417 research outputs found

    Determining Future Success of College Students

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    Many people invest a lot of money in order to go to college with the hope that they will eventually be rewarded with higher salaries. This paper attempts to determine what aspects of college are most important in determining the future income of students. In particular, this paper studies whether GPA is an important determinant of income as well as whether some majors are better investments than others after controlling for other factors. In addition, the effect of math and verbal ability on income and how they interact with different fields of study are examined. The data comes from the National Longitudinal Study of Youth database and OLS regressions are used. The regression results show that grades, natural ability, and major all significantly affect income

    Determining the Future Income of College Students

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    Many people invest a lot of money in order to go to college with the hope that they will eventually be rewarded with higher salaries. This paper attempts to determine what aspects of college are most important in determining the future income of students. In particular, this paper studies whether GPA is an important determinant of income as well as whether some majors are better investments than others after controlling for other factors. In addition, the effect of math and verbal ability on income and how they interact with different fields of study are studied. The data comes from the National Longitudinal Study of Youth database and ordinary least-squares regressions are used. The regressions show that grades, natural ability, and major all significantly affect income

    Substrate and Donor Specificity of Glycosyl Transferases

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    It has been shown that all selectins recognize the carbohydrate epitopes sialyl Lewisx and sialyl Lewisa. For the establishment of the structure-activity relationship, the efficient synthesis of these tetrasaccharides and derivatives is therefore of vital interest. The glycosyl transferase-mediated approach is summarized with emphasis on the use of modified acceptors and modified sugar-nucleotide donors. A survey of the involved enzymes: β(1-3) and β(1-4)galactosyl transferases, α(2-3)sialyl transferase, FucT III and FucT VI reveals that the enzymatic synthesis is highly efficient for the rapid preparation of sialyl Lewisx- and sialyl Lewisa-derivative

    Using Google Trends Data to Learn More About Survey Participation

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    As response rates continue to decline, the need to learn more about the survey participation process remains an important task for survey researchers. Search engine data may be one possible source for learning about what information some potential respondents are looking up about a survey when they are making a participation decision. In the present study, we explored the potential of search engine data for learning about survey participation and how it can inform survey design decisions. We drew on freely available Google Trends (GT) data to learn about the use of Google Search with respect to our case study: participation in the Family Research and Demographic Analysis (FReDA) panel survey. Our results showed that some potential respondents were using Google Search to gather information on the FReDA survey. We also showed that the additional data obtained via GT can help survey researchers to discover topics of interest to respondents and geographically stratified search patterns. Moreover, we introduced different approaches for obtaining data via GT, discussed the challenges that come with these data, and closed with practical recommendations on how survey researchers might utilize GT data to learn about survey participation.Da Response Rates in Umfragen immer weiter sinken, bleibt es eine wichtige Aufgabe für methodische Forschung, mehr über den Teilnahmeprozess zu lernen. Search Engine Data können eine mögliche Quelle sein, um herauszufinden, welche Informationen potenzielle Befragte über eine Umfrage suchen, wenn sie eine Teilnahmeentscheidung treffen. In der vorliegenden Studie untersuchten die Autor*innen das Potenzial von Suchmaschinendaten, um etwas über die Teilnahme an Umfragen zu erfahren und wie diese Daten in Entscheidungen über die Gestaltung von Umfragen einfließen können. Sie stützten sich auf frei verfügbare Daten von Google Trends (GT), um mehr über die Nutzung der Google-Suche in Bezug auf eine Fallstudie zu erfahren: die Teilnahme an der Panel-Umfrage Family Research and Demographic Analysis (FReDA). Die Ergebnisse zeigten, dass einige potenzielle Befragte die Google-Suche nutzten, um Informationen über die FReDA-Umfrage einzuholen. Die Autoren zeigen ebenfalls, dass die über GT gewonnenen zusätzlichen Daten den Umfrageforschern helfen können, Themen, die für die Befragten von Interesse sind, sowie geografisch geschichtete Suchmuster zu entdecken. Darüber hinaus stellen die Autoren verschiedene Ansätze für die Beschaffung von Daten über GT vor, erörtern die mit diesen Daten verbundenen Herausforderungen und geben abschließend praktische Empfehlungen, wie Umfrageforscher GT-Daten nutzen können, um mehr über die Teilnahme an ihren Umfragen zu erfahren

    Modeling of radiation damage in silicon solar cells

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    One MeV electron irradiation produces preponderantly isolated vacancy interstitial pairs. If neither of these defects is mobile, the concentration of each grows linearly with fluence. Annealing of damage depends on the nature of the damage. Vacancy interstitial pairs which are bound by an interaction such that they mutually annihilate rather than dissociate are termed close pairs; close pair recovery usually occurs at a lower temperature than the temperature at which long distance defect migration occurs. Annealing of the remaining frozen in damage occurs when a temperature is reached where the vacancy or interstitial is mobile; usually the interstitial is more mobile than the vacancy. The recovery occurs in two regimes which may be resoluable

    Teie tervis oleneb hammastest

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    Digiteeritud Euroopa Regionaalarengu Fondi rahastusel, projekti "Eesti teadus- ja õppekirjandus" (2014-2020.12.03.21-0848) raames.https://www.ester.ee/record=b1502789*es

    A Network Flow Model for the Analysis of Green Spaces in Urban Areas

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    Green spaces in urban areas offer great possibilities of recreation, provided that they are easily accessible. Therefore, an ideal city should offer large green spaces close to where its residents live. Although there are several measures for the assessment of urban green spaces, the existing measures usually focus either on the total size of green spaces or on their accessibility. Hence, in this paper, we present a new methodology for assessing green-space provision and accessibility in an integrated way. The core of our methodology is an algorithm based on linear programming that computes an optimal assignment between residential areas and green spaces. In a basic setting, it assigns a green space of a prescribed size exclusively to each resident such that the average distance between residents and assigned green spaces is minimized. We contribute a detailed presentation on how to engineer an assignment-based method such that it yields reasonable results (e.g., by considering distances in the road network) and becomes efficient enough for the analysis of large metropolitan areas (e.g., we were able to process an instance of Berlin with about 130000 polygons representing green spaces, 18000 polygons representing residential areas, and 6 million road segments). Furthermore, we show that the optimal assignments resulting from our method enable a subsequent analysis that reveals both interesting global properties of a city as well as spatial patterns. For example, our method allows us to identify neighborhoods with a shortage of green spaces, which will help spatial planners in their decision making

    Study of Rigidity and Flexibility in Preschool Children

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    Family Relations and Child Developmen
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