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Electricity dependent heating-cooling (H/C) system has increased rapidly to provide thermal comfort to the occupants. H/C is a major source of energy consumption in residential buildings around the world. Studies revealed that the thermal properties of building materials are converted into the same unit as thermal resistance (R) in the USA, Canada, The UK, Australia, and other countries. However, none of the previous studies have considered the adaptation of national insulation codes to reduce electricity cost and greenhouse gas (GHG) emissions with the correlations of energy consumption (Q) to thermal resistances (R) of the building envelop (A). Therefore, this study attempts to review the optimum energy consumption of a selected house due to H/C at different choices of national code standardized R values. Accurate envelop areas (A) of the selected house components are estimated by applying the Autodesk Revit Building Information Model (BIM) to use in the energy model. The case study critically evaluates the variation of electricity cost, GHG emissions, and selection of the optimized thermostat settings for energy savings in different climatic regions and seasons of a year. Different correlations are obtained using risk analysis software on energy consumptions with code recognized arrays of insulations. This sensitivity analysis result shows that the corelation coefficient of energy consumption with medium-low insulated building envelop (r = 0.44) is more significant than improved, maximum, medium-high, and minimum insulations (r = 0.14–0.29) which indicates the insulation range where more emphasis should be put to get an optimized solution. Thus the developed analytical framework supports inclusive decision-making by selecting appropriate kinds of insulation for the design of a sustainable house. Image 1 • Presents a framework for the use of rated thermal insulation (R) to show the variation of electricity cost and greenhouse gas emission for energy consumption of residential buildings in different climate zones to achieve a sustainable housing. • The study employs Fourier's law of thermal conductivity to estimate energy consumption considering building envelop of a base house and temperature deviations of different climatic zones. • The parameters specify the connections of Insulation Council of Australia and New Zealand (ICANZ) codes with the prices of Australian Energy Market Commission (AEMC) and the emission factors of National Greenhouse Accounts to sustainability. • Electricity prices with temperature variation in different climatic zones of Australia can assist to select suitable thermostat temperature for energy savings. • Sensitivity analysis shows where to emphasize for insulation considering building envelop areas. [ABSTRACT FROM AUTHOR]

Schizophrenia is a severe mental disorder affecting more than 21 million people worldwide. Scientific collaborations are required to research schizophrenia. However, there have been limited publications to date investigating scientific collaborations in schizophrenia research or reporting individual researchers' achievements(IRA) for authors. This study aimed to investigate the pattern of coauthor collaborations in schizophrenia research. We conducted a bibliometric study of international scientific publications on schizophrenia. About 57,964 abstracts were identified and downloaded from MEDLINE. All were examined using social network analysis (SNA) on February 20, 2018. The clusters of author nationalities, the authors, and the medical subject headings (MESH) terms were presented on Google Maps. A total of 36,934 articles met the inclusion criteria. The mean number of authors per article increased from 4.5 in 2008 to 6.4 in 2017. The proportion of published articles decreased in North America from 46.7% in 2008, to 32.3% in 2017. In contrast, the proportion of published articles in Asia increased from 14.5% in 1998 to 23.9% in 2017. Among the countries generating schizophrenia research the most prominent is China (corr. = 0.98), followed by India (corr. = 0.94), and France (corr. = 0.93). The representative of the biggest cluster is the author Michael F Green from the United States. The top three MESH terms are physiopathology, schizophrenic psychology, and complications. The scientific interest in schizophrenia remains significant. The application of bibliometric indicators of production is evident in the growth of scientific literature on the topic of schizophrenia. [ABSTRACT FROM AUTHOR]

Methyl tert -butyl ether (MtBE) has been used as a gasoline additive to increase the octane rating and reduce air pollution in the United States. Due to its high solubility in water, mobility, and low natural biodegradation potential in the subsurface environment, MtBE has become a significant groundwater contaminant. During the last decade, the public, scientific, and regulatory communities have gained a great deal of knowledge about MtBE behavior in the subsurface. This article presents a review of MtBE historical data and its trends over a four-year period at a number of gasoline impacted sites in Los Angeles, California. This article uses field data obtained in the last four years to compare the highest concentration of MtBE at a well with the current concentration at the same well, and with the current highest concentration at the site (may not be the same well as that with the highest historical MtBE value). Statistics of the MtBE data showed that the MtBE historical highest concentrations have decreased between one and two orders of magnitude over the last four years. This result may be explained by the active cleanup at the sites, natural attenuation, and a better management of MtBE. However, the correlation coefficient revealed that a site with a relatively high historical highest concentration (C HH ) may not have a relatively high current concentration (C C ) today at the same well, suggesting that once the source is removed, the center of the MtBE plume may migrate downgradient of groundwater flow. The correlation coefficient also showed that a site with the relatively high C HH relates to current highest concentrations (C CH ) at the site. [ABSTRACT FROM AUTHOR]

Abstract: Positive matrix factorization (PMF) was used to infer the sources of PM2.5 observed at four sites in Georgia and Alabama. One pair of urban and rural sites in each state is used to examine the regional and urban influence on PM2.5 concentrations in the Southeast. Eight factors were resolved for the two urban sites and seven factors were resolved for the two rural sites. Spatial correlations of factors were investigated using the square of correlation coefficient (R 2) calculated from the resolved G factors. Fourier transform was used to define the temporal characteristics of PM2.5 factors at these sites. Factors were normalized by using aerosol fine mass concentration data through multiple linear regression to obtain the quantitative factor contributions for each resolved factor. Common factors include: (1) secondary sulfate dominated by high concentrations of sulfate and ammonium with a strong seasonal variation peaking in summer; (2) nitrate and the associated ammonium with a seasonal maximum in winter; (3) “coal combustion/other” factor with presence of sulfate, EC, OC, and Se; (4) soil represented by Al, Ca, Fe, K, Si and Ti; and (5) wood smoke with the high concentrations of EC, OC and K. The motor vehicle factor with high concentrations of EC and OC and the presence of some soil dust components is found at the urban sites, but cannot be resolved for the two rural sites. Among the other factors, two similar industry factors are found at the two sites in each state. For the wood smoke factor, different seasonal trends are found between urban and rural sites, suggesting different wood burning patterns between urban and rural regions. For the industry factors, different seasonal variations are also found between urban and rural sites, suggesting that this factor may come from different sources or a common source may impact the two sites differently. Generally, sulfate, soil, and nitrate factors at the four sites showed similar chemical composition profiles and seasonal variation patterns reflecting the regional characteristics of these factors. These regional factors have predominantly low frequency variations while local factors such as coal combustion, motor vehicle, wood smoke, and industry factors have high frequency variations in addition to low frequency variations. [Copyright &y& Elsevier]