Search Results (1,914)

The transition to smart, zero-carbon cities relies on advanced, sustainable energy solutions, with artificial intelligence (AI) playing a crucial role in optimizing renewable energy management. This study evaluates state-of-the-art AI models for solar power forecasting, emphasizing accuracy, reliability, and environmental sustainability. Using operational data from Benban Solar Park in Egypt and Sakaka Solar Power Plant in Saudi Arabia, two of the world’s largest solar installations, the research highlights the effectiveness of hybrid AI techniques. The hybrid Convolutional Neural Network–Long Short-Term Memory (CNN-LSTM) model outperformed other models, achieving a Mean Absolute Percentage Error (MAPE) of 2.04%, Root Mean Square Error (RMSE) of 184, Mean Absolute Error (MAE) of 252, and R² of 0.99 for Benban, and an MAPE of 2.00%, RMSE of 190, MAE of 255, and R² of 0.98 for Sakaka. This model excels at capturing complex spatiotemporal patterns in solar data while maintaining low computational CO₂ emissions, supporting sustainable AI practices. The findings demonstrate the potential of hybrid AI models to enhance the accuracy and sustainability of solar power forecasting, thereby contributing to efficient, resilient, and zero-carbon urban environments. This research provides valuable insights for policymakers and stakeholders aiming to advance smart energy infrastructure. Full article

Mining (1) operations in remote areas (2) face significant challenges related to energy supply, high fuel costs, and limited infrastructure. This study investigates the potential for achieving energy independence (3) and resilience (4) in such environments through the integration of renewable energy sources (5) and battery–electric mining equipment. Using the “Studena Vrila” underground bauxite mine as a case study, a comprehensive techno-economic and environmental analysis was conducted across three development models. These models explore incremental scenarios of solar and wind energy adoption combined with electrification of mobile machinery. The methodology includes calculating levelized cost of energy (LCOE), return on investment (ROI), and greenhouse gas (GHG) reductions under each scenario. Results demonstrate that a full transition to RES and electric machinery can reduce diesel consumption by 100%, achieve annual savings of EUR 149,814, and cut GHG emissions by over 1.7 million kg CO₂-eq. While initial capital costs are high, all models yield a positive Net Present Value (NPV), confirming long-term economic viability. This research provides a replicable framework for decarbonizing mining operations in off-grid and infrastructure-limited regions. Full article

Understanding how energy use and economic activity shape carbon emissions is pivotal for achieving global climate targets. This study quantifies the dynamic nexus between disaggregated energy consumption, economic growth, and CO₂ emissions in India and China—two economies that together account for more than one-third of global emissions. Using annual data from 1990 to 2021, we implement Long Short-Term Memory (LSTM) neural networks, which outperform traditional linear models in capturing nonlinearities and lagged effects. The dataset is split into training (1990–2013) and testing (2014–2021) intervals to ensure rigorous out-of-sample validation. Results reveal stark national differences. For India, coal, natural gas consumption, and economic growth are the strongest positive drivers of emissions, whereas renewable energy exerts a significant mitigating effect, and nuclear energy is negligible. In China, emissions are dominated by coal and petroleum use and by economic growth, while renewable and nuclear sources show weak, inconsistent impacts. We recommend retrofitting India’s coal- and gas-plants with carbon capture and storage, doubling clean-tech subsidies, and tripling annual solar-plus-storage auctions to displace fossil baseload. For China, priorities include ultra-supercritical upgrades with carbon capture, utilisation, and storage, green-bond-financed solar–wind buildouts, grid-scale storage deployments, and hydrogen-electric freight corridors. These data-driven pathways simultaneously cut flagship emitters, decouple GDP from carbon, provide replicable models for global net-zero research, and advance climate-resilient economic growth worldwide. Full article

Despite advances in medicine, cancer remains one of the foremost global health concerns. Conventional treatments like surgery, radiotherapy, and chemotherapy have advanced with the emergence of targeted and immunotherapy approaches. However, therapeutic resistance and relapse remain major barriers to long-term success in cancer treatment, often driven by cancer stem cells (CSCs). These rare, resilient cells can survive therapy and drive tumour regrowth, urging deeper investigation into the mechanisms underlying their persistence. CSCs express ion channels typical of excitable tissues, which, beyond electrophysiology, critically regulate CSC fate. However, the underlying regulatory mechanisms of these channels in CSCs remain largely unexplored and poorly understood. Nevertheless, the therapeutic potential of targeting CSC ion channels is immense, as it offers a powerful strategy to disrupt vital signalling pathways involved in numerous pathological conditions. In this review, we explore the diverse repertoire of ion channels expressed in CSCs and highlight recent mechanistic insights into how these channels modulate CSC behaviours, dynamics, and functions. We present a concise overview of ion channel-mediated CSC regulation, emphasizing their potential as novel diagnostic markers and therapeutic targets, and identifying key areas for future research. Full article

Urban sustainability challenges demand integrated frameworks capable of addressing the dynamic, non-linear nature of cities. This study explores how the principles of the circular economy and complexity theory intersect to support systemic transformation in sustainable urban planning. Through a systematic literature review of 71 peer-reviewed articles published between 2015 and 2025, we analyze conceptual, methodological, and practical articulations across multiple thematic axes, including circular governance, urban metabolism, regenerative design, adaptive planning, digital integration, and environmental justice. Bibliometric and content analyses were conducted using Scopus metadata, VOSviewer for thematic clustering, and the StArt software (Version 3.4) to structure article selection. The findings reveal that circular economy provides practical tools for resource efficiency and regeneration, while complexity theory offers an adaptive framework to navigate uncertainty, emergent behaviors, and feedback dynamics. The synthesis suggests that their integration enables a more holistic and resilient approach to urban transformation. However, gaps remain in social inclusivity, long-term assessment, and the operationalization of complexity-informed planning. This study contributes to advancing a transdisciplinary agenda for circular and adaptive urban futures, offering insights for scholars, planners, and policymakers aiming to reconfigure cities within planetary boundaries. Full article

This study explores the role of solidarity finance in promoting local development and the empowerment of marginalized communities through financial inclusion and access to community credits. It focuses on how solidarity-based financial mechanisms provide accessible credit with fewer barriers, fostering productive activities and economic resilience. This study employed a quantitative and exploratory design, analyzing data from 51 community funds in Ecuador out of a total of 220 through a self-administered online survey, validated by auditing professionals and answered by community representatives. The 25-item questionnaire gathered data on organizational dynamics, financial practices, and perceptions of sustainability. Descriptive analysis was complemented with an analysis of variance to test hypotheses concerning associativity, self-management, and organizational performance. The results show that while associativity, self-management, and organizational management are perceived as institutional strengths, aspects such as autonomy and solidarity received lower evaluations, suggesting critical areas for strategic improvement. Notably, significant differences emerged between self-management–organization and solidarity–organization groups, emphasizing the importance of associativity (collaboration) in enhancing the sustainability of solidarity finance, which proves to be a vital mechanism for community empowerment and local development; however, its long-term sustainability depends on strengthening internal dimensions, particularly autonomy and solidarity, and reinforcing associativity as a core driver of organizational resilience. Full article

Openings in two-way reinforced concrete (RC) slabs are frequently incorporated for architectural and functional purposes, such as providing pathways for mechanical, electrical, and plumbing services. While necessary, these openings can significantly compromise the structural performance of slabs, particularly by reducing their capacity to resist punching shear, an effect that is especially critical when the openings are located near column–slab connections. This paper provides a detailed review of the existing research, examining how various opening parameters such as their size, shape, and position affect key structural performance metrics including their stiffness, ductility, and failure modes. The findings highlight that opening geometry is a major determinant of a slab’s overall behavior. Notably, the proximity of openings to column faces is identified as a critical factor that can substantially influence the extent of strength degradation and failure mechanisms. Furthermore, this review identifies a significant research gap concerning the behavior of slabs with openings under non-standard loading conditions, such as seismic activity, blasts, and impact loads. It also emphasizes the need for further investigation into the long-term performance of such slabs under adverse environmental influences, including elevated temperatures, corrosion, and material degradation. By consolidating the current knowledge and identifying unresolved challenges, this review aims to guide engineers and researchers in developing more robust design strategies and performance-based solutions for RC slabs with openings, ultimately contributing to safer and more resilient structural systems. Full article

Nanotechnologies bring a rapid paradigm shift in hard and soft bone tissue regeneration (BTR) through unprecedented control over the nanoscale structures and chemistry of biocompatible materials to regenerate the intricate architecture and functional adaptability of bone. This review focuses on the transformative analyses and prospects of current and next-generation nanomaterials in designing bioactive bone scaffolds, emphasizing hierarchical architecture, mechanical resilience, and regenerative precision. Mainly, this review elucidated the innovative findings, new capabilities, unmet challenges, and possible future opportunities associated with biocompatible inorganic ceramics (e.g., phosphates, metallic oxides) and the United States Food and Drug Administration (USFDA) approved synthetic polymers, including their nanoscale structures. Furthermore, this review demonstrates the newly available approaches for achieving customized standard porosity, mechanical strengths, and accelerated bioactivity to construct an optimized nanomaterial-oriented scaffold. Numerous strategies including three-dimensional bioprinting, electro-spinning techniques and meticulous nanomaterials (NMs) fabrication are well established to achieve radical scientific precision in BTR engineering. The contemporary research is unceasingly decoding the pathways for spatial and temporal release of osteoinductive agents to enhance targeted therapy and prompt healing processes. Additionally, successful material design and integration of an osteoinductive and osteoconductive agents with the blend of contemporary technologies will bring radical success in this field. Furthermore, machine learning (ML) and artificial intelligence (AI) can further decode the current complexities of material design for BTR, notwithstanding the fact that these methods call for an in-depth understanding of bone composition, relationships and impacts on biochemical processes, distribution of stem cells on the matrix, and functionalization strategies of NMs for better scaffold development. Overall, this review integrated important technological progress with ethical considerations, aiming for a future where nanotechnology-facilitated bone regeneration is boosted by enhanced functionality, safety, inclusivity, and long-term environmental responsibility. Therefore, the assimilation of a specialized research design, while upholding ethical standards, will elucidate the challenge and questions we are presently encountering. Full article

Soil microbial communities are crucial for ecosystem services, soil fertility, and the resilience of agroecosystems. This study investigated how long-term (31 years) agronomic practices—tillage, NPK fertilization, and cropping system—along with measured environmental variables influence the microbial biomass and its community composition in Chernozem soil under corn cultivation. The polyfactorial field experiment included three tillage treatments ((moldboard (MT), ripped (RT), strip (ST)), two fertilization regimes (NPK (N: 160; P: 26; K: 74 kg/ha), and unfertilized control) and two cropping systems (corn monoculture and corn–wheat biculture). The soil samples (0–30 cm) were collected in June and September 2023. Microbial biomass and community structure were quantified using phospholipid fatty acid (PLFA) analysis, which allowed the estimation of total microbial biomass and community composition (arbuscular mycorrhizal (AM) fungi, fungi, Gram-negative (GN) and Gram-positive (GP) bacteria, actinomycetes). Our results showed that microbial biomass increased from June to September, rising by 270% in unfertilized plots and by 135% in NPK-fertilized plots, due to higher soil moisture. Reduced tillage, especially ST, promoted significantly higher microbial biomass, with biomass reaching 290% and 182% of that in MT plots in June and September, respectively. MT had a higher ratio of bacteria-to-fungi compared to RT and ST, indicating a greater sensitivity of fungi to disturbance. NPK fertilization lowered soil pH by about one unit (to 4.1–4.8) and reduced microbial biomass—by 2% in June and 48% in September—compared to the control, with the particular suppression of AM fungi. The cropping system had a smaller overall effect on microbial biomass. Full article

Early-career teachers (ECTs) entered the profession during the COVID-19 pandemic, a period that introduced unique stressors to an already-demanding career phase. This systematic review examines empirical studies published between 2020 and February 2025 to explore how the pandemic influenced ECT wellbeing, with particular attention to stressors and protective factors impacting long-term retention and professional sustainability. Guided by PRISMA protocols, databases including Web of Science, ERIC, Google Scholar, and Scopus were searched, screening 470 records and identifying 30 studies that met inclusion criteria: peer-reviewed, empirical, focused on early-career teachers (within the first five years), and situated in or explicitly addressing the pandemic and its ongoing impacts. The results of Braun and Clarke’s thematic analysis (2006) revealed that pandemic-related challenges such as increased workload, professional isolation, disrupted induction processes, and emotional strain have persisted into the post-pandemic era, contributing to sustained risks of burnout and attrition. Regardless, protective factors identified during the pandemic—including high-quality mentoring, structured induction programmes, collegial support, professional autonomy, and effective individual coping strategies—continue to offer essential support, enhancing resilience and professional wellbeing. These findings underscore the necessity of institutionalising targeted supports to address the enduring effects of pandemic-related stressors on ECT wellbeing. By prioritising sustained mental health initiatives and structural supports, education systems can effectively mitigate long-term impacts and improve retention outcomes for early-career teachers in a post-pandemic educational landscape. Full article

Effective management of cascade reservoir systems is essential for balancing hydropower generation, flood control, and ecological sustainability, especially under increasingly uncertain runoff conditions driven by climate change. Traditional optimization methods, while widely used, often struggle with high dimensionality and fail to adequately address inflow variability. This study introduces a novel deep reinforcement learning (DRL) framework that tightly couples probabilistic runoff forecasting with adaptive reservoir scheduling. We integrate a Long Short-Term Memory (LSTM) neural network to model runoff uncertainty and generate probabilistic inflow forecasts, which are then embedded into a Proximal Policy Optimization (PPO) algorithm via Monte Carlo sampling. This unified forecast–optimize architecture allows for dynamic policy adjustment in response to stochastic hydrological conditions. A case study on China’s Xiluodu–Xiangjiaba cascade system demonstrates that the proposed LSTM-PPO framework achieves superior performance compared to traditional baselines, notably improving power output, storage utilization, and spillage reduction. The results highlight the method’s robustness and scalability, suggesting strong potential for supporting resilient water–energy nexus management under complex environmental uncertainty. Full article

In the past three decades, localized research has highlighted shifts in rainfall patterns and temperature trends in central Ethiopia, a region vital for agriculture and economic activities and heavily dependent on climate conditions to sustain livelihoods and ensure food security. However, comprehensive analyses of long-term climate data remain limited for this area. Understanding local climate trends is essential for enhancing agricultural resilience in the study area, a region heavily dependent on rainfall for crop production. This study analyzes historical rainfall and temperature patterns over the past 30 years and projects future climate conditions using downscaled CMIP6 models under SSP4.5 and SSP8.5 scenarios. Results indicate spatial variability in rainfall trends, with certain areas showing increasing rainfall while others experience declines. Temperature has shown a consistent upward trend across all seasons, with more pronounced warming during the short rainy season (Belg). Climate projections suggest continued warming and moderate increases in annual rainfall, particularly under SSP8.5 by the end of the 21st century. It is concluded that both temperature and rainfall are projected to increase in magnitude by 2080, with higher Sen’s slope values compared to earlier periods, indicating a continued upward trend. These findings highlight potential breaks in agricultural calendars, such as shifts in rainfall onset and cessation, shortened or extended growing seasons, and increased risk of temperature-induced stress. This study highlights the need for localized adaptation strategies to safeguard agriculture production and enhance resilience in the face of future climate variability. Full article

The resilience concept is well established in engineering, but the quantitative studies of vessel impact resilience for bridge structures remain limited. This paper presents an integrated framework for assessing vessel impact resilience under combined rebar corrosion and vessel collision effects. First, a corroded reinforced concrete bridge is considered for nonlinear static analysis to quantify initial corrosion damage and for nonlinear dynamic analysis to evaluate post-impact function loss. Then, recovery for each damage state is modeled by using both negative exponential and triangular recovery functions to estimate restoration times and to obtain a vessel impact resilience index. The results show that increasing corrosion severity markedly reduces resilience capacity. Furthermore, resilience indices obtained from the negative exponential function generally exceed those from the triangular function, and this improvement becomes more significant at lower resilience levels. Resilience indices calculated by using negative exponential and triangular recovery functions show negligible differences when the concrete bridge is in the uncorroded initial state and the vessel impact velocity is below 1.5 m/s. However, as reinforcement corrosion increases, the maximum discrepancy between these two recovery functions also increases, reaching a value of 67% at a corrosion level of 15.0%. From the numerical results obtained from a case study, it is important to select an appropriate recovery model when assessing vessel impact resilience. For rapid initial restoration followed by slower long-term recovery, the negative exponential model yields greater resilience gains compared to the triangular model. The proposed method thus provides an effective tool for engineers and decision makers to evaluate and improve the vessel impact resilience of aging bridges under the combined corrosion and impact effects. This proposes a quantitative metric for resilience-based condition assessment and maintenance planning. Full article

Background: The progression of Alzheimer’s Disease (AD) deeply affects not only the diagnosed person but also their close relatives, who are often called to take on the role of informal caregivers. This transition is frequently unplanned and emotionally complex, yet poorly understood in its deeper processual dimensions. This study aims to explore and theorize the transition experienced by a family member becoming the primary informal caregiver for a person with advanced AD. Methods: A qualitative study based on the Constructivist Grounded Theory according to Charmaz’s approach (2006) was conducted. In-depth interviews were carried out with 10 participants who had become informal caregivers for a loved one with advanced AD. Data were analyzed using initial coding, focused coding, the constant comparative method, and theoretical coding. Results: Ten caregivers (mean age 39 years, range 35–54; nine females) of patients with advanced AD participated in the study. The analysis revealed a complex, emotionally intense caregiving experience marked by sacrifice, feelings of powerlessness, identity loss, and the necessity of sharing caregiving responsibilities. A core category emerged: A Silent and Certain Willingness to Care, representing the caregivers’ deep, often unconscious commitment to prioritize the care of their loved ones above their own needs. Four interconnected phases characterized the caregiving process: (1) The Changing Daily Life—involving significant sacrifices in personal and social life; (2) Feeling Powerless—confronting the inevitable decline without means to alter the course; (3) Losing Oneself—experiencing physical and psychological exhaustion and a sense of identity loss; and (4) Sharing with Others—seeking external support to sustain caregiving. These findings highlight the evolving nature of becoming a caregiver and the enduring dedication that sustains this role despite the challenges. Conclusions: The progression of AD deeply transforms the lives of caregivers, who become co-sufferers and active participants in the disease’s management. The results underscore the urgency of designing integrative care strategies—including psychological, social, and potentially technological support—that can enhance both patient outcomes and caregiver resilience. Grounded in real-world experiences, this study contributes to the broader neurodegeneration discourse by emphasizing caregiving as a critical factor in long-term disease management and therapeutic success. Full article

The ten-year fishing ban on the Yangtze River aims to restore aquatic biodiversity and rebuild fishery resources. Megalobrama skolkovii, a key species in the basin, was investigated using 2024 data to provide a preliminary assessment of its population structure, stock dynamics, and early recovery. Age analysis (n = 243) showed that 1–6-year-olds were dominated by fish aged 3 (35%), with few older than 4, indicating moderate structural truncation. Growth parameters modeled by the von Bertalanffy Growth Function yielded L_∞ = 61.89 cm and k = 0.25 year⁻¹, with a weight–growth inflection age of 4.4 years. Natural mortality (M = 0.48 year⁻¹) was estimated using Pauly’s empirical formula, and total mortality (Z = 0.55 year⁻¹) was estimated from the catch curve analysis. While fishing mortality (F) was statistically indistinguishable from zero, a plausible low-intensity fishing scenario was explored to assess potential impacts of residual activities. Length-based indicators (LBIs) showed P_mat = 46.05%, P_opt = 9.51%, and P_mega = 6.88%, suggesting reproductive recovery but incomplete structural restoration. These preliminary findings reveal an asymmetrical recovery trajectory, whereby physiological improvements and enhanced recruitment have occurred, yet full structural restoration remains incomplete. This underscores the need for continued, long-term conservation and monitoring to support population resilience. Full article