Comparative analysis of environmental performance of an office building using BREEAM and GBL

With rapid economic growth and urban expansion in China, the Chinese building sector is now facing the huge challenge of balancing its energy demand and pollution. In order to minimize the environmental impact, the Ministry of Housing Urban-Rural Development (MOHURD) has set an ambitious energy reduction target requiring that 30% of all new constructions to be green by 2020. This paper presents comparative analysis of two environmental rating systems: the latest version of Chinese Green Building Label (GBL 2014) released by the MOHURD in order to promote the market transformation of green buildings and Building Research Establishment Environmental Assessment Method (BREEAM 2014), the widely recognised environmental assessment methodology in the global construction industry. To compare the two environment assessment standards, a public office building currently under construction in Fujian (China) has been used as a case-study to rate its environmental credentials using both BREEAM and GBL. Results have shown that although both standards use a similar methodology, they require different levels of input data and may result in different ratings for the same building

Utilization of the Arkansas Prescription Monitoring Program to combat prescription drug abuse

AbstractObjectiveThe Arkansas Prescription Monitoring Program (AR PMP) was implemented in 2013 to combat prescription drug abuse. All enrollees were invited to participate in a user survey available in February 2014, to identify makeup of users, utilization of the program, and changes made to health care practices after implementation of the program.MethodsOf the 3694 individual enrollees invited to participate, 1541 (41.7%) completed the survey. Data collected were analyzed to identify changes in health care practices by program frequency of use and user profession.ResultsMedical doctors, advanced practice nurses, and pharmacists are the professions who use the program most frequently. Daily AR PMP users are considerably more likely than infrequent users to be prompted to access the program by the involvement of a controlled substance (CS) prescription or by office/facility policy requirements. Increased frequency of use of the AR PMP results in positive impacts on CS prescribing and dispensing practices.ConclusionCompelling more users of the AR PMP to be prompted to access the program by the involvement of a CS prescription or by requirements per office/facility policy may increase frequency of use of the program and thereby changes in health care practices to combat prescription drug abuse

How Do Sociodemographics and Activity Participations Affect Activity-Travel? Comparative Study between Women and Men

Activity-travel behaviors of women and men are different because they have different social and household responsibilities. However, studies concerning gender differences are mainly limited in developed countries. This paper concentrates on gender role-based differences in activity-travel behavior in a typical developing country, namely, China. Using data from 3656 cases collected through surveys conducted in Shangyu, data processing, method choice, and descriptive analysis were conducted. Binary and ordered logistic regression models segmented by gender were developed to evaluate the mechanism through which individual sociodemographics, household characteristics, and activity participations affect the number of trip chain types and activities for women and men. The results show that women aged 30 to 50 perform less subsistence activities. However, the difference between the different age groups of men is not as significant. In addition, men with bicycles and electric bicycles have more subsistence and maintenance activities, whereas women do not have these attributes. Moreover, women with children under schooling age make more maintenance trip chains but less leisure trip chains and activities, whereas men are free from this influence. Furthermore, both women and men perform more subsistence activities if the duration increases, and men have less influences than women do

Subnetwork Estimation for Spatial Autoregressive Models in Large-scale Networks

Large-scale networks are commonly encountered in practice (e.g., Facebook and Twitter) by researchers. In order to study the network interaction between different nodes of large-scale networks, the spatial autoregressive (SAR) model has been popularly employed. Despite its popularity, the estimation of a SAR model on large-scale networks remains very challenging. On the one hand, due to policy limitations or high collection costs, it is often impossible for independent researchers to observe or collect all network information. On the other hand, even if the entire network is accessible, estimating the SAR model using the quasi-maximum likelihood estimator (QMLE) could be computationally infeasible due to its high computational cost. To address these challenges, we propose here a subnetwork estimation method based on QMLE for the SAR model. By using appropriate sampling methods, a subnetwork, consisting of a much-reduced number of nodes, can be constructed. Subsequently, the standard QMLE can be computed by treating the sampled subnetwork as if it were the entire network. This leads to a significant reduction in information collection and model computation costs, which increases the practical feasibility of the effort. Theoretically, we show that the subnetwork-based QMLE is consistent and asymptotically normal under appropriate regularity conditions. Extensive simulation studies, based on both simulated and real network structures, are presented