Found 400 results
Open Access
Article
21 May 2026Stand Still and Die: Integrating Multi-Stakeholder Communication to Bring Fairness Back to the Autonomous Vehicle Trolley Problem
While rare, it is widely accepted that autonomous vehicles (AVs) will find themselves in dilemma scenarios involving vulnerable road users (VRUs). The ethics of these dilemma situations have been debated extensively in the context of trolley-problem-like scenarios. What has not been noted is the inherent unfairness implicit in many of these discussions, in which VRUs are seen as passive bystanders with no say in what befalls them. Rather than simply remaining still in a collision scenario, VRUs can (and often do) take action that needs to be accounted for. If we are to increase fairness on public roads, it is important that AVs communicate with VRUs. This paper presents a highly theoretical discussion on the possibility of using communication tools (such as the V2X system) and techniques (derived from the science of human-machine interaction) to support protective, risk-reducing responses from VRUs during inevitable AV collisions. The paper begins with a brief ethical exploration of fairness in the context of current debates surrounding AV collisions. We proceed to discuss possible technical solutions to AV-VRU communication, as well as the types of audio, visual, and tactile communication strategies necessary in critical scenarios.
Open Access
Article
15 May 2026Reframing ʿUrf and Istiṣlāḥ in Biocultural Governance: Indonesian Halal-Health Movements
This study examines how classical Islamic legal concepts are rearticulated within contemporary Indonesian halal-health governance. Focusing on the concepts of ʿurf (custom) and istiṣlāḥ (public interest), the research investigates how normative traditions are integrated into biomedical regulation and institutional decision-making. Using qualitative textual and discursive analysis, the study analyzes fatwa documents, regulatory guidelines, policy statements, and scholarly writings related to halal pharmaceuticals, vaccination, and health certification. The findings indicate that ʿurf is increasingly mediated through administrative and certification frameworks, while istiṣlāḥ is progressively proceduralized through technical evaluation and performance indicators. Religious authority is reconfigured through interdisciplinary expert networks that combine juristic reasoning with scientific and bureaucratic validation. At the discursive level, Islamic ethical vocabulary is systematically integrated with public health rationality, producing hybrid forms of moral-technical legitimacy. These transformations suggest that halal-health governance operates through negotiated continuity rather than epistemic rupture. Classical legal concepts are neither abandoned nor preserved unchanged; rather, they function as discursive interfaces between tradition and institutional governance. By highlighting the infrastructural conditions of ethical adaptation, this study contributes to a more nuanced understanding of Islamic normativity under contemporary biocultural and regulatory regimes.
Open Access
Article
13 May 2026Multi-Agent Reinforcement Learning for Optimal Operation of PV-ES-EV Microgrids
Aiming at the difficulty in balancing economic efficiency and islanding autonomy security during grid-connected operation of microgrids, as well as the limitation of fixed weights in traditional multi-objective optimization, this paper proposes a grid-connected interactive optimization strategy considering dynamic autonomy weights. A microgrid autonomy index is defined to quantify islanding preparedness, and a lightweight prediction network is designed to generate online weights for the three objectives of economy, security, and autonomy, so as to realize adaptive adjustment of the optimization focus. Furthermore, the Multi-Agent Proximal Policy Optimization (MAPPO) algorithm is adopted to coordinate photovoltaics, energy storage, electric vehicle chargers, various loads, as well as power purchasing and selling, enabling decentralized decision-making. Results show that the proposed strategy achieves economic performance close to that of economic-only optimization (i.e., disregarding islanding preparedness) under grid-connected conditions without external faults, while shortening the interruption duration of critical loads by more than 72% during islanding transition caused by external grid faults. Meanwhile, the state of charge (SOC) remains strictly within the operational safety band of 20–90% throughout all dispatch cycles, complying with industry norms for battery cycle life preservation. The dynamic weights for economy, security, and autonomy are generated online by a lightweight neural network based solely on real-time system states rather than being fixed a priori, verifying the effectiveness of the proposed mechanism in achieving a context-aware trade-off among conflicting objectives.
Open Access
Article
13 May 2026Exploration of Management Systems for Characteristic and Endemic Regional Food Resources in China
China, with its vast territory, harbors abundant regional food resources with multiple values in nutrition, ecology, and anthropology. However, simply adopting the World Trade Organization’s (WTO) Geographical Indication (GI) system for classifying and managing these agricultural products fails to fully reflect their authentic natural and anthropological attributes, which cannot support the development of local characteristic economies and food cultural ecosystems. Therefore, there is an urgent need to establish a hierarchical classification standard system for regional food resources tailored to China’s national conditions. This paper proposed a new definition for China’s endemic and characteristic food resources and summarizes interdisciplinary research methods for exploring their biological and cultural attributes. Additionally, the economic and sociological values of these resources were discussed. The proposed classification standards provide guidance for the industrialization of regional food resources in China and offer new ideas for transforming biodiversity into novel productive forces in characteristic industries.
Open Access
Article
12 May 2026Detecting and Mapping Stoebe vulgaris Post Herbicide Control, Using UAV Imagery and Machine Learning
Stoebe vulgaris is a declared indigenous bush encroacher species in South Africa. It has invaded over 11 million ha of grasslands. It is commonly called bankrupt bush due to its ability to outcompete other indigenous forb and grass species, decreasing grazing capacity, biodiversity, and ecosystem functioning, eventually leading to financial ruin for farmers. Landowners are legally required to control the plant. A herbicide trial was set up in a severely encroached camp at Dundee Research Station in KwaZulu-Natal, South Africa, to test the effectiveness of metsulfuron-methyl (50 g active ingredient ha−1) in controlling S. vulgaris. Applying metsulfuron-methyl provided a significant long-term reduction in S. vulgaris cover over six years. However, effective monitoring and management strategies depend on knowledge of the spatial distribution and expansion patterns of invasive species. We evaluated the ability of UAV-based imagery and machine learning, using Picterra, to detect and map S. vulgaris, while determining the optimal parameters to maximise detection accuracy. The best season for image acquisition was late summer when vegetation was at peak growth and maturity, providing the best spectral distinction between species, under light overcast and mild wind conditions. We recommend careful consideration of the flight orientation to the solar angle. We achieved 92% detector accuracy, with multispectral imagery enhancing the discrimination of similarly coloured plants. Plants smaller than 10 cm were not detected by the model. Our approach, using high-resolution drone imagery and AI, is capable of individual plant detection suited to a farm scale. This opens the way for using advances in drone technology for targeted, spot-application of herbicide.
Open Access
Article
12 May 2026Impact of a Government Ban on Paraphenylenediamine (PPD) Availability: An Interrupted Time Series Analysis of Suicidal Poisoning Cases in Bahawalpur, Pakistan (2016–2024)
Paraphenylenediamine (PPD), locally known as “Kala Pathar”, has historically been a major agent of suicidal self poisoning in Southern Punjab, Pakistan. In response to escalating morbidity and mortality, the Government of Punjab implemented a policy prohibiting the commercial scale distribution of raw PPD at the end of 2017. This study aimed to quantitatively evaluate the impact of this policy on the incidence of PPD-related suicidal poisoning in Bahawalpur using an interrupted time series design. A quasi-experimental, retrospective interrupted time series (ITS) analysis was conducted using hospital records from the emergency department of Bahawal Victoria Hospital, Bahawalpur, from January 2016 to March 2024. Annual counts of confirmed PPD poisoning cases were analyzed. The intervention point was defined as January 2018. Segmented regression analysis was performed to estimate changes in both the level and the trend following policy implementation. A total of 4455 PPD poisoning cases were recorded during the study period. Prior to the intervention, cases increased from 832 in 2016 to a peak of 1243 in 2017. Following the prohibition, cases declined sharply to 407 in 2019 and further to 155 in 2023. Segmented regression analysis demonstrated a statistically significant immediate reduction in case level after the intervention (β2 < 0, p < 0.05), along with a significant negative change in post intervention trend (β3 < 0, p < 0.05), indicating a sustained decline in PPD poisoning incidence. The majority of cases occurred among males (72%) and individuals aged 21–40 years (48%). The prohibition of commercial scale PPD distribution was associated with a significant and sustained reduction in PPD-related suicidal poisoning in Bahawalpur. These findings support targeted means restriction policies as an effective suicide prevention strategy in resource limited settings.
Open Access
Article
12 May 2026Low-Carbon Economic Dispatch for Offshore Wind-Solar Grid-Connected Systems Considering Source-Load Uncertainty and Carbon Emission Flow
Marine are endowed with abundant renewable resources such as wind and solar energy. The rational utilization of these resources through offshore wind turbines and photovoltaic plays a vital role in achieving energy conservation and emission reduction for marine energy systems. However, the challenges of grid integration and prominent uncertainties caused by large-scale penetration of offshore wind and photovoltaic (PV) energy into marine power systems severely threaten power balance, operational stability, and reserve allocation. To pursue low-carbon economic operation and collaboratively address source-load uncertainties in marine energy systems, this paper proposes a low-carbon economic dispatch model for offshore wind-PV grid-connected systems that considers source-load uncertainties and carbon emission flow (CEF). A bi-level optimization framework is adopted. The upper level establishes a unit output optimization model to handle source-load uncertainties via fuzzy chance-constrained programming, which converts the uncertain problem into a deterministic equivalent under a predefined confidence level, with the objective of minimizing the total operation cost and carbon cost. The lower level constructs a load response model incorporating CEF theory and carbon trading mechanisms to optimize load allocation, thereby achieving coordinated reductions in carbon emissions and carbon-related costs. Finally, the modified IEEE 57-node system is employed for case studies, and the proposed model is solved and validated using the CPLEX solver. The results demonstrate that the presented method can effectively mitigate the adverse impacts of offshore renewable energy fluctuations, enhance the stability and low-carbon economy of marine power systems, and provide a feasible dispatch solution for large-scale grid integration of offshore wind and PV energy.
Open Access
Article
12 May 2026Critical Conservation Gaps for Microendemic Axolotls Reveal Inadequate Protection in Central Mexico
Salamanders of the genus Ambystoma in the Trans-Mexican Volcanic Belt are experiencing severe population declines due to habitat loss and fragmentation. This study evaluated critical protection gaps for four Critically Endangered microendemic species: A. amblycephalum, A. andersoni, A. dumerilii and A. mexicanum. We compiled and cleaned 89 validated presence records from databases and the literature. Refined areas of occupancy were calculated using minimum convex polygons adjusted with elevation masks, hydrographic network filters, and species-specific buffer zones (50–100 m). Bioclimatic variables (temperature and precipitation-based) were derived from MexHiResClimDB, and overlap with protected areas, and the Ecosystem Integrity Index (EII) was quantified. The resulting areas of occupancy (0.38–108.19 km2) were larger than previous IUCN estimates for A. amblycephalum and A. dumerilii, yet showed null or minimal overlap with protected areas for these two species (4.79% and 0%, respectively). Ecosystem integrity was low across all species (EII 0.05–0.43), indicating severe degradation. Climatic niches were narrow, differentiated, and associated with restricted altitudinal ranges. These results reveal a crisis of effective protection, where expanded distribution knowledge does not translate into improved conservation status, demanding urgent expansion of active conservation strategies to counteract severe habitat degradation caused by urbanization, intensive agriculture, pollution, and invasive species.
Open Access
Article
09 May 2026Chiral Aromatic Hydroxylamine-Coadsorbed TiO2 Photocatalysts for Enantioselective Hydrogenation of Aromatic Ketones: Influence of Crystal Shapes and Facets
Enantioselective photohydrogenation using semiconductor photocatalysts remains challenging because of the heterogeneity of solid surfaces and the difficulty in controlling adsorption geometries. In this study, we systematically investigated the enantioselective photohydrogenation of aromatic ketones using TiO2 photocatalysts in the presence of chiral co-adsorbents, focusing on the combined effects of co-adsorbent structure and TiO2 crystal morphology. Chiral aromatic amino alcohols, such as 2-amino-1-phenylethanol (PhEA), were identified as effective and relatively photostable co-adsorbents, affording moderate enantioselectivity with reduced inhibition compared with carboxylate-type co-adsorbents. Structural analyses revealed pronounced differences in particle size, lattice distortion, and inferred exposed crystal facets among anatase TiO2 samples. TIO-13, composed of larger particles with relatively well-defined surface structures, exhibited higher and more reproducible enantioselectivity, whereas TIO-7, composed of smaller nanoparticles with more heterogeneous surfaces, showed higher reaction rates but lower enantioselectivity. Consecutive photohydrogenation experiments provided supportive evidence that residual surface-adsorbed chiral co-adsorbent contributes to both asymmetric induction and inhibition of the reaction. Although the present work should be regarded primarily as a fundamental study rather than a practically optimized catalytic methodology, it provides useful insight into the design of chiral semiconductor photocatalysts for heterogeneous asymmetric photocatalysis.
Open Access
Article
08 May 2026Macroeconomic Dynamics of Environmental Degradation in India: Evidence and Limits of Structural Transition Toward Sustainability
Understanding the macroeconomic determinants of environmental degradation is critical for designing effective and evidence-based sustainability policies in emerging economies. This study provides a comprehensive empirical re-examination of the growth–energy–environment nexus in India over the period 1990–2023 within an extended macroeconomic framework. It integrates key structural drivers—economic growth, energy consumption, industrialization, trade openness, urbanization, and renewable energy—into a unified analytical model to capture the complex interactions between development processes and environmental outcomes. Methodologically, the study employs the Autoregressive Distributed Lag (ARDL) bounds testing approach within an error-correction framework, allowing for the estimation of both long-run equilibrium relationships and short-run dynamic adjustments under mixed orders of integration. The robustness of long-run estimates is further assessed using alternative cointegration techniques, while diagnostic and stability tests ensure the reliability of the empirical specification. The results confirm the presence of a stable long-run cointegrating relationship among the variables. However, the estimated long-run elasticities are heterogeneous and generally weak in statistical strength. Economic growth and energy consumption exhibit positive but modest associations with environmental degradation, indicating the persistence of scale effects and structural dependence on fossil fuel–based energy systems. In contrast, the effects of trade openness and industrialization are not statistically robust, suggesting that structural transformation and globalization have not yet translated into consistent environmental efficiency gains. Renewable energy does not demonstrate a significant long-run mitigating effect, reflecting its limited penetration and integration within the broader energy system. Short-run dynamics reveal asymmetric adjustment patterns. Energy consumption shows a negative and significant short-run effect, implying transitional efficiency gains, whereas industrialization contributes positively to environmental pressure in the short term. Urbanization exhibits divergent temporal effects, with short-run improvements but long-run environmental costs. The significant error-correction term indicates gradual convergence toward equilibrium. Overall, the findings highlight a nuanced and evolving relationship between macroeconomic processes and environmental degradation in India, underscoring the need for structurally aligned and context-specific policy interventions.
