Search Results (2,776)

Urban residents spend an estimated 80–90% of their time indoors, yet urban indoor air quality (IAQ) science remains fragmented across pollutant types, settings, mitigation strategies, and governance contexts, contributing to an estimated 6.7 million deaths annually from indoor air pollution worldwide. This review asks the following question: what are the critical, multi-dimensional research and governance gaps in urban IAQ, and how can they be systematically derived and organized into a reference framework for future research and policy? A PRISMA 2020-aligned hybrid systematic evidence synthesis, combining bibliometric science mapping and structured thematic synthesis, was conducted across 105 records, primarily published between 2011 and 2026, with three pre-2011 foundational records retained, spanning 15 national contexts. A seven-stage hybrid deductive–inductive derivation procedure was applied to the coded corpus to produce the Multi-Dimensional Gap Identification Framework (MGIF), organizing research gaps across five dimensions: knowledge, methodological, technological, policy and implementation, and equity and urban context. Recurrent gaps include the absence of multi-pollutant mixture assessment in monitoring frameworks, the lack of standardized measurement protocols limiting cross-study comparability, a systematic gap between laboratory-validated and field-measured intervention performance, the near-total absence of enforceable indoor air quality standards across most jurisdictions, and the severe underrepresentation of Global South populations in both primary evidence and regulatory design. Building on the MGIF output, the Urban Indoor Air Quality Nexus (UIAQN) is proposed as a four-level conceptual organizing architecture linking pollutant dynamics, building systems, personal exposure, and governance mechanisms. Both frameworks are grounded in the coded corpus, have not been subjected to external validation, and are designed as structured reference architectures for future research investment, standard harmonization, and equity-centered policy design rather than as empirically validated predictive models. Full article

Whether and how Agricultural Socialized Services (ASS) are associated with grain-growing smallholders’ general self-reported subjective well-being (SWB) remains unclear. Using 894 survey records collected in Sichuan Province, China, from 21 to 31 August 2023, we estimate ordered probit and instrumental variable two-stage least-squares models. ASS Adoption Breadth is positively associated with SWB. One additional service category is associated with a 2.73-percentage point increase in the probability of reporting the highest SWB category. The IV estimate remains positive and statistically significant (0.077, p < 0.05), conditional on the maintained instrument assumptions. ASS Adoption Breadth is also positively associated with Relative Income Comparison, Log Hired Labor Expenditure, and Plant-protection Drone Adoption. These measured behavioral indicators provide evidence consistent with the hypothesized channels of Perceived Relative Economic Gain, Market-based Labor Substitution, and technology-enabled reduction in direct occupational exposure. They do not directly measure physical workload, pesticide exposure, or health outcomes. The findings inform policies that expand smallholders’ access to agricultural services, but the mechanism interpretations remain provisional. Full article

Reducing fertilizer usage from the perspective of farm household behavior is important for mitigating agricultural environmental pollution. However, existing studies often treat farmers as independent decision-makers in a risk-free setting and overlook the role of risk, particularly subjective risk, in fertilizer application decisions. Drawing on Arrow–Pratt’s theory of risk aversion, this paper develops a decision-making framework for fertilizer input under risk, examines the effect of risk attitudes on fertilizer input and its underlying mechanisms, and further investigates the heterogeneous impacts of risk attitude across different orientations of farmers’ economic benefit pursuits and intergenerational cohorts. The results indicate that: (1) more risk-averse farmers apply more fertilizer, and this finding remains robust after addressing endogeneity and conducting several robustness checks; (2) mediation analysis results indicate that both expected returns and path dependence have significant indirect effects in the association between risk attitude and farmers’ chemical fertilizer input; and (3) the positive effect of risk attitude on fertilizer input is more pronounced among farmers with a short-term orientation in their economic benefit pursuits and among the older-generation farmer groups. These findings offer a new theoretical perspective for understanding farmers’ fertilizer input decisions under risk and provide theoretical and practical implications for designing more effective fertilizer reduction policies that account for heterogeneous economic benefit orientations and intergenerational differences among farmers. Full article

Smart city initiatives increasingly claim to be citizen-centric, yet governance frameworks persistently conflate two analytically distinct concepts, citizen participation and citizen engagement, in ways that undermine the design and evaluation of civic involvement mechanisms. This conceptual ambiguity represents a structural problem in the field, not a transitional oversight, and carries direct consequences for how urban managers design governance instruments and measure their effectiveness. This study systematically examines the scope, definition, and operationalization of both concepts in smart city research through a Systematic Literature Review (SLR) following the SPAR-4-SLR protocol. A corpus of 43 peer-reviewed articles published between 2011 and 2025, retrieved from Scopus and Web of Science, was subjected to qualitative content analysis using a structured coding framework. Findings reveal that 53% of reviewed studies use participation and engagement interchangeably, a pattern that remains stable across all publication periods, confirming the structural rather than incidental nature of the ambiguity. Only 26% of articles establish a rigorous conceptual distinction and operationalize both terms through distinct analytical frameworks. The review further identifies a critical mechanism design gap: 30% of articles report no engagement mechanism whatsoever, and only 23% report outcomes with verifiable indicators. Based on these findings, this study proposes a conceptual framework that explicitly distinguishes participation, as a behavioral, often episodic act, from engagement, as a sustained, intrinsically motivated process characterized by genuine influence over governance outcomes. The framework offers researchers a theoretically grounded basis for construct differentiation and provides urban managers with actionable criteria for designing governance mechanisms that move beyond symbolic consultation toward authentic co-creation. Implications for digital governance research and smart city policy are discussed, with particular attention to underrepresented contexts in the Global South. Full article

This study examines consumer acceptance of genetically modified foods (GMFs) by integrating the Theory of Planned Behavior (TPB), brand equity dimensions, and sociodemographic factors within a configurational framework. Drawing on a sample of 405 Spanish consumers, the research combines correlational analysis with fuzzy-set qualitative comparative analysis (fsQCA) to identify the causal paths leading to both purchase intention and purchase non-intention. The findings show that the traditional TPB constructs and brand equity dimensions are positively associated with purchase intention, whereas belonging to older generations is negatively associated with it. However, the configurational analysis reveals a more nuanced picture. Purchase intention is explained by four configurations, grouped into two main profiles: one based on favorable subjective norms among younger consumers, and another centered on the joint presence of brand trust and brand familiarity. In contrast, purchase non-intention is explained by seven configurations, mainly characterized by the absence of favorable TPB conditions and weak brand equity, especially lack of trust and familiarity. The results confirm the causal asymmetry between acceptance and rejection of GMFs, as the configurations leading to purchase intention are not the mirror image of those leading to purchase non-intention. These findings challenge the assumption that GMF acceptance and rejection are symmetrical phenomena, and demonstrate that brand trust and familiarity complement attitudinal factors and constitute relevant conditions in several configurations associated with purchase intention. From a managerial and policy perspective, the findings suggest that promoting GMFs’ acceptance requires not only improving attitudes and perceived social approval, but also fostering trustworthy and familiar brand environments that may contribute to reducing uncertainty, alongside credible scientific information and effective institutional oversight. Full article

Cooperative adaptive cruise control (CACC) platoons rely on Vehicle-to-Vehicle communication and GPS to maintain sub-second headways, creating cyberattack surfaces underrepresented in standard surrogate-safety metrics. We built a fully equation-based, Routh–Hurwitz- and Lp-string-stability-verified simulation of a ten-follower (eleven-vehicle, including the leader) CACC platoon (point-mass dynamics, actuator lag, PD spacing control) and subjected it to a two-channel GPS-spoofing attack corrupting both the attacked vehicle’s control loop and its broadcast position; velocity and acceleration broadcasts, and the CACC feed-forward term they drive, are left uncorrupted, so the reported boundaries are conditional on this restricted, single-channel threat model and should be read as a lower bound on attack severity rather than a worst case. Across a 64-cell severity–duration grid (2–20 m, 1–10 s; h = 0.6 s), minimum time-to-collision fell from 31.7 s to a simulated collision in 6/64 cells (9.4%), driven more by magnitude than duration; the disturbance decays sharply after the first hop rather than cascading down the platoon, so the resulting risk is local, not cascading. A 48-cell headway grid showed h ≥ 0.7 s eliminated all collisions at the originally tested attack duration (3/8 → 0/8 at fixed severity), a result that held under two alternative controller-gain sets tested for sensitivity and was largely, though not universally, robust to a substantially stiffer third set. A position sweep found risk invariant across nine of ten platoon positions. Batch-computed first-hop propagation and tail-to-origin amplification ratios showed the disturbance transiently amplifies (ratio > 1) at its first hop in a third of tested attacks despite decaying three orders of magnitude by the platoon’s tail, a behavior distinct from the front-injected Lp string stability verified separately. Peak root-mean-squared jerk stayed within the comfortable range (≤1 m/s³) in every tested cell, including collisions, showing collision and comfort risk are governed by different parameters. Embedding a representative detection and elastic-control layer alongside headway optimization eliminated collisions within the tested range and remained robust at three times that severity, where headway alone failed; because the detector’s residual is computed directly from the true offset magnitude and detector failure is not modeled, this joint-defense result is illustrative rather than a validated-detector-calibrated estimate. These results give a reproducible, quantified basis for headway- and detection-based mitigation policy in connected-vehicle platoons. Full article

This study examined how living costs, employment, and smoking are associated with subjective economic status and quality of life among middle-aged Koreans aged 45 to 57, the cohort that will constitute the older population of the coming decades. Drawing on social determinants of health theory, the study specified expenditure on food, vehicles, and housing as curvilinear rather than monotonic correlates of the two outcomes. Data were drawn from the 2022 wave of the Korean Longitudinal Study of Older Adults’ Employment (n = 4392), and quadratic multiple regression models were estimated for each outcome. Food cost and vehicle cost displayed inverted U-shaped associations with subjective economic status, and vehicle cost displayed the same pattern with quality of life, whereas housing cost was negatively and linearly associated with subjective economic status. Employment was positively associated with subjective economic status but negatively associated with quality of life, and smoking was negatively associated with both outcomes. Subjective economic status was, in turn, positively associated with quality of life. These results indicate that the level at which expenditure occurs, rather than expenditure as such, is relevant to how middle-aged Koreans evaluate their economic circumstances and their lives, and they carry implications for welfare policy addressed to the pre-old cohort. Full article

In submitting conference proceedings for the 2nd International Conference on Sciences and Techniques for Renewable Energy and the Environment (STR2E 2026) to Engineering Proceedings, the Volume Editors of the proceedings would like to certify to the publisher that all papers published in this volume have been subjected to peer review by the designated expert referees and were administered by the Volume Editors strictly following the policies announced on the conference website [...] Full article

Renewable energy communities (RECs) are increasingly recognised as important instruments for accelerating the transition towards decentralised, low-carbon energy systems. However, technological progress and supportive policies alone cannot ensure their success, as participation depends largely on citizens’ behavioural readiness. This study investigates the behavioural determinants of participation in renewable energy communities by extending the Theory of Planned Behaviour (TPB) with four motivational dimensions: environmental, economic, technical, and social. A quantitative cross-sectional survey of 174 household electricity users in Slovenia was analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The findings show that environmental and economic motivations were positively associated with Attitudes, Technical Motivation was positively associated with Perceived Behavioural Control, and Social Motivation was positively associated with Subjective Norms. These TPB constructs are positively associated with behavioural readiness to participate in renewable energy communities. A supplementary exploratory multi-group analysis suggested possible differences between prosumers and conventional consumers. Prosumer status reflected individual household renewable electricity production and not verified REC membership, while Behavioural Readiness captured prospective stated intention and willingness rather than observed participation. However, because the prosumer subgroup comprised only 15 respondents, these group-specific patterns should be interpreted cautiously and require confirmation in larger and more balanced samples. The study extends the Theory of Planned Behaviour by integrating a multidimensional motivational framework and conceptualises participation in renewable energy communities as a socio-technical behavioural process. The findings provide empirically informed insights for policymakers, municipalities, and renewable energy community developers seeking to support citizens’ behavioural readiness to participate in renewable energy communities. Full article

This paper presents, to our knowledge, the first framework that jointly and provably optimizes communication and computation energy across an entire fleet of wirelessly connected mobile robots, rather than for a single device or under a fixed offloading policy as in prior work. Battery capacity limits the endurance of autonomous mobile robots, and on-board computation and radio communication increasingly rival locomotion in energy draw; across a fleet, the two are further coupled through shared uplink bandwidth and edge computing capacity. We formulate the joint selection of each robot’s task-offloading ratio, DVFS processor frequency, and transmit power, together with the fleet-wide allocation of bandwidth and edge capacity, subject to hard per-task deadlines. Closed-form inner solutions reduce each robot’s problem to a jointly convex program, coupled fleet-wide only through two linear resource constraints. We exploit this structure in JECCO-M, a distributed price-based algorithm that provably converges to the global fleet optimum while exchanging only a few scalars per iteration. A trajectory-conditioned channel-prediction extension handles robot mobility. Evaluated in simulations against optimization-based and learning-based baselines from the literature and on a physical three-robot testbed with embedded GPU compute, an IEEE 802.11ac uplink, and instrumented power rails, JECCO-M substantially reduces combined electronic energy while meeting all deadlines, and the measured hardware behavior tracks the analytical model closely. The results indicate that treating radio energy, processor energy, and shared edge resources as a single optimization domain is a practical route to extending the operating time of connected robot fleets. Full article

The spatial allocation of urban road infrastructure directly affects urban operational efficiency, social equity, and ecological environmental quality. Taking 36 major Chinese cities as the research subjects and drawing on data from municipal statistical yearbooks, this study employs a composite index method, Theil index decomposition, and correlation analysis to reveal spatial differentiation patterns, imbalances, and driving factors of urban road infrastructure levels, based on both aggregate and average indicators. The results indicate that the aggregate road infrastructure level exhibits a “high in the southeast, low in the northwest” pattern along the Hu Huanyong Line, while the average road infrastructure level reveals relatively lower performance in some first-tier cities. Imbalances exist in both aggregate and average dimensions, with Theil indices of 0.231 and 0.059, respectively; intra-regional disparities contribute more to total inequality than inter-regional disparities. Urban permanent population (ridge regression coefficient: 0.1991) and fiscal revenue (ridge regression coefficient: −0.1087) are the core driving factors among the four influencing factors of aggregate road infrastructure level spatial differentiation, whereas GDP (−0.0318) and built-up area (0.0703) exert only marginal effects. This suggests that current aggregate urban road infrastructure levels are shaped by the interplay of urbanization stage, economic development level, fiscal system, and spatial planning policies, all operating within the constraints imposed by the city’s natural geographical conditions, and have not yet adequately addressed residents’ demand for spatial equity. The study recommends establishing differentiated investment mechanisms, optimizing road network density in developed cities, and constructing a spatial matching early-warning system to promote people-oriented new urbanization and coordinated regional sustainable development. Full article

We develop a tensor-based dynamical framework for monetary flows in multi-sector, multi-agent economies and quantify the information destroyed when the monetary state is reduced to a scalar aggregate. The state is a third-order tensor encoding capital flows across sectors, agent classes, and time; deviations from equilibrium obey a tensor-indexed Langevin (multivariate Ornstein–Uhlenbeck) equation with a coupling operator and channel-specific friction rates. Using standard Lyapunov theory, we assemble a stability and convergence framework for the induced vectorized system, with a bound stated so as to remain valid for the non-normal system matrices generated by asymmetric economic coupling, and characterize the stochastically forced case in the mean-square sense. Shannon entropy, Kullback–Leibler divergence, and sector–agent mutual information measure the structural information discarded by scalar aggregation. We then study a stylized, heuristically calibrated $3\times 3$ economy subject to a shock inspired by the 2007–2009 crisis; we emphasize at the outset that the figures reported below are properties of that calibration and are not empirical estimates. In this scenario Finance absorbs an 18.9% peak capital loss while Manufacturing and Services suffer 5.8% and 3.9% secondary drops, against an aggregate contraction of only 8.6%; the Kullback–Leibler divergence of the sector–agent flow distribution recovers systematically later than the aggregate signal, a lag that is positive in 96.6% of a 1000-draw Monte Carlo ensemble, although its magnitude is calibration-dependent. Under a symmetric exit rule, a deficit-targeted stimulus restores equilibrium substantially faster than a share-weighted uniform stimulus in 100% of the ensemble while spending strictly less—its realized expenditure saturates below the uniform budget because it self-terminates as deficits close—and attains integrated disequilibrium within 18% of the exact linear-quadratic optimum at equal control effort while requiring no knowledge of the system matrix. The ordinal conclusions—aggregation masks the epicenter, structure lags the aggregate, and deficit targeting dominates uniformity—are robust across a wide neighborhood of the calibration, and identify the disaggregated state as the object that stabilization policy needs and that scalar aggregation destroys. Full article

Battery-powered mobile robots that rely on an edge server for perception spend energy in three places at once: the on-board processor, the radio front end and the drivetrain. These budgets are normally optimised separately, which is a mistake, as lowering the processor clock pushes work onto the wireless link, transmitting into a poor channel costs far more than waiting for a better one, and where the robot drives determines what the channel will be. We formulate the co-management of all three as a minimisation of long-run average energy for a fleet sharing an access point and subject to task deadlines, a power budget and a mission-progress constraint that forces every policy under comparison to cover the same ground. The resulting stochastic mixed-integer non-convex program is made tractable by a Lyapunov drift-plus-penalty argument that decomposes it into four per-slot subproblems: a square-root clock rule, a water-filling transmit-power rule with an explicit on/off test, a join-the-shorter-queue offloading split, and a short lookahead over admissible speeds. The policy needs no channel or workload statistics and attains an A per-task deadline mechanism, feasibility floors on the clock and transmit decisions, and closes the gap between queue-stability guarantees and individual task deadlines, which drift arguments alone do not bound. The policy needs no channel or workload statistics and attains an $\left[O\right(1/V),O(V\left)\right]$ energy–delay tradeoff, stated under precisely qualified assumptions. In a per-task simulation study against six baselines, the policy reduced combined communication and computation power by 25% relative to the strongest deadline-compliant baseline ($p<{10}^{-4}$) at equal mission progress, and was the only scheme to hold deadline violations below 0.5% across the full load range, where every baseline exceeded 16% at high load. Full article

Fixed-wing UAVs operating in long-range missions often fly through airspace subject to heterogeneous multi-source constraints that vertically compress the flyable space into a constraint corridor of continuously varying thickness. Conventional path planning methods incur high online computational costs in such scenarios. Deep reinforcement learning can generate reactive decisions from local observations, yet existing approaches predominantly target multirotor obstacle avoidance and rely on observations designed for discrete obstacles, lacking a unified representation for corridor constraints. Moreover, constraint conditions vary across mission scenarios, demanding cross-scenario policy generalization. This paper proposes the Egocentric Constraint Corridor (ECC), which fuses multi-source constraints into upper and lower boundary surfaces defining the corridor, then egocentrically encodes the surrounding corridor relative to the vehicle into a margin field serving as structured policy input. A deep reinforcement learning framework built on ECC is trained end-to-end, with its multi-branch network and composite reward function following from the structure of the corridor encoding. Experiments show that ECC-DRL achieves path efficiency approaching that of globally informed A*, and that it is the only one of the compared methods that computes its decisions online within the decision interval. Ablation studies confirm the margin field is necessary for reliable navigation, and the ECC encoding enables zero-shot transfer to scenarios with unseen terrains and radar deployments without retraining. Hardware-in-the-loop experiments on an embedded platform verify real-time closed-loop feasibility. Full article

Promoting the adoption of climate-smart agricultural technologies (CSATs) is essential for food security and achieving the Sustainable Development Goals (SDGs). However, adoption rates remain low. The objective of this study is to reveal the associations between financial instruments and farmers’ adoption of CSATs. Using survey data from 1219 farmers in climatic transition zone of China, the Probit model, and mediation model were used to empirically test the associations of credit and insurance on farmers’ adoption of CSATs. The results show that both credit and insurance are positively associated with CSATs adoption, with insurance exhibiting a stronger marginal effect than credit. Mediation analysis reveals that credit and insurance are positively associated with farmers’ adoption behavior through attending technical training, strengthening subjective norms, and improving risk attitudes. Heterogeneity analysis indicates that these associations vary significantly across different climatic sub-regions. The findings provide evidence-based policy insights for leveraging targeted financial instruments to accelerate CSATs adoption among smallholders in China and other countries. Full article