Martin Luther University of Halle-Wittenberg

About: Martin Luther University of Halle-Wittenberg is a education organization based out in Halle, Germany. It is known for research contribution in the topics: Population & Liquid crystal. The organization has 20232 authors who have published 38773 publications receiving 965004 citations. The organization is also known as: MLU & University of Wittenberg.

Fundamentals of soiling processes on photovoltaic modules

Abstract: The topic of soiling of photovoltaic module (PV) and concentrated solar power (CSP) collectors has recently gained increasing attention due to its impact on solar power production, especially in arid and semi-arid areas with high concentrations of airborne dust. Soiling describes the deposition of dust and other contaminants on surfaces, reducing solar irradiation by absorbing or reflecting the sunlight, causing energy yield losses which can exceed 1% per day. The amount of soiling is influenced by complex interactions of many factors which can vary significantly from site to site. In this study we provide a detailed overview of macroscopic and microscopic factors influencing soiling. This includes a global analysis of key parameters including airborne dust concentrations, dust characteristics (mineral composition, size distribution), and particle deposition rates. A theoretical model for relevant particle adhesion and removal forces is presented to achieve a microscopic understanding of wind cleaning effects. Further, it was found that dew occurs frequently on PV modules in many soiling affected areas and that this can significantly increase particle adhesion. Therefore, a detailed analysis and model of the dew-driven soiling mechanisms of cementation, particle caking, and capillary aging are given on the basis of microstructural material and dust characterization of outdoor exposed glass samples. Furthermore, we study the complex interplay and dynamics of different environmental parameters (relative humidity, ambient and module temperature, airborne dust concentration, wind speed) and their correlation to dust accumulation, and provide explanations with the help of the developed models. Overall the study aims to provide a useful, in-depth but also global overview and fundamental understanding of soiling processes on PV modules down to the microscale, which could be used to develop appropriate soiling mitigation strategies.

Focal Lesions of Human Hippocampal CA1 Neurons in Transient Global Amnesia Impair Place Memory

Abstract: A critical role in place learning has been attributed to place cells within the cornu ammonis 1 (CA1) sector of the hippocampus in rodents. The role of CA1 cells in the human hippocampus with regard to place learning remains elusive. Using a virtual Morris water maze, we investigated patients with acute transient global amnesia (TGA), a rare self-limiting dysfunction of the hippocampal system. Fourteen individuals with selective and focal lesions in the CA1 sector of the hippocampus showed a profound impairment in place learning. The size of the lesions and the duration of the TGA correlated with the deficit in the performance.

Path2Models: large-scale generation of computational models from biochemical pathway maps

Abstract: Background: Systems biology projects and omics technologies have led to a growing number of biochemical pathway models and reconstructions. However, the majority of these models are still created de novo, based on literature mining and the manual processing of pathway data. Results: To increase the efficiency of model creation, the Path2Models project has automatically generated mathematical models from pathway representations using a suite of freely available software. Data sources include KEGG, BioCarta, MetaCyc and SABIO-RK. Depending on the source data, three types of models are provided: kinetic, logical and constraint-based. Models from over 2 600 organisms are encoded consistently in SBML, and are made freely available through BioModels Database at http://www.ebi.ac.uk/biomodels-main/path2models. Each model contains the list of participants, their interactions, the relevant mathematical constructs, and initial parameter values. Most models are also available as easy-to-understand graphical SBGN maps.

A proteomic fingerprint of dissolved organic carbon and of soil particles

Abstract: Mass spectrometry-based proteomics was applied to analyze proteins isolated from dissolved organic matter (DOM). The focal question was to identify the type and biological origin of proteins in DOM, and to describe diversity of protein origin at the level of higher taxonomic units, as well as to detect extracellular enzymes possibly important in the carbon cycle. Identified proteins were classified according to their phylogenetic origin and metabolic function using the National Center for Biotechnology Information (NCBI) protein and taxonomy database. Seventy-eight percent of the proteins in DOM from the lake but less than 50% in forest soil DOM originated from bacteria. In a deciduous forest, the number of identified proteins decreased from 75 to 28 with increasing soil depth and decreasing total soil organic carbon content. The number of identified proteins and taxonomic groups was 50% higher in winter than in summer. In spruce forest, number of proteins and taxonomic groups decreased by 50% on a plot where trees had been girdled a year before and carbohydrate transport to roots was terminated. After girdling, proteins from four taxonomic groups remained as compared to nine taxonomic groups in healthy forest. Enzymes involved in degradation of organic matter were not identified in free soil DOM. However, cellulases and laccases were found among proteins extracted from soil particles, indicating that degradation of soil organic matter takes place in biofilms on particle surfaces. These results demonstrate a novel application of proteomics to obtain a “proteomic fingerprint” of presence and activity of organisms in an ecosystem.

GWAS of Suicide Attempt in Psychiatric Disorders and Association With Major Depression Polygenic Risk Scores

Abstract: OBJECTIVE: More than 90% of people who attempt suicide have a psychiatric diagnosis; however, twin and family studies suggest that the genetic etiology of suicide attempt is partially distinct from that of the psychiatric disorders themselves. The authors present the largest genome-wide association study (GWAS) on suicide attempt, using cohorts of individuals with major depressive disorder, bipolar disorder, and schizophrenia from the Psychiatric Genomics Consortium. METHODS: The samples comprised 1,622 suicide attempters and 8,786 nonattempters with major depressive disorder; 3,264 attempters and 5,500 nonattempters with bipolar disorder; and 1,683 attempters and 2,946 nonattempters with schizophrenia. A GWAS on suicide attempt was performed by comparing attempters to nonattempters with each disorder, followed by a meta-analysis across disorders. Polygenic risk scoring was used to investigate the genetic relationship between suicide attempt and the psychiatric disorders. RESULTS: Three genome-wide significant loci for suicide attempt were found: one associated with suicide attempt in major depressive disorder, one associated with suicide attempt in bipolar disorder, and one in the meta-analysis of suicide attempt in mood disorders. These associations were not replicated in independent mood disorder cohorts from the UK Biobank and iPSYCH. No significant associations were found in the meta-analysis of all three disorders. Polygenic risk scores for major depression were significantly associated with suicide attempt in major depressive disorder (R2=0.25%), bipolar disorder (R2=0.24%), and schizophrenia (R2=0.40%). CONCLUSIONS: This study provides new information on genetic associations and demonstrates that genetic liability for major depression increases risk for suicide attempt across psychiatric disorders. Further collaborative efforts to increase sample size may help to robustly identify genetic associations and provide biological insights into the etiology of suicide attempt.