Maltreatment affected an estimated 794,000 children in the 50 States, the District of Columbia, and Puerto Rico in 2007 (United States Department of Health and Human Services [USDHHS], 2009). The purpose of this study was to examine the risk factors of young maternal age, parents' marital status, multiple birth, preterm birth, birth defects/disability, low economic status, and parental substance abuse related to suspected maltreatment of children 3 years of age or younger from the prospective of pediatric nurse practitioners (PNPs). A cross-sectional survey design, using the Tailored Design Method, was used in this study. A convenience sample consisting of the National Association of Pediatric Nurse Practitioners (NAPNAP) email registry was used for this study with a response rate of 11%. The respondents represented all regions of the United States. Seventy-nine percent of the PNP's (n=363) who completed the survey had suspected child abuse or neglect within the last year in a child three years of age or younger compared to 21% of PNPs (n=96) who did not suspect child maltreatment within the past year. The prevalence of suspected child maltreatment in the study population was 2.35%. According to the model examining child risk factors and abuse, the log of the odds of a child being abused was negatively related to preterm birth (p = .036) and birth defects/disability (p = .001). Multiple birth was positively related but not significant (p = .359). There were no statistically significant child risk factors found in the logistical regression for neglect (preterm birth, p = .180; multiple births, p = .938; birth defects/disabilities, p = .234). When examining the abuse and neglect groups together, the log of the odds of a child being abused and neglected was negatively related to birth defects/disabilities (p = .030). Preterm birth (p = .364) and multiple birth (p = .298) were positively related to the abuse and neglect group but were not significant. According to the model examining parental risk factors and abuse, the log of the odds of a child being abused due to a parent characteristic was negatively related to low economic status, with the proxy being WIC eligibility (p = .001) and a history of substance abuse (p = .031). The regression for abuse indicated a positive, yet insignificant, relationship with young maternal age (p = .129) and single marital status (p = .816). The logistic regression for neglect indicated a positive significant relationship with a substance abuse history (p = .012). The regression for neglect indicated positive but insignificant relationships for young maternal age (p = .693), marital status (p = .343), and WIC eligibility (p = .106). There were no statistically significant parental risk factors found in the logistical regression for abuse and neglect together (young maternal age, p = .263; marital status, p = .523; WIC eligibility, p = .131; substance abuse, p = .985). Findings indicated that child maltreatment is suspected by PNPs in primary care settings, and that PNPs recognize signs and symptoms of abuse and neglect.

In this study I analyze the Swedish parental benefit system focusing on a certain component, the basic level, and its effects on childbearing. The basic level consists of a fixed monetary amount given to parents. The compensation level was raised three times between 2002 and 2004, which would, according to economic theories, imply increased incentives for having children. I use longitudinal data of women in fertile age between 1993 and 2005. Applying a difference-in-differences model on comparison groups based on region of birth I conclude that the policy changes probably did not cause increased probabilities of having children.

Unibrands is a small company that has implemented a postponement strategy without knowing it. However, they have not implemented completely because they do not know the theories behind it. This report is an attempt to understand and analyze the problems of the implementation of postponement in the supply chain of Unibrands, in terms of examining the theoretical succeeds factors of postponement implementation in the case of Unibrands.The purpose is to determine what type of postponement strategy the supply chain use and what factors can hinder the use of postponement strategy in a SME fashion supply chain by applying an qualitative research approach. The collection of empirical data was through the interview guide approach in which we used meetings and telephone interviews with people representing Unibrands and their contact trading company. The results of this research can be concluded in few perspectives. Unibrands is imple-menting postponement in an improper format, with the results of several gaps in the supply chain related to the success factor in postponement. The request for the fully customization in colors and materials, the bottleneck of relationship developing which is caused by factory manager,  complicated procedures for sample testing, and lack of knowledge of different relationships in the supply chain. Postponement is never perfect, but for Unibrands some problems could very well hinder the efficiency in the supply chain. Solutions are proposed to solve the problems in chain. The proposals suggest re-lationship improvement and information sharing. In addition, culture adaptation by in-volving the right people in the right process.

This research investigated the association of street network connectivity differences across travel modes with travel behaviour – mode choice, distance traveled and number of trips. To date research on travel behaviour relationships with urban form has not developed empirical evidence on street designs as distinct networks for walking and driving. A street network having greater connectivity and continuity for the pedestrian mode of travel vis-à-vis the vehicular network, like the Fused Grid, will likely encourage more walking. This hypothesis was investigated using a quasi-experimental approach within a rational utility behavioural framework. Local travel behaviour is theorized to be affected by desire to access goods and services (broadly termed, ‘activities’) in the community where people live. Using inferential statistics, the research tested for relationships between measured street patterns and self-reported local travel by King County, WA households. The main variables were ratios (walking : driving) of network connectivity and density, in the vicinity of travel survey households. Demographics and household characteristics, as well as other behaviourally influential urban form factors (residential density, proximity of destinations, etc.), were included in regression models, allowing control for confounding factors. Findings suggest that street networks with connectivity that provides better routing for one mode of transportation over others encourage more travel by the favored mode. The regression model demonstrated that a change from a pure small-block grid to a modified grid (i.e. Fused Grid) can result in an 11.3% increase in odds of a home-based trip being walked. The modified street pattern like a Fused Grid is also associated with a 25.9% increase, over street patterns with equivalent route directness for walking and driving, in the odds a person will meet recommended levels of physical activity. Finally, the Fused Grid’s 10% increase in relative connectivity for pedestrians is associated with a 23% decrease in local vehicle travel distance (VMT), and its improved continuity is associated with increased walking trips and distance. Conclusions: Other factors being equal, residential street networks with either more direct routing for pedestrians or more pedestrian facilities relative to vehicular network are associated with improved odds of walking and reduced odds of driving.

In recent years, changes in government policies, supply and demand fundamentals and price patterns in the cotton market have led to several shifts in how producers market their cotton. This thesis examined producer cash marketing choices, including direct and indirect hedging, in four different periods since 2001. Special emphasis was placed on the 2010 season - a season characterized by historically high prices and volatility. Producer marketing behavior was modeled as a discrete choice between four different cash market outlets: forward contracting with a merchant, post-harvest cash contracting, contracting with a merchant pool and contracting with a cooperative pool. Hedging was characterized as a tool that was used in conjunction with one of the four discrete choices. This thesis employed multinomial logit estimation to determine the influence of factors on producers' choice of primary cash marketing decisions. Data were collected from a mail survey of the population of cotton growers in Texas, Oklahoma and Kansas. The most important determinants of cotton cash marketing choices were 1) prior participation in cooperative pools, beliefs about the value of pre-harvest pricing, beliefs about the performance of merchant pools, willingness to accept lower prices to reduce risk, and several socio-economic variables.

Time-rate analysis and time-rate-pressure analysis methods are available to estimate reserves and study flow performance of wells in unconventional gas reservoirs. However, these tools are often incorrectly used or the analysis can become difficult because of the complex nature of the reservoir system. Conventional methods (e.g., Arps' time-rate relations) are often used incorrectly to estimate reserves from such reservoirs. It was only recently that a serious study was conducted to outline the limitations of these relations and to set guidelines for their correct application. New time-rate relations, particularly the Duong and logistic growth model, were introduced to estimate reserves and forecast production from unconventional reservoirs. These new models are being used with limited understanding of their characteristics and limitations. Moreover, well performance analyses using analytical/semi-analytical solutions (time-rate-pressure) are often complicated from non-uniqueness that arises when estimating well/formation properties. In this work, we present a detailed study of the Duong model and logistic growth model to investigate the behaviors and limitations of these models when analyzing production data from unconventional reservoirs. We consider production data generated from numerical simulation cases and data obtained from unconventional gas reservoirs to study the quality of match to specific flow regimes and compare accuracy of the reserve estimates. We use the power-law exponential model (PLE), which has been shown to model transient, transition and boundary-dominated flow regimes reliably, as a benchmark to study performance of Duong and logistic growth models. Moreover, we use the "continuous EUR" approach to compare these models during reserve estimation. Finally, we develop four new time-rate relations, based on characteristics of the time-rate data on diagnostic plots. Using diagnostic plots we show that the new time-rate relations provide a quality match to the production data across all flow regimes, leading to a reliable reserve estimate. In a preliminary study, we integrated time-rate model parameters with fundamental reservoir properties (i.e., fracture conductivity (Fc) and 30 year EUR (EUR30yr)), by studying 15 numerical simulation cases to yield parametric correlations. We have demonstrated a methodology to integrate time-rate model parameters and reservoir properties. This method avoids the non-uniqueness issues often associated with model-based production data analysis. This study provides theoretical basis for further demonstration of the methodology using field cases.

No description available.

The objective of this thesis is to evaluate different models and methods for website classification. The websites are classified based on their functionality, in this case specifically whether they are forums, news sites or blogs. The analysis aims at solving a search engine problem, which means that it is interesting to know from which categories in a information search the results come. The data consists of two datasets, extracted from the web in January and April 2013. Together these data sets consist of approximately 40.000 observations, with each observation being the extracted text from the website. Approximately 7.000 new word variables were subsequently created from this text, as were variables based on Latent Dirichlet Allocation. One variable (the number of links) was created using the HTML-code for the web site. These data sets are used both in multinomial logistic regression with Lasso regularization, and to create a Naive Bayes classifier. The best classifier for the data material studied was achieved when using Lasso for all variables with multinomial logistic regression to reduce the number of variables. The  accuracy of this model is 99.70 %. When time dependency of the models is considered, using the first data to make the model and the second data for testing, the accuracy, however, is only 90.74 %. This indicates that the data is time dependent and that websites topics change over time.

The duration of children stay in a temporary foster care system needs to be minimal in order to ensure a stable and successful life. However, a time-consuming procedure of investigations is usually taken to decide whether they can reunite with their birth parents. Moreover, if the child fails to reunite with their family, another discharge decision needs to be assessed, leading to even longer time without a normal life. Based on the data from Adoption and Foster Care Analysis and Reporting System (AFCARS), this thesis derives a prediction model to discriminate the children with a tendency of unsuccessful reunification from the rest. An alternative discharge option can therefore be prepared concurrently for the foster youth with high non-reunification probability. The model is obtained by logistic regression and evaluated with receiver operating characteristic (ROC) curve.

The association between the risk of liver cancer and blood chemistry was investigated in a cohort study with 95,150 men and women from two counties in Sweden. In 1963-65, blood tests and physical measurements were undertaken. All individuals were then followed up until 2007, and a total of 312 were diagnosed with liver cancer. Using survival analysis and logistic regression, significant risk factors were identified. Stepwise Cox proportional hazards regression applied to a main effect model revealed that Glutamic Pyruvate Transaminase (GPT) and Thymol Turbidity (TYM) were the most significant risk factors (p<0.0001), followed by Protein-Bound Hexoses (HEX)  (p=0.002), sex (p=0.02), and Serum Iron (p= 0.03). Increasing the level of GPT expressed in U/L from normal (<21) to slightly elevated (21, 31) or substantially elevated (>31) raised the hazard of experiencing liver cancer by a factor of 1.45 and 4.09, respectively. In addition, GPT was found to be the most significant risk factor in almost all age groups among both men and women. However, there was no evidence that elevated GPT levels within the normal range (<21), influenced the risk of liver cancer. Additional subgroup analyses revealed that TYM was highly significant within the group with normal GPT, and a high level of HEX (≥134 mg/dl) increased the hazard 1.55 times in comparison with the lowest HEX group (<115 mg/dl). BMI was significant only in the male subgroup  (p<0.01) and, in the obesity group, the hazard of experiencing liver cancer was 1.99 times higher than in the normal BMI group. A significant three-way interaction between GPT, BMI and gender was present (p=0.05) with a robust significant two-way interaction between GPT and BMI (p<0.01) in the male subgroup.