Ultrakurzwellen der Wellenlänge 1,50 m hatten bei einer Feldstärke von etwa 0,02 V/m—2 V/m keinen nachweisbaren Einfluß auf die Keimfähigkeit und Keimungsgeschwindigkeit der Samen von Digitalis lutea sowie auf die Sporenkeimung und das Mycelwachstum von Aspergillus niger.
This paper presents a new copula to model dependencies between insurance entities, by considering how insurance entities are affected by both macro and micro factors. The model used to build the copula assumes that the insurance losses of two companies or lines of business are related through a random common loss factor which is then multiplied by an individual random company factor to get the total loss amounts. The new two-component copula is not Archimedean and it extends the toolkit of copulas for the insurance industry.
The field of clinical proteomics offers opportunities to identify new disease biomarkers in body fluids, cells and tissues. These biomarkers can be used in clinical applications for diagnosis, stratification of patients for specific treatment, or therapy monitoring. New protein array formats and improved spectrometry technologies have brought these analyses to a level with potential for use in clinical diagnostics. The nature of the human body fluid proteome with its large dynamic range of protein concentrations presents problems with quantitation. The extreme complexity of the proteome in body fluids presents enormous challenges and requires the establishment of standard operating procedures for handling of specimens, increasing sensitivity for detection and bioinformatical tools for distribution of proteomic data into the public domain. From studies of in vitro diagnostics, especially in clinical chemistry, it is evident that most errors occur in the preanalytical phase and during implementation of the diagnostic strategy. This is also true for clinical proteomics, and especially for fluid proteomics because of the multiple pretreatment processes. These processes include depletion of high-abundance proteins from plasma or enrichment processes for urine where biological variation or differences in proteolytic activities in the sample along with preanalytical variables such as inter- and intra-assay variability will likely influence the results of proteomics studies. However, before proteomic analysis can be introduced at a broader level into the clinical setting, standardization of the preanalytical phase including patient preparation, sample collection, sample preparation, sample storage, measurement and data analysis needs to be improved. In this review, we discuss the recent technological advances and applications that fulfil the criteria for clinical proteomics, with the focus on fluid proteomics. These advances relate to preanalytical factors, analytical standardization and quality-control measures required for effective implementation into routine laboratory testing in order to generate clinically useful information. With new disease biomarker candidates, it will be crucial to design and perform clinical studies that can identify novel diagnostic strategies based on these techniques, and to validate their impact on clinical decision-making.