A consumer seeking to purchase multiple products may do so at a single store (one-stop shopping) or across multiple stores (multistop shopping). Fixed shopping or search costs rationalize one-stop shopping, which often emerges as the only equilibrium behavior in theoretical models. In reality, however, multistop shopping is common, and evidence suggests that some consumers adopt it to save on expenditures. This paper uses NielsenIQ consumer scanner data to address two questions about multistop shopping: who engages in it, and why. We examine the first by relating households' multistop shopping tendencies to their demographic and economic characteristics, and the second by comparing actual expenditures to those under a counterfactual one-stop scenario. The regression results indicate that multistop shopping is more prevalent among households with lower opportunity costs of time (due to unemployment or old age). Greater heterogeneity in stores' product offerings and higher inflation – when adjusted for changes in shopping lists – is also associated with higher multistop shopping tendencies. The counterfactual analysis further shows that, for most trips, one-stop shopping would entail higher expenditures than the observed multistop trips. However, the magnitude of these savings is modest: households save between 4.7% and 11.5% of daily expenditures through multistop shopping.

Understanding carbon emissions of the railway transportation industry in China is critical for effective climate action. This study applied machine learning models to analyze railway operational conditions and socio-economic driving factors of carbon emissions across four railway operational regions with different terrain, climate, and economic development characteristics in China from 2009 to 2021. This study indicates that People, Electricity Carbon Emission Factor, Tertiary Industry Gross Domestic, Railway Passenger Volume, Railway freight Volume, Research and Development Investment and Railway Infrastructure Level have a significant impact on carbon emissions. The Lasso_LR model shows strong fitting performance, as the mean absolute error is 4.98% of the average carbon emissions. By 2021, the Qinghai-Tibet Plateau, Yunnan Province, the Guangxi Zhuang Autonomous Region, and the Yangtze River Delta Region showed a decline in carbon emissions, with emission reductions of 41.1%, 36.6%, 21.4%, and 21.5% compared to their levels in 2009. Model predictions indicate that carbon emissions from railways in the Qinghai-Tibet Plateau, Yunnan Province, the Guangxi Zhuang Autonomous Region, and the Yangtze River Delta Region are projected to decline by 15.8%, 12.23%, 34.15%, and 0.03% respectively by 2030, relative to 2021 levels in the regional emission-reduction scenario. This study offers insights into the socio-economic and internal mechanisms of emissions, guiding tailored reduction targets for different railway operational regions to aid China in achieving '3060' target.

To develop a scientific, objective, and quantitative clinical comprehensive evaluation index system for the first-line treatment of HER-2-negative advanced gastric cancer with immune checkpoint inhibitors, to provide a reference index for the clinical comprehensive evaluation of similar drugs in clinical settings, and to inform decision-making regarding the rational clinical use of medication and directory access in hospitals. A preliminary indicator pool was established based on the literature analysis method, and the final indicator system and weights were clarified by combining the use of two rounds of the Delphi expert consultation method and analysis hierarchical process (AHP). After expert consultation and validation, a comprehensive evaluation system of four primary indicators, 10 secondary indicators, and 18 tertiary indicators for the first-line treatment of HER-2-negative advanced gastric cancer with immune checkpoint inhibitors was finalized. The primary indicators were effectiveness (47%), safety (34%), economy (10%), and pharmacological properties (9%). The top three weights of the combination of secondary indicators were adverse reactions (26.8%), clinical efficacy (20.8%), and indications (15.6%), respectively. The top-ranked secondary indicators among the economic and pharmacological characteristics indicators were whether they were included in the national essential drug list (3.9%) and whether their pharmacological effects were clear (6.3%). The weights of the combination of tertiary indicators ranged from 0.4% to 15.3%, with the highest weights being the incidence of CTCAE grade ≥ 3 adverse events under the safety adverse reaction indicator (15.3%) and the incidence of adverse events leading to treatment interruption (11.6%). The comprehensive evaluation system based on the Delphi method and AHP for constructing the first-line treatment of HER-2-negative advanced gastric cancer with immune checkpoint inhibitors has a high degree of authority, scientificity and reliability. In view of the differences in drug attributes, disease characteristics, and medication populations, it is necessary to carry out a comprehensive clinical evaluation based on these three to meet the needs of the current medication.

Somalia has one of the lowest childhood immunization coverage rates globally, with only 34.8% of children aged 0-59 months having received at least one vaccine and a high burden of zero-dose children. Immunization uptake is influenced by socioeconomic, maternal, healthcare access, and geographic factors. This study examined determinants of childhood immunization coverage in Somalia to inform equity-focused strategies. A cross-sectional analysis was conducted using nationally representative data from the 2020 Somalia Demographic and Health Survey (SDHS), including 7,373 mother-child pairs. bivariate and multivariable logistic regression models assessed associations between sociodemographic, economic, maternal, healthcare access, and geographic characteristics and child vaccination status, accounting for survey design and confounders. Overall vaccination coverage was 34.8%. Health facility delivery was the strongest independent predictor (AOR = 1.93; 95% CI:1.68-2.22; p < 0.001). Children from the highest household wealth quintile had higher odds than the poorest (AOR = 2.45; 95% CI:2.00-3.00; p < 0.001). Maternal primary and secondary education were positively associated with vaccination (AOR = 1.58; 95% CI:1.34-1.87 and AOR = 1.94; 95% CI:1.40-2.67; respectively; p < 0.001). Nomadic residence was associated with higher odds compared with rural residence (AOR = 1.69; 95% CI:1.46-1.96; p < 0.001). Compared with infants aged 0-11 months, children aged 12-23 months (AOR = 1.36; 95% CI:1.10-1.69; p = 0.005) and 24-59 months (AOR = 1.33; 95% CI:1.12-1.59; p = 0.001) were more likely to be vaccinated. Lack of radio exposure was associated with lower vaccination odds (AOR = 0.64; 95% CI:0.50-0.82; p < 0.001). Children living in Gedo region had markedly lower odds of vaccination than those in Awdal region (AOR = 0.26; 95% CI:0.17-0.39; p < 0.001). Childhood immunization coverage in Somalia remains critically low, reflecting socioeconomic, maternal, healthcare access, and geographic inequalities that require strategies targeting disadvantaged populations and regions.

For-profit hospitals deliver lower coronary artery bypass graft value: National evidence on mortality and Medicare expenditures.

Family influences on type 2 diabetes self-management: Perspectives of African American adults with food insecurity.

Be rich, grow tall? Testing whether parental social origin is associated with filial body height using two German student cohorts.

Spices are essential in daily life, serving both culinary and medicinal purposes and have profoundly influenced human history, culture, economy, and health. However, a key challenge associated with these natural ingredients is the limited information available for their identification and quality assessment. The critical issues of spice processing and authentication, emphasize the need for a robust digital authentication system. Hence, there is a need for an innovative approach leveraging artificial intelligence and machine learning to enhance spice authentication. The integration of food computing and non-invasive experimental methods has emerged as a significant approach to enhance the analysis and quality control of spices. This review explores how advanced computational techniques, such as artificial intelligence, can be combined with non-destructive experimental methods such as Near-infrared spectroscopy, Fourier transform infrared spectroscopy and Hyper Spectral Imaging to achieve more comprehensive, efficient, and accurate spice components analysis. Spices, with complex compositions and high economic, nutritional, functional, and sensory value characteristics, serve as an ideal case study using artificial intelligence, machine learning, and deep learning for the classification, authentication, and quality assessment of spices. It highlights the ability of food computing to process and interpret large datasets obtained from spectroscopy, chromatography, and sensory evaluation. With recent advances and case studies, this review emphasizes the potential of AI-integrated non-destructive experimental approaches to address current challenges in spice quality analysis. This ensures the authenticity, safety, and quality of spices supporting industry efforts to enhance product quality, reduce waste, and meet consumer demands.

As energy systems transition toward decentralization and decarbonization, residential prosumers are playing an increasingly vital role in grid stability and energy market participation. However, the economic viability of investing in battery energy storage systems (BESS) and joining virtual power plant (VPP) schemes remains uncertain, particularly under real-world operating conditions where battery dispatch is optimized for grid objectives rather than prosumer benefit. Although a growing body of research examines VPP optimization and grid-level services, relatively limited attention has been given to evaluating the economic feasibility of prosumer participation using empirical operational data.. This study addresses that gap by using empirical data from a residential VPP trial involving 750 Australian households to evaluate the economic performance and dispatch characteristics of residential battery systems under real VPP control. A clustering analysis is used to characterize battery operational patterns, and a techno-economic framework assesses investment viability across twelve scenarios that vary electricity tariff structures and battery degradation assumptions. Financial performance is evaluated using payback period, net present value, and internal rate of return. The results show that VPP participation combined with government incentives can reduce the payback period by up to five years and improve annual energy bill savings by approximately 20 percent. However, under low tariff conditions and without targeted incentives, residential battery adoption remains economically challenging. These findings highlight the importance of aligning VPP incentive structures with prosumer economic viability to enable sustained participation and realize broader system-level benefits.

Socioeconomic vulnerability analysis evaluates the extent to which a community or region is susceptible to the adverse impacts of natural disasters, considering the specific social and economic characteristics of the community. This study examines the socioeconomic vulnerability of the City of Oslo, Norway, to natural hazards using two distinct indexes: the Social Vulnerability Index (SoVI), which distinguishes the population considered as socially vulnerable (due to variables such as age and gender), and the Socio-Economic Status Index (SESI), which incorporates the social and economic status of the total population. The findings revealed that, while the least vulnerable subdistricts varied only slightly between the two indexes, the distribution of the most vulnerable subdistricts remained largely consistent. The measurement of socioeconomic status, rather than the extent of social vulnerability in the SESI, highlighted additional social aspects of vulnerability. Additionally, some variables contributed to the indexes in ways that contradicted expectations, likely due to theoretical inconsistencies in the index methodologies. Both indexes play a critical role in disaster risk management by capturing certain epistemic uncertainties arising from limitations in data and knowledge. However, it is important to note that any index provides only a static picture of vulnerability, offering an initial estimate of the conditions that may increase susceptibility to hazards. It does not fully reflect the dynamic nature of risk and resilience, which should be considered when engaging with disaster management authorities.

Regional development aims to promote economic growth in society, which is commonly measured using Gross Regional Domestic Product (GRDP). Sumatra Island is one of the regions that makes a substantial contribution to national economic growth. However, compared to other provinces in Sumatra, Jambi Province still records a relatively lower GRDP value. In addition, GRDP growth among regencies/municipalities in Jambi Province shows disparities and fluctuates from year to year. This condition reflects variations in the influence of economic factors both spatially and temporally. Spatial variation is indicated by the interregional linkage of GRDP and differences in the economic characteristics of each area, while temporal variation is observed through changes in annual GRDP growth influenced by commodity price fluctuations, development projects, and local economic dynamics. If the analysis is conducted using conventional linear regression without considering spatial and temporal aspects, it may violate classical assumptions, such as the presence of heteroskedasticity, residual autocorrelation, and the inability of the model to capture the dynamics of GRDP changes. This may result in biased and less valid coefficient estimates. This study aims to analyze the effects of Domestic Investment, Human Development Index (HDI), Labor Force Participation Rate (LFPR), Local Own-Source Revenue, and Capital Expenditure on the GRDP of regencies/municipalities in Jambi Province during the 2021–2024 period using the Geographically and Temporally Weighted Regression (GTWR) method. The analysis is carried out through testing spatial and temporal effects, determining the weighting function, estimating parameters, and evaluating model goodness-of-fit using the AIC and R² values. The results show that the GTWR model yields an AIC value of 90.93 and an R² value of 0.526.

&amp;lt;i&amp;gt;Background&amp;lt;/i&amp;gt;: In Africa, healthcare is generally supported by households. The heavy burden of healthcare on household leaders can lead them to forego care. In this study, we analysed the determinants of healthcare renunciation among household leaders in Abidjan. &amp;lt;i&amp;gt;Methods&amp;lt;/i&amp;gt;: This cross-sectional study was carried out from May to July 2019 in &amp;quot;colombie&amp;quot;, a neighbourhood of Abidjan (Côte d’Ivoire). Heads of household that had been living there for at least 3 months were randomly selected. Sociodemographic, economic, health status and health care renunciation characteristics were collected. Logistic regression models were used. &amp;lt;i&amp;gt;Results:&amp;lt;/i&amp;gt; The sample consisted of 648 heads of household with a mean age of 35.6 ± 8.37 years and a sex ratio (F/M) of 1.59. Almost all of them (97.53%) had given up care at least once. Medical consultations foregone concerned 57.56% of them (including 18.21% to the general practitioner and 39.35% to the specialist). After the consultation, 39.97% of them gave up on other care. People who reported poorer health (OR= 1.93 [1.14–3.29], p=0.015) and those who had no health coverage (OR=6.42 [3.90–11.00], p&amp;lt;0.001) gave up significantly more medical consultations. Heads of households with dependent children (OR=1.93 [1.15–3.34], p=0.015), those who were still in school (OR=1.89 [1.06–3.36, p=0.030]) and those without health insurance (OR=3.30 [1.80–6.19], p&amp;lt;0.001) were significantly more likely to forego postconsultation care. &amp;lt;i&amp;gt;Conclusion:&amp;lt;/i&amp;gt; Literacy level, risk perception, health system responsiveness and health insurance coverage were drivers of healthcare renunciation. Health insurance coverage was the factor that most influenced renunciation at different stages of the care pathway. As a large number household leaders don’t benefit from health insurance, this work highlights the need to make health coverage functional in the country.

Fat deposition traits are crucial economic characteristics that directly influence production efficiency in pigs. To better understand the genetic mechanisms underlying fat deposition, four traits including backfat thickness (BF), caul fat rate (CFR), leaf fat rate (LFR), and internal fat rate (IFR) were measured in 421 Large White × Tongcheng crossbred pigs. A GWAS analysis identified 666, 15, 22, and 61 SNPs significantly associated with BF, LFR, CFR, and IFR, respectively. Bayesian fine-mapping revealed a major QTL on SSC7 (29.62-30.62 Mb) that influences all four fatness traits and harbors the candidate gene HMGA1 and NUDT3. Additionally, a QTL on SSC5 (28.67-30.52 Mb) was associated with BF and contains the candidate gene TBK1, while a QTL on SSC18 (8.01-9.88 Mb) associated with CFR includes AGK and TBXAS1. Integration of transcriptome, 3D genomic, and epigenomic data identified rs703100168 on SSC7 as a candidate functional SNP to control HMGA1 expression and regulate fat deposition in pigs. These findings provide valuable candidate genes and genetic variants for improving fatness traits in pig breeding programs.

Low-carbon energy transition (LET) has become an important global development strategy. However, in the contemporary industrial era, carbon emissions are intricately intertwined with economic growth based on the extensive use of fossil energy. To this end, the key to a more acceptable push for LET is to achieve carbon emissions decoupling (CED). The rapidly developing digital economy (DE) introduces novel possibilities for it. Using a Finite Mixture Model, this study aims to analyze how DE heterogeneously impacts CED across 66 countries from 2011 to 2022. As of 2022, 41% of countries attained strong decoupling status, 33% reached weak decoupling status. In terms of the effect of DE on CED, both chance and challenge are shown. DE exhibits dual effects: it enhances CED in high-education countries but hinders it in countries with rapid population growth. Government efficiency and gender equality amplify DE’s chance role, while natural gas or clean energy reliance weakens it. DE indirectly promotes CED via low-carbon behavior while raising risks through easier credit access. Meanwhile, the heterogeneity of institutional and economic characteristics in countries may influence the effect of DE on CED. These findings offer a theoretical foundation to reconcile economic sustainability with climate mitigation in digital transitions, providing actionable insights for policymakers to leverage DE’s potential in achieving SDG 13.

ABSTRACT In response to the COVID-19 pandemic, the federal government made an unprecedented outlay of funds for emergency rental assistance (ERA), providing more than $46 billion to renters and their landlords. Previous research has documented the logistical challenges of distributing these funds during the pandemic. In this study, we use restricted-use Treasury Department data on ERA payments to describe the distribution of rental assistance across neighborhoods, demonstrating significant variation in the scale and timing of payments. We analyze differences in the amount and pace of ERA payments made by neighborhood socio-demographic and economic characteristics, as well as pre-pandemic eviction filing patterns. We show that ERA was well-targeted to areas at greatest risk of housing instability and that a larger share of potentially eligible low-income renter households received assistance in such neighborhoods in 2021. Overall funding levels and use of programmatic flexibilities affected the pace of distribution between programs, but had minimal impact on within-program distribution patterns. Our findings help to inform both evaluation of pandemic-era policies and the design of future eviction prevention programs.

<sc></sc> Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS) are widely used in global health research. Cross-country evidence based on these surveys could be unreliable, if survey availability and quality exhibited systematic patterns. This paper documents whether such patterns exist in low- and middle-income countries (LMICs) over the period 1982–2016, examining countries’ economic, demographic, and political characteristics. Descriptively, DHS and MICS are very unevenly distributed across LMICs, but they show good data quality in terms of age and anthropometric mismeasurement. We explore country-level correlates of data availability and quality in cross-sectional and panel models (with country and time fixed effects). While economic and demographic factors show relatively weak influence, political factors do matter. Conflict is a negative predictor of DHS and MICS data availability. Democracy exhibits an inverted-U-shaped association with availability of USAID-financed DHS. Availability of UNICEF-financed MICS is negatively yet convexly associated with countries’ US-aligned voting in the UN. Predictors of data quality are unsystematic, but we detect regional differences. Overall, we recommend using DHS and MICS data together, and including country fixed effects in cross-country regressions. A crucial implication for higher-quality research is to harmonise and coordinate MICS with DHS, and make them jointly accessible.

Given the expanding scale of offshore wind power development, strict spatial constraints on offshore platforms and multi-source power coupling present operational challenges during the collaborative transmission of near-shore and far-offshore wind power through a shared corridor. To address these issues, this paper proposes a collaborative transmission scheme based on the Self-Adaption Statcom and Line-Commutation Converter (SLCC). The technical and economic characteristics of three typical topologies—Modular Multilevel Converter (MMC) onshore grid connection, MMC direct transmission, and SLCC direct transmission—are compared and analyzed. The results demonstrate the advantages of the SLCC scheme in reducing the offshore platform footprint and lowering engineering costs. Furthermore, a hierarchical collaborative control strategy is designed to mitigate the power coupling between near-shore AC wind generation and far-offshore DC wind generation at the converter bus. The bottom layer utilizes a valve-side parallel Static Var Generator (SVG) to achieve reactive power self-balance and quasi-resonant suppression of specific harmonics. In the top layer, an LCC active power-following control strategy based on instantaneous power feedback is implemented. This achieves the logical decoupling of near-shore and far-offshore wind power transmission. The effectiveness of the proposed scheme in managing wind power fluctuations, riding through AC faults, and maintaining stable operation under weak grid conditions is verified using the PSCAD/EMTDC software.

Farming of broiler poultry has become a significant element of the agricultural sector in Lucknow with significant contribution to rural livelihoods, job creation, and food security. This paper investigates the socio-economic nature, operational and economic features of broiler poultry farming in the four largest tehsils of the district, i.e., Bakhshi Ka Talab, Malihabad, Mohanlal Ganj, and Sarojini Nagar. The research is founded on primary data gathered by use of a structured questionnaire and field survey of 200 broiler poultry farmers. The study was to examine the socio-economic profile of poultry farmers, learn about the operations and production activities of broiler farming, and determine the primary determinants of farm performance and sustainability. The demographic and socio-economic characteristics of respondents, such as age, gender, education, income, and occupational pattern were presented in terms of descriptive statistics. Analysis of Variance (ANOVA) was utilised to determine variation between the sampled tehsils but Principal Component Analysis (PCA) was used to extract underlying factors affecting broiler farming practices. Moreover, the multiple regression analysis was used to test the dependency between the area of a farm performance and the predictive variables, including its size, experience of farming, the availability of markets, and the income level. The results indicates that farming of broiler poultry in the study region is male dominated and concentrated majorly in rural households that have diversified livelihood plans. The findings also reveal the presence of a great difference in operational practices and economic performance within the chosen tehsils. The most important determinants of the success of broiler farms are experience in farming, availability of infrastructure and market connections. The study identifies the significance of ensuring that accessibility to credit, market networks, and technical training programs are further increased to improve the productivity and profitability of broiler poultry farming in the area. The research findings are informative to policy makers, researchers, and stakeholders interested in achieving sustainable poultry production and rural economic growth.

The rapid development of metropolitan areas means that their spatial patterns must be reconstructed and brings a series of urban problems such as traffic congestion and imbalance among transportation facilities. As the skeleton of the comprehensive transportation network, the planning of passenger corridors in metropolitan areas has a positive impact on the integrative development of urban spaces and transportation systems. The identification of passenger corridors is the basis for the optimization of the configuration and organization of transportation facilities. In this paper, passenger transportation modes were distinguished through a multilayer network. Considering the technological and economic characteristics of each mode synthetically, an improved method for identifying passenger corridors was proposed. First, a multilayer network was constructed based on the passenger transportation facilities network in a metropolitan area to distinguish between different transportation modes. Based on the traditional importance degree model of nodes, an importance degree model of routes was constructed by considering transportation modes, passenger demand, and transportation costs. Through qualitative judging using regional planning, supported by quantification according to the importance degree of routes, passenger corridors in the chosen metropolitan area were identified and divided into primary and secondary corridors. Suzhou metropolitan area was studied as an example. Identification results for three transverse corridors and two longitudinal corridors were obtained after analysis and calculation, verifying the availability of the method. The study can contribute to the balance of transportation supply and demand, realize the intensive use of transportation facilities, and promote the sustainable development of metropolitan transportation systems. In particular, the proposed method provides a reference for the rational optimization of transportation facility configuration within passenger corridors in metropolitan development areas, facilitating the formation of efficient passenger transport organization systems and compact, transit-oriented land use patterns by improving the coordination between passenger corridors and ecological spaces.

The article examines the effectiveness of using self-supporting insulated wires (SIP) in the electrical networks of the southern region of Kyrgyzstan. An analysis of the technical, economic, and operational characteristics of SIP was conducted in comparison with traditional non-insulated wires. Special attention was given to improving the reliability of power supply, reducing energy losses, and lowering the costs of installation and maintenance of the lines. Based on the performed calculations and field studies, the feasibility of widespread implementation of SIP in the networks of the southern districts of the country is demonstrated, taking into account climatic and geographical conditions. The obtained results can be used for planning the modernization of distribution networks and enhancing their resilience to external influences.