To describe the empirical data of collaboration networks, several evolving mechanisms have been proposed, which usually introduce different dynamics factors controlling the network growth. These models can reasonably ...To describe the empirical data of collaboration networks, several evolving mechanisms have been proposed, which usually introduce different dynamics factors controlling the network growth. These models can reasonably reproduce the empirical degree distributions for a number of we11-studied real-world collaboration networks. On the basis of the previous studies, in this work we propose a collaboration network model in which the network growth is simultaneously controlled by three factors, including partial preferential attachment, partial random attachment and network growth speed. By using a rate equation method, we obtain an analytical formula for the act degree distribution. We discuss the dependence of the act degree distribution on these different dynamics factors. By fitting to the empirical data of two typical collaboration networks, we can extract the respective contributions of these dynamics factors to the evolution of each networks.展开更多
Food is one of the biggest industries in developed and underdeveloped countries. Supply chain sustainability is essential in established and emerging economies because of the rising acceptance of cost-based outsourcin...Food is one of the biggest industries in developed and underdeveloped countries. Supply chain sustainability is essential in established and emerging economies because of the rising acceptance of cost-based outsourcing and the growing technological, social, and environmental concerns. The food business faces serious sustainability and growth challenges in developing countries. A comprehensive analysis of the critical success factors (CSFs) influencing the performance outcome and the sustainable supply chain management (SSCM) process. A theoretical framework is established to explain how they are used to examine the organizational aspect of the food supply chain life cycle analysis. This study examined the CSFs and revealed the relationships between them using a methodology that included a review of literature, interpretative structural modeling (ISM), and cross-impact matrix multiplication applied in classification (MICMAC) tool analysis of soil liquefaction factors. The findings of this research demonstrate that the quality and safety of food are important factors and have a direct effect on other factors. To make sustainable food supply chain management more adequate, legislators, managers, and experts need to pay attention to this factor. In this work. It also shows that companies aiming to create a sustainable business model must make sustainability a fundamental tenet of their organization. Practitioners and managers may devise effective long-term plans for establishing a sustainable food supply chain utilizing the recommended methodology.展开更多
Before-and-after methods have been effectively used in the road safety studies to estimate Crash Modification Factors (CMFs) of individual treatments as well as the multiple treatments on roadways. Since the common pr...Before-and-after methods have been effectively used in the road safety studies to estimate Crash Modification Factors (CMFs) of individual treatments as well as the multiple treatments on roadways. Since the common practice is to apply multiple treatments on road segments, it is important to have a method to estimate CMFs of individual treatment so that the effect of each treatment towards improving the road safety can be identified. Even though there are methods introduced by researchers to combine multiple CMFs or to isolate the safety effectiveness of individual treatment from CMFs developed for multiple treatments, those methods have to be tested before using them. This study considered two multiple treatments namely 1) Safety edge with lane widening 2) Adding 2 ft paved shoulders with shoulder rumble strips and/or asphalt resurfacing. The objectives of this research are to propose a regression-based method to estimate individual CMFs estimate CMFs using before-and-after Empirical Bayes method and compare the results. The results showed that having large sample size gives accurate predictions with smaller standard error and p-values of the considered treatments. Also, results obtained from regression method are similar to the EB method even though the values are not exactly the same. Finally, it was seen that the safety edge treatment reduces crashes by 15% - 25% and adding 2 ft shoulders with rumble strips reduces crashes by 25% - 49%.展开更多
Different modification methods and software programs were developed to obtain accurate local geoid models in the past two decades.The quantitative effect of the main factors on the accuracy of local geoid modeling is ...Different modification methods and software programs were developed to obtain accurate local geoid models in the past two decades.The quantitative effect of the main factors on the accuracy of local geoid modeling is still ambiguous and has not been clearly diagnosed yet.This study presents efforts to find the most influential factors on the accuracy of the local geoid model,as well as the amount of each factor’s effect quantitatively.The methodology covers extracting the quantitative characteristics of 16 articles regarding local geoid models of different countries.The Statistical Package of Social Sciences(SPSS)software formulated a strong multiple regression model of correlation coefficient r = 0.999 with a high significance coefficient of determination R^2 = 0.997 and adjusted R^2 = 0,98 for the required effective factors.Then,factor analysis is utilized to extract the dominant factors which include:accuracy of gravity data(40%),the density of gravity data(25%)(total gravity factors is 65%),the Digital Elevation Model(DEM)resolution(16%),the accuracy of GPS/leveling points(10%)and the area of the terrain of the country/state under the study(9%).These results of this study will assist in developing more accurate local geoid models.展开更多
The distribution and the affecting factors of the artificial oasis and inartificial oasis have become a serious and widespread problem in arid lands. Understanding its controlling factors is vital for environmental go...The distribution and the affecting factors of the artificial oasis and inartificial oasis have become a serious and widespread problem in arid lands. Understanding its controlling factors is vital for environmental governance, improvement, and optimization. The study aimed to identify the crucial factors affecting the distribution of artificial oasis and inartificial oasis in arid land through the NDTG (the union of deep learning method, the modified a three-band maximal gradient method, Geodetector method) Model. Environmental factors include meteorological factors, chemical compositions, salinities, groundwater depth and time-series of Landsat images. The results show that Salinity factor was the dominant factor which explained 32.95% of the spatial variation of the artificial oasis distribution. Nonlinear enhancements were observed for the interactions between salt content and Evaporation (q = 0.93), salt content and Precipitation (q = 0.78). It indicated that Meteorological factors, and Salinity were the main factors determining the spatial pattern of the artificial oasis distribution. Salt, precipitation, evaporation, Mg, Cl, Na explained 37%, 26%, 25%, 24%, 23%, 20% of the spatial pattern of the inartificial oasis in arid lands, respectively. The results indicated that salinity, meteorological factors and chemical composition were the main factors determining the spatial distribution of inartificial oasis in arid lands. Moreover, the NDTG Model provided evidence to explore the factors controlling spatial patterns of the distribution of artificial oasis and inartificial oasis in arid lands.展开更多
目的探讨老年重症脑卒中患者发生多器官功能障碍综合征(multiple organ dysfunction syndrome,MODS)的危险因素。方法前瞻性选择2020年1月至2022年12月广东医科大学附属医院收治的老年重症脑卒中患者112例。根据入院后14 d内多器官功能...目的探讨老年重症脑卒中患者发生多器官功能障碍综合征(multiple organ dysfunction syndrome,MODS)的危险因素。方法前瞻性选择2020年1月至2022年12月广东医科大学附属医院收治的老年重症脑卒中患者112例。根据入院后14 d内多器官功能评分系统分为MODS组38例,非MODS组74例。根据最终预后又分为生存组33例和死亡组79例。收集患者一般临床资料、急性生理学与慢性健康状况评估Ⅱ(acute physiology and chronic health evaluation,APACHEⅡ)评分、格拉斯哥昏迷评分(Glasgow coma scale,GCS)和头颅影像学参数。采用logistic回归分析MODS发生的危险因素。结果MODS组脑卒中/脑出血、慢性阻塞性肺疾病、冠心病、吸烟、美国国立卫生研究院卒中量表(National Institute of Health Stroke Scale,NIHSS)评分、APACHEⅡ评分、多支血管病变、尿路感染、静脉血栓、出血、癫痫、心肌梗死、急性期机械通气、渗透疗法和住院病死率明显高于非MODS组,GCS明显低于非MODS组,差异有统计学意义(P<0.05,P<0.01)。二元logistic回归分析显示,NIHSS评分、APACHEⅡ评分及多支血管病变是MODS发生的独立危险因素(OR=1.124,95%CI:1.121~1.163,P=0.015;OR=1.265,95%CI:1.296~1.426,P=0.001;OR=2.532,95%CI:1.126~5.013,P=0.026)。死亡组MODS评分、APACHEⅡ评分明显高于生存组,差异有统计学意义(P<0.05)。结论老年重症脑卒中患者急性期易发生MODS。展开更多
基金Supported by the National Natural Science Foundation of China under Grant Nos 11305139 and 11147178
文摘To describe the empirical data of collaboration networks, several evolving mechanisms have been proposed, which usually introduce different dynamics factors controlling the network growth. These models can reasonably reproduce the empirical degree distributions for a number of we11-studied real-world collaboration networks. On the basis of the previous studies, in this work we propose a collaboration network model in which the network growth is simultaneously controlled by three factors, including partial preferential attachment, partial random attachment and network growth speed. By using a rate equation method, we obtain an analytical formula for the act degree distribution. We discuss the dependence of the act degree distribution on these different dynamics factors. By fitting to the empirical data of two typical collaboration networks, we can extract the respective contributions of these dynamics factors to the evolution of each networks.
文摘Food is one of the biggest industries in developed and underdeveloped countries. Supply chain sustainability is essential in established and emerging economies because of the rising acceptance of cost-based outsourcing and the growing technological, social, and environmental concerns. The food business faces serious sustainability and growth challenges in developing countries. A comprehensive analysis of the critical success factors (CSFs) influencing the performance outcome and the sustainable supply chain management (SSCM) process. A theoretical framework is established to explain how they are used to examine the organizational aspect of the food supply chain life cycle analysis. This study examined the CSFs and revealed the relationships between them using a methodology that included a review of literature, interpretative structural modeling (ISM), and cross-impact matrix multiplication applied in classification (MICMAC) tool analysis of soil liquefaction factors. The findings of this research demonstrate that the quality and safety of food are important factors and have a direct effect on other factors. To make sustainable food supply chain management more adequate, legislators, managers, and experts need to pay attention to this factor. In this work. It also shows that companies aiming to create a sustainable business model must make sustainability a fundamental tenet of their organization. Practitioners and managers may devise effective long-term plans for establishing a sustainable food supply chain utilizing the recommended methodology.
文摘Before-and-after methods have been effectively used in the road safety studies to estimate Crash Modification Factors (CMFs) of individual treatments as well as the multiple treatments on roadways. Since the common practice is to apply multiple treatments on road segments, it is important to have a method to estimate CMFs of individual treatment so that the effect of each treatment towards improving the road safety can be identified. Even though there are methods introduced by researchers to combine multiple CMFs or to isolate the safety effectiveness of individual treatment from CMFs developed for multiple treatments, those methods have to be tested before using them. This study considered two multiple treatments namely 1) Safety edge with lane widening 2) Adding 2 ft paved shoulders with shoulder rumble strips and/or asphalt resurfacing. The objectives of this research are to propose a regression-based method to estimate individual CMFs estimate CMFs using before-and-after Empirical Bayes method and compare the results. The results showed that having large sample size gives accurate predictions with smaller standard error and p-values of the considered treatments. Also, results obtained from regression method are similar to the EB method even though the values are not exactly the same. Finally, it was seen that the safety edge treatment reduces crashes by 15% - 25% and adding 2 ft shoulders with rumble strips reduces crashes by 25% - 49%.
文摘Different modification methods and software programs were developed to obtain accurate local geoid models in the past two decades.The quantitative effect of the main factors on the accuracy of local geoid modeling is still ambiguous and has not been clearly diagnosed yet.This study presents efforts to find the most influential factors on the accuracy of the local geoid model,as well as the amount of each factor’s effect quantitatively.The methodology covers extracting the quantitative characteristics of 16 articles regarding local geoid models of different countries.The Statistical Package of Social Sciences(SPSS)software formulated a strong multiple regression model of correlation coefficient r = 0.999 with a high significance coefficient of determination R^2 = 0.997 and adjusted R^2 = 0,98 for the required effective factors.Then,factor analysis is utilized to extract the dominant factors which include:accuracy of gravity data(40%),the density of gravity data(25%)(total gravity factors is 65%),the Digital Elevation Model(DEM)resolution(16%),the accuracy of GPS/leveling points(10%)and the area of the terrain of the country/state under the study(9%).These results of this study will assist in developing more accurate local geoid models.
文摘The distribution and the affecting factors of the artificial oasis and inartificial oasis have become a serious and widespread problem in arid lands. Understanding its controlling factors is vital for environmental governance, improvement, and optimization. The study aimed to identify the crucial factors affecting the distribution of artificial oasis and inartificial oasis in arid land through the NDTG (the union of deep learning method, the modified a three-band maximal gradient method, Geodetector method) Model. Environmental factors include meteorological factors, chemical compositions, salinities, groundwater depth and time-series of Landsat images. The results show that Salinity factor was the dominant factor which explained 32.95% of the spatial variation of the artificial oasis distribution. Nonlinear enhancements were observed for the interactions between salt content and Evaporation (q = 0.93), salt content and Precipitation (q = 0.78). It indicated that Meteorological factors, and Salinity were the main factors determining the spatial pattern of the artificial oasis distribution. Salt, precipitation, evaporation, Mg, Cl, Na explained 37%, 26%, 25%, 24%, 23%, 20% of the spatial pattern of the inartificial oasis in arid lands, respectively. The results indicated that salinity, meteorological factors and chemical composition were the main factors determining the spatial distribution of inartificial oasis in arid lands. Moreover, the NDTG Model provided evidence to explore the factors controlling spatial patterns of the distribution of artificial oasis and inartificial oasis in arid lands.
文摘目的探讨老年重症脑卒中患者发生多器官功能障碍综合征(multiple organ dysfunction syndrome,MODS)的危险因素。方法前瞻性选择2020年1月至2022年12月广东医科大学附属医院收治的老年重症脑卒中患者112例。根据入院后14 d内多器官功能评分系统分为MODS组38例,非MODS组74例。根据最终预后又分为生存组33例和死亡组79例。收集患者一般临床资料、急性生理学与慢性健康状况评估Ⅱ(acute physiology and chronic health evaluation,APACHEⅡ)评分、格拉斯哥昏迷评分(Glasgow coma scale,GCS)和头颅影像学参数。采用logistic回归分析MODS发生的危险因素。结果MODS组脑卒中/脑出血、慢性阻塞性肺疾病、冠心病、吸烟、美国国立卫生研究院卒中量表(National Institute of Health Stroke Scale,NIHSS)评分、APACHEⅡ评分、多支血管病变、尿路感染、静脉血栓、出血、癫痫、心肌梗死、急性期机械通气、渗透疗法和住院病死率明显高于非MODS组,GCS明显低于非MODS组,差异有统计学意义(P<0.05,P<0.01)。二元logistic回归分析显示,NIHSS评分、APACHEⅡ评分及多支血管病变是MODS发生的独立危险因素(OR=1.124,95%CI:1.121~1.163,P=0.015;OR=1.265,95%CI:1.296~1.426,P=0.001;OR=2.532,95%CI:1.126~5.013,P=0.026)。死亡组MODS评分、APACHEⅡ评分明显高于生存组,差异有统计学意义(P<0.05)。结论老年重症脑卒中患者急性期易发生MODS。
