Search Results (259)

Calibrating compensation programs for chemical-fertilizer reduction requires reliable evidence on farmers’ preferences across reduction practices and policy instruments. Existing choice-experiment evidence treats reduction as either a single aggregate attribute or mutually exclusive practices, specifies compensation independently of the practice bundle, and underuses the distinction between smallholders and new agricultural operating entities (NAOEs) in heterogeneity analysis. We surveyed 1066 rice farmers across six counties and districts of Jiangsu Province using a multi-binary-attribute choice experiment that represented five fertilizer-reduction measures (soil-testing-based fertilization, deep placement, organic substitution, crop rotation, and straw return) as separate binary attributes, with a cost-proportional compensation rate; estimation used mixed logit. Non-monetary preferences vary qualitatively across measures: soil-testing-based fertilization is intrinsically valued (willingness to pay 24 CNY/mu), while crop rotation imposes the largest non-monetary cost (willingness to accept 152 CNY/mu). Existing Jiangsu flat rates approximate farmer mobilization thresholds for low- and medium-cost practices but under-incentivize rotation. Income subsidies dominate non-income alternatives. Smallholders are more inertial and more compensation-responsive than NAOEs, requiring more compensation for crop rotation and showing a stronger income-subsidy preference. The findings support differentiated compensation by measure and farmer type; the methodological template extends to other agri-environmental contexts in which adoption is genuinely combinatorial. Full article

Hepatitis E virus (HEV) is an emerging zoonotic pathogen in Europe, mainly transmitted via consumption of naturally contaminated food or contact with infected animals. People living in the Balkans have diverse dietary habits, with high pork consumption in some countries, making this region a relevant setting for investigating HEV seroprevalence and its possible determinants. The current study aimed to estimate pooled HEV seroprevalence among adults in the general population and blood donors and to assess factors associated with regional variation. Twenty-eight eligible studies were identified from PubMed, Scopus, and Web of Science following the PRISMA guidelines. Pooled prevalence estimates were calculated using a random-effects meta-analysis of proportions implemented via a generalized linear mixed model (GLMM) with logit transformation. Potential factors associated with HEV seroprevalence, including national pork consumption, serological assay type, population group, year of publication, sex, and country, were evaluated. The pooled anti-HEV seroprevalence was estimated to be 5.68% (95% CI: 3.48–9.12%), with substantial heterogeneity. Country-specific estimates ranged from 1.01% in Greece to 26.66% in Bulgaria. Subgroup analyses showed significant variation according to national pork consumption category, serological assay type, year of publication, and country. However, meta-regression indicated that methodological and temporal factors, particularly serological assay type and year of publication, were the main significant moderators, whereas national pork consumption was not independently associated with seropositivity. Therefore, pork consumption should be interpreted as an exploratory ecological indicator rather than as evidence of a direct association. The methodological differences contribute substantially to the variability in HEV seroprevalence across the Balkans, emphasizing the need for standardized diagnostic approaches within a One Health framework. Full article

Parking management has become an increasingly important challenge in rapidly growing urban areas, yet evidence from intermediate Latin American cities remains scarce. This study analyzes parking choice behavior across Ecuadorian cities using a national stated preference (SP) experiment validated through revealed preference (RP) data and estimated via discrete choice models. Data were collected between 1 April and 3 May 2026 from 2150 active drivers across 12 cities spanning the Coast, Highlands, and Amazon regions. Multinomial Logit (MNL) and Mixed Logit (MIXL) models were estimated to evaluate the effects of parking cost, walking distance, search time, security, and surveillance on parking decisions. Results showed that all three cost-related attributes significantly reduced parking utility, while security improvements increased the probability of selecting formal parking alternatives. The MIXL model outperformed MNL specifications (ΔAIC = 211.84), revealing significant unobserved heterogeneity in cost (SD = 0.45) and security preferences (SD = 0.29). Willingness-to-pay estimates reached USD 0.64 per 100 m reduction in walking distance and USD 0.69 per 10-min reduction in search time, with substantial inter-city variability. Despite low current adoption (18.4%), willingness to use digital reservation systems exceeded 75% across income groups. The findings underscore the need for locally calibrated, context-sensitive parking policies and support differentiated smart parking strategies in developing urban systems. Full article

New towns often experience a structural transit gap in early stages, where transport supply lags behind population growth. Demand-responsive transit (DRT) has emerged as a promising complementary solution; however, most studies rely on MNL-based ICLV models that do not account for error covariance across alternatives. This study applies an ICLV model, integrating an Error Component Mixed Logit kernel with latent variables, to analyze mode choice behavior in transit-poor new towns. Based on an SP-off-RP survey of 644 residents in new towns, 2576 observations were analyzed. The model incorporates five latent variables, including Transit Dissatisfaction, Convenience, Safety, Travel Time, and Travel Companion Sensitivity, and captures unobserved correlations through a two-level nesting structure. Results show that DRT has a significantly positive alternative-specific constant, indicating latent acceptance beyond observable attributes. DRT adoption is more common among transit-poor new town residents and highly educated individuals, but less common among car owners. Users are more sensitive to access and waiting time than to in-vehicle time. Convenience, Safety, and Travel Time significantly influence DRT utility, while Travel Companion Sensitivity reveals heterogeneous effects across modes. These findings provide behavioral insights for designing effective DRT strategies in transit-poor new towns. Full article

Grocery shopping remains a heavily car-dependent activity in urban areas, even for short-distance trips within residential neighbourhoods. A primary barrier to shifting toward active travel (walking or cycling) is the physical burden of carrying heavy or bulky goods. This study investigates whether a retailer-managed home delivery service could encourage consumers who currently rely on motorised modes for grocery shopping to shift towards active travel while preserving the in-store shopping experience. The analysis focuses on urban Italian consumers who currently use motorised modes for grocery shopping. Using a Stated Preference (SP) experiment and a Mixed Logit (MMNL) model (n = 88), we analyse the conditions under which such a service may encourage the adoption of active travel modes and support proximity-based shopping patterns. Given the exploratory nature of the study and the small, non-representative sample, the findings should be interpreted as preliminary evidence for urban motorised grocery shoppers rather than as representative of the Italian population. The results indicate a substantial willingness among respondents to adopt the proposed service configuration. Delivery time, service cost, and the availability of delivery time-window selection emerge as critical factors influencing consumers’ choices. Acceptance of the service is also influenced by perceptions of walking and cycling infrastructure quality, trust in the integrity of delivered groceries, preferences for local products, and concerns regarding the working conditions of delivery personnel. Additionally, the model reveals significant heterogeneity in preferences regarding delivery by drone/autonomous vehicle and a 100% reduction in greenhouse gas emissions relative to conventional motorised transport. Younger respondents exhibit a more favourable attitude towards automated delivery technologies, while differences in the valuation of environmental benefits emerge between male and female respondents. The findings suggest that retailer-managed home delivery may represent a promising mechanism for encouraging active travel among current motorised grocery shoppers, while maintaining consumers’ relationship with neighbourhood retail services. These results provide retailers and urban policymakers with valuable insights, suggesting that appropriately designed delivery services may support more sustainable and proximity-oriented shopping behaviours. Such services could potentially contribute to maintaining the accessibility and vitality of neighbourhood retail activities, particularly in ageing urban contexts. Full article

The aesthetic value of agricultural landscapes is gaining importance as rural tourism burgeons during urbanization. To ascertain key elements influencing the visual appeal of agricultural landscapes, this research employed a visual choice experiment in Hangzhou Plain during the spring flowering period to assess public preferences for four landscape attributes in ground and aerial perspectives. The mixed logit model was utilized to evaluate the respondents’ average preference, while the latent class logit model helped in identifying distinct preference groups. The research revealed that participants exhibited different preferences between the two perspectives. The diversity within public preferences was highlighted, with respondents favoring oilseed rape-dominated landscapes with a single agricultural land cover proportion in ground perspective while favoring diverse landscapes in aerial perspective. Gender, education level, landscape familiarity, connection to agriculture, and membership in relevant organizations significantly shape individual preferences. These results can help refine multi-objective policy targeting by incorporating aesthetic value perspective in agricultural landscapes. Full article

Cross-scene Hyperspectral Image (HSI) classification faces substantial domain shifts caused by sensor heterogeneity, acquisition variation, and scene diversity. While benchmark annotations are assigned to individual center pixels, local patches often contain implicit multi-label semantics due to spectral mixing and spatial overlap. This mismatch distorts prediction structure, exacerbates generalization errors, and limits the effectiveness of standard domain generalization (DG) techniques focused solely on feature or prediction invariance. We propose Class-Aware Semantic Calibration (CASC), a systematic semantic structure calibration framework that addresses three complementary distortions induced by mismatched patch supervision: (i) Balance corrects class frequency bias via reweighted supervision; (ii) Separability enhances boundary decision stability through margin-based logit calibration; and (iii) Independence reduces domain-specific spurious co-occurrence via prediction covariance decorrelation. To preserve calibrated semantics under pseudo-source shift, we further introduce a complementary DualAlign (DA) module, which jointly aligns feature statistics and prediction distributions, enforcing consistency at both representation and semantic levels. Extensive experiments on three cross-scene benchmarks (Houston, Pavia, and WHU-Hi) demonstrate that CASC-DA consistently improves performance over strong baselines, achieving an average gain of 3.0% in overall accuracy and 4.9% in Kappa coefficient compared with the best-performing baseline on each dataset. These results underscore the importance of semantic structure calibration for domain-generalized HSI classification. Full article

Social media has become a significant factor in unhealthy consumption behaviors among adolescents, given the prevalent use of mobile phones and the internet. This study investigates the association between social media exposure and adolescents’ sugar-sweetened beverage (SSB) preferences, as well as their consumption behavior. This study included 1517 adolescents across Henan Province, China, in 2025. We employ a mixed logit model, a hurdle model, and an Ordinary Least Squares (OLS) model to assess the association of social media exposure with adolescents’ SSB preferences and consumption behavior. The findings indicate that social media exposure is positively associated with adolescents’ overall preference for SSB products. Specifically, it is associated with a higher preference for carbonated drinks and beverages containing sweeteners and a lower preference for juice. Furthermore, the association between social media exposure and SSB preferences differs between urban and rural adolescents. Rural adolescents exposed to social media tend to show a lower willingness to forgo SSB options, whereas urban adolescents exposed to social media tend to show less sensitivity to price attributes. Additionally, social media exposure is positively associated with both the selection and consumption of SSBs among adolescents, which in turn are linked to health concerns such as overweight and obesity. Full article

The IMO Net-Zero Framework and its carbon regulations impose binding constraints on fuel selection and fleet evolution. A techno-economic optimization model is developed to quantify this interaction along the Shanghai–Los Angeles green shipping corridor. The framework integrates vessel-level Mixed-Integer Non-Linear Programming (MINLP) with a Multinomial Logit formulation to simulate fleet diffusion, minimizing Total Cost of Ownership (TCO) over 2026–2050. The results identify a persistent marginal compliance regime driven by the tiered carbon penalty structure. Rather than achieving full compliance, fleets systematically position their Greenhouse Gas Fuel Intensity (GFI) near the penalty threshold, where limited penalties remain economically preferable to high-cost zero-carbon fuels. This behavior sustains fossil LNG as the dominant transitional option and delays the TCO crossover with ammonia until 2043. Under intensified penalties, the crossover advances to approximately 2030, triggering rapid cost escalation for LNG and eliminating the economic viability of drop-in biofuel strategies. Across all scenarios, absolute zero GHG emissions are not achieved due to residual fossil dependence and upstream Well-to-Wake (WTW) emissions. The transition is therefore bounded by the interaction between penalty avoidance behavior and the pace of Power-to-X fuel deployment. These findings indicate that carbon penalty levels determine the timing of decarbonization, while relative fuel prices govern technology selection, with direct implications for corridor-specific fuel infrastructure and investment decisions. Full article

Vehicle fleet renewal policies promoting NEVs aim to decarbonize transportation but inadvertently alter urban atmospheric corrosivity, threatening the durability of infrastructure coatings. This study investigated the cross-system impacts of vehicle trade-in subsidies on the degradation of protective coatings. We developed a coupled framework integrating a Mixed Logit model for fleet evolution, dynamic Life Cycle Assessment for tracking acidic precursors (SO₂, NO_x), and an Environmental Corrosion Risk Index. Using established Dose–Response Functions, we quantified the lifespan depletion of a standard epoxy zinc-rich primer and polyurethane topcoat system. Our results indicate that aggressive subsidies induce a transition to heavy NEVs, triggering an “emission inversion” that spikes upstream grid acidic emissions. This localized acidification significantly accelerates chemical degradation, reducing the effective service life of infrastructure coatings by 1.3–2.3 years and necessitating premature, costly recoating. We identify a Pareto-optimal subsidy window (8000–10,500 CNY) that effectively balances decarbonization targets with coating preservation. In conclusion, sustainable urban policies must incorporate surface engineering and material durability metrics to prevent emission shifts from compromising the physical integrity of transportation infrastructure. Full article

Despite Mozambique’s substantial natural gas reserves, most households rely on solid biomass for cooking, with serious consequences for public health, livelihoods, and the environment. The domestic use of these resources could improve energy efficiency, security, and sustainable development. This mixed-methods study uses household interviews, descriptive statistics, multinomial, and conditional logit models, analyzing data from a random survey of 434 households in energy-rich peripheries of northern Inhambane and Maputo City to ascertain the determinants of household cooking energy choice. Results reveal that rising income increases the odds of choosing electricity, LPG, and biomass over natural gas. In energy-rich peripheries, the odds of selecting biomass over natural gas are reduced by 96.2% compared to non-energy-rich regions. Educational and urban habitation are positively correlated with the adoption of electricity and liquefied petroleum gas (LPG). Price serves as a significant negative predictor of fuel selection (OR ≈ 0.000001), whereby each unit increase in price per GJ substantially diminishes the likelihood of opting for alternatives over domestic gas. Monthly fuel expenditure positively predicts electricity, LPG, and biomass adoption (OR = 1.0042), with effects accumulating meaningfully across realistic spending ranges. Households that experienced energy system incidents were more than twice as likely to switch away from natural gas (OR = 2.072), reflecting the critical role of infrastructure reliability in fuel choice. Given natural gas’s potential as a clean cooking transition fuel, the government should prioritize investment in gas infrastructure, expand domestic supply, and promote public awareness of the health and environmental benefits of clean cooking energy. Full article

South Korea’s official development assistance to the energy sector has increased steadily over the past decade, reaching USD 232.20 million in 2024. Yet public willingness to pay for renewable energy official development assistance remains largely unknown. This study uses a discrete choice experiment with 1000 nationally representative South Korean respondents and a mixed logit model to estimate marginal willingness to pay for key project attributes, including electrification, greenhouse gas reduction, firm expansion, expert training, and reputation enhancement. The results show that greenhouse gas reduction and expert training receive the highest willingness to pay, followed by firm expansion. Electrification and reputation enhancement receive relatively low support. The findings also reveal substantial preference heterogeneity, with younger and nationally oriented respondents placing greater value on economic returns. These results provide new donor country evidence on public preferences for renewable energy official development assistance and offer policy implications for designing a more climate-focused and socially supported green aid portfolio. Full article

Santiago, Dominican Republic, faces a growing deficit in the supply of drinking water. Rainwater harvesting systems have the potential to provide a reliable and sustainable source of drinking water. This research examines water quality from the pilot testing of a rainwater harvesting system designed to directly capture rainwater in planter boxes, pre-filter it and store it. The pilot testing consisted of a field experiment comparing rainwater harvested with four filter media compositions with varying levels of sand (34, 62, 66 and 76%). From May 2024 to May 2025, bi-weekly water samples were tested for physicochemical and microbiological parameters including pH, electrical conductivity, total dissolved solids, turbidity, biochemical oxygen demand, heterotrophic bacteria, total and fecal coliforms, E. coli, and Enterobacteriaceae. Statistical models were fitted for each water quality parameter, using linear mixed-effects models or generalized linear mixed-effects models with a logit link, to evaluate the association between filter unit design and water quality outcomes. Results showed that physicochemical quality met Dominican drinking water standards but infrequently met bacteriological standards. However, filters with higher sand composition produced higher quality water for both physicochemical and microbiological parameters. Additional treatment such as chlorination would reduce bacteria and protect the water during storage. Full article

Background: Cardiac involvement in dengue has been increasingly recognized, yet the true burden and spectrum of arrhythmias remain uncertain due to heterogeneous and fragmented evidence. We conducted a systematic review and meta-analysis to estimate the proportion of cardiac arrhythmias in patients with dengue and to describe the distribution of major arrhythmia subtypes. Methods: We searched PubMed/MEDLINE, EMBASE, LILACS, Global Index Medicus, and Google Scholar from inception to November 2025 without language restrictions. Observational studies reporting the number of dengue patients evaluated for arrhythmias and the number with at least one rhythm disturbance were included. Random-effects generalized linear mixed models with a logit transformation were used to estimate pooled proportion with 95% confidence intervals (CIs). Subgroup analyses were performed by age group. Risk of bias was assessed using the Joanna Briggs Institute tool, and certainty of evidence was evaluated with GRADE. Results: Thirty-five studies, including 6948 patients, were analyzed. The pooled proportion of any arrhythmia was 24.48% (95% CI 17.54–33.07), with a higher proportion in adults (30.00%) than in children (10.73%). Sinus bradycardia (11.84%) and sinus tachycardia (10.63%) were the most frequent abnormalities. Atrioventricular block was uncommon (1.33%). Between-study heterogeneity was high for most outcomes. No significant small-study effects were detected. Conclusions: Cardiac arrhythmias occur in approximately one in four patients with dengue, predominantly as sinus rate abnormalities. While often transient, these findings support the role of baseline and risk-based ECG monitoring, particularly in hospitalized adults and patients with severe disease. Full article

Bayesian optimization (BO) is a widely used framework for optimizing expensive black-box functions. Most BO methods rely on Gaussian process (GP) surrogates, which perform well in continuous domains but encounter difficulties when decision variables include categorical or mixed discrete–continuous components. In particular, GP-based approaches typically require ad hoc numerical encodings of categorical variables that may fail to capture the structure of discrete decision spaces. In this work, we propose MNL-BO (Multinomial Logit Bayesian Optimization), a preference-based Bayesian optimization framework that replaces the GP surrogate with a multinomial logit (MNL) model trained from pairwise preference comparisons. The resulting surrogate provides a natural and interpretable representation of categorical alternatives while allowing continuous, discrete, and categorical variables to be handled within a unified optimization framework. The predictive utility estimates and uncertainty indicators generated by the MNL model are employed to formulate acquisition functions that reconcile exploration with exploitation. The proposed methodology is evaluated on three progressively complex optimization challenges: a purely categorical benchmark, a combinatorial Traveling Salesman problem, and a constrained mixed-variable engineering design problem concerning material selection in pressure vessel optimization. Multi-run tests provide consistent advantages over random search and exhibit stable convergence behavior across diverse random initializations. In addition to heuristic baselines such as local search and classical metaheuristics, we also compare against tree-based Bayesian optimization baselines inspired by the Sequential Model-based Algorithm Configuration (SMAC) framework. The results indicate that the proposed MNL-BO method achieves competitive performance under comparable evaluation budgets while providing an interpretable probabilistic surrogate for categorical decision spaces. These findings suggest that preference-based surrogate modeling provides a practical and flexible alternative for Bayesian optimization in categorical and mixed-variable optimization problems. Full article