Search Results (26,799)

During public health emergencies, individuals typically obtain epidemic-related information through mass media channels and personal social media platforms. This information enables them to monitor epidemic progression and adjust their preventive behaviors accordingly to mitigate infection risks. To capture these processes, this paper proposes a three-layer coupled metapopulation network model that investigates the effects of regional mass media and social information propagation on the spatial spread of epidemic. The mass media layer represents regional outlets that propagate epidemic-related information to individuals within corresponding patches. Migrant individuals not only follow mass media information of the residential patch, but also continue to follow mass media information from their destination patch. The information layer captures the dynamics of information exchange on social media platforms. The epidemic layer depicts the spread of the epidemic within the metapopulation network and simulates the reaction-diffusion dynamics of migrating individuals across different patches through a Migration-Interaction-Return (MIR) mechanism; the coupling between the information layer and the epidemic layer is asymmetric. Theoretical analysis using the Microscopic Markov Chain Approach (MMCA) derives the evolution equation and determines the epidemic thresholds, while Monte Carlo (MC) simulations validate the model and explore factors influencing propagation dynamics. Our research indicates that when migrants simultaneously receive mass media information from both residential and destination patches, it significantly enhances information coverage and promotes protective behaviors, thereby effectively suppressing epidemic spread. Furthermore, promoting information propagation—particularly the communication among individuals within a patch—significantly increases the proportion of aware individuals, reduces the infection scale, and raises the epidemic threshold. Notably, population migration would originally lead to an increase in infection scale, but as the intensity of information propagation strengthens, migration instead has a good effect on controlling epidemic spread. These results provide deeper insights into the role of awareness propagation and human mobility in epidemic containment. Full article

Accurate core loss evaluation is essential in the design of magnetic components. Core loss is critically influenced by excitation waveform, temperature, and magnetic material; therefore, we develop a waveform equivalence coefficient, a temperature polynomial, and an electrical conductivity term to revise the Steinmetz Equation and propose a physics–data dual-driven core loss model across materials and operating conditions. The waveform equivalence coefficient achieved 100% waveform classification, and temperature polynomial modification reduced the mean square error by an order of magnitude. Using three-way analysis of variance (ANOVA), we measured the individual and synergistic impacts of the three key factors on core loss. The waveform exerts the greatest individual influence while waveform and material, as a combination, exerts the greatest synergistic influence. Given the discovery that Material 1 demonstrates a property transition point under triangular waveform, the dual-objective optimization result indicates that using Material 1 under operating conditions of 90 °C, 501,180 Hz frequency, 0.0047 T peak flux density, and a triangular excitation waveform enables the magnetic component to achieve minimum core loss with maximum transmitted magnetic energy. Full article

For a long time, low efficiency in the transfer of rural collective land use rights and the ambiguous attribution of collective land property rights have not only restricted the mobility of rural labor factors but have also hindered the release of vitality in the rural collective economy. This has resulted in lagging growth in the income that rural residents obtain from collective economic factors, contributing to the persistent widening of the urban/rural income gap. As an important institutional innovation to address these issues, the effects of the reform of the rural collective property rights system urgently need to be clarified. The reform of the rural collective property rights system constitutes a major initiative in the transformation of the rural land system. Centered on asset verification and valuation, as well as the demarcation of membership rights and the restructuring towards a shareholding cooperative system, it aims to establish a collective property rights regime characterized by clearly defined ownership and fully functional entitlements. This study takes the national pilot reform of rural collective property rights launched in 2016 as a quasi-natural policy experiment, systematically examining the impact of this pilot policy on the internal income gap within households and its spillover effects on the urban–rural income gap. Based on microdata from the China Household Finance Survey (CHFS) and the China Longitudinal Night Light Data Set (PANDA-China), this study constructs a five-period balanced panel dataset covering 2304 rural households across 25 provinces. A relative exploitation index based on the Kawani index is constructed, and empirical analysis is conducted using a combination of multi-period difference-in-differences (Multi-period DID), discrete binary models, and propensity score matching-difference-in-differences (PSM-DID) models. The results show that: First, the pilot reform significantly reduced the level of income inequality within rural areas in the pilot regions, and its policy benefits further generated positive spillovers via market-driven factor allocation mechanisms, effectively bridging the urban–rural income gap. Second, institutional reforms activated the potential of rural non-agricultural economic factors, establishing new channels for a two-way flow of urban and rural factors, becoming an important path to achieve the goal of common prosperity. Third, the policy effects exhibited significant heterogeneity, specifically manifested in the attributes of major grain-producing regions, initial household income levels, and the human capital characteristics of household heads having significant moderating effects on reform outcomes. This study not only provides theoretical support and empirical evidence for deepening rural property rights reforms under the new rural revitalization strategy, but it also reveals the driving role of institutional innovation in factor mobility, thereby influencing the transmission mechanism of income distribution patterns. This finding offers a China-based solution for developing countries to address the imbalance in urban–rural development and the widening income gap. Full article

Apple aroma is an important factor influencing consumers’ preferences. To understand the overall flavor characteristics of apples (Ruixue, Liangzhi, Grystal Fuji, and Guifei), volatile compounds and aroma profiles were investigated by headspace–gas chromatography–ion mobility spectrometry (HS-GC-IMS) combined with stir bar sorptive extraction (SBSE) and gas chromatography–mass spectrometry (GC-MS). The results showed that a total of 56 aroma compounds were identified by SBSE-GC-MS, and 39 aroma-active compounds were screened out using aroma intensity (AI) and odor activity value (OAV). Aroma recombination experiments showed enhanced ‘fruity’ and ‘sweet’ notes, whereas ‘floral’, ‘woody’, and ‘green’ aromas were weaker compared to the Crystal Fuji sample. Additionally, GC-IMS coupled with principal component analysis (PCA) was used to distinguish the apple samples, and partial least squares regression (PLSR) was applied to explore the correlation between sensory attributes and characteristic aroma compounds. The results indicated that Crystal Fuji exhibited the greatest correlation with the “woody” attribute, and Ruixue was highly correlated with “fruity”, “green”, and “sour” attributes, while butanoic acid, β-damascenone, butyl acetate, pentyl acetate, furfuryl alcohol, γ-decalactone, and vanillin had a significant impact on the “flower” and “sweet” attributes of Guifei. This study clarified the characteristic aroma composition of the four apple cultivars, providing data support for apple flavor quality evaluation and cultivar optimization. Full article

Background/Objectives: Human papillomavirus (HPV) is a major cause of cervical, penile, anal, and oropharyngeal cancers. HPV vaccination is the most effective public health strategy for its prevention. Understanding the factors influencing vaccination intentions is critical for developing effective public health policies and improving population-level vaccine uptake. Therefore, in this scoping review, we aimed to examine HPV vaccination research conducted in Korea, identify common trends and gaps in study populations and influencing factors, and provide evidence-based recommendations for public health policies. Methods: We systematically searched four Korean databases—Research Information Sharing Service (RISS), DBpia, Korean Studies Information Service System (KISS), and National Digital Science Library (NDSL)—for studies published from their respective inception dates to January 2025, using “human papillomavirus,” “HPV,” “vaccination,” and “intention” as keywords. Thirty-six studies were ultimately included. Study characteristics, populations, theoretical frameworks, and key variables were extracted and analyzed using descriptive statistics and content analysis. Results: Of the included studies, 61.1% and 38.9% targeted vaccination-eligible individuals (adolescents and adults) and parents/guardians, respectively, with 50% focusing exclusively on women. The major factors influencing HPV vaccination intention were attitude (47.2%), subjective norms (38.9%), and perceived behavioral control (30.9%). Attitude and knowledge were critical for vaccination-eligible individuals (Direct group), whereas subjective norms were key for parents/guardians (Indirect group). Conclusions: Korean HPV vaccination intention research has predominantly focused on women and parents, with insufficient attention to adolescents and men. Public health strategies must employ multilevel interventions tailored to each group’s decision-making structures, including school-based programs for adolescents, gender-inclusive policies for men, and community-based approaches to address social norms among parents. These findings provide evidence for policy development aligned with the WHO cervical cancer elimination goals. Full article

The heat island effect and air stagnation issues caused by high-density built-up areas are becoming increasingly severe. Optimising urban ventilation structures and establishing ventilation corridors have become key approaches to improving the urban thermal environment and enhancing liveability. However, traditional methods for constructing ventilation corridors often rely on empirical weighting or linear models, which struggle to accurately reveal the resistance coefficients of resistance indicators and fail to reflect the threshold at which indicators transition between positive and negative impacts. Consequently, this study employs Shanghai, China, as a case study, integrating machine learning models with the minimum cost path (MCR) model. Key variables were screened through multiple linear regression and variance inflation factor (VIF) analysis. Subsequently, machine learning models were compared to select the optimal model, with parameter optimisation conducted using Optuna, followed by computational implementation. The results indicate that built environment factors (such as building height, shape complexity, and road density) exert a significantly greater influence on ventilation potential than natural green space factors. By introducing the SHAP method, the positive and negative effects of each indicator on the ventilation environment and their threshold relationships were revealed. Negative indicators were converted into ventilation resistance factors to construct a resistance surface. Building upon this, cold and heat sources were identified using LST, NPP, and population density data. The MCR model was then employed to calculate the minimum resistance paths from cold to heat sources, forming an urban ventilation corridor network. The results indicate that primary corridors align with prevailing wind directions, following urban rivers and low-density green spaces. This study reveals the nonlinear effects of building and green space elements on ventilation systems, proposing machine learning-based optimisation strategies for ventilation corridors. It provides quantitative decision support for mitigating the urban heat island effect and enhancing city livability. Full article

The dynamic response accuracy of suspension servo actuators directly determines the vibration-reduction performance of active-suspension systems. However, during long-term service, the system is prone to the influence of compound-degradation faults, such as internal leakage and time delay, leading to a significant decline in control performance. To address this issue, this paper proposes a collaborative control framework combining model-free adaptive control with a differential term of tracking error (DE-MFAC) and an improved particle swarm optimization (IPSO) algorithm. Firstly, to overcome the limitations of traditional model-free adaptive control (MFAC), a DE-MFAC strategy is constructed by implicitly handling the time-delay term and introducing the differential term of tracking error and dynamic weight factor into the performance index. Secondly, to enhance the parameter-tuning effect, the traditional particle swarm optimization (PSO) algorithm is improved (IPSO) by incorporating a dynamic inertia weight and an out-of-bounds random reflection mechanism, thereby strengthening the global optimization capability. On this basis, a suspension servo actuator system model incorporating internal leakage and time-delay faults is established based on the co-simulation platform of Simulink and AMESim, and the proposed method is validated. The simulation results show that, compared with the optimized traditional MFAC, the DE-MFAC tuned by IPSO exhibits superior position-tracking accuracy, faster response speed, and stronger overshoot-suppression capability under various compound-fault conditions. Further analysis indicates that the Integral of Absolute Cubic Error (IACE) function, due to its higher sensitivity to large deviations, can more effectively suppress overshoot and is suitable for engineering scenarios with strict requirements on dynamic performance. In addition, the optimization of control parameters using the IPSO algorithm can effectively compensate for the performance degradation caused by degradation faults, providing a feasible technical approach for extending the service life of actuators through adaptive adjustment. Full article

Pesticide use in agriculture can have negative collateral effects on the environment. In this study, two groups of treatments (G1 and G2) based on active substances (ASs) with different mobility were evaluated in order to determine pesticide residues in the soil and their impact on soil microbial populations in two vineyards located in two Denominations of Origin (D.O.). Soil samples were collected in July, October, and the following March over two consecutive years. Pesticide residues were analyzed by liquid chromatography–tandem mass spectrometry (LC-MS/MS) after QuEChERS extraction. Microbial genera were identified by the amplification of the fungal ITS regions with the universal primers ITS86F and ITS4R, and the bacterial 16S rRNA gene (V4 region) with primers 515F and 806R. Although G1 consistently showed higher residues, primarily attributable to azoxystrobin, no significant differences were observed between the two pesticide groups in the total pesticide residues or diversity of microbial communities. The factors D.O., campaign, and sampling month influenced the concentration of residues. Several ASs exhibited different dissipation dynamics depending on the D.O. Azoxystrobin and metrafenone were the most persistent in soil. The LEfSe analysis associated four beneficial fungal genera with the G2 group. The judicious selection of ASs can help to minimize the pesticide residues in soil and their harmful effects on beneficial genera. Full article

The large-scale deployment of electric power wireless private networks (EPWPNs) has significantly increased the number of base stations in substations, transmission corridors, and distribution terminals, leading to rapidly rising electricity expenditure for continuous wireless coverage and power-grid monitoring services. However, the increasing number of base stations deployed across substations and distribution networks has led to rising electricity expenditure, making cost-effective energy supply a critical challenge. To reduce the operating costs of base station clusters and enhance the economic efficiency of power supply, this paper proposes a multimodal power consumption optimization method that coordinates wind energy, solar energy, and energy storage based on user interaction behavior. First, considering user interaction characteristics and the complementarity of multiple energy sources, a dual-layer cellular network architecture consisting of macro- and micro-base stations is constructed. This architecture incorporates grid power purchases, wind power generation, and photovoltaic energy. An optimization model is then developed, which includes both equipment operation constraints and energy interaction constraints. Second, the key factors influencing energy consumption are analyzed using operational research methods. The existence of an optimal solution for the energy consumption function is demonstrated based on the Weierstrass optimization theorem. An energy-saving strategy for base stations under user group access is then derived using Karush–Kuhn–Tucker (KKT) conditions. Through spatio-temporal (ST) dynamic analysis, the coupling relationships among wind power, solar energy, energy storage, and grid electricity purchases are quantified. Based on this analysis, a multimodal cost optimization scheme utilizing dynamic bandwidth allocation is proposed. Simulation results demonstrate that, compared with traditional single-source power supply models and representative existing optimization schemes, the proposed multimodal energy scheduling framework can significantly reduce the operating cost of base station clusters while maintaining communication performance. Full article

Background: The term immigrant health paradox describes how immigrants often have better health outcomes than their American-born counterparts. While existing literature treats this phenomenon as broadly generalizable, emerging research indicates that its expression varies across cultural and migration contexts. Understanding how the immigrant health paradox may appear across specific ethnic groups requires research that maps variation rather than assumes uniformity. Objectives: This study seeks to describe patterns, explore variation by nativity, and identify factors associated with well-being among the Vietnamese population in the United States (US). By focusing on descriptive trends and contextual influences, the study aims to generate new insights into how the paradox may manifest—or diverge—in the Vietnamese context. Methods: We conducted an online survey asking participants about their depressive disorders, physical and mental health status, demographics, socioeconomic status, social networks, and experiences with daily discrimination. Descriptive statistics were used to describe the study sample. Linear regression and ordinal logistic regression were performed to explore the relationships. Results: In this exploratory analysis, we did not observe indications of the Vietnamese immigrant health paradox. Material factors, especially perceptions of financial needs, as well as psychological factors, were somewhat associated with how Vietnamese people living in the US assess their health. Conclusions: The absence of the Vietnamese immigrant health paradox in the US underscores the need for nuanced health models that reflect diversity within immigrant groups. Their experiences reveal how migration histories, structural barriers, and racialization shape health outcomes in ways that differ from expectations. Full article

Despite the increasing emphasis on residents’ prosperity aspirations in rural development initiatives, the lack of a psychometrically sound measure limits comparability and rigor, as existing studies primarily focus on structural and policy factors influencing community prosperity, with insufficient attention to residents’ psychological processes and subjective experiences. Drawing on community psychology, this study develops and validates a measure of rural residents’ aspirations for common prosperity, integrating personal fulfillment with collective advancement across material and spiritual domains. Employing a three-phase mixed-methods design, Study 1 used in-depth interviews and grounded theory procedures (N = 28) to develop a theoretical model comprising four dimensions: material–individual, material–collective, spiritual–individual, and spiritual–collective. Study 2 generated a 19-item, four-factor scale via exploratory factor analysis and exploratory graph analysis (N = 581). Study 3 confirmed the scale’s second-order factor structure and psychometric properties with confirmatory factor analysis (N = 659). The Common Prosperity Aspiration Scale (CPAS) demonstrated strong reliability and validity across its four dimensions and the overarching second-order factor. This pioneering study elucidates the psychological structure of common prosperity aspirations and provides a psychometrically reliable measure for rural contexts. It serves as a valuable tool to explore their influence on behaviors and promote sustainable community development. Full article

Vultures are extraordinarily adapted to feed on carrion, providing them with a constant microbiologically hostile environment. This peculiar ecological position has influenced the evolution of their gut microbiota, potentially conferring its uncommon antimicrobial traits and resistance to stress. In this study, we report on the isolation and comprehensive characterization of a lactic acid bacterium strain, identified as Ligilactobacillus agilis, from vulture feces via 16S rRNA gene sequencing. This strain exhibited potent antagonistic activity against several clinically relevant bacterial pathogens, including Salmonella enterica Typhimurium (25.26 ± 0.26 mm), Escherichia coli (23.5 ± 0.88 mm), Staphylococcus aureus (23.1 ± 1.8 mm), and Listeria monocytogenes (24.88 ± 0.61 mm), as demonstrated by agar well diffusion assays. Remarkably, it also demonstrated considerable resilience in simulated gastrointestinal conditions, with survival rates of 52.5 ± 7.4% in artificial gastric juice and 61.1 ± 3.7% in intestinal fluids. Antimicrobial susceptibility profiling confirmed its sensitivity to a broad range of commonly used antibiotics, including gentamicin, streptomycin, clindamycin, and penicillin. Whole-genome sequencing further revealed a complete repertoire of core genes associated with genetic information processing, robust carbohydrate metabolism, and nutrient assimilation, underscoring its adaptability and probiotic potential. It is important to note that the analysis of the assembled genome against VFDB did not show the presence of any known virulence factor according to the given criteria, which is preliminary evidence of safety-related aspects that are to be followed with the help of guideline-based analyses. Taken together, the unique ecological origin and in vitro inhibitory activity against the tested pathogens, gastrointestinal robustness, genomic features, and safety credentials position this L. agilis strain as a promising probiotic candidate for mitigating enteric infections in animal production systems, warranting further functional validation and in vivo efficacy studies. Full article

This study investigates the relationship between religiosity and attitudes toward COVID-19 vaccination in Romania using nationally representative survey data from the Barometer of Religious Life (December 2021). Five survey items measuring religious beliefs and practices were used to construct a Religious Practice Index, whose reliability and one-dimensionality were confirmed through Cronbach’s Alpha and factor analysis. Correlation analysis revealed a small but statistically significant negative association between religiosity and vaccination acceptance (r = −0.106, p = 0.001). Binary logistic regression further indicated that higher religiosity, younger age, lower income, and rural residence were significant predictors of reduced vaccination likelihood, while older age, higher income, and urban residence were associated with greater acceptance. Nevertheless, the model explained only 9.3% of the variance and correctly classified 64.4% of cases, suggesting modest predictive power. These findings indicate that religiosity influences vaccination attitudes but does not serve as a dominant predictor, highlighting the importance of other additional factors that were beyond the scope of this analysis and were not measured. Full article

This study provides valuable insights into the factors influencing attitudes towards homosexuality and people living with Human Immunodeficiency Virus (HIV) among Slovenian high school students. The analysis identifies gender, school type, and religious affiliation as significant predictors of these attitudes. Consistent with previous research, gender differences emerge, with male students displaying more negative attitudes towards homosexuality compared to their female counterparts. This discrepancy is particularly pronounced among students attending vocational schools, aligning with existing data on attitudes towards sexuality. Sociological theories predicting social changes in intimacy, with women at the forefront, contribute to understanding this gender disparity. Full article

In recent years, the operational performance of agricultural enterprises has been influenced by both natural conditions and market environments, resulting in high uncertainty and volatility. When performance falls below expectations, agricultural enterprises consciously engage in strategic change and proactive risk-taking to alleviate performance pressures. Based on Firm Behavioral Theory, Performance Feedback Theory, and Prospect Theory, we examine how performance expectation gap affects risk-taking of agricultural enterprises by using panel data of Chinese A-share listed agricultural firms from 2007 to 2023. The results show that performance expectation gap has a positive effect on risk-taking, which means the greater the gap, the higher the level of risk-taking. And the better developed the institutional environment, the greater the tendency for risk-taking. Further analysis shows that performance expectation gap promotes risk-taking by driving strategic change within agricultural enterprises. This research enriches the study on the influencing factors of risk-taking in agricultural enterprises, offering decision-making insights for them to prudently assess and manage risks. Full article