Self-determination, Success, and College Readiness of First Generation Students in A Higher Education Institution

The purpose of the study was to describe and compare if self-determination factors differed in first and non-first generation college students and success levels. Additionally, comparisons of college readiness levels were measured, and finally a measure of factors that contribute to college success based in first and second semester grade point averages were investigated using multiple linear regression analysis. Using a Self-Determination Theory framework of human motivation, helps identify a basic psychological need for autonomy as a central feature for understanding effective regulation and well-being (Moller, Ryan, & Deci, 2006). The target population in this study was 1,586 returning students of the 2008 freshmen cohort for the University of Texas Pan American in the Fall of 2010. About 10% or 187 of the returning students completed the Academic Motivation Scale survey. However, after additional information were collected only 146 subjects had usable data for all variables. A number of group comparisons were made based on college generation, success as measured by first and second semester college grade point averages, and college readiness as measured by ACT composite scores. The comparisons yielded no differences in motivation with the exception of intrinsic motivation, to experience stimulation, where successful students showed higher motivation than less successful students. This phenomenon was only apparent the second semester of college attendance, not the first semester. The overall descriptive analysis indicates that there are very few differences in intrinsic and extrinsic motivation in these groups of students. Multiple linear regression analyses revealed that external regulation (external motivation) contributed with 5.8 percent of the total variance in grade point average for the first semester, toward accomplishment (intrinsic motivation) contributed with 4.7 percent, and the ACT composite score contributed with an additional 3.9 percent of the total variance in first semester grade point average. The variables that explained the amount of variance in second semester grade point average were to know (internal motivation) with 2.7 percent, and external regulation (extrinsic motivation) with 3.6 percent

Laser-processed parchment paper for fabrication of chronic wound dressings with selective oxygenation

Chronic non-healing wounds (e.g., diabetic foot ulcers and bed sores) impact over 6.5 million Americans per year, costs in excess of $25 billion to treat on an annual basis, and are on the rise due to increasing levels of obesity and diabetes compounded by an aging population. A major inhibitor of healing is suboptimal oxygenation of the wound bed. Unlike acute injuries that receive sufficient oxygen via a functional blood vessel network, chronic wounds often suffer from the lack of a proper vascular network; thus being incapable of providing sufficient oxygen for tissue growth. Typical medical treatment of hypoxic chronic wounds typically employs hyperbaric oxygen therapy, which requires bulky equipment and often exposes large areas of the body to unnecessarily elevated oxygen concentrations that can damage healthy tissue. A more recent and convenient approach is topical oxygen therapy (TOT), in which the dressing itself can generate and deliver the required oxygen; various such systems exist commercially, but they are not economical, they do not provide selective delivery to only hypoxic regions, and their design does not permit further expansion for other wound-healing therapies on the same platform. A more practical implementation of such dressings would comprise an inexpensive dressing platform for adaptive oxygen therapy which is capable of delivering appropriate oxygen gas where and when it is needed. This work presents a low-cost alternative for continuous oxygen delivery comprising of an inexpensive, paper-based, biocompatible, flexible platform for locally generating and delivering oxygen to selected hypoxic regions. The platform takes advantage of recent developments in the fabrication of flexible microsystems including the incorporation of paper as a substrate and the use of inexpensive laser machining. The use of paper simultaneously provides structural strength, flexibility, mammalian cell biocompatibility, as well as selective filtering functionality, i.e., it allows for oxygen to pass through while preventing aqueous solutions to reach the tissue. The laser machining enables the precise definition of oxygen generating regions that match the hypoxic wound profile. Together these two technologies enable the development of a low-cost patch/wound-dressing with customized, wound-specific oxygen generating regions

Interregional Interdependence among Ecuadorian Provinces: An Input-Output Analysis

In this paper, we explore the structural characteristics of the interregional input-output system developed for Ecuador for the year 2007. As part of an ongoing project that aims to develop an interregional CGE model for the country, this database was developed under conditions of limited information. It provides the opportunity to better understand the spatial linkage structure associated with the national economy in the context of its 22 provinces, 15 sectors and 60 different products. This exploratory analysis is based on the description structural coefficients and the use of traditional input-output techniques. Finally, we further explore the spatial linkage structure by looking at the decomposition of final demand components. It is hoped that this exercise might result in a better appreciation of a broader set of dimensions that might improve our understanding of the integrated interregional economic system in Ecuador.

Using context to improve protein domain identification

<p>Abstract</p> <p>Background</p> <p>Identifying domains in protein sequences is an important step in protein structural and functional annotation. Existing domain recognition methods typically evaluate each domain prediction independently of the rest. However, the majority of proteins are multidomain, and pairwise domain co-occurrences are highly specific and non-transitive.</p> <p>Results</p> <p>Here, we demonstrate how to exploit domain co-occurrence to boost weak domain predictions that appear in previously observed combinations, while penalizing higher confidence domains if such combinations have never been observed. Our framework, Domain Prediction Using Context (dPUC), incorporates pairwise "context" scores between domains, along with traditional domain scores and thresholds, and improves domain prediction across a variety of organisms from bacteria to protozoa and metazoa. Among the genomes we tested, dPUC is most successful at improving predictions for the poorly-annotated malaria parasite <it>Plasmodium falciparum</it>, for which over 38% of the genome is currently unannotated. Our approach enables high-confidence annotations in this organism and the identification of orthologs to many core machinery proteins conserved in all eukaryotes, including those involved in ribosomal assembly and other RNA processing events, which surprisingly had not been previously known.</p> <p>Conclusions</p> <p>Overall, our results demonstrate that this new context-based approach will provide significant improvements in domain and function prediction, especially for poorly understood genomes for which the need for additional annotations is greatest. Source code for the algorithm is available under a GPL open source license at <url>http://compbio.cs.princeton.edu/dpuc/</url>. Pre-computed results for our test organisms and a web server are also available at that location.</p

Will FTAA Bring Income Convergence?

By the beginning of year 2006, the Free Trade Area of the Americas, FTAA, will be launched. Mixed expectations and concerns about its effects on the individual economies have grown in the area since this process started in December, 1994. This paper aims to discuss a particular expectation –or concern- which is: Will this liberalization of the Americas contribute to increase or to decrease the huge gap in per capita income between the industrialized economies of the North, -Canada and the U.S.- and the other thirty-two countries? Based on the analysis of empirical evidence on current trade areas in the region, we conclude that even in the case of equal trade, where the agreement manages to conciliate the interests of developed and less developed countries, income convergence will, probably, not be one of the outcomes of this liberalization. The lack of symmetry in an area which gathers countries at very different stages of development, an asymmetry much more pronounced in them FTAA because it includes the largest economy in the world, prevent us from expecting income convergence even if this trade area becomes a successful one.A comienzos del 2006 se espera el lanzamiento del ALCA. Muchas inquietudes existen en torno a los posibles efectos que la conformación de esta área de libre comercio tendrá sobre las economías de los países integrantes. Este artículo analiza una de estas inquietudes la cual se refiere a si esta integración de las Americas contribuirá a cerrar la brecha en el ingreso per capita de las naciones industrializadas del norte –Canadá y Estados Unidosy las otras treinta y dos naciones o, por el contrario, profundizará dicha brecha? Con base en la evidencia empírica de otras zonas de libre comercio de la región, se concluye que, aún en el caso de que en el tratado se logren conciliar los intereses de los países desarrollados y los no desarrollados para un comercio justo, la convergencia del ingreso per cápita no será, probablemente, uno de los resultados de esta integración. La asimetría existente en esta región, más aguda en el caso del ALCA por el hecho de que esta área comprende la más grande economía del mundo, impide esperar que se logre convergencia aunque el área resulte exitosa

Interregional input-ouptut system for Ecuador, 2007: methodology and results

In this paper, we explore the structural characteristics of the interregional input-output system developed for Ecuador for the year 2007. As part of an ongoing project that aims to develop an interregional CGE model for the country, this database was developed under conditions of limited information. It provides the opportunity to better understand the spatial linkage structure associated with the national economy in the context of its 22 provinces, 15 sectors and 60 different products. This exploratory analysis is based on the description of structural coefficients and the use of traditional input-output techniques. Finally, we further explore the spatial linkage structure by looking at the regional decomposition of final demand. It is hoped that this exercise might result in a better appreciation of a broader set of dimensions that might improve our understanding of the integrated interregional economic system in Ecuador.Interregional input-output model; Ecuador; spatial linkages

Will FTAA Bring Income Convergence?

By the beginning of year 2006, the Free Trade Area of the Americas, FTAA, will be launched. Mixed expectations and concerns about its effects on the individual economies have grown in the area since this process started in December, 1994. This paper aims to discuss a particular expectation –or concern- which is: Will this liberalization of the Americas contribute to increase or to decrease the huge gap in per capita income between the industrialized economies of the North, -Canada and the U.S.- and the other thirty-two countries? Based on the analysis of empirical evidence on current trade areas in the region, we conclude that even in the case of equal trade, where the agreement manages to conciliate the interests of developed and less developed countries, income convergence will, probably, not be one of the outcomes of this liberalization. The lack of symmetry in an area which gathers countries at very different stages of development, an asymmetry much more pronounced in them FTAA because it includes the largest economy in the world, prevent us from expecting income convergence even if this trade area becomes a successful on

Removing superfluous versions in polyvariant specialization of prolog programs.

Polyvariant specialization allows generating múltiple versions of a procedure, which can then be separately optimized for different uses. Since allowing a high degree of polyvariance often results in more optimized code, polyvariant specializers, such as most partial evaluators, can genérate a large number of versions. This can produce unnecessarily large residual programs. Also, large programs can be slower due to cache miss effects. A possible solution to this problem is to introduce a minimization step which identifies sets of equivalent versions, and replace all occurrences of such versions by a single one. In this work we present a unifying view of the problem of superfluous polyvariance. It includes both partial deduction and abstract múltiple specialization. As regards partial deduction, we extend existing approaches in several ways. First, previous work has dealt with puré logic programs and a very limited class of builtins. Herein we propose an extensión to traditional characteristic trees which can be used in the presence of calis to external predicates. This includes all builtins, librarles, other user modules, etc. Second, we propose the possibility of collapsing versions which are not strictly equivalent. This allows trading time for space and can be useful in the context of embedded and pervasive systems. This is done by residualizing certain computations for external predicates which would otherwise be performed at specialization time. Third, we provide an experimental evaluation of the potential gains achievable using minimization which leads to interesting conclusions

Prediction of time series using wavelet Gaussian process for wireless sensor networks

Articulo de investigacion idizado en JCR con factor de impacto 2.2The detection and transmission of a physical variable over time, by a node of a sensor network to its sink node, represents a significant communication overload and consequently one of the main energy consumption processes. In this article we present an algorithm for the prediction of time series, with which it is expected to reduce the energy consumption of a sensor network, by reducing the number of transmissions when reporting to the sink node only when the prediction of the sensed value differs in certain magnitude, to the actual sensed value. For this end, the proposed algorithm combines a wavelet multiresolution transform with robust prediction using Gaussian process. The data is processed in wavelet domain, taking advantage of the transform ability to capture geometric information and decomposition in more simple signals or subbands. Subsequently, the decomposed signal is approximated by Gaussian process one for each subband of the wavelet, in this manner the Gaussian process is given to learn a much simple signal. Once the process is trained, it is ready to make predictions. We compare our method with pure Gaussian process prediction showing that the proposed method reduces the prediction error and is improves large horizons predictions, thus reducing the energy consumption of the sensor network