Multiple Linear Regression Models: Predicting the Texas Windstrom Insurance Association Claim Payout and Ratio Versus the Appraised Value of Commercial Buildings from Hurricae Ike

Following growing public awareness of the danger from hurricanes and tremendous demands for analysis of loss, many researchers have conducted studies to develop hurricane damage analysis methods. Although researchers have identified the significant indicators, there currently is no comprehensive research for identifying the relationship among the vulnerabilities, natural disasters, and economic losses associated with individual buildings. To address this lack of research, this study will identify vulnerabilities and hurricane indicators, develop metrics to measure the influence of economic losses from hurricanes, and visualize the spatial distribution of vulnerability to evaluate overall hurricane damage. This paper has utilized the Geographic Information System (GIS) to facilitate collecting and managing data, and has combined vulnerability factors to assess the financial losses suffered by Texas coastal counties. A multiple linear regression method has been applied to develop hurricane economic damage predicting models. To reflect the pecuniary loss, insured loss payment was used as the dependent variable to predict the actual financial damage and ratio. Geographical vulnerability indicators, built environment vulnerability indicators, and hurricane indicators were all used as independent variables. Accordingly, the models and findings may possibly provide vital references for government agencies, emergency planners, and insurance companies hoping to predict hurricane damage

Green benefits on educational buildings according to the LEED certification

Countries around the world are making efforts to develop and introduce green building certification systems to save energy and reduce greenhouse gas emissions. As a result of these efforts, green certification systems are rapidly spreading. Consistent with this, certification systems are also being developed and research related to various technologies and regulations is ongoing. However, most research focuses on residential and commercial buildings and there is still a lack of scientific research on educational facilities. To fill the gap and support the former studies, this research statistically studies the economic effects of green certification systems on educational facilities. For this purpose, the benefits, i.g., building price and maintenance & repair costs, were examined for universities in Canada that were admitted to the Canadian Educational Institution. As shown by the results of this study, Leadership in Energy and Environmental Design (LEED)-certified buildings cost 49.9% more to build and had 25.6% lower maintenance and repair costs than non-LEED certified buildings

Weekly Cycle of Lightning and Associated Patterns of Rainfall, Cloud, and Aerosols over Korea and Adjacent Oceans during Boreal Summer

In this study, we analyze the weekly cycle of lightning over Korea and adjacent oceans and associated variations of aerosols, clouds, precipitation, and atmospheric circulations, using aerosol optical depth (AOD) from the NASA Moderate resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging SpectroRadiometer (MISR), cloud properties from MODIS, precipitation and storm height from Tropical Rainfall Measuring Mission (TRMM) satellite, and lightning data from the Korean Lightning Detection Network (KLDN) during 9-year from 2002 to 2010. Lightning data was divided into three approximately equal areas, land area of Korea, and two adjacent oceans, Yellow Sea and South Sea. Preliminary results show that the number of lightning increases during the middle of the week over Yellow Sea. AOD data also shows moderately significant midweek increase at about the same time as lightning peaks. These results are consistent with the recent studies showing the invigoration of storms with more ice hydrometeors by aerosols, and subsequently wash out of aerosols by rainfall. Frequency of lightning strokes tend to peak at weekend in land area and over South Sea, indicating local weekly anomalous circulation between land and adjacent ocean. On the other hand, lightning frequency over Yellow Sea appears to have very strong weekly cycle with midweek peak on around Wednesday. It is speculated that the midweek peak of lightning over Yellow Sea was related with aerosol transport from adjacent land area. AOD data also suggests midweek peak over Yellow Sea, however, the weekly cycle of AOD was not statistically significant. Changes in weekly cycle of lightning from pre-monsoon to monsoon season, as well as associated clouds and circulation patterns are also discussed

A quantitative risk assessment development using risk indicators for predicting economic damages in construction sites of South Korea

The purpose of this study is to suggest a quantitative risk assessment approach for construction sites using risk indicators to predict economic damages. The frequency of damage in building construction has recently increased, and the associated costs have been increased as well. Although a request for a damage estimation model has been extended, the industry still lacks quantitative and comprehensive research that reveals the physical relationship between damage and risk indicators. To address that issue, we use an insurance company’s payouts from construction site claims in South Korea to reflect the real financial damage. We adopted a multiple regression method to define the risk indicators: geographic vulnerability, natural hazards, capability, and general project information. The results and findings of this research will be accepted as an essential guideline for developing a construction risk estimation model

Tonicity response element binding protein associated with neuronal cell death in the experimental diabetic retinopathy

AIM: To study the contribution of tonicity response element binding protein (TonEBP) in retinal ganglion cell (RGC) death of diabetic retinopathy (DR). METHODS: Diabetes was induced in C57BL/6 mice by five consecutive intraperitoneal injections of 55 mg/kg streptozotocin (STZ). Control mice received vehicle (phosphate -buffered saline). All mice were killed 2mo after injections, and the extent of cell death and the protein expression levels of TonEBP and aldose reductase (AR) were examined. RESULTS: The TonEBP and AR protein levels and the death of RGC were significantly increased in the retinas of diabetic mice compared with controls 2mo after the induction of diabetes. Terminal deoxynucleotidyl transferase (TdT) -mediated dUTP nick end labeling (TUNEL) -positive signals co -localized with TonEBP immunoreactive RGC. These changes were increased in the diabetic retinas compared with controls. CONCLUSION: The present data show that AR and TonEBP are upregulated in the DR and TonEBP may contribute to apoptosis of RGC in the DR.close2

Analysis of plant construction accidents and loss estimation using insurance loss records

There are many risks and uncertainties in plant construction projects, because of their complexity, difficulty in loss prediction and size of construction being large. The risk management of plant construction projects should not be relied solely on experiences and intuition of the contractors or the construction managers as it has been in the past. Therefore, a new quantitative and empirical risk analysis is required, in order for the development of a risk assessment using risk indicators for the plant construction projects. This research used the insurance payout record from a global insurance company to reflect the actual quantitative loss in the risk assessment model for plant construction project. The researchers adopted the geographic information as well as construction information (construction phase and commissioning phase, schedule rate, total duration), as the independent variables, which found to be statistically significant in the analysis in this study. It was found that the relationship between damage ratio and the valid variables was statistically significant, and thus, the damage model is also statistically significant. This research suggests that the regression model containing such valid independent variables could be beneficial in terms of providing foundational guidelines for the plant construction project risk analysis