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Penn State University und Universität Freiburg: Projektstart für 3 gemeinsame Forschungsprojekte

Projektbeginn ist der 1. März 2019

Zum 1. März 2019 begann die Förderphase für die drei erfolgreichen Teams der aktuellen Runde im Freiburg Penn State Joint Collaboration Development Program. Der thematische Fokus der Ausschreibung lag in den Forschungsbereichen "Water-Food-Energy, Sustainability & Health“. Hier die ausgewählten Projekte, die jeweils mit 25.000 Euro ausgestattet wurden:

 

Framing and Analyzing Novel Internventions for Sustainable Communities in Africa

Prof. Dr. Bernhard Neumärker, University of Freiburg, Department of Economics and Behavioral Sciences, Economic Policy and Constitutional Economic Theory; Prof. Dr. Michael Jacobson, Penn State University, Ecosystem Science and Management, Forest Resources

Contact: bernhard.neumaerker@vwl.uni-freiburg.de

Improvements in the agricultural sector, including land intensification, are essential for poverty reduction in many places in Africa. An important question is whether to focus on increasing yields among subsistence farmers, or instead re-direct efforts to other labor and land use opportunities. Many areas that are marginal for staple crop production could be better-suited for other land uses and job- or wealth-creation activities, which would in turn have a stronger welfare- and health-enhancing effect among the rural poor. Such an argument has been put forward by proponents of so-called large-scale foreign land acquisition (LSFA)—also referred to as land grabs—in which large tracts of land are sold or leased to capital-rich farmers for intensive agriculture. Our project addresses this question through the lens of the water-energy-food (WEF) nexus, which captures the complex interactions between the major socio-ecological systems underpinning human welfare and health. We link this analysis to Foreign Aid Basic Income (FABI) as economic and socially sustainable options, which could prevent communities and states from accepting land grabs and encourage the development of sustainable communities. The focus on the intersection of WEF systems, LSFA and FABI will inform interventions that promote sustainability, poverty reduction, and food, health, and nutritional security of the rural poor. The project will further long-term collaboration between project investigators and African colleagues and stakeholders.

Machine Learning Models for Human Disease Discovery and Prediction

Prof. Dr. Harald Binder, University of Freiburg, Institute of Medical Biometry and Statistics (IMBI), Medical Biometry and Statistics; Prof. Dr. Conrad Tucker, Penn State University, NSF Center for Health Organization Transformation (CHOT), Engineering Design, Industrial Engineering, Computer Science and Engineering

Contact: binderh@imbi.uni-freiburg.de

There is enormous potential for machine learning approaches and in particular, artificial intelligence techniques, to improve health care and address other societal challenges. Successful development of techniques requires enormous amounts of data. In Europe, a framework for such sensitive Big Data applications has recently been established by the General Data Protection Regulation (GDPR). In the US, there is a different cultural background for data protection regulations, which has made it easier in some instances, to develop and implement machine learning-based frameworks for Big Data applications. In this project we will initiate an interaction between the US and the European perspective, in order to inspire technical developments and the education of students and future researchers for mutual benefit. From a subject matter perspective, the objective of this collaboration is to explore areas within healthcare where big data and machine learning methods can help to increase the speed, scalability and efficiency of disease detection and wellness planning.

Ultrasensitive Liquid Biopsy for Early Cancer Diagnostics

Dr. Manching M. Ku, University of Freiburg Medical Center, Department of Pediatrics, Division of Hematology and Oncology; Prof. Dr. Tak-Sing Wong, Penn State University, Department of Mechanical and Nuclear Engineering; Engineering and Biomedical Engineering

Contact: manching.ku@uniklinik-freiburg.de


Cancer remains one of the leading causes of death worldwide. Most cancers are caused by the abnormal change in our genome. Dysfunctional cells with mutant DNA undergo abnormal proliferation or lack of cell death, leading to cancer. The ability to detect cancer in the early stage will significantly improve the survival rates of cancer patients and decrease healthcare cost. Through the research collaboration between University of Freiburg and The Pennsylvania State University, our long term vision is to develop an affordable ultrasensitive detection platform that can identify cancers at their early stages through the use of advanced genomic and bioinspired sensing technologies. Here, we propose to develop a new method to decipher genetic and epigenetic codes of human DNA with a better resolution and higher sensitivity than current state-of-the-art techniques. Through the use of advanced optical spectroscopy and bioinspired surface technology, we plan to detect and study genetic and epigenetic codes of human DNA down to single molecule resolution. Combining our expertise in biosensing and epigenomics, we aim to apply this cutting-edge novel technique for quick and affordable non-invasive cancer diagnostics.