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Shopping mobility accounts for a significant share of total travel, while the growth of e-commerce is reshaping consumer purchasing behaviour and retail dynamics. Comprehending how territorial and sociodemographic factors shape the choice between physical and digital retail channels is therefore a key issue for transport planning and sustainable urban mobility. In this context, it is important to understand how accessibility to different classes of retailers is configured and how it can impact purchasing choices. Through a discrete choice analysis, this study examines the sociodemographic and territorial determinants of purchasing behaviour, focusing on the clothing market. Four purchase alternatives are considered: medium-sized and small urban retail stores, shopping malls, online purchasing, and no purchase. This multi-alternative framework enables the direct estimation of substitution patterns not only between physical and digital retail, but also between distinct forms of physical retail. Data were collected through a survey conducted in Southern Italy, providing empirical evidence from a territorial setting that is structurally underrepresented in the existing literature. A multinomial logit model and a two-level hierarchical logit model incorporating pedestrian accessibility—measured as walking time from residence to the nearest clothing store—alongside sociodemographic and territorial attributes were calibrated to analyse alternative choice behaviour. The calibrated models show interesting results, highlighting the role of pedestrian accessibility in the choice of clothing stores in city centres. Age, income, and territorial variables further differentiate channel preferences across population segments. The findings offer relevant implications for policymakers, governance managers, urban planners, and researchers concerned with retail location, sustainable accessibility, and consumer behaviour. These insights are highly valuable for developing planning that addresses the United Nations 2030 Agenda, particularly Sustainable Development Goal 11. Full article

Endoscopic resection (ER) has become the preferred curative-intent treatment for early upper gastrointestinal cancer, given its superior safety profile compared to surgery. Over the past decade, technological and procedural innovation has substantially expanded the scope, safety, and precision of endoscopic submucosal dissection (ESD) and related techniques. This review synthesises current evidence on key advances relevant to upper gastrointestinal ESD practice. Enhanced imaging modalities have improved lesion detection and characterisation, as well as recognition of intraoperative anatomical structures during third-space endoscopy. A new generation of therapeutic endoscopes combines high-definition optics with substantially improved tip-down angulation and channel size, addressing a longstanding gap between diagnostic-class image quality and procedural capability. Resection strategies—including mechanical traction systems, saline immersion therapeutic endoscopy (SITE), and luminal drainage techniques—have reduced procedural complexity and improved dissection conditions. Dedicated closure technologies have improved management of large resection defects, potentially reducing resection-related morbidity. Deep resection techniques, including submucosal tunnelling endoscopic resection (STER), device-assisted endoscopic full-thickness resection (FTRD), knife-assisted full-thickness resection (kFTR), and endoscopic intermuscular dissection (EID), are extending organ-preserving resection to deeply invasive cancers and subepithelial lesions. Management of non-curative ESD resections is being refined through multicentre risk stratification studies. Advances in simulation, competency-based training, and artificial intelligence hold promise for standardising technique acquisition and real-time procedural support. Together, these innovations are reshaping upper gastrointestinal oncology by positioning minimally invasive, organ-preserving digestive endoscopy as a central therapeutic strategy. Full article

This study proposes a multi-objective optimization strategy for the structural design of liquid-cooled channels in battery systems, aiming to identify liquid-cooled plate design schemes with better cooling performance and acceptable flow resistance. Optimal Latin hypercube sampling (OLHS) was combined with computational fluid dynamics (CFD) simulations to construct a CFD-generated dataset that includes the maximum temperature and system pressure drop. Then, modeFRONTIER was employed to integrate surrogate-model training, rapid prediction, and non-dominated sorting genetic algorithm II (NSGA-II) optimization, thereby obtaining the Pareto optimal set. The technique for order preference by similarity to ideal solution (TOPSIS) decision method was further introduced to determine the final optimal design. Results indicate that the optimized liquid-cooling system exhibits outstanding comprehensive performance in terms of balancing heat dissipation and flow resistance at a 5 C discharge rate. Remarkably, sensitivity analysis shows that inlet velocity is the dominant factor affecting the maximum battery temperature, with a correlation coefficient of −0.789. The maximum temperature of the battery module is effectively limited to 30.07 °C, while the flow pressure drop is only 799.58 Pa, achieving an excellent balance between heat dissipation efficiency and energy consumption. Full article

The rapid expansion of the platform economy has made data-driven marketing a key mechanism through which e-commerce platforms create value, coordinate market participation, and shape downstream welfare outcomes. This study examines how competing e-commerce platforms choose between reselling and agency modes when only one platform can endogenously implement data-driven marketing. We develop a game-theoretic model consisting of one manufacturer, one data-capable platform, one traditional platform, and a consumer market. Four channel structures are considered: reselling–reselling, agency–reselling, reselling–agency, and agency–agency. The analysis combines Stackelberg game modeling within each channel structure with Nash equilibrium analysis across platform channel choices. The results show that channel equilibrium is jointly determined by the agency fee ratio and data-driven marketing efficiency. The data-capable platform is generally more inclined to adopt the agency mode, whereas the traditional platform’s preferred response varies across parameter regions. Under a low-commission environment, the two platforms may fall into a prisoner’s-dilemma structure in which joint reselling is Pareto superior but not stable in equilibrium. The results further show that manufacturer profit decreases with the agency fee ratio but increases with data-driven marketing efficiency, while consumer surplus rises with stronger data-driven marketing and is generally higher when the data-capable platform adopts agency. By linking platform competition, channel strategy, and stakeholder outcomes under data-driven marketing, this study contributes to research on value creation and sustainable governance in the platform economy, and it offers managerial implications for data monetization, channel coordination, and welfare-enhancing digital retail design. Full article

This paper investigates the integration of distributed computing and edge Artificial Intelligence (edge AI) as foundational enablers of sixth-generation (6G) mobile networks. Through a systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, encompassing over 200 peer-reviewed papers, architectural proposals, and standardization documents retrieved from IEEE Xplore, Scopus, Web of Science, MDPI, arXiv, ITU-R, 3GPP, and ETSI, this study provides a structured computational analysis of architectural approaches that integrate distributed computing paradigms and edge AI as core enablers of 6G. The analysis examines the evolution from cloud-centric to edge-centric computing, key edge AI techniques—including Federated Learning (FL), Split Learning (SL), and edge-adapted Large AI Models (LAMs)—and their role in enabling intelligent orchestration, resource optimization, and context-aware services. The comparative analysis demonstrates that edge computing architectures reduce end-to-end latency by 85–95% relative to cloud-centric deployments (under conditions of MEC servers within 1 km and 5G NR fronthaul), while federated learning with gradient compression achieves communication overhead reductions of up to 99% under IID data distributions and stable channel conditions. The results indicate that the tight integration of distributed computing and edge AI enhances network responsiveness, scalability, and adaptability, while also revealing persistent challenges related to orchestration complexity, resource constraints, security, and interoperability. The study concludes that holistic computational architectures and AI-native design principles are essential for the effective realization of 6G networks and for guiding future research and standardization efforts. Full article

Geopolitical shocks affect small open economies through multiple, correlated channels, yet applied CGE analyses typically impose the timing and persistence of those shocks by assumption. This paper develops a two-stage SVAR–CGE framework that links econometrically identified shock dynamics to general-equilibrium welfare evaluation for Thailand. First, a seven-variable narrative SVAR estimated on monthly data for 2000–2025, identified using the Caldara–Iacoviello Geopolitical Risk Index, is used to recover the persistence of five transmission channels: oil prices, shipping costs, exchange rates, tourism demand, and private investment. Second, these estimated persistence parameters discipline the shock paths in a 22-sector recursive comparative-static CGE model calibrated to Thailand’s 2025 Social Accounting Matrix and simulated over three annual periods using a present-value integral transformation. Under the baseline shock bundle, GDP declines by 3.18% and CPI increases by 5.49%, with welfare losses exhibiting a bimodal distributional pattern—largest for Q1 through consumption-share exposure and for Q4 through tradeable-sector intensity—departing from the monotonically regressive pattern in single-channel analyses. Policy simulations show that targeted transfers calibrated to income rank dominate a universal fuel subsidy on fiscal efficiency, welfare effectiveness (welfare multiplier 1.377 vs. 0.334), and progressivity (1.00 vs. 0.94), at half the fiscal cost (1.48% vs. 2.97% of baseline GDP). An additional bimodal-targeting scenario (S4) at identical fiscal cost underperforms income-rank targeting on all metrics, confirming the latter as the robust second-best instrument under LES preferences with strong MPC heterogeneity. These rankings are supported by the central calibration of a 9-point sensitivity grid, with partial corroboration at off-baseline configurations. The paper contributes by showing that empirically disciplining inter-annual shock dynamics in CGE analysis can materially alter policy conclusions under correlated multi-channel external shocks, shifting the preferred response from sector-specific price subsidies toward demand-side household transfers. Full article

United States (U.S.) specialty crop growers face myriad decisions regarding substrate selection as sustainability, market demands, and resource limitations influence soilless production systems. Peat is a common component in container substrates despite public concerns about its limited availability, finite supply, and associations with greenhouse gas emissions and environmental impacts, which have prompted growers to seek alternative materials. However, limited research has focused on the experiences, challenges, and research needs of U.S. specialty crop growers related to substrate transitions. The purpose of this mixed-methods study was to explore growers’ key considerations, research interests, and preferred communication methods associated with substrate transitions. An online survey and three focus groups were used to gain insights into growers’ experiences, concerns, and perceived impacts of peat replacement, research needs, and preferred communication channels. Results indicated that financial costs, peat availability, access to peat alternative substrates, and environmental considerations were the main factors influencing potential changes in substrate use. Growers identified key research priorities to assist decision-making, including (1) irrigation and nutrient management strategies, (2) the economic performance of alternative substrates, and (3) locally validated trials demonstrating system compatibility. They preferred practical communication methods for sharing results, including websites, YouTube videos, in-person meetings, on-farm demonstrations, and short podcasts accessible during routine work hours. The findings implied that research, outreach, and communication efforts tailored to growers’ operational contexts will support informed substrate transitions. Full article

Anabranching, sedimentation, island growth, and bank scouring are key morphological processes occurring in the Tigris River. These processes can disrupt navigation, affect water intake, and compromise the safety of infrastructure near the riverbanks. This study aims to simulate and assess the responses of a 4.75 km meandering–anabranching reach of the Tigris River in Baghdad city center to various alternative groyne dimensions designed to control natural morphological processes, using a depth-averaged hydro-morphodynamic model (Delft3D-FM). Bathymetric and field measurements, including sediment load, velocity, water level, and discharge, were conducted and used for model calibration and validation. The model demonstrated good agreement with observed water levels (Root Mean Square Error (RMSE) = 0.02 m) and depth-averaged velocities (RMSE = 0.068–0.142 m/s), and it reproduced morphological changes with a maximum bed-level error of approximately 13% at control sections. More than 20 groyne configurations, varying in orientation, length (L), and spacing (S), were simulated and assessed. In this study, the selection of the best groyne design for controlling morphological processes in the target reach was carried out using a proposed composite Groyne Performance Index (GPI). The index is based on weighted contributions from flow partitioning, thalweg stability, cross-channel infilling, island-margin response, and corridor deposition. While the straight–groyne configuration with L = 0.25 W (river width) and S = 2 L achieved the highest GPI, the L = 0.25 W and S = 3 L configuration is selected as the preferred design as it provided a more balanced response in terms of flow redirection, thalweg stability, reduced anabranching and deposition, and lower scour risk. The adopted selection methodology demonstrates a valuable indicator-based framework for selecting river-training layouts in low-slope, sand-bed, meandering–anabranching reaches of alluvial rivers. Full article

This paper presents a numerical comparative study on the ignition characteristics of straight-channel and U-bend micro catalytic combustors, with particular focus on the role of inlet velocity. A two-dimensional computational fluid dynamics model with coupled gas-phase and surface catalytic reaction kinetics for propane combustion is developed using a fluid simulation program ANSYS Fluent. The catalyst coating (Pt/Al₂O₃) is modeled as a zero-thickness reaction surface, and the U-bend design features an uncoated recirculating channel to ensure identical catalyst loading between the two configurations. Simulations are conducted over an inlet velocity range of 0.25–8 m/s. Key ignition and combustion metrics including ignition temperature, ignition time, maximum combustion temperature, heterogeneous reaction contribution, and thermal/species field distributions are systematically compared. Results reveal a crossover in relative performance depending on flow regime. At low velocities (≤2 m/s), the straight-channel combustor exhibits lower ignition temperatures; at high velocities (≥4 m/s), the U-bend design achieves superior ignition performance with lower ignition temperatures (e.g., 526 K vs. 555 K at 8 m/s) and higher combustion temperatures (1726 K vs. 1474 K at 8 m/s). However, the straight-channel combustor consistently yields shorter ignition times across all velocities (25.9–108.6 s) compared to the U-bend (52.6–145.2 s). The heterogeneous reaction contribution decreases with increasing inlet velocity for both designs, with the straight-channel maintaining higher values than the U-bend. The U-bend achieves higher maximum temperatures due to enhanced heat recirculation, particularly at high flow rates. The findings suggest that the U-bend configuration is advantageous for high-flow-rate applications requiring low ignition temperatures and high combustion temperatures, whereas the straight-channel design is preferable for rapid cold-start scenarios. Full article

We propose QwenMoE-SC, a semantic communication framework that integrates a Mixture-of-Experts (MoE) Large Language Model with three complementary modules: (1) a Graph Neural Network (GNN)-based Unequal Error Protection (UEP) plug-in that assigns semantic importance scores via syntactic dependency graph message passing for adaptive bit allocation, without modifying the pre-trained LLM; (2) NEFTune noise injection during fine-tuning for channel robustness; and (3) a Communication-aware Direct Preference Optimization (C-DPO) strategy that favors semantically faithful yet token-efficient transmissions. Comprehensive ablation studies on AWGN and Rayleigh fading channels show that each component contributes distinct gains, and their combination consistently outperforms traditional separation-based methods and neural baselines in sentence similarity, BLEU score, and semantic-level BER, with the largest improvements at low-to-mid SNR regimes. QwenMoE-SC can also serve as a semantic interface layer within expert and decision-support systems, enabling robust, bandwidth-efficient communication between data sources, inference engines, and human users. Full article

Voltage-gated ion channels are central regulators of cardiac, neuronal, and skeletal muscle excitability, and their dysfunction underlies a wide spectrum of channelopathies, including arrhythmias and neuromuscular disorders. While conventional ion channel therapeutics typically target a single pore-binding site, emerging evidence supports the therapeutic potential of polypharmacological compounds capable of modulating multiple channel subtypes. ARumenamides represent a novel class of sulfonamide-based ligands originally identified as fenestration-targeting sodium channel modulators; however, their cross-family binding mechanisms and multitarget potential remain incompletely defined. Here, we employed an integrated structure-based computational workflow combining molecular docking, in silico ADMET profiling, and long-timescale (250 ns) molecular dynamics simulations to systematically evaluate 20 ARumenamide derivatives across 15 voltage-gated sodium, calcium, and potassium channel structures. Docking analyses revealed broad multitarget binding profiles, with several compounds exhibiting high predicted affinity across cardiac, neuronal, and skeletal muscle channel isoforms. ADMET predictions demonstrated favorable intestinal absorption and metabolic safety for most candidates, although solubility and mutagenicity liabilities were identified for select derivatives. Detailed molecular dynamics simulations of prioritized compounds (AR-310, AR-769, and AR-946) uncovered site-specific binding behaviors and conformational effects. AR-769 exhibited exceptional stability at both fenestration and central pore sites of Cav1.2, associated with persistent hydrogen-bond networks, reduced protein flexibility, and a well-defined free energy minimum. In contrast, AR-310 and AR-946 displayed selective stability within Nav1.4 fenestrations and the Kv4.3 central pore, respectively, highlighting how subtle chemical features bias binding site preference and dynamic retention. Collectively, these findings establish a structure–dynamics framework for rational design of ARumenamide-based multitarget ion channel modulators. Our results demonstrate that fenestration-focused binding can support sustained ligand engagement without obligatory pore occlusion, offering a mechanistically distinct strategy for developing next-generation polypharmacological therapeutics for cardiac and neuromuscular disorders. Full article

Public goods provision is vulnerable to free riding, making sustained cooperation a central challenge in economics. Fehr and Schmidt’s inequity-aversion model explains how fairness concerns can support cooperation, but it treats preferences as fixed. Motivated by Kimbrough and Vostroknutov’s norm-sensitivity framework, this paper develops a reduced-form dynamic framework in which observed norm violations erode normative commitment over time. As normative commitment declines, the model maps this change into Fehr–Schmidt-style fairness parameters: guilt weakens and envy rises. These parameters provide an interpretive representation of norm erosion, while behavior is generated through a tractable contribution-scaling rule. The framework is calibrated illustratively to the public goods experiment of Fischbacher and Gächter. The calibration is not causal evidence of preference change and does not directly identify inequity-aversion parameters. It shows that a context-dependent preference channel can reproduce the observed aggregate decline in cooperation and generate testable implications. When no free-rider exposure is present, cooperation does not decline within the model. The model also predicts a nonlinear relationship between population-level free-rider prevalence and cooperation. Finally, because the model imposes a lower bound on normative commitment, this institutional floor determines long-run cooperation. The findings should be interpreted as model-based hypotheses for future experimental and field research. Full article

This field study examined extant aquatic food production and marketing in the three coastal states of Lagos, Ogun, and Ondo before IMTA across 15 Local Government Areas (LGAs)/Local Council Development Areas (LCDAs). Marketing mix practices in coastal aquatic food systems were explored through a structured, qualitative assessment using a multi-value chain perspective. Monthly sales volumes most frequently fell within the range of 1–5 tonnes. The local market was dominant, with some sales in the international markets. Respondents asserted that post-harvest processing was diverse, and some were satisfied with the technology available to preserve their products. Cold storage practices across coastal states were hindered by unreliable power supply. Zero-level channel distribution dominated among traders, with over 90% relying on word-of-mouth (WOM) to promote their products. Consumers showed a strong preference for the quality of local products and expressed openness to incorporating seaweed into their purchases. Health benefits, taste, and other reasons for purchase decisions varied significantly across the state χ² (df = 8, n = 300) = 92.39, p < 0.001. These findings provide a baseline for IMTA in Nigeria, highlighting existing strengths, market dynamics, and infrastructure gaps that must be addressed to support sustainable integration. Full article

In the context of revitalizing rural development, farmer entrepreneurship has emerged as a significant driver of rural economic growth. However, existing research has not sufficiently examined the specific mechanisms or heterogeneous effects through which digital skills influence farm household entrepreneurial behavior. This gap is the focus of the present study. Utilizing micro-level survey data collected from 936 farm households across Shandong, Shaanxi, and Henan provinces in 2021, we construct a digital skills index using factor analysis. We then employ a Probit model and an Interaction term model to examine the impact of digital skills on entrepreneurial behavior among Chinese rural households and its underlying mechanisms. Additionally, we explore heterogeneity across different household types. The results show that digital skills are positively associated with entrepreneurial decision-making. Further analysis provides suggestive evidence that this relationship may operate through three channels: shaping risk preferences, expanding relational networks, and improving access to credit. Heterogeneity tests reveal that the promoting effect of digital skills is stronger among disadvantaged households, households with a head younger than 45, and those engaged in opportunity-driven or online entrepreneurship. Theoretically, this study contributes by empirically validating a multi-pathway mechanism framework and identifying relevant boundary conditions. Practically, it offers targeted insights for policymakers to design skill-based interventions and foster inclusive entrepreneurial ecosystems in rural areas. Full article

The inner beauty functional food sector has grown rapidly in South Korea. These products are orally consumed bioactive formulations designed to improve skin health, hair vitality, and overall wellness. However, empirical evidence on consumption patterns and product format preferences across different demographic groups remains limited. This cross-sectional study examined consumption patterns, purchase channels, and product format preferences among 502 Korean adults who had experience with inner beauty functional foods. Chi-square analysis was used to examine differences in consumption reasons, duration of use, purchase channels, and product format preferences according to socio-demographic characteristics. Results showed that skin health was the dominant consumption motivation (47.6%), particularly among younger and female consumers, while weight management and hair and nail health were more prevalent among older adults. Online purchasing dominated (57.8%), with significant age- and education-based variation; consumers in their 20s purchased online at 67.5%, declining to 44.4% among those aged 40 and above. Capsule and tablet formats were most prevalent overall (41.6%), with males, married consumers, and graduate-degree holders showing significantly stronger preference for this format, whereas gummy and chewable formats were more frequently preferred by female consumers. These findings provide practical implications for inner beauty producers, food distributors, and nutrition educators seeking to align product development and communication strategies with the heterogeneous preferences of Korean inner beauty consumers. Full article