Search Results (5,105)

Carassius auratus exhibits significant physiological and behavioral alterations under the combined stress of temperature and dissolved oxygen (DO) fluctuations, which are common challenges in aquaculture. In this investigation, we employed controlled thermal and DO gradients to characterize the multidimensional response profile of this species. The key findings revealed that thermal elevation profoundly influenced blood glucose and cortisol concentrations. Notably, exposure to hyperoxic conditions markedly attenuated stress responses relative to hypoxia at equivalent temperatures: cortisol levels were significantly suppressed (reductions of 60.11%, 118.06%, and 34.72%), while blood glucose levels exhibited concurrent increases (16.42%, 26.43%, and 26.34%). Distinctive behavioral patterns, including floating head behavior, surface swimming behavior, and rollover behavior, were identified as indicative behaviors of thermal–oxygen stress. Molecular analysis demonstrated the upregulated expression of stress-associated genes (HSP70, HSP90, HIF-1α, and Prdx3), which correlated temporally with elevated cortisol and glucose concentrations and the manifestation of stress behaviors. Furthermore, a muscle texture assessment indicated that increased DO availability mitigated the textural deterioration induced by heat stress. Collectively, this work establishes an authentic biomarker framework, providing crucial threshold parameters essential for the development of intelligent, real-time environmental monitoring and dynamic regulation systems to enhance climate-resilient aquaculture management. Full article

Understanding the entrepreneurial profile is essential for developing effective regional policies that promote business growth. The path of an entrepreneur is shaped not only by individual decisions but also by the inherent risks of managing a business. This study aims to identify the characteristics of entrepreneurs at the regional level, specifically highlighting the impact of accumulated experience in their fields. Our central hypothesis asserts that entrepreneurial experience significantly influences how business owners perceive and respond to economic challenges. Utilizing survey data from 120 entrepreneurs in Romania’s Center Region (a NUTS 2 area), we reveal that entrepreneurial experience profoundly affects perceptions of key business challenges, such as legislative instability, taxation predictability, governmental support strategies, and access to SME financing. Importantly, our findings demonstrate that entrepreneurs with less than 10 years of experience express greater concerns about these challenges compared to their more seasoned peers. This novel insight highlights the need for tailored policy interventions aimed at enhancing regional economic resilience and fostering entrepreneurial sustainability. By addressing the specific needs of less experienced entrepreneurs, our study contributes to a deeper understanding of how experience shapes business dynamics in the region. Full article

pH is a critical parameter requiring precise monitoring across scientific, industrial, and biological domains. Fluorescent pH probes offer a powerful alternative to traditional methods (e.g., electrodes, indicators), overcoming limitations in miniaturization, long-term stability, and electromagnetic interference. By utilizing photophysical mechanisms—including intramolecular charge transfer (ICT), photoinduced electron transfer (PET), and fluorescence resonance energy transfer (FRET)—these probes enable high-sensitivity, reusable, and biocompatible sensing. This review systematically details recent advances, categorizing probes by operational pH range: strongly acidic (0–3), weakly acidic (3–7), strongly alkaline (>12), weakly alkaline (7–11), near-neutral (6–8), and wide-dynamic range. Innovations such as ratiometric detection, organelle-specific targeting (lysosomes, mitochondria), smartphone colorimetry, and dual-analyte response (e.g., pH + Al³⁺/CN⁻) are highlighted. Applications span real-time cellular imaging (HeLa cells, zebrafish, mice), food quality assessment, environmental monitoring, and industrial diagnostics (e.g., concrete pH). Persistent challenges include extreme-pH sensing (notably alkalinity), photobleaching, dye leakage, and environmental resilience. Future research should prioritize broadening functional pH ranges, enhancing probe stability, and developing wide-range sensing strategies to advance deployment in commercial and industrial online monitoring platforms. Full article

European pig farmers are challenged by increasingly stringent EU regulations to protect the environment from pollution, to meet animal welfare standards and to make pig farming more sustainable. Economic sustainability is defined as the ability to achieve higher profits by respecting social and natural resources. This study is focused on the analysis of the economic resilience of intensive and extensive farming systems, based on data collected from 56 farms located in Denmark, Poland, Italy and Spain. Productive and economic performances of these farms are analyzed, and economic resilience is assessed through a survey including a selection of indicators, belonging to different themes: [i] resilience of resources, [ii] entrepreneurship, [iii] propensity to extensification. The qualitative data from the questionnaire allow for an exploration of how production systems relate to the three dimensions of resilience. Different levels of resilience were found and discussed for intensive and extensive farms. The findings suggest that intensive farms benefit from high standards and greater bargaining power within the supply chain. Extensive systems can achieve profitability through value-added strategies and generally display good resilience. Policies that support investment and risk reduction are essential for enhancing farm resilience and robustness, while strengthening farmer networks can improve adaptability. Full article

Microalgae, with their unparalleled capabilities for sunlight-driven growth, CO₂ fixation, and synthesis of diverse high-value compounds, represent sustainable cell factories for a circular bioeconomy. However, industrial deployment has been hindered by biological constraints and the inadequacy of conventional genetic tools. The advent of CRISPR-Cas systems initially provided precise gene editing via targeted DNA cleavage. This review argues that the true transformative potential lies in moving decisively beyond cutting to harness CRISPR as a versatile synthetic biology “Swiss Army Knife”. We synthesize the rapid evolution of CRISPR-derived tools—including transcriptional modulators (CRISPRa/i), epigenome editors, base/prime editors, multiplexed systems, and biosensor-integrated logic gates—and their revolutionary applications in microalgal engineering. These tools enable tunable gene expression, stable epigenetic reprogramming, DSB-free nucleotide-level precision editing, coordinated rewiring of complex metabolic networks, and dynamic, autonomous control in response to environmental cues. We critically evaluate their deployment to enhance photosynthesis, boost lipid/biofuel production, engineer high-value compound pathways (carotenoids, PUFAs, proteins), improve stress resilience, and optimize carbon utilization. Persistent challenges—species-specific tool optimization, delivery efficiency, genetic stability, scalability, and biosafety—are analyzed, alongside emerging solutions and future directions integrating AI, automation, and multi-omics. The strategic integration of this CRISPR toolkit unlocks the potential to engineer robust, high-productivity microalgal cell factories, finally realizing their promise as sustainable platforms for next-generation biomanufacturing. Full article

Agricultural production in southern Angola faces challenges due to unsustainable practices, including inefficient use of water, fertilizers, and machinery, resulting in low yields and environmental degradation. Therefore, clear and measurable indicators are needed to guide farmers toward more sustainable practices. The scientific literature insufficiently addresses this issue, leaving a significant gap in the evaluation of key performance indicators (KPIs) that can guide good agricultural practices (GAPs) adapted to the context of southern Angola, with the goal of promoting a more resilient and sustainable agricultural sector. So, the objective of this study is to identify and assess KPIs capable of supporting the selection of GAPs suitable for maize, potato, and tomato cultivation in the context of southern Angolan agriculture. A systematic literature review (SLR) was conducted, screening 2720 articles and selecting 14 studies that met defined inclusion criteria. Five KPIs were identified as the most relevant: gross margin, net profit, water use efficiency, nitrogen use efficiency, and machine energy. These indicators were analyzed and standardized to evaluate their contribution to sustainability across different GAPs. Results show that organic fertilizers are the most sustainable option for maize, drip irrigation for potatoes, and crop rotation for tomatoes in southern Angola because of their efficiency in low-resource environments. A clear, simple, and effective representation of the KPIs was developed to be useful in communicating to farmers and policy makers on the selection of the best GAPs in the cultivation of different crops. The study proposes a validated KPI-based methodology for assessing sustainable agricultural practices in developing regions such as southern Angola, aiming to lead to greater self-sufficiency and economic stability in this sector. Full article

In power distribution networks, the growing integration of renewable energy sources (RESs) presents a challenge for the electricity system and its operators, who need to make the energy sector more flexible and resilient. In this context, this paper proposes a novel flexibilization service for the distribution system leveraging the role of renewable energy communities (RECs), an emerging entity with the potential to facilitate the sustainable energy transition through Virtual Islanding operation. The concept of Virtual Islanding is investigated in the paper and a methodology for its validation is developed. Its effectiveness is then assessed using an IEEE-standard 33-node network with significant penetration of RESs, considering the presence of multiple RECs to prove its benefits on electrical distribution networks. The results showcase the advantages of the VI paradigm both from technical and sustainability viewpoint. Full article

Tunisia faces significant challenges related to climate change, which deeply affect its natural and agricultural resources. This reality threatens not only food security but also the economic stability of rural communities and mainly rural women. This research aims to assess the impact of climate change on rural women in the agricultural development group in Sidi Bouzid, focusing on the strategies adopted and the support provided by various stakeholders to mitigate this impact. To achieve this, we developed a rigorous methodology that includes structured questionnaires, focus group discussions, and topological analysis through Multiple Correspondence Analysis (MCA). The results revealed that rural women were categorized into three groups based on their vulnerability to climate change: severely vulnerable, vulnerable, and adaptive. The findings highlighted the significant impact of climate change on water resources, which has increased family tensions and reduced agricultural incomes, making daily life more challenging for rural women. Furthermore, a deeper analysis of interactions with external stakeholders emphasized the important role of civil society, public organizations, and research institutions in strengthening the climate resilience of rural women. Given these findings, strategic recommendations aim to enhance stakeholder coordination, expand partnerships, and improve access to essential technologies and resources for women in agricultural development groups. Full article

Improving occupational health and safety (OHS) in the construction industry can contribute to the advancement of the Sustainable Development Goals (SDGs), particularly Goals 3 (Good Health and Well-being) and 8 (Decent Work and Economic Growth). Yet, workers’ risk-taking behaviors (RTBs) remain a persistent challenge. Drawing on Social Cognitive Theory and Social Information Processing Theory, this study develops and tests a social influence model to examine how foremen’s safety attitudes (SAs) shape workers’ RTBs. Drawing on survey data from 301 construction workers in China, structural equation modeling reveals that foremen’s SAs significantly and negatively predict workers’ RTBs. However, the three dimensions of SAs—cognitive, affective, and behavioral—exert their influence through different pathways. Risk perception (RP) plays a key mediating role, particularly for the cognitive and behavioral dimensions. Furthermore, interpersonal trust (IPT) functions as a significant moderator in some of these relationships. By identifying the micro-social pathways that link foremen’s attitudes to workers’ safety behaviors, this study offers a testable theoretical framework for implementing the Sustainable Development Goals (particularly Goals 3 and 8) at the frontline workplace level. The findings provide empirical support for organizations to move beyond rule-based management and instead build more resilient OHS governance systems by systematically cultivating the multidimensional attitudes of frontline leaders. Full article

Occupational heat stress represents an increasing challenge to safety and operational performance in underground mining, where elevated temperatures, humidity, and limited ventilation are common. This study proposes an integrated framework to analyze the systemic impact of heat stress on human reliability in mining operations. We conducted a systematic literature review to identify empirical studies addressing thermal exposure, extracting key operational functions for modeling. These functions were structured using the Functional Resonance Analysis Method (FRAM) to reveal interdependencies and performance variability. Human reliability was evaluated using Fuzzy CREAM, which quantified the degree of contextual control associated with each function. Finally, we applied the Gaussian Analytic Hierarchy Process (AHP) to prioritize functions based on thermal impact, contextual reliability, and systemic connectivity. The results showed that functions involving subjective or complex judgment, such as assessing thermal stress or identifying psychophysiological indicators, exhibited lower reliability and higher vulnerability. In contrast, monitoring and control functions based on standardized procedures were more stable and resilient. This combined approach identified critical points of systemic fragility and offers a robust decision-support tool for prioritizing thermal risk mitigation. The findings contribute to advancing the scientific understanding of heat stress impacts in mining and support the development of targeted interventions to enhance human performance and safety in extreme environments. Full article

Effective earthquake early warning (EEW) is essential for disaster prevention in the built environment, enabling a rapid structural response, system shutdown, and occupant evacuation to mitigate damage and casualties. However, most current EEW systems lack rigorous reliability analyses of their predictive outcomes, limiting their effectiveness in real-world scenarios—especially for on-site warnings, where data are limited and time is critical. To address these challenges, we propose a Bayesian neural network (BNN) framework based on Stein variational gradient descent (SVGD). By performing Bayesian inference, we estimate the posterior distribution of the parameters, thus outputting a reliability analysis of the prediction results. In addition, we incorporate a continual learning mechanism based on elastic weight consolidation, allowing the system to adapt quickly without full retraining. Our experiments demonstrate that our SVGD-BNN model significantly outperforms traditional peak displacement (Pd)-based approaches. In a 3 s time window, the Pearson correlation coefficient R increases by 9.2% and the residual standard deviation $SD$ decreases by 24.4% compared to a variational inference (VI)-based BNN. Furthermore, the prediction variance generated by the model can effectively reflect the uncertainty of the prediction results. The continual learning strategy reduces the training time by 133–194 s, enhancing the system’s responsiveness. These features make the proposed framework a promising tool for real-time, reliable, and adaptive EEW—supporting disaster-resilient building design and operation. Full article

Effective water infrastructure planning and management is key to sustainable water supply globally. This research assesses water infrastructure planning and management in Gauteng, South Africa, amid growing challenges from rapid urbanisation, high water demand, climate change, and resource scarcity. These challenges threaten the achievement of Sustainable Development Goals 6 and 11; hence, an integrated approach is required for water sustainability. The study responds to a gap in the literature, which often treats planning and management separately, by adopting an integrated, multi-institutional approach across the water value chain. A mixed-methods triangulation strategy was employed for data collection whereby surveys provided quantitative data, while two sets of structured interviews were conducted: the first round to determine causal relationships among the critical success factors and the second round to validate the proposed framework. The findings reveal a misalignment between infrastructure planning and implementation, contributing to infrastructure backlogs and a short- to medium-term focus. Infrastructure management is further constrained by inadequate system redundancy, leading to ineffective maintenance. External factors such as delayed adoption of 4IR technologies, lack of climate resilient strategies, and fragmented institutional coordination exacerbate these issues. Using Decision-Making Trial and Evaluation Laboratory (DEMATEL) analysis, the study identified Strategic Alignment and a Value-Driven Approach as the most influential critical success factors in water asset management. The research concludes by proposing an integrated water infrastructure and planning framework that supports sustainable water supply. Full article

Increased food production demands, labor shortages, and environmental concerns are driving the need for innovative agricultural technologies. However, effective adoption depends critically on aligning robot innovations with the needs of farmers. This paper examines the alignment between the needs of farmers and the robotic systems used in row crop farming. We review current commercial agricultural robots and research, and map these to the needs of farmers, as expressed in the literature, to identify the key issues holding back large-scale adoption. From initial pool of 184 research articles, 19 survey articles, and 82 commercial robotic solutions, we selected 38 peer-reviewed academic studies, 12 survey articles, and 18 commercially available robots for in-depth review and analysis for this study. We identify the key challenges faced by farmers and map them directly to the current and emerging capabilities of agricultural robots. We supplement the data gathered from the literature review of surveys and case studies with in-depth interviews with nine farmers to obtain deeper insights into the needs and day-to-day operations. Farmers reported mixed reactions to current technologies, acknowledging efficiency improvements but highlighting barriers such as capital costs, technical complexity, and inadequate support systems. There is a notable demand for technologies for improved plant health monitoring, soil condition assessment, and enhanced climate resilience. We then review state-of-the-art robotic solutions for row crop farming and map these technological capabilities to the farmers’ needs. Only technologies with field validation or operational deployment are included, to ensure practical relevance. These mappings generate insights that underscore the need for lightweight and modular robot technologies that can be adapted to diverse farming practices, as well as the need for farmers’ education and simpler interfaces to robotic operations and data analysis that are actionable for farmers. We conclude with recommendations for future research, emphasizing the importance of co-creation with the farming community to ensure the adoption and sustained use of agricultural robotic solutions. Full article

In light of the increasing frequency and intensity of natural phenomena, whether climatic or telluric, the relevance of multi-risk assessment approaches has become an important issue for understanding and estimating the impacts of disasters on complex socioeconomic systems. Two aspects contribute to the worsening of this situation. First, climate change has heightened the incidence and, in conjunction, the seriousness of geohazards that often occur with each other. Second, the complexity of these impacts on societies is drastically exacerbated by the interconnections between urban areas, industrial sites, power or water networks, and vulnerable ecosystems. In front of the recent research on this problem, and the necessity to figure out the best scientific positioning to address it, we propose, through this review analysis, to revisit existing literature on multi-risk assessment methodologies. By this means, we emphasize the new recent research frameworks able to produce determinant advances. Our selection corpus identifies pertinent scientific publications from various sources, including personal bibliographic databases, but also OpenAlex outputs and Web of Science contents. We evaluated these works from different criteria and key findings, using indicators inspired by the PRISMA bibliometric method. Through this comprehensive analysis of recent advances in multi-risk assessment approaches, we highlight main issues that the scientific community should address in the coming years, we identify the different kinds of geohazards concerned, the way to integrate them in a multi-risk approach, and the characteristics of the presented case studies. The results underscore the urgency of developing robust, adaptable methodologies, effectively able to capture the complexities of multi-risk scenarios. This challenge should be at the basis of the keys and solutions contributing to more resilient socioeconomic systems. Full article

In today’s dynamic and highly uncertain environment, organizations, particularly in the aviation sector, face increasing challenges that demand resilient, flexible, and data-driven change management decisions. Responding to the growing need for structured approaches to managing complex uncertainties—geopolitical tensions, economic volatility, social shifts, rapid technological advancements, environmental pressures and regulatory changes—this research proposes a theoretical change management model for aviation service providers, such as airports. Integrating three analytical approaches, the model offers a robust, multi-method approach for supporting sustainable transformation under uncertainty. Normative analysis using Bayesian decision theory identifies influential external environmental factors, capturing probabilistic relationships, and revealing causal links under uncertainty. Prescriptive planning through scenario theory explores alternative future pathways and helps to identify possible predictions, offer descriptive evaluation employing fuzzy comprehensive evaluation, and assess decision quality under vagueness and complexity. The proposed four-stage model—observation, analysis, evaluation, and response—offers a methodology for continuous external environment monitoring, scenario development, and data-driven, proactive change management decision-making, including the impact assessment of change and development. The proposed model contributes to the theoretical advancement of the change management research area under uncertainty and offers practical guidance for aviation organizations (airports) facing a volatile external environment. This framework strengthens aviation organizations’ ability to anticipate, evaluate, and adapt to multifaceted external changes, supporting operational flexibility and adaptability and contributing to the sustainable development of aviation services. Supporting aviation organizations with tools to proactively manage systemic uncertainty, this research directly supports the integration of sustainability principles, such as resilience and adaptability, for long-term value creation through change management decision-making. Full article