Through secondary analyses of quantitative data obtained from the Transition and Postsecondary Programs for Students with Intellectual Disabilities (TPSID) National Coordinating Center database from the first cohort (2010-2015) of model demonstration sites in Florida, this study examined components of the postsecondary education programs for students with intellectual disabilities that are correlated with employment upon program exit. This study adds to the emergent knowledge base on inclusive higher education by identifying the programmatic components of the postsecondary education programs for students with intellectual disability most correlated with successful transition from college to employment. This information can be used to inform program development and refinement to foster employment upon exit, a worthy outcome that leads to greater quality of life. The academic access program component of inclusive coursework was found to have the strongest correlation with the post-school outcome of paid, competitive employment upon exit. This program component aligns with the established predictors of post-school success for students with disabilities (Mazzotti et al., 2016) and employment for people with intellectual disabilities (Southward & Kyzar, 2017). Areas of agreement are discussed as well as implications for a number of stakeholders.

The subject is financial analysis of STOCK Plzeň a.s. The aim of the thesis is propose the analysisi of ekonomical and financial situation of the company. The analysis refers to stage ang progress of the company between the years 2002 - 2006. Especially due to accounting reports.

The goal of my disertation is to evaluate financial situation of a cooperative KARKO during 1.1.2004-30.11.2009 through the use of financial indicators and predictor models.

The purpose of this study was to investigate predicting student success on one example of a "high stakes" test, the Texas Assessment of Academic Skills Exit Level Exam. Prediction algorithms for the mathematics, reading, and writing portions of the test were formulated using SPSS® statistical software. Student data available on all 440 students were input to logistic regression to build the algorithms. Approximately 80% of the students' results were predicted correctly by each algorithm. The data that were most predictive were the course related to the subject area of the test the student was taking, and the semester exam grade and semester average in the course related to the test. The standards of success or passing were making a 70% or higher on the mathematics, 88% or higher on the reading, and 76% or higher on the writing portion of the exam. The higher passing standards maintained a pass/fail dichotomy and simulate the standard on the new Texas Assessment of Knowledge and Skills Exit Level Exam. The use of the algorithms can assist school staff in identifying individual students, not just groups of students, who could benefit from some type of academic intervention.

Orientador: Aurelio Ribeiro Leite de Oliveira / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Matemática, Estatística e Computação Científica / Made available in DSpace on 2018-08-24T06:40:02Z (GMT). No. of bitstreams: 1 SunaguaSalgado_Porfirio_D.pdf: 2121161 bytes, checksum: 6d961fd2da8ded7cbc0733d9f190497a (MD5) Previous issue date: 2014 / Resumo: Uma abordagem do método preditor-corretor de Mehrotra para resolver problemas de programação linear de grande porte, que utiliza uma classe do precondicionador separador, para resolver sistemas lineares envolvidos por métodos iterativos precondicionados, necessita de uma base que é encontrada por um sofisticado processo de fatoração LU retangular da matriz de restrições. O precondicionador separador tem bom desempenho perto de uma solução ótima, onde as matrizes envolvidas ficam muito mal condicionadas. Neste trabalho, primeiro desenvolvemos o método preditor-corretor com o parâmetro de penalização a fim de reduzir o mau condicionamento da matriz de equações normais. O sucesso desta abordagem é garantido pela demonstração do teorema de convergência de penalização mista com o parâmetro de barreira. Em seguida, implementamos uma nova abordagem para encontrar uma base para o precondicionador separador mediante um processo de fatoração LU retangular padrão aplicada à matriz transposta de restrições escalada. Na maioria das vezes, esta base encontrada é melhor condicionada que a base do método de fatoração retangular anterior. Testes computacionais comprovam uma redução da média do número de iterações do método de gradientes conjugados precondicionado. Também, a eficácia e a robustez da nova abordagem é comprovada por conseguir uma melhor curva de desempenho / Abstract: The class of splitting preconditioners for the iterative solution of linear systems arising from Mehrotra's predictor-corrector method for large-scale linear programming problems needs to find a base by a sophisticated process based upon applying a rectangular LU factorization. The class of splitting preconditioners works better near a solution of the linear programming problems when the matrices are highly ill-conditioned. In this work, we develop the penalty parameter in Mehrotra's predictor-corrector method in order to reduce the ill-conditioning of the normal equations matrix. The success of this approach is guaranteed by the proof of the theorem of convergence of mixed penalty with the barrier parameter. In addition, we develop and implement a new approach to find a basis for the splitting preconditioner, based upon standard rectangular LU factorization with partial permutation of the transpose of the scaled linear programming constraint matrix. In most cases, the basis is better conditioned than the existing one. Computational tests show a reduction in the average number of iterations of the preconditioned conjugate gradient method. Also, the efficiency and robustness of the new approach is demonstrated by achieving better performance profile / Doutorado / Matematica Aplicada / Doutor em Matemática Aplicada

This article wants to show that it is fruitful for homiletics to continue to listen to what is offered from a biblical-theological perspective, especially when it comes to addressing a life of fear. After a short introduction, an overview is given of some important homiletical-exegetical notes, followed by the insights obtained from a focus group following a sermon on Mark 6:45–52. Finally, a number of homiletical insights received from listening to this text will follow.

Overlapping genes are adjacent genes that share a portion of their coding sequence. Such genes are often observed in the compact genomes of viruses, prokaryotes,and mitochondria. Overlapping genes are also seen in human and other mammalian genomes. Gene overlapping is a phenomenon to minimize genomic size and maximize encoding capacity. Overlapping genes produce different proteins. A major task in the post genomic era is the large-scale study of the structures and functions of proteins. Proteins play crucial roles in virtually all biological processes. In general it is assumed that 3-D structure determines the function of proteins, but many proteins or region of proteins may function in the absence of 3-D structure. The term disordered is used to describe these proteins. A large number of studies has shown that biological functions depend on both ordered and disordered proteins. Natively disordered regions are common and play essential roles in many proteins, especially, with regard to activities involved in signaling and regulation. The goal of this research was the analysis of the ordered and disordered tendencies of viral proteins encoded by overlapping genes. Our hypothesis is that, in a pair of proteins or protein regions encoded by overlapping genes, at least one of the pair is disordered (or unstructured). Our hypothesis is based on the observation that structural proteins require highly specific amino acid sequences, while unstructured (disordered) sequences are essentially unconstrained. Thus, given a structural protein and its associated mRNA sequence, any sequence derived from an overlapping reading frame seems highly unlikely to have a sequence pattern commensurate with a structural protein; on the other hand, a sequence pattern consistent with a disordered protein seems much more likely. We performed studies on the protein products of overlapping gene sequences, tested the hypothesis and addressed the following two questions: First do the proteins encoded by overlapping genes have opposite order-disorder content, that is, does the ordered part of one of the overlapping proteins correspond to a disordered part in the other overlapping protein? Second, does the encoded protein in the overlapping regions have more disordered amino acids than the non-overlapping regions? Using our database of overlapping viral genes and the protein predictor PONDR VL3, we predicted the order-disorder of amino acids in the sequence of 97 viral protein samples. An analysis of the results supported our hypothesis and indicated that the ordered amino acids are mostly associated with non-overlapping regions while disordered amino acids are more prevalent in overlapping regions. In the overlapping regions for 52 protein pairs, we showed that most of the amino acid pairs facing each other on the protein sequences had at least one disorder for most cases. Out of 52 pairs, there were 3 protein pairs where there were no disordered amino acids and 22 protein pairs where there were no ordered amino acids on either sequence. The fraction of ordered pairs in the pool of overlapping regions of 52 protein pairs was 0.28. The non-overlapping region of 97 proteins had predominantly ordered proteins. The fraction of ordered amino acids in the pool of non-overlapping regions was determined to be 0.77.

Blood trihalomethanes (THMs) and urinary haloacetic acids (HAAs) are the leading candidate biomarkers for disinfection byproduct (DBP) exposure. However, no studies have assessed the exposure profiles, temporal variability, and potential predictors of these biomarkers during pregnancy. Here we collected blood (n = 4304) and urine samples (n = 4165) from 1760 Chinese pregnant women during early, mid-, and late pregnancy, which were separately analyzed for 4 THMs and 2 HAAs. We calculated the intraclass correlation coefficients (ICCs) to assess the variability of these biomarkers and estimated their correlations with sociodemographic, water-use behavioral, dietary and sample collection factors using mixed models. The median concentrations of TCM, BDCM, Br-THMs [sum of BDCM, dibromochloromethane (DBCM), bromoform (TBM)], total THMs (TTHMs, sum of TCM and Br-THMs), DCAA and TCAA in the water distribution system were 4.2 μg/L, 1.7 μg/L, 2.9 μg/L, 7.1 μg/L, 3.4 μg/L and 8.2 μg/L, respectively. Chloroform (TCM), bromodichloromethane (BDCM), dichloroacetic acid (DCAA) and trichloroacetic acid (TCAA) were detected in > 75% of the biospecimens. Repeated measurements of blood TCM, BDCM, Br-THMs and TTHMs and urinary DCAA and TCAA uniformly exhibited high variability (ICCs = 0.01–0.13); the use of a single measurement to classify gestational average exposure resulted in a high degree of exposure misclassification. The sampling season was a strong predictor of all analyzed DBPs. Additionally, we detected a positive association of blood TCM and BDCM with household income, urinary DCAA with age, and urinary TCAA with tap water usage, education level and amount of tap water consumed. Inverse associations were found between blood BDCM and vegetable consumption, and between blood Br-THM and TTHM and time interval since the last bathing/showering. Afternoon samples had lower DCAA concentrations than did early morning samples. Our results indicate that blood THM and urinary HAA concentrations vary greatly over the course of pregnancy and are affected by sampling season, time of day of blood/urine collection, sociodemographic factors, recent water-use activities and dietary intake.

Social interactions between 153 mother-infant dyads in the laboratory were examined for associations with language and play preferences when infants were 14 months old. Later associations with reading skills, attention, and book reading were examined at the end of second grade. Mothers and infants were videotaped in a 20-minute laboratory observation at 14 months, and joint visual attention and social toy play were coded from the interactions. Language was assessed at 14 months using a standardized instrument, and mothers rated their own and their infants' preferences for specific types of play. A follow-up study, conducted at the end of second grade, assessed decoding and reading comprehension skills, attention and distractibility in the classroom and at home, and the frequency of mother-child book reading. A path model was constructed to examine predictive relations from infancy to second grade. The results suggest that early social interactions are both directly and indirectly related to language in infancy. Joint attention was associated with maternal responses during play and infant preferences for point and name games, which were in turn related to language development. Social interactions in infancy were negatively related to cognitive problems in second. There were small bivariate associations between infant language and play interactions with later reading skills. However, the strongest predictors of reading skills in second grade were children's abilities to sustain attention in relation to cognitive tasks in the classroom. The results suggest that early social interactions involving language and play may foster both language abilities and attention-sustaining abilities, which then influence the development of literacy skills.

The purpose of this study was to determine which variables contribute to high school dropout in a north central Mississippi school district’s only high school. The study population consisted of 301 students who enrolled as freshman in a north central Mississippi school district’s only high school during the 2002-2003 academic year and could have graduated from high school in 2006. Student data were obtained from the Mississippi Student Information System (MSIS) database, which contained all relevant information to this study. Data were collected on the following variables: gender, ethnicity, age, disciplinary infractions, whether or not a student was socially promoted, number of grades retained, number of absences, subject area testing scores, ninth grade retention, and special education enrollment. The findings of this study indicated there were relationships between the criterion variable, high school dropout, and the following predictor variables: age, ethnicity, whether or not a student was socially promoted, number of absences, number of grades retained, ninth grade. retention, and disciplinary infractions. The findings from this investigation also suggested that both socially promoted and students with high numbers of absences were more likely to drop out of high school than those who were not socially promoted, or had fewer absences.