphasized as crucial for sustainable water resource management. Originality/value: The study highlights the complex interactions between precipitation, evaporation, and effluent dynamics, offering a foundation for improved water management practices and contributing to the preservation of regional water resources. The study contributes to the understanding of water dynamics at effluent treatment stations, offering practical insights for managing water resources effectively. It highlights the importance of adaptive strategies and continuous monitoring to maintain pond levels and optimize the treatment process.

Model and Ensemble Indicator-Guided Assessment of Robust, Exploitable Groundwater Resources for Denmark

Groundwater constitutes 99% of the Earth’s liquid freshwater and is crucial for human health, economic development, and ecosystem sustainability. This study assesses groundwater sustainability in Denmark by employing a comprehensive hydrological model and a set of ensemble indicators. The paper describes the methodology and the results based on nine selected indicators. Three indicators focus on recharge capture and aquifer sustainability, one focuses on groundwater level and wetland capture, two focus on baseflow and drainage flow capture, and three focus on eco flow capture. Our findings highlight that while overall exploitable groundwater resources are estimated at 1.1 billion m3/year, significant regional disparities exist, with certain areas, notably Zealand, facing over-exploitation rates exceeding 250% of sustainable limits. The indicators developed not only provide a framework for assessing current groundwater resource limits, but also serve as a basis for future monitoring and adaptive management strategies. This research underscores the need for stakeholder engagement and integrated approaches to ensure the sustainability of groundwater resources in the face of growing anthropogenic pressures and climate change. Our work contributes to the ongoing discourse on sustainable water management and offers a robust methodology for assessing groundwater sustainability.

Dynamics of Shoreline Changes Along the Coast of Subarnarekha and Budhabalanga River Estuary, North Eastern Coast of India Using DSAS Technique: A Geospatial Technology Approach

ABSTRACTThe coastal regions represent one of the most significant environmental and economic resources, offering critical ecosystems that support biodiversity. Shoreline change analysis offers critical insights into coastal dynamics, providing trends in erosion and accretion, enabling effective coastal management and hazard mitigation. In the current study, shoreline change is assessed utilizing the Digital Shoreline Analysis System (DSAS) model for Subarnarekha and Budhabalanga river estuaries in Baleswar district, Odisha, India. The shoreline was extracted using multitemporal satellite images like Landsat‐5 and Landsat‐7 for the years 1991, 2000, and 2011. Similarly Sentinel‐2 and Landsat‐8 satellite imagery were used for the year 2022. The satellite data from 1991 to 2022 were processed using Envi, ArcGIS softwares and the shoreline is extracted for each year using band ratioing methods to demarcate shoreline. In the current research, the net accretion and erosion along the coast were analyzed using the GIS (geographic information systems) technique and the DSAS model. The four important statistical parameters of the DSAS model utilized in the study area are end point rate (EPR), net shoreline movement (NSM), linear regression rate (LRR), and least median of squares (LMS). The shoreline change analysis for the coast of Subarnarekha and Budhabalanga river estuary area from 1991 to 2022 reveals that 44% of the coast is under accretion, 7% is under stable coast, and 23% is under erosion. According to the findings, the coastal area of the recent study is both progressive and regressive in nature. For the study area, the average rates of shoreline accretion and erosion are 1.05 m and 0.45 m per year, respectively. The study gives information on erosion and accretion near the Subarnarekha and Budhabalanga river estuaries, which will aid in the development of an adaptive shoreline management strategy and coastal vulnerability assessment.

Interdisciplinary Perspectives on Forest Ecosystems and Climate Interplay: A Review

This review comprehensively examines the multifunctional role of forest ecosystems in climate regulation and the consequential impacts of climate change on these critical biomes. A systematic approach was employed, utilizing extensive bibliometric analysis and synthesis of recent literature from databases such as Web of Science, ScienceDirect, and Google Scholar. Key ecological functions of forests, including carbon sequestration, albedo modulation, evapotranspiration, and cloud formation, were scrutinized to elucidate their contributions to the global carbon cycle and local/regional climate dynamics. The analysis highlights significant phenological shifts, species migrations, and increased vulnerabilities to pests, diseases, and fire disturbances as primary indicators of climate-induced ecological changes. Furthermore, the study explores the intricate feedback loops that exacerbate deforestation and alterations in forest structure and function. Predictive models incorporating various climate scenarios are discussed, emphasizing their importance in developing adaptive management strategies for forest conservation. The findings underscore the necessity for interdisciplinary approaches and stakeholder engagement to formulate effective strategies for mitigating climate change impacts and enhancing forest ecosystem resilience. This review advances the field of ecology by providing critical insights into the interplay between forest ecosystems and climate dynamics, offering a foundation for future research and policy development.

Subsidence and Uplift in Active and Closed Lignite Mines: Impacts of Energy Transition and Climate Change

This study examines the combined effects of decommissioning lignite mining operations and long-term climate trends on groundwater systems and land surface movements in the Konin region of Poland, which is characterised by extensive open-pit lignite extraction. The findings reveal subsidence rates ranging from −26 to 14 mm per year within mining zones, while land uplift of a few millimetres per year occurred in closed mining areas between 2015 and 2022. Groundwater levels in shallow Quaternary and deeper Paleogene–Neogene aquifers have declined significantly, with drops of up to 26 m observed near active mining, particularly between 2009 and 2019. A smaller groundwater decline of around a few metres was observed outside areas influenced by mining. Meteorological data show an average annual temperature of 8.9 °C from 1991 to 2023, with a clear warming trend of 0.0050 °C per year since 2009. Although precipitation patterns show a slight increase from 512 mm to 520 mm, a shift towards drier conditions has emerged since 2009, characterised by more frequent dry spells. These climatic trends, combined with mining activities, highlight the need for adaptive groundwater management strategies. Future research should focus on enhanced monitoring of groundwater recovery and sustainable practices in post-mining landscapes.

Professional values, ethical climate and job satisfaction of nurses and their selected sociodemographic and occupational characteristics.

To explore the relationship of selected socio-demographic and occupational characteristics of nurses and their level of professional values, hospital ethical climate and job satisfaction. Cross-sectional study was conducted among 388 Polish nurses from the spring of 2021 to winter of 2023, in the eastern part of Poland; and followed by Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. Four research tools were used to collect data together with questionnaire for socio-demographic and occupational characteristics. Professional values such as activism correlate negatively with religious beliefs (Z = -1.789; p = 0.044), this means that nurses who are more involved in professional change activities are likely to be less associated with religious beliefs. A positive correlation was observed between the Ethical Hospital Climate Survey subscale-peer relations and nurses' education level (H = 5.638; p = 0.048), indicating that a higher education level was associated with better relationships with colleagues at work. A negative relationship was identified between nurses' external job satisfaction and their marital status (Z = -1.958; p = 0.040), that is, married nurses feel less satisfaction with the external aspects of their jobs than their single colleagues. These findings underscore that medical staff management should take into account both sociodemographic factors [e.g., age, education, place of residence, marital status, religious beliefs, as well as professional factors (working hours, qualification course, etc.)] that affect nurses' professional values, job satisfaction and the ethical climate of the hospital. These underscore the need to adapt management strategies to the individual needs of employees, which can contribute to improving working conditions in healthcare facilities. The data collection tool consists of four sections. Collected background and demographic information. Assessed professional values among nurses. Assessed hospital ethical climate among nurses. Assessed job satisfaction levels among nurses.

Energy Management System for Polygeneration Microgrids, Including Battery Degradation and Curtailment Costs.

Recent advancements in sensor technologies have significantly improved the monitoring and control of various energy parameters, enabling more precise and adaptive management strategies for smart microgrids. This work presents a novel model of an energy management system (EMS) for grid-connected polygeneration microgrids that allows optimizing the management of electrical storage systems, electric vehicles, and other deferrable loads such as heat pumps. The main novelty of this model is that it incorporates both climate comfort variables and the consideration of the degradation of the energy storage capacity in the control strategy, as well as a penalty for the dumping of surpluses. The model has been applied to a smart, sustainable building as a case study. The results show that the proposed model is highly adaptable to diverse weather conditions, minimizing renewable energy losses while satisfying the energy demand and providing comfort to the building's users. The study shows (i) that EVs' dynamic charging schedules play a crucial role, (ii) that it is possible to minimize a battery's degradation by optimizing its cycling, averaging one cycle per day, and (iii) the critical impact of seasonal weather patterns on microgrid energy management and the strategic role of EVs and storage systems in maintaining energy balance and efficiency.

SAR image integration for multi-temporal analysis of Lake Manchar Wetland dynamics using machine learning

The Manchar Lake wetland complex, Pakistan’s largest freshwater-lake, faces unprecedented ecological challenges amidst climate change and human pressures, necessitating urgent, data-driven conservation strategies. This study employs cutting-edge multi-sensor remote sensing techniques to quantify and analyze the dynamic changes in this critical ecosystem from 2015 to 2023, aiming to provide a comprehensive understanding of wetland dynamics for informed management decisions. Integrating Sentinel-1 Synthetic Aperture Radar (SAR) and Sentinel-2 multispectral imagery, we assessed changes in wetland extent, vegetation health, and land-use patterns using spectral indices and topographic data. Our methodology achieved classification accuracies exceeding 92% across all study years, revealing significant ecosystem fluctuations. Water body extent exhibited a non-linear trend, expanding from 318.5 km² (5%) in 2015 to 397.0 km² (7%) in 2019, before contracting to 369.9 km² (6%) in 2023. This pattern was corroborated by MNDWI values. Concurrently, vegetation covers dramatically increased from 405.5 km² (7%) in 2019 to 1081.6 km² (18%) in 2023. The Enhanced Vegetation Index (EVI) reflected this trend, decreasing from 0.61 in 2015 to 0.41 in 2019, before recovering to 0.53 in 2023. Land use changes were substantial, with agricultural areas increasing from 118.4 km² (2%) in 2015 to 498.0 km² (8%) in 2023. SAR data consistently supported these observations. Topographic analysis, including the Topographic Wetness Index (TWI), provided crucial insights into wetland distribution and resilience. This comprehensive analysis highlights the complex interplay between natural processes and human influences shaping the Manchar-Lake ecosystem, underscoring the urgent need for adaptive management strategies in the face of rapid environmental change.