Search Results (7,579)

Agriophyllum squarrosum (L.) Moq. is a desert-adapted pseudocereal that has recently attracted attention as a climate-resilient crop and source of valuable phytochemicals and nutritionally relevant metabolites. Despite their ecological and nutritional importance, comprehensive studies combining lipid and phenolic profiles across natural populations remain limited. In the present study, five populations of A. squarrosum from ecologically contrasting regions of Kazakhstan were analyzed to evaluate biochemical diversity and potential for functional food applications. Total lipid content was determined using near-infrared spectroscopy, fatty acid composition was assessed by GC-MS, and phenolic compounds were quantified by HPLC. Multivariate approaches, including PCA, MANOVA, PLS analysis, correlation networks, and TOPSIS ranking, were applied to evaluate population differentiation and relationships between biochemical traits and environmental conditions. Total lipid content in seeds ranged from 7.71% to 15.40%, linoleic acid represented 50.20–57.67% of total fatty acids, and oleic acid ranged from 24.80% to 40.10%. Isorhamnetin was the dominant phenolic compound in leaves, with concentrations between 0.24 and 0.65 mg/g. Populations from Aktobe showed higher lipid and oleic acid contents, whereas Almaty populations accumulated greater flavonoid levels, including isorhamnetin, quercetin, and kaempferol. These findings reveal substantial metabolic differentiation among populations and suggest possible associations with ecological conditions. The observed accumulation of unsaturated fatty acids and phenolic compounds, including isorhamnetin, quercetin, and kaempferol, identifies promising germplasm resources for future studies on functional food development and biological activity evaluation. The results further support the potential utilization of A. squarrosum in sustainable agriculture in arid regions. Full article

Recent advances in generative modeling have shifted plant breeding from predictive selection to de novo generative design. This review outlines generative methods for navigating the design space and introduces the latent space as a continuous, designable representation that enables a transition from static plant design to dynamic adaptive response programs. We then categorize navigation of the latent space into three strategies: exploration through unconditional generation, guidance through conditional generation, and optimization through feedback loops. We propose a dual-loop generative artificial intelligence-enhanced Design–Build–Test–Learn framework for accelerated plant design. The inner computational loop performs Design–Predict–Optimize guided by causal constraints and virtual evaluators, while the outer experimental loop (Build–Test–Learn) validates elite designs through digital twins and field trials to bridge the reality gap. A proof-of-concept simulation for drought-tolerance design demonstrates the framework’s dual-loop logic and quantitative performance. We further identify five hierarchical challenges that hinder real-world application: the pitfall of continuity assumption, multi-modal data fusion, causal identifiability, and trustworthy evaluation, as well as pleiotropy and genetic load. Finally, we discuss limitations and risks across data, model, regulatory, and interpretability dimensions and highlight critical open questions for realizing dynamic, adaptive, and climate-resilient breeding. This review provides a biology-grounded, systematic framework for next-generation intelligent plant improvement. Full article

The primary objective of this article is to examine the organizational, economic, and sustainability-related implications of implementing artificial intelligence (AI) systems in small and medium-sized enterprises (SMEs) in Poland. The study combines a survey of 112 SMEs in the Kuyavian–Pomeranian region, including 70 AI-using firms, with 13 in-depth interviews with managers. The quantitative analysis applies logit models to identify determinants of perceived AI effects on internal processes: working time and workload reduction, automation, cost effects, and creativity. The qualitative component explains how AI is adopted and embedded in business practice. The results show that AI adoption in SMEs is increasingly common but remains uneven and mostly operational. The strongest effects concern workload reduction and time efficiency, particularly in service firms and where AI is used intensively. Advanced AI adoption increases the probability of perceiving workload and cost-related effects. However, these effects should not be interpreted simply as direct cost reduction. Rather, AI improves productivity and work capacity while creating new costs related to paid tools, data preparation, integration, output verification, and governance. The interviews show that AI implementation follows a staged path: from curiosity-driven experimentation, through cognitive work augmentation, to workflow integration and, in selected cases, AI-enabled business model innovation. The transition from ad hoc use to strategic implementation depends less on firm size alone and more on process maturity, capabilities, and data readiness. Barriers also change with maturity: early-stage firms face a lack of knowledge, time, and clear use cases, whereas advanced users encounter data quality, hallucinations, security, integration, and governance problems. The study finds that sustainability considerations, particularly environmental impacts and ESG-related implications of AI, remain largely unperceived in SME decision-making. Entrepreneurs primarily interpret sustainability through the lenses of organizational resilience, long-term competitiveness, adaptability, and responsible digital transformation rather than through formal environmental metrics. The findings suggest that SME managers should implement AI gradually, link adoption to measurable process-level outcomes, and invest in AI literacy and governance. They should also integrate responsible AI principles into organizational strategy to support sustainable digital transformation. The study contributes to the literature by showing that AI adoption in SMEs should be understood not only as a productivity-enhancing process but also as a broader organizational transition shaping long-term sustainability and resilience. Full article

Circadian clocks are endogenous timing systems that coordinate plant physiology, metabolism, development, and stress responses with daily and seasonal environmental cycles. In crops, circadian and photoperiodic pathways influence agronomically important traits including photosynthesis, carbon allocation, flowering time, growth, stress resilience, and nutritional quality. Although flowering time and photoperiod response pathways have long been indirectly exploited during domestication and breeding, the broader potential of circadian regulation for crop improvement and time-sensitive management remains only partially developed. This review examines the role of plant circadian clocks in crop productivity, with emphasis on molecular mechanisms, crop-specific clock-associated loci, breeding strategies, and chrono-agricultural applications. We summarize conserved and divergent features of the plant clock, including transcriptional repression and activation modules, environmental entrainment, and post-transcriptional regulatory layers. We then discuss how circadian regulation shapes productivity traits and highlight examples from rice, wheat, barley, maize, soybean, sorghum, tomato, and other crops. These examples show that agricultural adaptation often involves fine-tuning or rewiring circadian and photoperiodic outputs rather than maintaining a universal optimal clock state. Finally, we evaluate chrono-agriculture as an emerging framework for aligning management practices with biological timing. While controlled-environment agriculture and high-value horticultural systems are currently the most practical settings for testing chrono-agricultural strategies, open-field applications require careful consideration of environmental variability, sensor limitations, labour, machinery logistics, economic feasibility, and multi-environment validation. Integrating circadian biology with crop genetics, phenotyping, modelling, and agronomy may provide new opportunities to improve productivity, resilience, resource-use efficiency, and quality traits in sustainable agricultural systems. Full article

Contemporary post-war cities increasingly require adaptive urban systems capable of addressing climate vulnerability, infrastructural instability, environmental degradation, and human well-being simultaneously. This study develops an interdisciplinary framework for adaptive biophilic infrastructure and resource governance within the context of sustainable post-war reconstruction in Ukraine. The research combines literature analysis, comparative urban assessment, and experimental evaluation of eco-modified construction materials. Particular attention is given to vertical greening systems, adaptive underground infrastructure, daylight-integrated public environments, multifunctional urban systems, and environmentally responsive concrete composites incorporating porous minerals and plant-based biomass. Comparative examples from Montreal, New York, Seoul, and Singapore are examined alongside differentiated Ukrainian urban contexts, including Kyiv, Kharkiv, Dnipro, Odesa, Kherson, Lviv, and Uzhhorod. The findings demonstrate that adaptive biophilic infrastructure may improve urban microclimates, strengthen thermal and acoustic regulation, enhance infrastructural adaptability, and support psycho-emotional comfort within dense and post-conflict urban environments. The study further indicates that underground and layered urban systems increasingly function as multifunctional socio-ecological infrastructures integrating mobility continuity, environmental regulation, public accessibility, emergency protection, and human-centered spatial resilience. The experimental assessment demonstrates that eco-modified materials contribute to moisture stabilization, thermal buffering, acoustic moderation, and passive environmental regulation within adaptive urban systems. The incorporation of porous mineral additives and plant biomass improved the environmental responsiveness of the investigated composites while supporting more resource-efficient construction approaches. The study concludes that sustainable post-war reconstruction requires a transition from fragmented technological interventions toward integrated socio-ecological urban frameworks capable of combining environmental regulation, infrastructural resilience, resource efficiency, adaptive governance, and human-centered spatial design within long-term urban sustainability strategies. Full article

Understanding phenotypic variation in traits associated with drought and heat tolerance is essential for developing climate-resilient spring wheat cultivars under increasingly variable environmental conditions. To evaluate phenotypic and physiological variation in water-use efficiency (WUE), carbon isotope discrimination (δ¹³C), and heat tolerance, 198 Canadian spring wheat cultivars representing diverse breeding backgrounds were assessed under controlled drought and high-temperature conditions. Traits measured included whole-plant water-use efficiency (WUE_WP), carbon isotope composition (δ¹³C), biomass accumulation, water use per plant, and chlorophyll fluorescence across six developmental stages. Whole-plant WUE ranged from 3.07 to 7.81 g L⁻¹, while δ¹³C values ranged from −24.06‰ to −29.33‰. Biomass accumulation and water use were strongly positively correlated (r = 0.94, p < 0.001), indicating that greater biomass production was associated with increased water consumption. In contrast, the relationship between WUE_WP and δ¹³C was weak (r = −0.09), suggesting that δ¹³C alone may not be a reliable proxy for WUE_WP under combined drought and heat stress conditions. Phenotypic diversity across the cultivar panel was relatively low to moderate (Shannon diversity index, H^′ = 1.88–2.62), indicating limited adaptive capacity within the evaluated germplasm. Principal component analysis explained 76.6% of the total variation and effectively differentiated cultivar responses to stress. Chlorophyll fluorescence, particularly the maximum quantum efficiency of PSII photochemistry (F_V/F_M), was highly sensitive to stress-induced reductions in photosynthetic performance. Measurements obtained during reproductive drought and heat stress stages showed stronger associations with biomass, water use, WUE_WP, and δ¹³C than measurements collected during non-stress periods, indicating that F_V/F_M can be a reliable physiological indicator for screening drought and heat tolerance. Overall, the results revealed detectable phenotypic variation but relatively modest diversity and generally weak to moderate trait associations, highlighting the potential value of incorporating diverse germplasm and integrated phenotyping approaches to improve climate resilience in Canadian spring wheat. Full article

Climate change, rapid urbanization, land-use changes, and the creation of a multi-layered risk environment by multiple disaster hazards have made interdisciplinary educational models—capable of integrating resilience knowledge into planning and design education—all the more essential. Nevertheless, the systematic and competency-based integration of scientific knowledge generated in the fields of ecological planning, nature-based solutions, multi-hazard analysis, and digital planning tools into higher education curricula remains limited. This study aims to develop a competency-based curriculum model for ecological planning and disaster-resilient cities by adapting the resilience literature into a modular educational model. Literature mapping, thematic clustering, gap identification, competence framework building, and curricular architecture development are the steps of the study’s design-based analytical framework. Studies published between 2015 and 2025 were examined in terms of disaster types, analytical tools, and planning approaches; they were then reorganized based on three competency areas: green skills, digital skills, and resilience skills. The findings have resulted in a modular curriculum comprising 35 modules and 105 topics, structured within a three-tiered framework consisting of conceptual content, practical application, and case-based learning. The original contribution of this study is its proposal of a structured educational model that bridges the gap between the production of scientific knowledge and curriculum design. The proposed framework provides a scalable and adaptable foundation for undergraduate, graduate, and professional education contexts; it also establishes a foundation for AI-supported personalized learning pathways in ecological planning and disaster resilience education. Full article

This discussion paper examines the evolution of freshwater distribution networks from smart to intelligent and ultimately meta-intelligent or wise systems, highlighting the transition from human-supervised operation to autonomous adaptive management. Smart systems integrate monitoring, automation and remote control through information technologies. Intelligent systems extend these capabilities by adding predictive analytics, demand forecasting and automated operational optimization. Wise systems further evolve through adaptive learning mechanisms that allow continuous self-improvement while minimizing dependence on operators. Evidence from Greek water utilities demonstrates practical applications and operational outcomes. The analysis discusses implementation challenges including investment costs, system complexity, data governance and resilience. Finally, the paper proposes design principles for scalable adaptive water networks applicable to utilities with different sizes, resources and levels of technological maturity. Full article

The purpose of this study is to explore how Zimbabwean firms use Environmental Management Accounting (EMA) and climate risk disclosure amid climate policy uncertainty and how managers perceive these practices as relevant to organisational resilience and long-term sustainability within a volatile institutional and macroeconomic context. The study was couched in the interpretivist research philosophy and adopted the inductive research approach. A case study research design, which aligns with a qualitative research design, was chosen for the study. The study employed in-depth interviews with management accountants, finance executives, and industry leaders across firms in Harare. The study adopted the cross-sectional time horizon and analysed data using thematic analysis to develop insights into the role of EMA and climate risk disclosure in times of policy uncertainty. The findings suggest that participants perceived climate policy uncertainty as influencing organisational efforts to reconfigure management accounting practices through greater environmental performance monitoring, adaptive budgeting, and scenario-based planning. The findings of this study suggest that organisational actors interpreted climate policy uncertainty as a condition requiring greater flexibility in budgeting, environmental monitoring, and strategic planning. Participants in this study associated EMA with improved environmental cost visibility and more adaptive approaches to investment appraisal and risk management under uncertain policy conditions. Similarly, participants perceived climate risk disclosure as increasingly crucial for strengthening organisational legitimacy, stakeholder confidence, and institutional credibility. While respondents linked sustainability-oriented accounting adaptation to broader organisational resilience and long-term sustainable growth aspirations, these relationships were understood through managerial perceptions and organisational experiences rather than as directly measurable macroeconomic outcomes. The study contributes to the sustainability accounting literature by providing qualitative, context-sensitive insights into how managers in an emerging economy interpret climate policy uncertainty and adapt EMA and climate risk disclosure practices within volatile institutional conditions. The study further contributes by integrating sensemaking theory and institutional theory to explain how organisational interpretations of uncertainty shape sustainability-oriented accounting adaptation and perceptions of organisational resilience. It is therefore recommended that the regulatory institutional pillar be strengthened to reduce uncertainty and enhance the EMA’s strategic adaptation. Full article

Protein nitration within the nitro-proteome is a dynamic component of drought and recovery responses in wheat (Triticum aestivum L.), yet its role in stress adaptation remains unclear. Young wheat seedlings demonstrate a degree of drought resistance, characterized by physiological and morphological adaptations, during the initial growth phases. However, this tolerance begins to diminish significantly in 5-day-old seedlings. The mechanisms behind this phenomenon are unclear. Our results indicate that it may be related to protein nitration. This study compared the physiological and nitrosative responses of 4-day-old drought-tolerant and 6-day-old sensitive wheat seedlings subjected to drought followed by rehydration. In tolerant seedlings, in contrast to sensitive ones, the water saturation deficit after rehydration returned to the control levels, confirming their drought tolerance. Moreover, NO₂⁻ accumulation in the recovery group was significantly higher in sensitive seedlings than in the control group. Results indicate that drought resistance correlates with protein nitration during the recovery phase. Nitro-proteomic analysis revealed that in tolerant seedlings, protein nitration is limited. The most significant differences are observed in the recovery group, with predominant downregulation of protein nitration in tolerant seedlings and significant upregulation of numerous proteins in sensitive seedlings. Upregulated nitration of vital proteins involved in energy production, photosynthesis (such as the Rubisco large subunit), ATP synthases, and cytosolic malate dehydrogenase may lead to disturbances in energy metabolism and thus prevent an effective response to changing environmental conditions. These findings suggest that regulation of protein nitration during recovery may contribute to drought resilience in wheat and could represent a potential target for improving stress tolerance. Full article

Traditional Mediterranean grapevine landraces represent irreplaceable reservoirs of adaptive diversity, yet many regional germplasm pools remain poorly characterized, limiting conservation strategies and climate-resilient breeding. This study presents the first comparative genetic assessment of 154 local Vitis accessions from three historically interconnected but genomically underrepresented Mediterranean regions: Greece, Morocco, and Slovenia. Using 12 highly polymorphic nuclear SSR markers, we detected substantial genetic diversity (168 alleles; mean heterozygosity He = 0.881) with distinct regional signatures. Moroccan accessions exhibited the highest allelic richness and 11 private alleles, reflecting diverse agroecological adaptation. Slovenian germplasm formed a cohesive, genetically stable cluster with high effective allele numbers. Greek accessions exhibited the highest observed heterozygosity and 14 private alleles, consistent with the Aegean’s role as a major diversification hotspot. Despite >90% of variance occurring within individuals, AMOVA and pairwise FST (0.050–0.061) revealed low to moderate but significant geographic differentiation. Multivariate analyses (PCA, UPGMA) and Bayesian clustering (sNMF, K = 3) consistently resolved three regional genetic groups with varying admixture levels, consistent with a mosaic domestication model, as previously proposed for the Mediterranean basin, shaped by recurrent introductions, wild introgression, and region-specific selection. Our results show that peripheral Mediterranean germplasm harbors meaningful, regionally distinctive, substantial, non-redundant diversity not fully represented in surveys focused on climate adaptation, disease resistance breeding, and long-term genetic resource conservation. These findings challenge simplistic diffusion models and emphasize the strategic importance of geographically comprehensive sampling in grapevine conservation programs. Full article

The construction sector needs to transform to address increasing sustainability and resilience challenges driven by climate change and increasing demands from stakeholders such as governments and customers. While previous research has examined individual aspects of sustainable construction, there remains an important need for an integrated, performance-oriented framework to guide organisational capability development. This research study develops a novel Sustainability Performance-Led Progression Framework (SPL-PF) to support the systematic assessment of and improvement in sustainability and resilience performance within the construction sector. A structured literature review of global academic and industry sources (2020–2025) was conducted to identify key challenges and evidence-based strategies and solutions. Through systematic synthesis, ten challenge areas and forty-one success strategies were identified and consolidated into a staged maturity framework. The SPL-PF defines five progressive levels (compliance, integration, optimisation, collaboration, and innovative leadership) supported by performance criteria, measurement indicators, and an operational scoring approach. This framework enables organisations to benchmark current capability, prioritise interventions, and monitor continuous improvement across sustainability and resilience dimensions. Full article

Desert expressway corridors exposed to strong wind hazards often rely on single high-grade routes, with limited alternatives, high detour costs, and low network redundancy. These constraints make it difficult to maintain traffic operation resilience through route substitution alone. Taking the Hami–Tuyugou section of the G30 Lianhuo Expressway in Xinjiang, China, as a case study, this study investigates the formation and evaluation of traffic operation resilience in a wind-hazard-affected, low-redundancy desert expressway corridor. A hierarchical indicator system was constructed with four first-level, fourteen second-level, and thirty-one third-level indicators. Fuzzy DEMATEL(Decision Making Trial and Evaluation Laboratory)–ISM(Interpretive Structural Modeling) was used to identify causal relationships and hierarchical transmission paths; fuzzy DANP(DEMATEL-based Analytic Network Process)–AHP(Analytic Hierarchy Process) was applied to determine indicator weights; and a cloud model was employed to evaluate the overall resilience level. The results show that institutional adaptability, organizational learning, monitoring and information support, and multi-actor collaboration are the main upstream drivers. The corridor was evaluated as Grade IV, indicating a relatively high resilience level approaching Grade V. Sensitivity analyses confirm the robustness of the substantive conclusion. The findings suggest that, under low-redundancy conditions, resilience depends less on structural redundancy and more on adaptive governance, information support, and coordinated response. Full article

The health system is now more complex, uncertain, interdependent, and dynamically interconnected than ever, making traditional planning decisions based on static, reductionist models increasingly impracticable. Systems analytics approaches such as system dynamics, agent-based modeling, and network analysis are often deployed in isolation and fail to capture cross-level interactions and emergent system behavior. This study proposes an integrated multi-layer systems analytics framework that combines these analytical paradigms within a unified architecture to support adaptive health systems planning under uncertainty. The proposed framework introduces an Adaptive Policy Intelligence Layer (APIL), which enables continuous feedback-driven policy adaptation through dynamic monitoring, scenario evaluation, and real-time adjustment mechanisms. The model is evaluated under multiple simulation scenarios, including baseline conditions, demand shocks, resource constraints, and digital transformation environments. The findings provide strong quantitative and analytical evidence of improved system performance and resilience. More specifically, the digital transformation scenario achieved the lowest mean system pressure (0.128) and the highest resilience index (0.887), while the demand shock scenario produced the highest peak system pressure (0.306). The results demonstrate enhanced system resilience, more efficient resource deployment, and superior policy responsiveness compared with traditional single-method approaches. The originality of this study lies in integrating multi-level systems analytics with adaptive policy intelligence into a unified, feedback-driven decision-support framework for resilient health systems governance. The study contributes to systems analytics literature by advancing a synergistic and adaptive modeling paradigm capable of supporting policymakers in navigating complex and unstable healthcare environments. Full article

Cape Coast is a prominent tourism destination in Ghana, distinguished by its historical landmarks, coastal ecosystems, and cultural heritage. Yet the city faces mounting threats from environmental hazards such as coastal erosion, flooding, extreme heat, and lagoon degradation, which directly compromise the sustainability of its tourism sector. Guided by the Sustainable Tourism Development Theory (STDT) and the Tourism Resilience and Adaptation Theory (TRAT), this study investigates the impacts of these hazards on tourism development, the effectiveness of current disaster risk reduction (DRR) strategies, and the roles of key stakeholders in building sectoral resilience. Using a qualitative research design, data were collected through in-depth interviews with eighteen stakeholders comprising four policymakers, six community leaders, five tourism business operators, and three representatives from non-governmental organisations, alongside documentary analysis of four institutional reports. The study contributes to the literature by demonstrating that fragmented, reactive DRR strategies and weak stakeholder coordination undermine Cape Coast’s tourism resilience, and by showing how urban natural assets, a dimension largely neglected in existing tourism–DRR scholarship, are central to both hazard exposure and adaptive capacity. The findings call for integrated, ecosystem-based DRR frameworks that align governance mechanisms with sustainable tourism imperatives. Full article