DCSI -- An improved measure of cluster separability based on separation and connectedness

Whether class labels in a given data set correspond to meaningful clusters is crucial for the evaluation of clustering algorithms using real-world data sets. This property can be quantified by separability measures. A review of the existing literature shows that neither classification-based complexity measures nor cluster validity indices (CVIs) adequately incorporate the central aspects of separability for density-based clustering: between-class separation and within-class connectedness. A newly developed measure (density cluster separability index, DCSI) aims to quantify these two characteristics and can also be used as a CVI. Extensive experiments on synthetic data indicate that DCSI correlates strongly with the performance of DBSCAN measured via the adjusted rand index (ARI) but lacks robustness when it comes to multi-class data sets with overlapping classes that are ill-suited for density-based hard clustering. Detailed evaluation on frequently used real-world data sets shows that DCSI can correctly identify touching or overlapping classes that do not form meaningful clusters

Anarquia em Sicília – uma revolta de escravos na Siracusa Antiga 491/490 A.C.

No ano 491 ou 490 a.C. o demos de Siracusa, uma das principais cidades gregas na parte oriental da ilha de Sicília, se alia aos kyllyrioi, uma população agrária escravizada, expulsando a aristocracia escravocrata e latifundiária dos gamoroi da cidade. Segue-se o que Aristóteles chama de um estado de anarquia, que é somente terminado com a ascensão da tirania de Gelão, que cria uma nova ordem política em Siracusa. Este artigo pretende examinar a relevância da análise de classes para o entendimento destes eventos, ponderando assim também a relevância da categoria para a história da antiguidade em geral. Adicionalmente, se tenciona mostrar, como classe e trabalho na Sicília antiga estavam vinculados a  relações espaciais, criando assim uma situação de fronteira que moldou a forma das lutas político-sociais sicilianas no 5º século a.C

Large-scale benchmark study of survival prediction methods using multi-omics data

Multi-omics data, that is, datasets containing different types of high-dimensional molecular variables, are increasingly often generated for the investigation of various diseases. Nevertheless, questions remain regarding the usefulness of multi-omics data for the prediction of disease outcomes such as survival time. It is also unclear which methods are most appropriate to derive such prediction models. We aim to give some answers to these questions through a large-scale benchmark study using real data. Different prediction methods from machine learning and statistics were applied on 18 multi-omics cancer datasets (35 to 1000 observations, up to 100 000 variables) from the database 'The Cancer Genome Atlas' (TCGA). The considered outcome was the (censored) survival time. Eleven methods based on boosting, penalized regression and random forest were compared, comprising both methods that do and that do not take the group structure of the omics variables into account. The Kaplan-Meier estimate and a Cox model using only clinical variables were used as reference methods. The methods were compared using several repetitions of 5-fold cross-validation. Uno's C-index and the integrated Brier score served as performance metrics. The results indicate that methods taking into account the multi-omics structure have a slightly better prediction performance. Taking this structure into account can protect the predictive information in low-dimensional groups-especially clinical variables-from not being exploited during prediction. Moreover, only the block forest method outperformed the Cox model on average, and only slightly. This indicates, as a by-product of our study, that in the considered TCGA studies the utility of multi-omics data for prediction purposes was limited

Aggregated NETs Sequester and Detoxify Extracellular Histones

In response to various infectious and sterile stimuli neutrophils release chromatin decorated with bactericidal proteins, referred to as NETs. Their scaffolds are formed from chromatin fibers which display an apparent diameter of 15–17 nm and mainly consist from DNA (2 nm) and DNA-associated histones (11 nm). The NET-forming strands are thus not naked DNA but higher ordered chromatin structures. The histones may be released from the NET, especially if their tail arginines have been citrullinated. Several studies indicate that extracellular histones are toxic for mammalian epithelia and endothelia and contribute to the microvascular dysfunction observed e.g., in patients suffering from autoimmune diseases or sepsis. NETs formed at sites of very high neutrophil densities tend to clump and form fairly stable enzymatically active aggregates, referred to as aggNETs. The latter are endowed with a bunch of enzymes that cleave, bind, and/or modify autologous as well as foreign macromolecules. The tight binding of the serine proteases to the matrix precludes the spread of these toxic enzymes into the tissue but still allows the access of soluble inflammatory mediators to the enzymatic active internal surfaces of the NETs where they are degraded. Here, we describe that externally added histones are removed from culture supernatants of aggNETs. We will address the fate of the histones and discuss the feature on the background of neutrophil-driven diseases and the resolution of inflammation

Einfluss des Wassergehaltes auf das an der Bodenoberfläche messbare Gamma-Spektrum: Durchführung eines Austrocknungsversuches im Feld

Die Gammaspektrometrie ermöglicht die nicht-invasive Ermittlung verschiedener Elementgehalte im Boden auf Grundlage natürlicher Radionuklide wie 40-Kalium, 238-Uran und 232-Thorium. Da Wasser die Gammastrahlung abschwächt, können räumlich variable Bodenwassergehalte die Interpretation gammaspektrometrischer Erkundungen erschweren. Die Stärke der daraus resultierenden Ab- schwächung ist von der Bodenzusammensetzung und der Photonenenergie selbst abhängig. Das Ziel dieser Arbeit war, durch einen Austrocknungsversuch unter realen Be- dingungen im Feld, den Einfluss des Bodenwassergehaltes auf das an der Bodenoberfläche messbare Gammaspektrum zu quantifizieren. Dafür wurde ein Bodenzylinder (r = 0,9 m) angelegt und mit Folie vom umgebenden Boden separiert. Nach Aufsättigung wurde das Gammaspektrum über drei Monate während der Austrocknungsphase unter natürlichen Verdunstungsbedingungen an der Bodenoberfläche gemessen. Die Gammastrahlung nahm über den Versuchszeitraum um ca. ein Drittel zu. Regressionsanalysen lassen lineare Abhängigkeiten für Kalium und Thorium erkennen. Aussagen zu Uran und der Gesamtstrahlung ("Total Counts") sind vermutlich aufgrund eines säkularen Un- gleichgewichtes in der Uran-Zerfallsreihe (Radon-Akkumulation) nicht möglich. Die Ergebnisse bilden eine erste Grundlage für mögliche Korrekturverfahren

Process Monitoring of a Vibration Dampening CFRP Drill Tube in BTA deep hole drilling using Fibre-Bragg-Grating Sensors

The large tool length in BTA deep hole drilling often leads to strong torsional vibrations of the tool system, leading to a reduced bore hole quality failures. When substituting steel drill tubes with tubes from composite material, the laminate structure dampens these vibrations. Secondly, the integration of sensors allow to monitor process vibrations. This contribution introduces a new sensor platform to measure process vibrations, feed force and drilling torque using Fibre-Bragg Grating Sensors. The presented experimental results focus on characteristic frequency spectra with natural torsional and compression frequencies of the CFRP drill tube, which show variations due to changed feed

Supplementary information "Model-based analysis of the dynamic capacity ramp-up of closed-loop supply chains for lithium-ion batteries in Japan and Germany"

Mathematical formulation of a capacity planning model for the proceedings paper for the EcoDesign 2023 conference in Japan