Search Results (732)

This study examines how different types of word-of-mouth (WOM) influence online purchase intention (OPI) among rural residents, an area not yet fully explored. Based on social tie strength theory, we classify WOM into “quantity-sourced” (e.g., friends, family, general consumers) and “quality-sourced” (e.g., influencers, celebrities, professionals). We propose a chain mediation model involving social distance (SD) and perceived value (PV). Using survey data from 1005 rural residents in Jiangxi Province, China, and analyzing the data with structural equation modeling (SmartPLS 4), we find that quantity-sourced WOM positively affects OPI (β = 0.135), while quality-sourced WOM negatively affects it (β = −0.166). Mechanism analysis shows SD is a key mediator: quantity-sourced WOM shortens SD, thereby increasing OPI (β = 0.152), whereas quality-sourced WOM widens SD, reducing OPI (β = −0.047). PV mediates between quantity-sourced WOM and OPI (β = 0.043), but it shows no significant mediation between quality-sourced WOM and OPI (β = −0.002). Additionally, SD and PV serve as chain mediators between both types of WOM and OPI. These findings extend WOM theory to rural contexts and offer practical insights for governments and e-commerce platforms to develop differentiated WOM strategies and build localized WOM networks. Full article

Urban inland flooding has become a serious problem in many cities because heavy rain often exceeds the capacity of drainage systems. In Japan, GIS-based evacuation maps are commonly used to support disaster preparedness, but they still have several limitations. In particular, they do not avoid flooded road segments and cannot generate multiple evacuation options at the same time. This study proposes an improved evacuation route method using the free and open-source software QGIS. The method combines flood-depth data with road network processing to remove roads where the predicted water depth is higher than 0.5 m. It also provides several evacuation paths to different shelters at the same time. A case study in Kurashiki City, Okayama Prefecture, demonstrates that about 1.37% of the road network becomes unusable during an inland-flood scenario. Several existing evacuation routes also pass through hazardous areas, but the QGIS-based method avoids these areas in most cases. Since the workflow uses only built-in QGIS functions and does not require programming or plug-ins, it is easy to reproduce and apply in other regions. This study offers a practical and low-cost method to support inland-flood evacuation planning for local governments. Full article

When it rains or snows over a city, water droplets capture airborne pollutants and transport them to the ground. Prolonged precipitation over the same area can remove a larger amount of pollution; however, rainfall systems vary in duration and tend to move rapidly across regions. Wet deposition sprinklers replicate this natural scavenging process. They can operate for extended periods as needed and can be installed at specific locations where pollution mitigation is most necessary. Despite encouraging experimental results and the widespread use of similar technologies in industrial sectors—such as mining, the construction industry, and waste management—very limited scientific research has focused on their application in urban environments. In particular, their use as an emergency measure during severe pollution episodes as a protective intervention for sensitive subjects, while awaiting the effects of long-term structural solutions, remain largely unexplored. In the present work, we systematically discuss the key elements required to design and implement a network of anti-smog cannons (ASC) to protect sensitive receptors from severe air pollution events in large cities. Based on this analysis, we established a generalized framework that can be applied to any urban context worldwide. We also examine the potential application of the proposed method to the city of Turin (≈850,000 inhabitants, north-western Italy), which is considered a representative case study for other cities in Western Europe. Our findings indicate that such a network is both technically feasible and economically sustainable for local government authorities. Full article

Many Australian suburbs are threaded with open drainage networks. However, a preoccupation with drainage functions means that most of this drainage land delivers few liveability benefits to surrounding communities. As a result, numerous Local and State Governments are engaged in providing Living Stream upgrades to drainage land. Nonetheless, questions remain about where such improvements should be targeted for maximum benefit. In response, this paper documents a Delphi survey of experts and a related geospatial suitability analysis using a wide-ranging set of urban, societal, and environmental criteria to determine which areas of drainage land are most suitable for upgrades in Perth, Western Australia, a city which experiences a Mediterranean climate. The novelty of the paper’s contribution stems from the highly seasonal rainfall and related ephemeral summer hydrology distinguish Perth from many other cities where Water-Sensitive Urban Design is well-established. Moreover, the inclusion and evaluation of both tangible criteria (e.g., areas with a shortage of Public Open Space) and more intangible criteria (e.g., areas with population experiencing psychological distress) in the suitability analysis are comparatively rare. The results indicate that Living Stream-oriented Public Open Space should be deployed in areas with limited Public Open Space reserves, urban forest degradation, increasing urban densification, and Urban Heat Island challenges. Full article

This study explores the persistent barriers hindering women’s meaningful participation in South African politics, with a particular focus on the widespread lack of support that women encounter across various social and institutional domains. Despite South Africa’s progressive constitutional and legislative framework promoting gender equality, the research reveals that many women in politics face systemic non-support from family structures, peer networks, community members, political parties, and even fellow women leaders. Using a feminist political theory lens, particularly liberal and radical feminism, the study focuses on how these barriers constrain women’s political participation at the local level. The study specifically investigates how lack of support affects women’s ability to participate, exercise influence, and access decision-making in local governance. Qualitative data drawn from in-depth interviews highlights experiences of tokenism, exclusion from decision-making, inadequate mentorship, and intra-gender rivalry. Political parties, in particular, emerge as critical gatekeepers that publicly promote gender equity while privately reproducing male-dominated power structures. The study concludes that achieving substantive equality requires more than representational quotas; it demands a structural shift in political culture, values, and leadership practices to foster inclusive and supportive environments that empower women to lead authentically and effectively. Full article

Nonlinear seepage behavior within rock fractures represents a critical and actively researched challenge in underground engineering, energy exploitation, and environmental sciences. Through the integration of nonlinear seepage theory with coupled numerical simulations of fracture flow and matrix flow, this study systematically investigates the synergistic mechanisms governing the influence of filling particles, tortuous fractures, and porous matrices on fluid transport within fracture–porous matrix seepage systems. Key findings reveal that: (1) Horizontal fractures continuously receive fluid influx from the surrounding porous matrix, where the flow field maintains remarkable symmetry, with a critical matrix height-to-fracture aperture ratio regulating streamline divergence and convergence at the fracture outlet; (2) The flow field within horizontal fractures undergoes substantial transformation when the Reynolds number exceeds a critical threshold, while maintaining stable flow patterns and -ΔP-Q relationships below this value, demonstrating a distinct inertial-controlled flow regime transition; (3) Tortuous fracture geometries induce localized vortex formation and significant velocity fluctuations, particularly in the front and rear dip-angle zones, substantially enhancing fluid exchange efficiency compared to horizontal configurations; (4) The volumetric flow rate exhibits a non-monotonic relationship with inclination angle, peaking at approximately 36°, while a synergistic effect between fracture inclination and infill particle diameter systematically modulates pressure-drop-flow-rate relationships, with a critical d/h = 0.5 threshold distinguishing fundamentally different flow behaviors. These findings provide quantitative criteria for predicting nonlinear seepage in practical engineering scenarios involving complex fracture networks and filling materials, offering significant implications for risk assessment and drainage design in deep underground projects. Full article

This study examines the roles, policy alignment, and challenges of civil society organizations (CSOs) in China’s disaster risk reduction (DRR) efforts post-2008 Wenchuan Earthquake. Using qualitative analysis of national policies, international frameworks, and academic literature, it traces the evolution of Chinese CSOs from peripheral actors to state-integrated partners in disaster risk governance. Findings reveal that China’s top-down system has progressively institutionalized CSOs through Five-Year Plans, enabling their participation in emergency response and community resilience by using technological innovation. However, their contributions remain skewed toward short-term relief, with limited engagement in risk reduction or global humanitarian initiatives. Challenges include fragmented government–CSO collaboration and reliance on informal networks. While CSOs demonstrate growing technical proficiency, systemic barriers—such as funding gaps, weak institutionalized partnerships, and ideological divergences—hinder sustainability. Recommendations emphasize capacity building in risk education, policy literacy, and technology adoption, alongside reforms to formalize cross-sector collaboration and expand international engagement. By addressing these gaps, Chinese CSOs could transition from crisis responders to proactive agents of sustainable resilience, aligning local actions with global DRR agendas. This research offers critical insights for policymakers and practitioners seeking to optimize CSOs’ role in national and local risk governance and invest in their development. Full article

The digital economy (DE) serves as a crucial engine for breaking through technological stagnation at the low end and achieving carbon neutrality. However, existing studies predominantly explore the impact of the DE on local carbon reduction based on “attribute data”, with less focus on regional carbon collaborative reduction. This study employs a directed-weighted complex network analysis, using provincial panel data from China spanning 2012 to 2022, to characterize the evolutionary features of China’s Inter-regional Collaborative Carbon Reduction Governance Network (ICCGN). Using the Exponential Random Graph Model (ERGM) as an empirical test, the study explores how the DE facilitates collaborative carbon reduction. The results indicate the following: (1) The ICCGN demonstrates transitive triadic linkages, accompanied by increasingly blurred governance boundaries. The Eastern coastal areas have the highest network centrality, and the network core areas, including Guangdong, Chongqing, Gansu, and Qinghai, are gradually expanding, leading to further weakening of governance boundaries. The network’s spatial clustering structure presents four distinct blocks, with network spillover relationships concentrated in the first, third, and fourth blocks. The Eastern coastal areas play a “hub” role in undertaking carbon collaborative reduction, radiating and driving the central and western provinces. (2) From the perspective of the induced effect, the DE enables carbon collaborative reduction, exhibiting isotropic characteristics. (3) Heterogeneity tests show that regions with well-developed digital infrastructure and those with free trade zone constructions promote better effects, with a positive feedback effect in network status: betweenness centrality > degree centrality > closeness centrality. (4) Regarding the enabling mechanism, the DE drives carbon collaborative governance by enhancing technological innovation, promoting industrial structure upgrades, nurturing scientific talents, and reducing educational disparities. Full article

Rural gentrification is transforming China’s countryside, yet the ways gentrified landscapes shape community co-build willingness across social groups remain unclear. Guided by the Hierarchy Effects Model (HEM) and Martin Phillips’ four-dimensional view of rural landscapes (material, symbolic, social, and living), this study develops a “landscape–emotion–intention” framework linking spatial–environmental continuity, cultural landscape transition, social interaction embeddedness, and new rural livability to community identity, sense of belonging, and co-build willingness. Based on 50 in-depth interviews in She Village, Nanjing, latent Dirichlet allocation (LDA) is used to extract key themes, which are combined with the four-dimensional framework to construct a 25-item questionnaire; 376 valid responses from immigrants and local villagers are then examined through multi-group structural equation modeling and artificial neural networks for robustness and importance analysis. Results indicate that cultural landscape transition and new rural livability are the main drivers of identity and belonging among immigrants, whereas cultural landscape transition, spatial–environmental continuity, and social interaction embeddedness are more critical for local villagers; in both groups, sense of belonging is the strongest predictor of co-build willingness. The study embeds HEM within gentrified rural settings, operationalizes stakeholder perceptions via an LDA–SEM–ANN pipeline, and proposes differentiated strategies for inclusive rural community building and sustainable governance. Full article

The exploration potential, storage capacity, and exploitability of the deep shale-gas reservoirs are governed by various characteristics of their pore networks. Conventional methods cannot fully capture these features across scales, highlighting the need for an integrated, multi-technique approach. In this study, pore structure and connectivity of the Wufeng–Longmaxi Formation (Luzhou Block) were investigated using Scanning Electron Microscopy (SEM) with the Mosaic Acquisition and Positioning System (MAPS), ImageJ (ImageJ 2.14.0)-based pore analysis, Mercury Intrusion Porosimetry (MIP), and Nuclear Magnetic Resonance (NMR). Based on the samples from eight reservoir layers of Wufeng-WF and Longmaxi-LM1₁^1–7, shale pore connectivity was classified into three grades. Grade A layers, with connected pore volumes above 0.0067 cm³/g and porosity exceeding 1.75%, showed trimodal NMR pore-size distributions and strong connectivity among micro, meso, and macropores. Grade B layers exhibited bimodal pore distributions, moderate pore connectivity (0.0057–0.0067 cm³/g; 1.55–1.75% porosity), and sponge-like organic pores with isolated mineral pores. Grade C layers, with connected pore volumes below 0.0057 cm³/g, showed poor connectivity and unimodal NMR responses. Connected pores (1–100 nm) contributed 20–35% of total pore volume, reflecting the strong heterogeneity of the formation. Interconnected inorganic mineral-hosted pores were found to link locally connected organic pores, forming continuous pore networks. The qualitative and quantitative identification of the pore connectivity of shale reservoirs with MAPS, MIP, and NMR approach provides a robust framework for evaluating shale pore connectivity and identifying high-quality reservoir targets. Full article

Agroecology is recognized as a resilient agricultural system amid the ecological crisis, but also as a social movement working towards better livelihoods for farmers. In Burkina Faso, the dynamics among actors promoting agroecology are not well understood. Effective governance of the agroecological transition necessitates a deeper comprehension of the interactions and networks involved. This study aims to identify, characterize, and analyze local actors and their networks to enhance governance for agroecological transition, focusing on two north and south-west regions of Burkina Faso to highlight regional differences. Using the Agricultural Knowledge and Information Systems (AKIS) as a conceptual framework, we conducted a literature review and facilitated focus group discussions during a workshop with stakeholders. Key participants include farmers, service providers, researchers, policymakers, NGOs, and organizations, which engage in political and technical interactions. The results show that the governance landscape is fragmented with public policies at both strategic and operational levels failing to effectively engage mainstream actors or translate into actionable support for agroecological practices. To transition agroecology from a fragmented niche to a widely adopted system, there is a critical need for consistent support for farmers, including knowledge sharing, networking opportunities, and marketing strategies. Full article

Zinc oxide (ZnO) nanostructures have been intensively investigated for applications in sensing, photocatalysis, and optoelectronic devices, where functional performance is strongly governed by morphology, crystallinity, and defect structure. Conventional wet-chemical and vapor-phase growth methods often require long processing times or complex chemistries and face reproducibility and compatibility challenges when applied to thin, flexible, or curved metallic substrates. Pulsed high-energy techniques—such as pulsed laser deposition (PLD), high-power impulse magnetron sputtering (HiPIMS), and pulsed laser or plasma processing—offer a versatile alternative, enabling rapid and localized synthesis both from and on Zn-bearing thin shells. These methods create transient nonequilibrium conditions that accelerate oxidation and promote spatially controlled nanostructure formation. This review highlights the emerging integration of artificial intelligence (AI) with pulsed ZnO synthesis on thin metallic substrates, emphasizing standardized data reporting, Bayesian optimization and active learning for efficient parameter exploration, physics-informed and graph-based neural networks for predictive modeling, and reinforcement learning for adaptive process control. By connecting synthesis dynamics with data-driven modeling, the review outlines a path toward predictive and autonomous control of ZnO nanostructure formation. Future perspectives include autonomous experimental workflows, machine-vision-assisted diagnostics, and the extension of AI-guided pulsed synthesis strategies to other functional metal oxide systems. Full article

The dynamic interaction of memory and forgetting processes determines the formation, stability, and specificity of the engram. While the molecular genetic processes of learning and memory have been intensively studied, the mechanisms of active forgetting have only recently attracted the attention of neuroscientists. The emergence and disappearance of memory traces in the brain are regulated by specific signaling cascades that influence the morphological and functional properties of synaptic connections. Actin remodeling is known to be the basis of neuroplasticity. Cofilin normally acts as an actin severing protein, allowing the actin cytoskeleton to locally change its structure. LIMK-dependent inactivation of cofilin stabilizes filamentous (F)-actin in dendritic spines, being crucial for engram consolidation. On the other hand, a lack of globular (G)-actin prevents actin remodeling, so inactivation of cofilin also stimulates forgetting after learning. The effects of cofilin-dependent signaling pathways on the engram depend on both the type of memory and the model object. In this review, I focus on the role of neuronal actin remodeling in learning, memory retention and forgetting processes, as well as the signal pathways that govern actin cytoskeleton dynamics. Parallels between neuroplasticity and learning in artificial neural networks (ANNs) are also discussed. Full article

This study examines how environmental journalists in Eastern Indonesia develop innovative digital strategies to counter corporate disinformation while maintaining credible climate reporting amid systematic censorship and algorithmic suppression. Through ethnographic fieldwork with 34 environmental journalists in Makassar and surrounding maritime communities (2023–2024), combined with digital platform analysis and content verification tracking, this investigation reveals how local journalists create “networked verification archipelagos” that mirror traditional maritime communication systems to combat extractive industry misinformation. Our analysis revealed three primary counter-disinformation mechanisms: (1) community-based verification networks that successfully identified 87% of corporate misinformation within 48 h through traditional knowledge integration; (2) algorithmic resistance strategies that increased environmental content visibility by 156% through cultural framing techniques; and (3) cross-platform coordination that maintained journalist communication networks despite 34 documented censorship campaigns. These networks enable accurate environmental reporting despite corporate-sponsored disinformation campaigns, government restrictions on mining coverage, and social media algorithms that amplify climate denial content. The research demonstrates how journalists in the Global South develop decolonial approaches to counter-disinformation that challenge Western platform-centric fact-checking models while maintaining journalistic credibility and community accountability. These findings contribute to understanding power dynamics and coloniality in disinformation studies while offering insights for media literacy and democratic integrity in climate-vulnerable regions. Full article

Homeostasis, which supports and maintains brain function, results from the continuous regulation of thermodynamics within tissue: the balance of heat production, redox oscillations, and vascular convection regulates coherent energy flow within the organ. Neuroinflammation disturbs this balance, creating measurable entropy gradients that precede structural damage to its tissue components. This paper proposes that a thermodynamic unity can be devised that incorporates nanoscale physics, energetic neurophysiology, and systems neuroscience, and can be used to understand and treat neuroinflammatory processes. Using multifactorial modalities such as quantum thermometry, nanoscale calorimetry, and redox oscillometry we define how local entropy production (s_t), relaxation time (τ^R), and coherence lengths (λc) allow quantification of the progressive loss of energetic symmetry within neural tissues. It is these variables that provide the basis for the etiology of thermodynamic biomarkers which on a molecular-redox-to-network scale characterize the transitions governing the onset of the neuroinflammatory process as well as the recovery potential of the organism. The entropic probing of systems (PEP) further allows the translation of these parameters into dynamic patient-specific trajectories that model the behavior of individuals by predicting recurrent bouts of instability through the application of machine learning algorithms to the vectors of entropy flux. The parallel development of the nanothermodynamic intervention, which includes thermoplasmonic heat rebalancing, catalytic redox nanoreacting systems, and adaptive field-oscillation synchronicity, shows by example how the corrections that can be applied to the entropy balance of the cell and system as a whole offer a feasible form of restoration of energy coherence. Such closed loop therapy would not function by the suppression of inflammatory signaling, but rather by the re-establishment of reversible energy relations between mitochondrial, glial, and vascular territories. The combination of these factors allows for correction of neuroinflammation, which can now be viewed from a fresh perspective as a dynamic phase disorder that is diagnosable, predictable, and curable through the physics of coherence rather than the molecular suppression of inflammatory signaling. The significance of this set of ideas is considerable as it introduces a feasible and verifiable structure to what must ultimately become the basis of a new branch of science: predictive energetic medicine. It is anticipated that entropy, as a measurable and modifiable variable in therapeutic “inscription”, will be found to be one of the most significant parameters determining the neurorestoration potential in future medical science. Full article