Peaks Over Thresholds Modeling With Multivariate Generalized Pareto Distributions

When assessing the impact of extreme events, it is often not just a single component, but the combined behavior of several components which is important. Statistical modeling using multivariate generalized Pareto (GP) distributions constitutes the multivariate analogue of univariate peaks over thresholds modeling, which is widely used in finance and engineering. We develop general methods for construction of multivariate GP distributions and use them to create a variety of new statistical models. A censored likelihood procedure is proposed to make inference on these models, together with a threshold selection procedure, goodness-of-fit diagnostics, and a computationally tractable strategy for model selection. The models are fitted to returns of stock prices of four UK-based banks and to rainfall data in the context of landslide risk estimation. Supplementary materials and codes are available online.     

Extracellular Vesicles and Asthma—More Than Just a Co-Existence

Extracellular vesicles (EVs) are membranous structures, which are secreted by almost every cell type analyzed so far. In addition to their importance for cell-cell communication under physiological conditions, EVs are also released during pathogenesis and mechanistically contribute to this process. Here we summarize their functional relevance in asthma, one of the most common chronic non-communicable diseases. Asthma is a complex persistent inflammatory disorder of the airways characterized by reversible airflow obstruction and, from a long-term perspective, airway remodeling. Overall, mechanistic studies summarized here indicate the importance of different subtypes of EVs and their variable cargoes in the functioning of the pathways underlying asthma, and show some interesting potential for the development of future therapeutic interventions. Association studies in turn demonstrate a good diagnostic potential of EVs in asthma.     

Fourier Analysis of Serial Dependence Measures

Classical spectral analysis is based on the discrete Fourier transform of the autocovariances. In this article we investigate the asymptotic properties of new frequency‐domain methods where the autocovariances in the spectral density are replaced by alternative dependence measures that can be estimated by U‐statistics. An interesting example is given by Kendall's τ, for which the limiting variance exhibits a surprising behavior.     

Switchable Plasmonic Metasurface Utilizing the Electro-Optic Kerr Effect of a Blue Phase Liquid Crystal

A switchable metasurface composed of plasmonic split ring resonators and a polymer-stabilized liquid crystal blue phase is developed. Owing to field-induced birefringence (electro-optic Kerr effect), the state of polarization of the incident near infrared radiation changes, when a voltage is applied to the liquid crystal. Thus, different resonant modes of the split ring resonators can be addressed and the transmission spectrum changes accordingly. In comparison with other liquid crystal phases, blue phases have several advantages. For example, they are optically isotropic in the field-off state, so that no alignment layer is required. The results of the present study indicate that the advantages of these mesophases can be utilized for switchable metasurfaces.     

Radiomics and Machine Learning in Oral Healthcare

The increasing storage of information, data, and forms of knowledge has led to the development of new technologies that can help to accomplish complex tasks in different areas, such as in dentistry. In this context, the role of computational methods, such as radiomics and Artificial Intelligence (AI) applications, has been progressing remarkably for dentomaxillofacial radiology (DMFR). These tools bring new perspectives for diagnosis, classification, and prediction of oral diseases, treatment planning, and for the evaluation and prediction of outcomes, minimizing the possibilities of human errors. A comprehensive review of the state‐of‐the‐art of using radiomics and machine learning (ML) for imaging in oral healthcare is presented in this paper. Although the number of published studies is still relatively low, the preliminary results are very promising and in a near future, an augmented dentomaxillofacial radiology (ADMFR) will combine the use of radiomics‐based and AI‐based analyses with the radiologist's evaluation. In addition to the opportunities and possibilities, some challenges and limitations have also been discussed for further investigations.     

Exposure to virtual nature: the impact of different immersion levels on skin conductance level,heart rate,and perceived relaxation

Virtual Reality - It is generally accepted that natural environments reduce stress and improve mood. Since access to natural environments is sometimes limited, virtual natural environments,...     

Sanierungsforschung in regional kontaminierten Aquiferen (SAFIRA) – 2. Projektüberblick und Pilotanlage

The joint research project SAFIRA, which is supported by the Federal Ministry of Science and Education (BMBF), deals with the development of innovative technologies for the in situ remediation of heavily contaminated groundwater at the in situ pilot facility in Bitterfeld. In order to evaluate the new promising technological approaches comprehensively, methodological tools are developed to comparatively address economical, ecological as well as a environmental issues of related remediation scenarios. The design period for innovative technologies can hardly be forecasted and/or its success be guaranteed. To prove a long-term stability as well as to reach a sound economical and ecological evaluation for new approaches an on site operation over extended periods of time is needed. Therefore a variety of technologies are tested and optimized simultaneously, in order to achieve a thorough comparison of technologies at the end of the project.     

Sanierungsforschung in regional kontaminierten Aquiferen (SAFIRA) – 1. Information zum Forschungsschwerpunkt am Standort Bitterfeld

The SAFIRA-project (remediation research in regionally contaminated aquifers) focuses on innovative in situ remediation technologies to treat complex groundwater contamination. For this purpose, a model site located in Bitterfeld, Germany, was selected. The site is heavily contaminated with aliphatic and aromatic chlorinated hydrocarbons. The goal of the project is to develop, test and optimize new technologies of reactive barriers under controlled in situ conditions in a pilot plant. In order to create the necessary basis for this model project, the hydrogeological and hydrogeochemical conditions at the selected field site were investigated and various technologies for the design of the in situ pilot plant were examinated. Small-scale laboratory studies and tests in a mobile test unit (scale 1 m) were carried out in order to test the technologies prior to their application in the field. The technologies now tested in the reactive columns at the pilot plant include physico-chemical, microbial and combined techniques.