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Aim The aim of this study was to investigate the most commonly used approaches to measure individual genome-wide heterozygosity (IGWH) and to investigate whether IGWH can be considered as a health risk factor or a protective factor in humans. Methods This study was based on two samples from isolated communities of Croatian Adriatic islands, with a total of 1,930 adult examinees from Islands of Vis (N=986) and Korcula (N=944). Examinees were genotyped with a total of 302,662 single nucleotide polymorphisms. Heterozygosity was estimated using five commonly calculated methods. Results Correlation coefficients between different heterozygosity methods were generally in the range of 0.7-0.8. A worsening in some phenotypic traits, including cholesterol and triglycerides as well as increased odds for osteoporosis and metabolic syndrome was recorded in cases of IGWH reduction. Nevertheless, in these cases heterozygosity explained a relatively low amount of variance, generally in range of 0.4-0.6% of total trait variance. Conclusion However, these results were significant in Vis Island sample, while in the replication sample, Korcula Island, most of the associations were not significant, possibly due to the overall lower amount of inbreeding and higher heterozygosity in Korcula Island sample. The results warrant further research in order to provide more information on the extent and importance of individual genome-wide heterozygosity, which might have an important role in communities which experience consanguinity on a greater scale. Two main shortcomings of the study include possible lack of power to detect inbreeding depression and the need to replicate the results in other populations.

Few investigators have used robust analytic methods to assess risk factors and outcomes for surgical site infections (SSIs) after craniotomy and craniectomy (CRANI) procedures. We performed a retrospective study among patients undergoing CRANI procedures between 2006 and 2010 at the University of Iowa Hospitals and Clinics (UIHC) to assess the effect of an intervention (e.g., limiting Gliadel wafer use among patients with malignant brain tumors) on the trend of SSI rates, to identify independent risk factors for SSIs, and to evaluate one-year postoperative patient outcomes associated with these SSIs. We abstracted demographic data and clinical data from medical records or from the UIHC's Health information Management System. We identified 104 patients with SSIs and selected 312 controls. Of SSIs, 88% were deep incisional or organ space infections, 70% were identified after patients were discharged from their initial hospitalizations, 32% were caused by Staphylococcus aureus alone or in combination with other organisms, and 27% were caused by Gram-negative organisms alone or in combination with other organisms. Significant independent risk factors for SSIs were: previous chemotherapy (odds ratio [OR], 10.0; 95% confidence interval [CI] 1.1, 92.1), preoperative length of stay ≥ 1 day (OR, 2.1; 95% CI 1.3, 3.5), preoperative serum glucose ≥ 100 mg/dL (OR, 1.7; 95% CI, 1.0, 3.0), Gliadel® wafer use (OR, 8.6; 95% CI 3.2, 23.1), and postoperative cerebrospinal fluid leak (OR, 4.0; 95% CI, 1.6, 10.3). Gliadel® wafer use was the strongest risk factor; however, limiting Gliadel® wafer use did not decrease SSI rate significantly among patients with brain tumors. Perioperative ventricular drains or lumbar drains were not independently associated with an increased risk of SSIs, but drains may have clinical significance. An SSI risk index that included the significant preoperative patient-related risk factors had a better predictive power than the National Healthcare Safety Network (NHSN) risk index. After adjusting for preoperative length of stay, age, comorbidity score, severity of illness score, the reason for the procedure, and procedure month, patients with SSIs were hospitalized longer postoperatively than were controls during their readmissions (2.3 days; P < 0.0001). After controlling for the same covariates and treating SSI as a time-varying factor, patients with SSIs were more likely than controls to: die (hazard ratio [HR], 3.3; 95% CI, 1.8, 5.8), be readmitted (HR, 4.1; 95% CI, 2.9, 5.8), and have reoperations (HR, 56.6; 95% CI, 38.1, 84.0). In conclusion, surgeons could predict patients' risk of SSIs based on their preoperative risk factors and surgeons could modify some processes of care to lower the SSI risk. Preventing SSIs after CRANI procedures could improve patient outcomes and decrease healthcare utilization.

The purpose of this study was to compare the health profiles of women seeking residential treatment for substance abuse with women in the community. These 2 data sets consisted of a total of 621 participants. An additional aim of the present study was to examine whether these health profiles differ between the monosubstance abusing and polysubstance abusing women within the treatment group. There were a total of 257 participants in this group. All analyses controlled for the effects of age, insurance, marital status, employment and race/ethnicity. Binary logistic regressions were used to compare between and within the specified groups on the following variables: asthma, dyslipidemia, diabetes, Hepatitis B vaccination, HIV testing, hypertension, Pap smear testing, mental health problems, overweight/obesity and smoking. A follow-up analyses examined whether differences in the variables could be explained by the effects of specific control variables. Results suggested that differences in four outcomes might be explained by a single or smaller number of specific control variables. The overall results revealed that age was one of the strongest predictors of differences between the treatment and community group. When we controlled for age, marital status, low socioeconomic status (insurance, employment) and ethnicity we found that only two variables were significantly different. Women in residential showed significantly more smoking and mental health symptoms than were found in the community sample. There were no significant differences in the health profiles of polysubstance substance abusing than were found in monosubstance abusing women. The findings of the present study indicate that women seeking treatment are individuals with similar health disorders and health maintaining behaviors as the general population of women. However, women seeking treatment have significant increases in mental health disorders and smoking. Older age was related to increases in the odds of having dyslipidemia, diabetes, hypertension, and decreases in the odds of being immunized for Hepatitis B, tested for HIV, and having a Pap test in the last year. Due to anticipated-age related disorders, screening for dyslipidemia, diabetes, and hypertension should be provided for older women seeking admission to treatment. Substance abuse treatment centers for women should provide for mental health services and offer smoking cessation.

Dental caries in the primary dentition is a risk factor for dental caries in the permanent dentition. The aim of this pilot project was to establish if high levels of dental caries very early in life translate into increased levels of dental caries in adulthood. Our objective was to determine the mean DMFT score of individuals with a history of severe early childhood caries (S-ECC) and compare it with the mean DMFT score of individuals who were caries-free in the primary dentition. The results of our analyses indicate that adults who experienced S-ECC manifest significantly higher levels of dental caries in their adulthood. The best predictor for dental caries in adulthood was caries experience in primary dentition. This preliminary study, the first of its kind, suggests that early childhood caries might indeed be associated with dental caries in adulthood.

Dental caries in the primary dentition is a risk factor for dental caries in the permanent dentition. The aim of this pilot project was to establish if high levels of dental caries very early in life translate into increased levels of dental caries in adulthood. Our objective was to determine the mean DMFT score of individuals with a history of severe early childhood caries (S-ECC) and compare it with the mean DMFT score of individuals who were caries-free in the primary dentition. The results of our analyses indicate that adults who experienced S-ECC manifest significantly higher levels of dental caries in their adulthood. The best predictor for dental caries in adulthood was caries experience in primary dentition. This preliminary study, the first of its kind, suggests that early childhood caries might indeed be associated with dental caries in adulthood.

Mobile robots are used on many areas and its demand on extreme terrain, hazardous area, or life-threatening place is increasing to reduce the loss of life. A good decision making capability is essential for successful navigation of autonomous robot and it affect finding the shortest or optimal path within given condition. The wavefront algorithm is simple to apply, yet yield an optimal path for a robot to follow in many different configurations. Although the path created using wavefront algorithm is an optimal in the sense that every node has the same cost, the result is not the best result in global perspective because of the algorithm is inconsiderate on the surrounding condition. To solve this issue and create the best result on global perspective, risk factor analysis method was implemented on the wavefront algorithm to improve the performance. In this work, the relationship between the wavefront algorithm and dynamic programming will be explained to show that the wavefront algorithm obeys the principle of optimality. The simulation result displays better performance on safety, while keeping the travelling distance minimum, if the risk factor is used on the wavefront algorithm and the robot on actual test behave accordingly. This work will contribute on decision making of mobile robot using risk factor method to create a most desirable and safe path. In addition to that, it will demonstrate how the risk factor method can be applied to the mobile robot navigation.

The objective of this study is to discover the sources of securities return in forecasting stock return from different sides of potential factors including fundamental and market information. We test currency sensitivity, earnings variability, earnings yield, growth, leverage, trading activity, momentum, size, value, volatility, capital spending discipline, free cash flow, efficiency, solvency, earnings quality, corporate finance policy and technical 17 factors basing on different factor dimensions in this study. We construct a Taiwan multi-factor model by using the most significant factors for universal stocks according to 0HMSCI Barra¡¦s Multiple-Factor Modeling process, and then apply market neutral investment to build portfolios for performance back-testing. As a result, the most significant top five factors in forecasting are respectively ¡§Volatility2,¡¨ ¡§Earnings Quality1,¡¨ ¡§Trading1,¡¨ ¡§Volatility1¡¨ and ¡§Growth1¡¨ factors. In addition, we find the most useless bottom four factors in forecasting are respectively ¡§Size1,¡¨ ¡§Earning Yield1,¡¨ ¡§Value1,¡¨ and ¡§Capital Spending1.¡¨ No matter which strategies we adopt to build the portfolio, the Sharpe ratios of back-testing performance are all higher than the Benchmark, and all bring stable and consistent performance. It actually proves that this model is robust.

This paper provides a credit risk quantification system for banks to estaminate the credit risk of loans to small and mediume nterprises(SMEs). As we know, the most difficult thing for banks to handle SME loans is whose financial reporting lacks transparency and no valuable reference. We use non-financial variables and employ the logisitic regression to develop the credit risk predict model. We concludet: first, when construct a SMEs credit rating system, non-financial factors should be seriously considered and adopted. Second, because of positioned different stage of firm life cycle, the credit rating model should be set up differently by different stage of firm. Third, SME loans should to make much of establishing ¡§relationship-based¡¨ in order to meet the various demands of risk management.

Behavior risk factors include health risk factors that increase a person's chances of developing a disease, such as having a high blood pressure, high blood cholesterol, tobacco smoke, physical inactivity, obesity or overweight, diabetes, poor nutrition, lack of sex education and car safety. They can be classified as: Background risk factors, such as age, sex, level of education and genetic compositions; Behavioral risk factors, such as smoking, unhealthy diet and physical inactivity; and Intermediate risk factors, such a serum cholesterol levels, diabetes, hypertension and obesity/overweight. This study describes a comparison and assessment of Behavior Risk Factor Surveillance Systems for the U.S., Canada, and Italy. The aim of this project is to assess and analyze the behavior surveillance systems of U.S., Canada and Italy, compare their strengths and weaknesses and provide recommendations that can be used as a guide for the design of new BRFS systems or the assessment of existing systems. The purpose of the assessment is to identify ways of improving the respective systems, and also to compare public health BRFS systems in the three different countries. The attributes used in the evaluation of the systems include simplicity, flexibility, data quality, acceptability, sensitivity, predictive value positive, representativeness, timeliness, and stability. The criteria and standards are based on the CDC Guidelines for Evaluating Surveillance Systems published on 1988 and updated on 2001.