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Study on the Effect of Individual Characteristics and Cognitive Degree on Green Food Consumption Behavior

JOURNAL OF FOOD QUALITY 2024年第1期2024卷

作者： Deng, Zhiying Huang, Yi Tan, Qiuxia Changsha Social Work Coll Sch Business Changsha 410004 Peoples R China Hunan Inst Engn Sch Management Xiangtan 411104 Peoples R China

The study of consumption behavior on green food plays an important role in promoting agricultural environmental protection and eco-agricultural production. Based on the practical investigation, this paper makes an empirical study on the consumption behavior of green food by using binary logistic regression model. It is found that consumer's education level has a significant positive effect on green food consumption. Consumer income level does not pass the test on consumption behavior, but the change direction is opposite. Consumer age and premium of green food are negatively correlated with consumption motivation and behavior, while green food reliability and satisfaction are positively correlated with consumption motivation and behavior. Consumer gender, marital status, and information channels have no significant impact on consumption motivation and behavior. According to the research results, the production and marketing of green food should pay attention to the product quality and the actual feedback from consumers, and should increase the market propaganda to improve the attention and recognition ability on green food, and should take effective measures to develop the older consumer's market.

关键词： agricultural ecology China consumption behavior green food logistic regression model

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Exposure to multiple metals in adults and diabetes mellitus: a cross-sectional analysis

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ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2023年第6期45卷 3251-3261页

作者： Wu, Zhen Guan, Tong Cai, Dandan Su, Gang Suqian Ctr Dis Control & Prevent 8 Renmin Ave Suqian 223899 Jiangsu Peoples R China

Diabetes mellitus (DM) is the most widely recognized metabolic illness with expanding morbidity among ongoing years. Its high incapacity rate and death rate badly affect individuals' quality of life. Increasing proofs backed the relationship between metal exposures with the risk of DM, but the methodological boundedness cannot clarify the complexity of the internal relationship of metal mixtures. We fitted the logistic regression model, weighted quantile sum regression model, and Bayesian kernel machine regression model to assess the relationship between the metal exposures with DM in adults who participated in the National Health and Nutrition Examination Survey 2013-2016. The metals (lead, cadmium, and copper) levels were significantly higher among diabetic compared to the healthy controls. In the logistic regression model established for each single metal, lead and manganese were associated with DM in both unadjusted and mutually adjusted models (highest vs. lowest concentration quartile). When considering all metal as a mixed exposure, we found a generally positive correlation between metal mixtures with DM (binary outcome) and glycohemoglobin (HbA1c) levels (continuous outcome). Exposure to metal mixtures was associated with an increased risk of DM and elevated levels of HbA1c.

关键词： Diabetes mellitus Blood metals Serum metals logistic regression model BKMR model WQS model

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logistic regression prediction models and key influencing factors analysis of diabetes based on algorithm design

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NEURAL COMPUTING & APPLICATIONS 2023年第36期35卷 25249-25261页

作者： Li, Zhijian Pang, Sulin Qu, Hongying Lian, Wanmin SUNY Stony Brook Stony Brook NY 11794 USA Jinan Univ Inst Finance Engn Sch Emergency Management Guangzhou 510632 Peoples R China Guangdong Second Prov Gen Hosp Guangzhou 510317 Peoples R China Guangdong Emergency Technol Res Ctr Risk Evaluat & Guangzhou 510632 Peoples R China

This article focuses on the key influencing factors and prediction accuracy of diabetes. Nine test indexes were mainly considered: low density lipoprotein, triglyceride, total cholesterol, white blood cell, temperature, blood pressure, heart rate, blood sugar, and age. By designing data experiment method and logistic regression prediction algorithm based on fivefold cross validation, it is used to analyze odds ratio, full subset screening regression, cross validation, root mean square error and confusion matrix on 96 original data samples with 76 diabetes patients and 20 non-diabetes patients. Based on statistical test and innovation, two modeling ideas based on the combination of clinical experience and statistical test are proposed. logistic regression model I with 2 parameter variables and logistic regression model II with 5 parameter variables are, respectively, established to predict and compare the accuracy of five groups of different cross validation test sets. The prediction accuracy of the former is 93.7895%, and that of the latter is 91.7895%. This study found that age and blood sugar are the key influencing factors of diabetes. However, total cholesterol, temperature and white blood cell have little effect on diabetes. The research method has high application value and can provide scientific solutions for medical institutions to predict, analyze and early diagnose diabetes.

关键词： Detection index Diabetes logistic regression model Algorithm design Statistical test Clinical experience

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Krylov subspace solvers for l1 regularized logistic regression method

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COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION 2023年第6期52卷 2738-2751页

作者： El Guide, M. Jbilou, K. Koukouvinos, C. Lappa, A. Mohammed VI Polytech Univ Ctr Behav Econ & Decis Making CBED FGSES Green City Morocco Univ Littoral Cote dOpale Dept Math Calais France Natl Tech Univ Athens Dept Math Athens 15773 Greece

In this paper, we propose an approach based on Krylov subspace methods for the solution of l(1) regularized logistic regression problem. The main idea is to transform the constrained l(2)-l(1) minimization problem obtained by applying the IRLS method to a l(2)-l(2) one that allow regularization matrices in the usual 2-norm regularization term. The regularization parameter that controls the equilibrium between the minimization of the two terms of the l(2)-l(2) minimization problem can be then chosen inexpensively by solving some reduced minimization problems related to generalized cross-validation (GCV) methods. These reduced problems can be obtained after a few iterations of Krylov subspace based methods. The goal of our simulation study is directed toward the variable selection and the prediction accuracy performance of the proposed method in solving a l(1) regularized logistic regression problem in large dimensional data with different correlation structures among predictors. Finally, real data are used to confirm the efficiency of the proposed method in terms of the computational cost.

关键词： logistic regression model Krylov subspace methods regularization l(1)-norm variable selection

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Trajectory data-based severe conflict prediction for expressways under different traffic states

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PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS 2023年 621卷

作者： Cao, Jieyu Chen, Junlan Guo, Xiucheng Wang, Ling Southeast Univ Sch Transportat 2 Southeast Univ Rd Nanjing 211189 Peoples R China Tongji Univ Minist Educ Key Lab Rd & Traff Engn 4800 Caoan Rd Shanghai 201804 Peoples R China

Conflict prediction is prevalent in the field of expressway safety management. As the precursor of crashes, severe conflict draws great concentration in previous studies. However, the conflict mechanism heterogeneity under different traffic states is always ignored. The different traffic environment affects driving behavior, resulting in various casual factors. In order to better predict and understand the influencing factors of severe conflicts, this study proposes severe conflict prediction models under three traffic states based on a 3-hour vehicle trajectory data on the Shanghai Inner Ring Expressway. Firstly, the data is labeled with three traffic states based on the Traffic State Index and road average speed. Modified Time to Collision (MTTC) of vehicle pairs is calculated to identify severe conflicts. Second, the spatial and temporal characteristics of conflicts are analyzed to explore the conflict heterogeneity under different traffic states and the impact area of different ramps. Finally, logistic regression models are established to predict the likelihood of severe conflicts. Compared with the model without division of traffic states, congestion state model and transition state model have an increase of 1.7% and 8.9% in prediction accuracy, respectively. Main casual factors of severe conflicts differ under three traffic states. The occurrence of severe conflicts is more sensitive to the change in traffic volume and ramps when the traffic state becomes more congested. Vehicles in 300-meter area upstream exit ramps/downstream entrance ramps suffers from higher risk of collisions. However, when the traffic state approaches free flow, severe conflicts are more caused by drivers' unsafe behavior such as high speed and short spacing between vehicles. The findings can help transportation managers figure out the main casual factors of expressway crashes under different traffic states, and thus develop more targeted safety management strategies. (c) 2023 Published

关键词： Severe traffic conflict MTTC Traffic state Conflict heterogeneity logistic regression model

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Estimation for volunteer web survey samples using a model-averaging approach

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JOURNAL OF APPLIED STATISTICS 2023年第16期50卷 3251-3271页

作者： Liu, Zhan Zheng, Junbo Tu, Chaofeng Pan, Yingli Hubei Univ Sch Math & Stat Hubei Key Lab Appl Math Wuhan 430062 Hubei Peoples R China

Propensity score approach is a popular technique for estimating the population based on volunteer web survey samples. Various models have been used to estimate propensity scores and produce different population estimates. To obtain more accurate population estimators, we propose a model-averaging estimation approach based on propensity score estimates from a parametric logistic regression model and a nonparametric generalized boosted model. Consistency and asymptotic normality of the proposed estimators are established. A computation algorithm is also developed to implement the proposed method. Simulation studies are conducted to compare the performance of the proposed method with the other methods. A survey data from the Netizen Social Awareness Survey (NSAS) is used to illustrate the proposed methodology.

关键词： Volunteer web survey sample model-averaging approach propensity score logistic regression model generalized boosted model

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Analysis of household food security status in Hadiya Zone, Central Ethiopia

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JOURNAL OF AGRICULTURE AND FOOD RESEARCH 2025年 19卷

作者： Gebre, Amanuel Ayele Deshmukh, Mahadeo S. Wachemo Univ Dept Agr Econ Hossana Ethiopia Shivaji Univ Dept Econ Kolhapur India

Ensuring food security is one of the paramount challenges facing the developing world today. Developing countries like Ethiopia have been facing food insecurity for many decades. Despite many efforts undertaken by the government of Ethiopia, the country has not yet achieved food self-sufficiency. The current household food security status and determining factors are inadequately recognized in Hadiya Zone. Thus, this study aims to contribute to filling this gap. The study utilized both primary and secondary data sources. A multistage sampling technique was used to select 384 respondents. A seven-day food consumption score method was used to determine dietary energy intake in kilocalories per person per day, which was then employed to evaluate household food security status. Descriptive and inferential statistics as well as the binary logistic regression model were used to analyze the data. The findings show that 52.1 % of respondents were food insecure, and the remaining 47.9 % were food secure households. The logistic regression model results show that household food security status was mainly influenced by sex, dependency ratio, technology adoption, annual income, non/offfarm participation, soil and water conservation practices, credit use, and market participation. The extent and severity of food insecurity vary across different areas and depend on various factors. To transform the food system into resilient and sustainable, this study recommends that concerned government bodies and stakeholders support rural households with improved agricultural technologies, promote rural entrepreneurship, scale up soil and water conservation practices, provide affordable credit schemes, and enhance market access through improving rural infrastructure.

关键词： Household Food security Determinants logistic regression model Hadiya zone Ethiopia

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Examining Individuals' Use of the Internetfor Health Care Activities OverTime: Results from the US National Health Interview Survey

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JMIR HUMAN FACTORS 2025年 12卷 e58362页

作者： Junkins, Zachary Zahan, Nusrath Neyens, David Clemson Univ Dept Ind Engn 100 Freeman Hall Clemson SC 29634 USA

Background: Telehealth is an increasingly important component of health care services. Telehealth services may present an opportunity to increase the equity, accessibility, and effectiveness of health care. As such, it is critical that telehealth design focuses on reducing the barriers to access and usability that may impair some telehealth users. Objective: Our goal was to identify different demographic characteristics, behaviors, or opinions that may predict groups who are likely to face a barrier to using telehealth services. Methods: We used data from the National Health Interview Survey and multiple logit regression models focused on different aspects of telehealth to examine threedifferent avenues of telehealth service: looking up health information using the internet, scheduling an appointment using the internet, and communicating with a care provider through email using the internet in order to consider the ways in which different telehealth services may face different barriers. Results: Our results suggest that middle-aged (36-55 years old) and older adult (56-85 years old) respondents were significantly less likely to look up health information using the internet or schedule an appointment using the internet versus younger individuals (18-35 years old). Specifically, our analysis found that middle-aged adults were found to have a higher odds ratio than older adults (0.83 vs 0.65) for looking up health information using the internet. We also found that there were differences in age groups for using technology to perform health care-related tasks. In terms of searching for health information using the internet and scheduling appointments using the internet, wefound differences between men and women, with women being significantly more likely than men to look up health information using the internet, schedule an appointment using the internet, and communicate with a care provider through email using the internet. Across all the investigated variables, we foun

关键词： internet web search internet search internet use searching behavior access to health information telemedicine telehealth virtual care virtual health virtual medicine logistic regression model regression model National Health Interview Survey NHIS

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Research on regional water environmental carrying capacity based on GIS and TOPSIS comprehensive evaluation model

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ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 2023年第20期30卷 57728-57746页

作者： Wang, Peng Deng, Hongwei Cent South Univ Sch Resources & Safety Engn Changsha 410083 Hunan Peoples R China

Water environmental carrying capacity (WECC) is an important indicator for assessing the coordination between the water environment and the social-economic-resources and environment subsystems. In this study, to determine the WECC of Changsha-Zhuzhou-Xiangtan urban agglomeration in Xiang River Basin, a three-level index system was established using an analytic hierarchy process. Because the previous evaluation system lacked continuous indicators, the results could not reflect the differences of WECC within the administrative units, thus, this study selected 4 continuous indicators, and finally an evaluation index system including 15 indicators was established. Based on the TOPSIS model and logistic regression model, the current situation and change trend of WECC in the study area were obtained in ArcGIS. The results showed that the comprehensive WECC in this region was inferior in 2020, particularly in urban concentrated areas, and it was extremely uneven in spatial distribution. The WECC decreased significantly from 2011 to 2014 and gradually improved from 2014 to 2020. According to the prediction results, the WECC will increase in the future, with an average value of 0.54 in 2025 and 0.60 in 2035. This study will have important guiding implications for the protection and improvement of the water environment in the study area and related areas.

关键词： Xiang River Basin Water environmental carrying capacity ArcGIS TOPSIS logistic regression model Comprehensive evaluation

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Rolling Bearing Reliability Estimation Based on logistic regression model

Rolling Bearing Reliability Estimation Based on Logistic Reg...

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International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering

作者： Li, Hongkun Wang, Yinhu Dalian Univ Technol Sch Mech Engn Dalian Peoples R China

ISBN: (纸本)9781479910144

Rolling bearing (RB) has been broadly applied on mechanical systems. Its reliability is directly related to the performance of the whole mechanical system. RB reliability estimation technology is crucial for mechanical system. logistic regression model (LRM) is constructed for RB reliability estimation in this paper. Vibration data acquisition and feature extraction are carried on for. Based on feature extraction investigation, root mean square and wavelet entropy are used to construct characteristics vector. Therefore, bearing degradation state information is determined by vibration information. Reliability estimation model based on LRM is constructed to estimate bearing performance. By using LRM, it has good performance on reliability estimation. It can be concluded that LRM is beneficial for RB life prediction.

关键词： rolling bearing reliability estimation logistic regression model vibration feature extraction

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