检索结果-内蒙古大学图书馆

Predicting the risk of groundwater arsenic contamination in drinking water wells

JOURNAL OF HYDROLOGY 2018年 560卷 318-325页

作者： Cao, Hailong Xie, Xianjun Wang, Yanxin Pi, Kunfu Li, Junxia Zhan, Hongbin Liu, Peng China Univ Geosci State Key Lab Biogeol & Environm Geol Wuhan 430074 Hubei Peoples R China China Univ Geosci Sch Environm Studies Wuhan 430074 Hubei Peoples R China Texas A&M Univ Dept Geol & Geophys College Stn TX 77843 USA

Arsenic (As)-contaminated groundwater is a global concern with potential detrimental effects on the health of hundreds of millions of people worldwide. However, the extent of this problem may be more severe than anticipated, as many wells have not been tested and may contain unsafe-level of As. An optimized statistical regression model was developed to predict the probability of geogenic high As groundwater (As > 10 mu g/L) in this study. Easily obtained hydrogeochemical and geological parameters that are significantly related to As geochemical behaviors were selected as explanatory variables in the model. The results indicate that pH, Cl-, HCO3-, SO42-, and NO3- concentrations, stratigraphic information, and well depth are excellent predictors of As exposure in the Datong Basin, China. Predicted unsafe wells correspond well with the known distribution of high As groundwater in the Datong Basin. The successful application of a data set from Bangladesh also demonstrated the applicability and credibility of this proposed method. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Groundwater Arsenic contamination Risk prediction logistic regression model

来源：评论

学校读者我要写书评

暂无评论

Effects of mobile phone use on pedestrian crossing behavior and safety at unsignalized intersections

引用

CANADIAN JOURNAL OF CIVIL ENGINEERING 2019年第5期46卷 381-388页

作者： Zhang, Hualong Zhang, Cunbao Chen, Feng Wei, YuanYuan Wuhan Univ Technol Intelligent Transport Syst Res Ctr 1040 Heping Rd Wuhan 430063 Hubei Peoples R China

Using mobile phones can be a source of distraction for pedestrians when crossing streets, it is especially dangerous at unsignalized intersections. To investigate the effects of mobile phone use on pedestrian crossing behavior and safety at unsignalized intersections, we carried out a field survey at three selected locations in Wuhan, China. Then, the pedestrians' crossing behavior characteristics were statistically analyzed, and a logistic regression model was established to quantitatively analyze pedestrian safety. The results showed that 15.6% of pedestrians used mobile phones when crossing unsignalized intersections and 64.1% of them were young pedestrians. Pedestrians using mobile phones while crossing unsignalized intersections were at higher risk of accident, crossed more slowly, and were less likely to look at traffic status than those not using a mobile phone. Moreover, the probability of conflicts when watching the screen, talking, and listening to music are 2.704, 1.793, and 1.114 times greater, respectively, than those who do not use a mobile phone.

关键词： pedestrian safety pedestrian crossing behavior mobile phone use logistic regression model unsignalized intersections

来源：评论

学校读者我要写书评

暂无评论

Development and validation of a risk prediction model and prediction tools for post-thrombotic syndrome in patients with lower limb deep vein thrombosis

引用

INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS 2024年 187卷 105468-105468页

作者： Sun, Xiao-Xuan Ling, Hua Zhang, Lei Chen, Rui-Bin Zhong, An-qi Feng, Li-qun Yu, Ran Chen, Ying Liu, Jia-Qiu Nanchang Univ Affiliated Hosp 1 Jiangxi Med Coll Nursing Dept Nanchang 330000 Peoples R China Nanchang Univ Jiangxi Med Coll Sch Nursing Nanchang 330000 Peoples R China Nanchang Univ Jiangxi Med Coll Sch Clin Med 1 Nanchang 330000 Peoples R China Nanchang Univ Affiliated Hosp 1 Jiangxi Med Coll Informat Off Nanchang 330000 Peoples R China Jiangsu Univ Jingjiang Coll Sch Life Sci & Technol Jiangsu 212013 Zhenjiang Peoples R China Nanchang Univ Affiliated Hosp 1 Jiangxi Med Coll Dept Vasc Surg Nanchang 330000 Peoples R China Nanchang Univ Affiliated Hosp 1 Jiangxi Med Coll Cardiovasc Med Dept Nanchang 330000 Peoples R China

Purpose: Our research aims to compare the predictive performance of decision tree algorithms (DT) and logistic regression analysis (LR) in constructing models, and develop a Post-Thrombotic Syndrome (PTS) risk stratification tool. Methods: We retrospectively collected and analyzed relevant case information of 618 patients diagnosed with DVT from January 2012 to December 2021 in three different tertiary hospitals in Jiangxi Province as the modeling group. Additionally, we used the case information of 212 patients diagnosed with DVT from January 2022 to January 2023 in two tertiary hospitals in Hubei Province and Guangdong Province as the validation group. We extracted electronic medical record information including general patient data, medical history, laboratory test indicators, and treatment data for analysis. We established DT and LR models and compared their predictive performance using receiver operating characteristic (ROC) curves and confusion matrices. Internal and external validations were conducted. Additionally, we utilized LR to generate nomogram charts, calibration curves, and decision curves analysis (DCA) to assess its predictive accuracy. Results: Both DT and LR models indicate that Year, Residence, Cancer, Varicose Vein Operation History, DM, and Chronic VTE are risk factors for PTS occurrence. In internal validation, DT outperforms LR (0.962 vs 0.925, z = 3.379, P < 0.001). However, in external validation, there is no significant difference in the area under the ROC curve between the two models (0.963 vs 0.949, z = 0.412, P = 0.680). The validation results of calibration curves and DCA demonstrate that LR exhibits good predictive accuracy and clinical effectiveness. A web-based calculator software of nomogram (https://***/dynnomapp/) was utilized to visualize the logistic regression model. Conclusions: The combination of decision tree and logistic regression models, along with the web-based calculator software of nomogram, can

关键词： Post-thrombotic syndrome (PTS) Decision tree algorithm logistic regression model Predictive modeling Risk stratification

来源：评论

学校读者我要写书评

暂无评论

Identification of invasive vegetation using hyperspectral remote sensing in the California Delta ecosystem

引用

REMOTE SENSING OF ENVIRONMENT 2008年第11期112卷 4034-4047页

作者： Hestir, Erin L. Khanna, Shruti Andrew, Margaret E. Santos, Maria J. Viers, Joshua H. Greenberg, Jonathan A. Rajapakse, Sepalika S. Ustin, Susan L. Univ Calif Davis Dept Land Air & Water Resources Davis CA 95616 USA Univ Calif Davis Dept Environm Sci & Policy Davis CA 95616 USA

Estuaries are among the most invaded ecosystems on the planet. Such invasions have led in part, to the formation of a massive $1 billion restoration effort in California's Sacramento-San Joaquin River Delta. However, invasions of weeds into riparian, floodplain, and aquatic habitats threaten the success of restoration efforts within the watershed and jeopardize economic activities. The doctrine of early detection and rapid response to invasions has been adopted by land and water resource managers, and remote sensing is the logical tool of choice for identification and detection. However meteorological, physical, and biological heterogeneity in this large system present unique challenges to successfully detecting invasive weeds. We present three hyperspectral case studies which illustrate the challenges, and potential solutions, to mapping invasive weeds in wetland systems: 1) Perennial pepperweed was mapped over one portion of the Delta using a logistic regression model to predict weed occurrence. 2) Water hyacinth and 3) submerged aquatic vegetation (SAV). primarily composed of Brazilian waterweed, were mapped over the entire Delta using a binary decision tree that incorporated spectral mixture analysis (SMA), spectral angle mapping (SAM), band indexes, and continuum removal products. Perennial pepperweed detection was moderately successful;phenological stage influenced detection rates. Water hyacinth was mapped with modest accuracies, and SAV was mapped with high accuracies. Perennial pepperweed and water hyacinth both exhibited significant spectral variation related to plant phenology. Such variation must be accounted for in order to optimally map these species, and this was done for the water hyacinth case study. Submerged aquatic vegetation was not mapped to the species level due to complex non-linear mixing problems between the water column and its constituents, which was beyond the scope of the current study. We discuss our study in the context of providing g

关键词： Aquatic and wetland weeds logistic regression model Spectral mixture analysis Spectral Angle Mapper Hyperspectral HyMap Phenology

来源：评论

学校读者我要写书评

暂无评论

Prospectivity analysis of the Plutonic Marymia Greenstone Belt, Western Australia

引用

ORE GEOLOGY REVIEWS 2010年第3期38卷 208-218页

作者： Fallon, Matthew Porwal, Alok Guj, Pietro Barrick Australia Pacific Ltd Perth WA 6000 Australia Curtin Univ Technol Western Australian Sch Mines Ctr Explorat Targeting Perth WA 6845 Australia

The Plutonic Marymia Greenstone Belt is the sixth largest gold camp in Western Australia. Quantitative estimates of the residual endowment of this greenstone belt based on Zipf's Law indicate that the belt contains between 5.5 and 5.9 Moz of gold in undiscovered deposits larger than 0.1 Moz, including six undiscovered deposits ranging in size between 0.7 Moz and 0.4 Moz and another six undiscovered deposits ranging between 0.3 Moz and 0.2 Moz, in addition to several smaller deposits. GIS-based prospectivity analyses using weights-of-evidence and logistic regression models were undertaken to delineate prospective areas where these yet-to-be-discovered deposits could be spatially located. This knowledge will be critical in guiding future exploration programs in the Plutonic Marymia Greenstone Belt, Crown Copyright (c) 2010 Published by Elsevier B.V. All rights reserved.

关键词： Plutonic Marymia Greenstone Belt Quantitative resource estimation Zipf's law GIS-based prospectivity mapping Weights-of-evidence model logistic regression model

来源：评论

学校读者我要写书评

暂无评论

AnkPlex: algorithmic structure for refinement of near-native ankyrin-protein docking

引用

BMC BIOINFORMATICS 2017年第1期18卷 1-12页

作者： Wisitponchai, Tanchanok Shoombuatong, Watshara Lee, Vannajan Sanghiran Kitidee, Kuntida Tayapiwatana, Chatchai Chiang Mai Univ Fac Associated Med Sci Div Clin Immunol Dept Med Technol Chiang Mai 50200 Thailand Chiang Mai Univ Fac Associated Med Sci Ctr Biomol Therapy & Diagnost Chiang Mai 50200 Thailand Mahidol Univ Fac Med Technol Ctr Data Min & Biomed Informat Bangkok 10700 Thailand Commiss Higher Educ Thailand Ctr Excellence Phys Bangkok 10400 Thailand Univ Malaya Dept Chem Fac Sci Kuala Lumpur 50603 Malaysia Mahidol Univ Fac Med Technol Ctr Res & Innovat Bangkok 10700 Thailand

Background: Computational analysis of protein-protein interaction provided the crucial information to increase the binding affinity without a change in basic conformation. Several docking programs were used to predict the near-native poses of the protein-protein complex in 10 top-rankings. The universal criteria for discriminating the near-native pose are not available since there are several classes of recognition protein. Currently, the explicit criteria for identifying the near-native pose of ankyrin-protein complexes (APKs) have not been reported yet. Results: In this study, we established an ensemble computational model for discriminating the near-native docking pose of APKs named "AnkPlex". A dataset of APKs was generated from seven X-ray APKs, which consisted of 3 internal domains, using the reliable docking tool ZDOCK. The dataset was composed of 669 and 44,334 near-native and non-near-native poses, respectively, and it was used to generate eleven informative features. Subsequently, a re-scoring rank was generated by AnkPlex using a combination of a decision tree algorithm and logistic regression. AnkPlex achieved superior efficiency with >= 1 near-native complexes in the 10 top-rankings for nine X-ray complexes compared to ZDOCK, which only obtained six X-ray complexes. In addition, feature analysis demonstrated that the van der Waals feature was the dominant near-native pose out of the potential ankyrin-protein docking poses. Conclusion: The AnkPlex model achieved a success at predicting near-native docking poses and led to the discovery of informative characteristics that could further improve our understanding of the ankyrin-protein complex. Our computational study could be useful for predicting the near-native poses of binding proteins and desired targets, especially for ankyrin-protein complexes. The AnkPlex web server is freely accessible at http://***.

关键词： Ankyrin-protein complexes Near-native docking pose Machine learning methods Decision tree logistic regression model AnkPlex

来源：评论

学校读者我要写书评

暂无评论

Contribution of 'human induced fires' to forest and savanna land conversion dynamics in the Luki Biosphere Reserve landscape, western Democratic Republic of Congo

引用

INTERNATIONAL JOURNAL OF REMOTE SENSING 2022年第17期43卷 6406-6429页

作者： Cirezi, N. C. Bastin, J-f. Tshibasu, E. Lonpi, E. T. Chuma, G. B. Mugumaarhahama, Y. Sambieni, K. R. Karume, K. C. Lumbuenamo, R. S. Bogaert, J. Ecole Reg Post Univ Amenagement & Gest Integres F Dept Protected Areas Mnagement Kinshasa DEM REP CONGO Univ Evangel Afrique Fac Agr & Environm Sci Dept Environm & Land Resources Management Bukavu DEM REP CONGO Univ Liege Gembloux Agro Bio Tech TERRA Teaching & Res Ctr Gembloux Belgium Environm Management Inst Superieur Dev Rural ISDR KAZIBA Kaziba DEM REP CONGO World Wildlife Fund WWF Forest & Agr Program Kinshasa DEM REP CONGO Univ Liege Laplec UR SPHERES Liege Belgium Univ Kinshasa Dept Nat Resources Management Fac Agr Kinshasa DEM REP CONGO

Human-induced fire is one of the most important determinants of forest cover and change in tropical and subtropical regions of the world. Yet its impact on forest cover and forest cover change remains unclear, as fires in Africa generally do not spread over very large area. This is particularly the case in the Democratic Republic of Congo (DRC), a region of the world that is still poorly investigated. Here, we propose to study the effect of human-induced fire on land use and land cover change in a protected area of the DRC, i.e. the Luki Biosphere Reserve (LBR). We investigate tree cover changes in and around the reserve between 2002 and 2019 using Landsat 7 ETM+, Landsat 8 OLI/TIRS and MODIS MCD12Q1 images and quantify human induced fires using MODIS MCD64A1 images. The study combines land use and land cover (LULC) change detection analysis of four images, two acquired in 2002 and two acquired in 2019, with multi-temporal assessment of annual burnt area acquired between 2002 and 2019 from MODIS MCD64A1 to assess the role of fire in LULC changes and the sensitivity of different LULC types to fire. The results show a dynamic conversion of primary forest to secondary forest over about 16% of the area, the evolution of savanna to secondary forest over 9.6% (Landsat image) and the replacement of secondary forest by savanna over 8.1% (MODIS image) of the total area of Luki Reserve. Of the total area undergoing land use change, 34.1% (Landsat image) and 35.7% (MODIS image) were caused by fire, which however did not cause a significant LULC change. For the LULC types that experienced fire events, the least stable type was primary forest, which had the lowest stability rate (34.2% and 23% for Landsat and MODIS image analysis, respectively) compared to others. This result illustrates the importance of fire as a driver of primary forest loss and degradation in the region. Despite the high exposure of savannas to fire events, they were not significantly destabilized by fire (s

关键词： Land use and land cover forest fire slash and burn agriculture remote sensing MODIS Landsat spatial correlation logistic regression model Luki Biosphere Reserve

来源：评论

学校读者我要写书评

暂无评论

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

引用

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

来源：评论

学校读者我要写书评

暂无评论

Assessing poverty and livelihood vulnerability of the fishing communities in the context of pollution of the Churni River, India

引用

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 2022年第18期29卷 26575-26598页

作者： Sarkar, Biplab Islam, Aznarul Aliah Univ Dept Geog 17 Gorachand Rd Kolkata 700014 India

The present study exhibits a critical outlook on the poverty and livelihood vulnerability of the fisherman community in the context of persistent water pollution of the Churni River. The logistic regression model has identified eight factors influencing the poverty of the study area while the entropy weight method identifies the livelihood vulnerability of the fishermen. The livelihood vulnerability index of the upper stretch of the river is higher (0.65-0.67) compared to that of the lower stretch (0.46-0.57). The typical spatiality in poverty and livelihood vulnerability is triggered by the fragility of fishing livelihoods in the wake of lower concentrations of dissolved oxygen (DO), and higher BOD, COD, ammonia, nitrate and phosphate mainly due to industrial water pollution. For example, average DO ranges from 1.65 mg/l (upper stretch) to 2.50 mg/l (lower stretch) while the average BOD ranges from 5.44 mg/l (lower stretch) to 9.42 mg/l (upper stretch). This pollution induces acute ecological stress concerning declining fish diversity (from 41 to 16 fish species at the upper stretch and 41 to 23 fish species at the lower stretch during 1980-2018) as well as productivity of the existing fish species. Therefore, paralysed fishing economy and high dependency of the fishermen on the Churni River have forced them to revolve into the vicious cycle of poverty and enduring fragile livelihoods. Thus, the fishermen adopt few coping strategies like access to the nearby wetland for fishing, diversity in earning strategy and environmental movements against pollution to reduce the intensity of vulnerability. The present study would help the regional planners to frame the participatory plans for the sustainability of the riverine ecology and economy.

关键词： Water pollution Churni River Fishing economy Coping strategy Livelihood vulnerability index logistic regression model

来源：评论

学校读者我要写书评

暂无评论

Research on residents' selection on supplying urban forestry ecological service Empirical analysis on sampling survey in Harbin

引用

FOREST POLICY AND ECONOMICS 2012年 15卷 22-26页

作者： Li, Ying Meng, Yao NE Forestry Univ Sch Econ & Management Harbin 150040 Peoples R China Harbin Inst Technol Harbin 150001 Peoples R China

In order to improve the worsening air pollution problem in Chinese cities, Chinese government has been vigorously developing the building of urban forest under the policy of "government leading, market driving and residents participating". However, residents are still unwilling to join in city greening. Therefore, it is very necessary to find out some effective methods to encourage residents to participate in urban forest ecological service. The paper firstly presents 7 logistic regression models for residents' supplying forest ecological service, and then the probabilities of the residents' willingness and unwillingness to supply urban forest ecological service are calculated using the proposed models. The probability analysis reveals that the invested amounts of residents with different income are with great difference, and residents unwilling to pay are mainly those who are over 60 years old or who have monthly income of less than RMB 600. Finally, the paper proposes some valuable suggestions to encourage residents to supply urban forest ecological service. (C) 2011 Published by Elsevier B.V.

关键词： Urban forest Ecological service Contingent valuation method logistic regression model

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：