Информационная система учета и анализа проектной деятельности студента

Объектом исследования является процесс учета и анализа проектной деятельности студента. Цель работы – исследование, проектирование и разработка информационной системы учета и анализа проектной деятельности студента В результате разработана информационная система учета и анализа проектной деятельности студента со следующим функционалом: формирование проектной составляющей учебного плана, учет проектной деятельности студента, контроль проектной деятельности студента, анализ проектной деятельности студента.The object of study is the process of accounting and analysis of the student's project activities. The purpose of the work - research, design and development of an information system for accounting and analysis of student project activities As a result, an information system was developed for accounting and analyzing student design activities with the following functionality: forming the design component of the curriculum, accounting for student design activities, monitoring student design activities, and analyzing student design activities

Simple Models For Complex Biomembranes

Biomembranen versteht man als komplexe zweidimensionale Fluide, die aus Proteinen und Lipiden bestehen. In dieser Arbeit werden möglichst einfache molekulare Modelle zur Beschreibungder thermodynamischen Eigenschaften von Biomembranen entwickelt, angewendet und diskutiert. Die Modelle geben Aufschluss über laterale Strukturen und charakterisieren diese als Cluster oder Domänen ("Rafts"). Den Ausgangspunkt bildet ein Gittergas (Ising-Modell) mit temperaturabhängigem Feld zur Beschreibung der Zustandsänderungen der Lipide in einer einzelnen flachen Membran. Die Proteine werden als zusätzliche Komponenten des Gitters in das Modell integriert.Die wesentlichen Aspekte der Untersuchung bestehen erstens in der Unterscheidung von peripheren und integralen Komponenten in einem Mehrschicht-Modell und zweitens in der Charakterisierung von weichen ausgedehnten Komponenten.Mittlere-Feld-Approximation inklusive Nachbarschafts-Korrelationen (Cluster-Variationsverfahren) ausreichend beschrieben werden. Das Modell der Lipidmembran mit ausgedehnten Adsorbaten wird einerseits analytisch auf ein effektives Lipidsystem mit Mehrteilchen-Kopplung abgebildet und andererseits durch Monte-Carlo-Simulation auf ein Proteinsystem mit effektiver Paar-Wechselwirkung.Beide Ansätze zeigen gegenüber der Wechselwirkung im Ausgangsmodell eine neue Kooperativität. Tatsächlich kann in Simulationen eine Entmischung des Gesamtsystems in einen bedeckten und unbedeckten Bereich aufgrund der Fluktuationen im Lipidsystem nachgewiesen werden.Die Grenzfläche zwischen den Phasen ist ungewöhnlich rau, was sich in einem statischen Skalenexponenten äußert, der signifikant größer ist als für typische zweidimensionale Modelle.Die erfolgreiche Anpassung der Modell-Parameter an Experimente zeigt, dass die Vorstellung von peripheren Proteinen, die mit mehr Lipiden wechselwirken als sie bedecken, realistisch ist.Die Diskussion schließlich führt zu einem Modell, das nur mit Hilfe der inneren Zustände der Komponenten die Krümmung der äußeren Membran-Oberfläche beschreibt

Machine Learning Supporting Experimental Design for Product Development in the Lab

An interactive decision support framework is presented that assists lab researchers in finding optimal product recipes. Within this framework, an approach for sequential experimental design for black box models in a multicriteria optimization context is introduced. An additional criterion involving the prediction error to design new experiments is used with the goal to get a reliable estimate of the Pareto frontier within a few experimental iterations. The resulting decision support approach accompanies the chemist through the whole workflow and supports the user via interactive, graphical elements

“Real impact”: Challenges and opportunities in bridging the gap between research and practice – Making a difference in industry, policy, and society

Achieving impact from academic research is a challenging, complex, multifaceted, and interconnected topic with a number of competing priorities and key performance indicators driving the extent and reach of meaningful and measurable benefits from research. Academic researchers are incentivised to publish their research in high-ranking journals and academic conferences but also to demonstrate the impact of their outputs through metrics such as citation counts, altmetrics, policy and practice impacts, and demonstrable institutional decision-making influence. However, academic research has been criticized for: its theoretical emphasis, high degree of complexity, jargon-heavy language, disconnect from industry and societal needs, overly complex and lengthy publishing timeframe, and misalignment between academic and industry objectives. Initiatives such as collaborative research projects and technology transfer offices have attempted to deliver meaningful impact, but significant barriers remain in the identification and evaluation of tangible impact from academic research. This editorial focusses on these aspects to deliver a multi-expert perspective on impact by developing an agenda to deliver more meaningful and demonstrable change to how “impact” can be conceptualized and measured to better align with the aims of academia, industry, and wider society. We present the 4D model - Design, Deliver, Disseminate, and Demonstrate - to provide a structured approach for academia to better align research endeavors with practice and deliver meaningful, tangible benefits to stakeholders

“Real impact”: challenges and opportunities in bridging the gap between research and practice – making a difference in industry, policy, and society

Achieving impact from academic research is a challenging, complex, multifaceted, and interconnected topic with a number of competing priorities and key performance indicators driving the extent and reach of meaningful and measurable benefits from research. Academic researchers are incentivised to publish their research in high-ranking journals and academic conferences but also to demonstrate the impact of their outputs through metrics such as citation counts, altmetrics, policy and practice impacts, and demonstrable institutional decision-making influence. However, academic research has been criticized for: its theoretical emphasis, high degree of complexity, jargon-heavy language, disconnect from industry and societal needs, overly complex and lengthy publishing timeframe, and misalignment between academic and industry objectives. Initiatives such as collaborative research projects and technology transfer offices have attempted to deliver meaningful impact, but significant barriers remain in the identification and evaluation of tangible impact from academic research. This editorial focusses on these aspects to deliver a multi-expert perspective on impact by developing an agenda to deliver more meaningful and demonstrable change to how “impact” can be conceptualized and measured to better align with the aims of academia, industry, and wider society. We present the 4D model - Design, Deliver, Disseminate, and Demonstrate - to provide a structured approach for academia to better align research endeavors with practice and deliver meaningful, tangible benefits to stakeholders.</p