Search Results (181)

The electricity supply system faces major challenges. The physical and social vulnerability of the monoculture of hierarchical, centralized systems urgently requires radical transformation of their organizational structures as well as their infrastructures. These transformations to low carbon are often characterized as ‘decentralization’. However, decentralization is a process that only signifies a move away from centralized models. This does not necessarily result in a decentralized architecture, but rather a model in which the dominance of ‘commercial private’ combined with ‘monopolistic public’ is replaced by cooperation and community. The research question is: what will be the design of future electricity grids after the transformation? The integration of distributed renewable resources and the growing need for resilience requires great diversity and flexibility from socio-technical smart grids. These involve digitization, enabling the transformation of power grids into networks of clustered, self-healing microgrids with distributed energy systems: generation, storage, transmission, demand response, and internal energy management. Several fundamentals of Common Pool Resources theory (Ostrom) on the analysis of sustainable management of natural resources are reviewed on their relevance: the Socio-Ecological System framework, distinct property regimes, the Polycentricity concept, and the Institutional Analysis and Development (IAD) framework. The transformation leads to ‘distributed’ rather than ’decentralized’ models. Governance no longer takes place from a single control point, but from many, spread across multiple levels, similar to ecosystems. End users play a key role and become partly coproducing prosumers. Governance is polycentric rather than decentral. The IAD provides as its most important condition that, at the legislative level, there must be minimum recognition of the right of ‘renewable energy communities’ to organize themselves as microgrids. This is immediately the biggest social acceptance challenge, as the current monoculture incorporates several lock-ins: incumbent powerful actors, centralized hierarchical control legislation, and obstructive market conditions, including taxing systems. Full article

Current Unmanned Aerial Vehicle (UAV) swarm designs prioritize physical reliability over network security, leaving systems vulnerable to increasingly sophisticated cyber threats in complex environments. Existing defense methods are mostly limited to peripheral network security technologies, such as encryption, authentication, and firewalls. Consequently, they lack deep integration at the formation architecture level. This separation results in a disconnect between system reliability design and security protection mechanisms, making it difficult to effectively deal with high-level security threats such as internal backdoor vulnerabilities. To this end, this paper proposes an endogenous security architecture for UAV swarm based on dynamic heterogeneous redundancy (DHR) and cooperative supervision. Firstly, a theoretical model of DHR system for UAV swarm was constructed, and discrete nodes are abstracted as dynamic heterogeneous resource pools. Through the formal definition of the heterogeneous executor space, redundancy adjudication mechanism, and dynamic scheduling method, we demonstrate how this architecture suppresses common mode failures by introducing internal and external uncertainties, thereby realizing the coordination and unification of safety and security. Secondly, a distributed security control strategy based on cooperative supervision is proposed, which uses cross-validation between neighbors to replace the centralized adjudication of traditional DHR, solves the problem of anomaly detection in a decentralized environment, and combines reactive cleaning and periodic disturbance scheduling to give the system the ability to self-heal against unknown threats. Simulations in various attack scenarios demonstrate the proposed method’s superiority over traditional architectures. Especially in the simulated dormant multi-mode Advanced Persistent Threat (APT) scenario, the system can still maintain availability of more than 81%, which effectively verifies the key role of the coordination mechanism of heterogeneity, redundancy and dynamics in enhancing the safety and security of UAV swarms. Full article

The lasca Protochondrostoma genei is an endemic freshwater fish of high conservation concern, listed in Annex II of the Habitat Directive and classified as Endangered in Italy. This study investigates the ecology, population structure, and habitat use of P. genei in the Chiarò di Cialla Creek (Northeast Italy), a biodiversity hotspot recently designated as a Special Area of Conservation (SAC IT3320041). Particular regard is given to the issue represented by the presence of the common nase Chondrostoma nasus, which competes with the lasca for habitats and trophic resources. Fish assemblages were surveyed by electrofishing during 2023 and 2024, coupled with detailed hydromorphological characterization of mesohabitats. Results highlighted that the lasca showed preference for glides and especially pools, characterized by moderate depths, low to moderate current velocities, high shading, and abundant shelters such as boulders, roots, and woody debris. However, P. genei extensively overlapped in habitat use with the invasive common nase C. nasus, whose density increased markedly during the study period, suggesting ongoing colonization and potential issues for the lasca conservation. Despite moderate river functionality scores and localized anthropogenic pressures, the Chiarò di Cialla Creek remains a key refuge for P. genei. These findings provide essential ecological information to support targeted conservation actions, including habitat management and invasive species control, within protected riverine systems. Full article

This conceptual article examines the shift of circular business models from policy-driven sustainability initiatives to commercially viable strategies in fast-moving product categories, with particular attention to repair, refurbishment, remanufacturing, and end-of-life recovery. Drawing on a structured narrative review and theoretical synthesis, it argues that circular models seldom scale within a single firm because slowing and closing resource loops require ecosystems that integrate product design, reverse logistics, and secondary markets. The paper develops an analytical framework that combines ecosystem strategy, complex adaptive systems, and common agency theory to explain how distributed complementarities, feedback dynamics, and multi-principal incentives jointly shape ecosystem trajectories. Reinforcing and balancing loops can accelerate, stabilise, or lock ecosystems into low-value routines, while incomplete contracts and divergent metrics may fragment effort and produce measurement traps. To address these coordination externalities, the framework introduces the super-principal as a meta-governance role that aligns principals through shared performance indicators, pooled funding rules, and investments in enabling infrastructures such as traceability. The framework offers implications for circular economy policy and ecosystem strategy aimed at sustaining higher-value circular loops. Full article

Weather modification has gained significant and growing interest in the United States (US) in recent years. The trend can be largely attributed to the changing climate, persistent droughts, and other extreme weather events that have been experienced across various regions of the US. This paper provides a critical review of weather modification program costs, benefits, policy, and governance to help shed light on policymaking and program management associated with the growing interest in adopting weather modification as a local climate management strategy in the US. Additionally, to deepen our understanding of the widely concerning issues, such as the financial burden on taxpayers and potential environmental risks, the paper explored the local implementation challenges and common environmental and public health concerns related to weather modification activities. A synthesis of the literature and policy debates reached four general conclusions: (1) The need for weather modification programs is expected to keep growing, though regional variations may exist due to regulatory and other local factors; (2) weather modification can bring significant local benefits, ranging from enhanced agricultural yield and recreational economy to extreme weather management and public environmental health benefits; (3) state-level and local support, including financial resources, will be essential for program development in the foreseeable future; and (4) technological advancements will be critical for addressing many of the project operation efficiency challenges and environmental and public health concerns related to weather modification programs. More specifically for program governance and local implementation, aspects such as project planning (including resource pooling), risk and liability management, communication and reporting, outcome measurability, and stakeholder engagement are indispensable for addressing issues related to program legality and oversight, public acceptance, and sustainability. Full article

Groundwater is a critical resource for agriculture and livelihoods, particularly in semi-arid regions such as Gujarat and Rajasthan in India. However, unsustainable extraction has led to aquifer depletion and increased water insecurity. This study uses Ostrom’s design principles to evaluate how Village Groundwater Cooperatives (VGCs) are transitioning toward self-governance in managing groundwater commons. Through field research in Dharta (Rajasthan) and Meghraj (Gujarat), including 33 key informant interviews and nine focus group discussions, this study assesses institutional robustness, rule enforcement, and community participation. Findings reveal that VGCs have the potential to enhance groundwater security through collective water budgeting and recharge interventions, though institutional robustness is constrained by limited formal enforcement. In Hinta, pipelines connected four wells to distribute water equitably, while in Dharta and Meghraj, traditional water-sharing agreements (two-part and three-part systems) sustained cooperation. Groundwater monitoring by trained “Bhujal Jankaars” helped farmers plan crop cycles, supporting informed crop choices that better aligned with available water supply. Despite these successes, to strengthen VGCs for effective groundwater management, formal sanctioning mechanisms are needed to address rule violations. Additionally, women’s participation in groundwater management decisions and operationalising VGCs is low. Conflict resolution mechanisms are currently informal. This study suggests that because women primarily manage domestic water needs while men manage irrigation, integrating women into decision-making is essential to reconcile competing water demands and ensure the long-term viability of VGCs. The findings provide policy insights for scaling up community-led groundwater governance in semi-arid regions. Full article

The global space economy, valued at approximately USD 400–630 billion (depending on definitional scope), is projected to expand rapidly, crossing USD 1 trillion as early as 2032 and reaching up to about USD 1.8 trillion by 2035. This growth has been driven by a surge (a roughly twelvefold increase) in satellite launches over the past decade, transforming Earth’s orbits into an increasingly congested domain plagued by space debris. The proliferation of space junk poses an escalating threat to orbital sustainability, yet effective governance mechanisms remain limited. This paper examines why conventional solutions for managing common-pool resources (command-and-control regulation, Pigouvian taxes, private property rights, allocation of tradable permits, and horizontal governance regimes) are not fully effective or are difficult to implement in addressing the orbital debris problem. Using a system dynamics perspective, the study qualitatively maps hypothesized feedback mechanisms shaping orbital expansion and space debris accumulation. It suggests that, under the assumed causal structure, reinforcing growth loops associated with geopolitical rivalry and commercial cost reductions linked to the New Space paradigm currently dominate over delayed balancing effects arising from the finite nature of orbital space, whose regenerative capacity is progressively degraded. There exists a threshold of exploitation beyond which orbital space effectively behaves as a non-renewable resource. The analysis suggests that, without binding international coordination, meaningful intervention may require the occurrence of a catalyzing crisis—e.g., a localized cascade of orbital object collisions that could transform stakeholder perceptions and enables active debris removal deployment. Full article

Background: Type B Aortic Dissection (TBAD) management relies on risk stratification, yet evidence-based tool adoption remains inconsistent in National Health Services (NHSs). Bridging the gap between Emergency Medicine (EM) and Vascular Surgery remains essential for timely diagnosis, optimal risk stratification, and appropriate intervention to improve outcomes and reduce mortality. Methods: A cross-sectional survey of EM consultants yielded n = 173 valid responses from n = 33 units across the UK. Subgroup analyses were conducted using a Chi-square test (p < 0.05) alongside descriptive analysis. A pooled prevalence analysis of the literature, utilizing a random-effects model at a 95% confidence interval (CI), served as a benchmark for perception analysis. Agreement was evaluated using Bland–Altman analysis, incorporating upper, lower, and overall bias of agreeability. Results: Access to a rapid Computed Tomography Angiogram (CTA) was 70% (95% CI: 63.3–76.8%, p < 0.001), while 32% had standard operating procedures (SOPs) for TBAD (95% CI: 25.3–39.1%), and 26% were aware of any decision tool (95% CI: 20.6–33.6%). Labetalol as a first-line antihypertensive was more common amongst least experience (p < 0.05). TBAD diagnosis increased 1.6-fold with every 4 years of additional experience (p < 0.05). Perception analysis showed strong agreement for pain (characteristics and location), hypertension, gender, and age with moderate-to-low agreement for other factors with a reported bias of 23.58% (−38.20% to 85.36%) (p = 0.02). Conclusions: The survey suggests a degree of misperception and inconsistency in recognition of most and least prevalence factors for TBAD suspicion and management. This outcome advocates targeted strategies to enhance diagnostic accuracy using tools aligned with NHS resources and QALY frameworks. Furthermore, upon recognition of the most prevalent factors, CTA and specialist referral is advocated. Full article

This work addresses whether heterogeneity in player endowments influences investment decisions in common pool resource (CPR) games, shedding light on the relationship between inequality and economic decision making. We explore two theoretical avenues from behavioral economics—linear other-regarding preferences and inequity aversion—and examine the predictions of each with a laboratory experiment. Our experimental results roundly reject the majority of these explanations: in treatments with endowment inequality, high endowment individuals invest more in the common pool resource than low endowment individuals. We discuss these results in the context of the literature on psychological entitlement and positional preferences. Full article

Quinoa (Chenopodium quinoa, 2n = 4x = 36, AABB subgenomes) is a highly nutritious crop with the potential to diversify global diets and alleviate malnutrition. It is also adaptable for production in soils increasingly affected by salinization and water scarcity. Quinoa was domesticated and artificially selected as a crop within the Andes Mountains, the geographically isolated Mediterranean climate zone of coastal Chile, and along the northwestern fringe of the Argentine dry Pampas. In addition, there is now abundant information regarding the wild species that were its immediate ancestors and which should be viewed as its secondary and tertiary breeding gene pools. These same ancestors contributed to independent domestications of the other forms of “quinoa” in ancient Mesoamerica and eastern North America from a common AABB ancestor-species, C. berlandieri, known commonly as pitseed goosefoot (PG). This review explores the biogeography of the diploid and polyploid relatives of the AABB allotetraploid goosefoot complex (ATGC). The seven or more ecotypes of PG, including the South American taxon C. hircinum, or avian goosefoot (AG), contain broad genetic variability, and some can be used directly as crossing partners in making quinoa breeding populations. Of the extant diploid relatives, C. subglabrum (SMG) is most closely related to the original maternal subgenome A of PG, while C. suecicum (SWG) or C. ficifolium (FG) are most closely related to paternal subgenome B. These and the other AA and BB diploids are valuable model organisms for locating and modifying genes of interest and their expression, the ultimate goals being to increase quinoa’s yield potential, improve its nutritional attributes, explore value-adding industrial uses, and enhance quinoa’s already formidable mechanisms to resist environmental stresses. This review is an update on the current state of quinoa breeding, with an emphasis on the value of wild genetic resources for quinoa improvement. It provides a comprehensive review of the scientific literature for scientists interested in adding quinoa to their breeding program. Full article

The demand for real-time land cover mapping from high-resolution remote sensing (HR-RS) imagery motivates lightweight segmentation models running directly on satellites. By processing on-board and transmitting only fine-grained semantic products instead of massive raw imagery, these models provide timely support for disaster response, environmental monitoring, and precision agriculture. Many recent methods combine convolutional neural networks (CNNs) with Transformers to balance local and global feature modeling, with convolutions as explicit information aggregation modules. Such heterogeneous hybrids may be unnecessary for lightweight models if similar aggregation can be achieved homogeneously, and operator inconsistency complicates optimization and hinders deployment on resource-constrained satellites. Meanwhile, lightweight Transformer components in these architectures often adopt aggressive channel compression and shallow contextual interaction to meet compute budgets, impairing boundary delineation and recognition of small or rare classes. To address this, we propose SatViT-Seg, a lightweight semantic segmentation model with a pure Vision Transformer (ViT) backbone. Unlike CNN-Transformer hybrids, SatViT-Seg adopts a homogeneous two-module design: a Local-Global Aggregation and Distribution (LGAD) module that uses window self-attention for local modeling and dynamically pooled global tokens with linear attention for long-range interaction, and a Bi-dimensional Attentive Feed-Forward Network (FFN) that enhances representation learning by modulating channel and spatial attention. This unified design overcomes common lightweight ViT issues such as channel compression and weak spatial correlation modeling. SatViT-Seg is implemented and evaluated in LuoJiaNET and PyTorch; comparative experiments with existing methods are run in PyTorch with unified training and data preprocessing for fairness, while the LuoJiaNET implementation highlights deployment-oriented efficiency on a graph-compiled runtime. Compared with the strongest baseline, SatViT-Seg improves mIoU by up to 1.81% while maintaining the lowest FLOPs among all methods. These results indicate that homogeneous Transformers offer strong potential for resource-constrained, on-board real-time land cover mapping in satellite missions. Full article

Sometimes referred to as an influential variant of payment for ecosystem services (PES), Water Funds are among the most promoted schemes in Latin America to foster environmental conservation while securing water provision to some of the region’s largest cities. Despite their growing importance, empirical research on the impacts of Water Funds as institutions that reshape watershed governance remains limited. In this study, we analyze five Water Funds in Colombia affiliated with the Latin American Water Funds Partnership through the lens of common-pool resource institutions. Drawing upon Ostrom’s Institutional Analysis and Development Framework, we analyze the factors that explain why some Water Funds in Colombia remain active while others dissolve. Specifically, we examine how the rule-making process is influenced by institutional strength, stakeholder trust, and collaboration with environmental authorities, creating outcomes of continuity or dissolution of these governance structures. Our research relies on qualitative methods, including remote interviews with pertinent actors and stakeholders associated with each Water Fund. The findings reveal that although Water Funds can serve as novel governance spaces where diverse public and private stakeholders engage concerning watershed governance, particular challenges persist, putting the continuity of Water Funds at risk. These challenges relate to including a wider array of actors, such as landowners and certain public institutions in the Funds’ management bodies, and the need to foster a shared watershed vision between actors to enhance legitimacy and trust among them. Full article

Accurate land cover mapping is essential for environmental monitoring and agricultural management. Sentinel-2 imagery, with high spatial resolution and open access, provides valuable opportunities for operational classification. Convolutional neural networks (CNNs) have demonstrated state-of-the-art results, yet their adoption is limited by high computational demands and limited methodological transparency. This study proposes a lightweight CNN for soil–vegetation classification, in Dolj County, Romania. The architecture integrates three convolutional blocks, global average pooling, and dropout, with fewer than 150,000 trainable parameters. A fully documented workflow was implemented, covering preprocessing, patch extraction, training, and evaluation, addressing reproducibility challenges common in deep leaning studies. Experiments on Sentinel-2 imagery achieved 91.2% overall accuracy and a Cohen’s kappa of 0.82. These results are competitive with larger CNNs while reducing computational requirements by over 90%. Comparative analyses showed improvements over an NDVI baseline and a favorable efficiency–accuracy balance relative to heavier CNNs reported in the literature. A complementary ablation analysis confirmed that the adopted three-block architecture provides the optimal trade-off between accuracy and efficiency, empirically validating the robustness of the proposed design. These findings highlight the potential of lightweight, transparent deep learning for scalable and reproducible land cover monitoring, with prospects for extension to multi-class mapping, multi-temporal analysis, and fusion with complementary data such as SAR. This work provides a methodological basis for operational applications in resource-constrained environments. Full article

Elite capture, a power structure problem involving rent-seeking, hinders sustainable water resources management. Governments play crucial roles in instilling public legitimacy in water governance, a common-pool resource that benefits from cooperative solutions such as pilot competitions, co-monitoring, and inter-agency coordination. A study of South-to-North Water Diversion Projects in China showed how, when governments outsource small projects to local sub-contractors, a method named moderate supervision (ruo jiandu) can enable effective oversight, which is superior to a bidding model with strict supervision (qiang jiandu). The concept of moderate supervision was initiated in 2023, before which most small projects had been left in a risky state with no supervision (ling jiandu). Analysis of a case in Shandong Yellow River Water Diversion Irrigation Area involved semi-structured in-depth interviews. Findings revealed that an elite-government-villagers tripartite spiral was composed of 3 dimensions reshaping a positive elite culture: first, a whitelist of qualified local contractors; second, co-monitoring of multiple stakeholders with influence exerted by a three-tier mobilization system; third, inter-agency coordination innovatively enabling smooth functioning between policy entrepreneurs of formal institutions and local social governance of informal ones. Policy implications to underscore real-world applicability are provided. Full article

This study examines the peer effects of bank digital transformation facilitated by shareholder networks and explores the underlying mechanisms. A time-varying network is constructed based on common shareholder connections among banks, and a corresponding measure is developed to quantify peer effects in digital transformation. Using the Peking University digital transformation index together with ownership and financial data from CSMAR, an empirical analysis is performed on a panel of 114 Chinese commercial banks from 2010 to 2021 to evaluate these effects. Fixed-effects estimations indicate that bank digital transformation is significantly affected by peer effects transmitted through common shareholder connections, with a one-unit increase in peers’ digitalization index associated with a 0.151-unit rise in the focal bank’s index. These findings remain robust and economically meaningful across alternative specifications, including system GMM, IV/2SLS designs, and different ownership thresholds. Further analyses indicate that the peer effects operate through mechanisms such as intensified competition, enhanced information sharing, and pooled resources. However, such peer influence also exacerbates disparities in digital progress across the industry, reflecting a Matthew Effect in which leading banks consolidate their advantages. Heterogeneity analysis reveals that the peer effects are more pronounced among banks with larger workforces, more diversified operations, and higher ownership concentration. The findings of this study provide insights into how financial institutions can leverage technological innovations through network-based channels, offering practical implications for promoting industry-wide transformation in the digital economy era. Full article