Approaches and Methods for Causal Analysis of Panel Data in the Area of Morbidity and Mortality

We aim to give an overview of the state of the art of causal analysis of demographic issues related to morbidity and mortality. We will systematically introduce strategies to identify causal mechanisms, which are inherently linked to panel data from observational surveys and population registers. We will focus on health and mortality, and on the issues of unobserved heterogeneity and reverse causation between health and (1) retirement, (2) socio-economic status, and (3) characteristics of partnership and fertility history. The boundaries between demographic research on mortality and morbidity and the neighbouring disciplines epidemiology, public health and economy are often blurred. We will highlight the specific contribution of demography by reviewing methods used in the demographic literature. We classify these methods according to important criteria, such as a design-based versus model-based approach and control for unobserved confounders. We present examples from the literature for each of the methods and discuss the assumptions and the advantages and disadvantages of the methods for the identification of causal effects in demographic morbidity and mortality research. The differentiation between methods that control for unobserved confounders and those that do not reveal a fundamental difference between (1) methods that try to emulate a randomised experiment and have higher internal validity and (2) methods that attempt to achieve conditional independence by including all relevant factors in the model. The latter usually have higher external validity and require more assumptions and prior knowledge of relevant factors and their relationships. It is impossible to provide a general definition of the sort of validity that is more important, as there is always a trade-off between generalising the results to the population of interest and avoiding biases in the estimation of causal effects in the sample. We hope that our review will aid researchers in identifying strategies to answer their specific research question. *  This article belongs to a special issue on "Identification of causal mechanisms in demographic research: The contribution of panel data"

A systematic literature review of studies analyzing the effect of sex, age, education, marital status, obesity, and smoking on health transitions

Sex, age, education, marital status, obesity, and smoking have been found to affect health transitions between non-disabled, disabled, and death. Our aim is to review the research literature on this topic and provide structured information, first on the availability of results for each risk factor and transition, and then on detailed study characteristics and disability measures. We use expert recommendations and the electronic databases Medline, PsycINFO, and SOCA. The search is confined to the years 1985-2005, and produced a total of 7,778 articles. Sixty-three articles met the selection criteria regarding study population, longitudinal design, risk factors, transition, and outcome measures.gender, health, mortality, obesity, review, sex, smoking, systematic review, transition

Implicit Neural Convolutional Kernels for Steerable CNNs

Steerable convolutional neural networks (CNNs) provide a general framework for building neural networks equivariant to translations and other transformations belonging to an origin-preserving group $G$, such as reflections and rotations. They rely on standard convolutions with $G$-steerable kernels obtained by analytically solving the group-specific equivariance constraint imposed onto the kernel space. As the solution is tailored to a particular group $G$, the implementation of a kernel basis does not generalize to other symmetry transformations, which complicates the development of group equivariant models. We propose using implicit neural representation via multi-layer perceptrons (MLPs) to parameterize $G$-steerable kernels. The resulting framework offers a simple and flexible way to implement Steerable CNNs and generalizes to any group $G$ for which a $G$-equivariant MLP can be built. We apply our method to point cloud (ModelNet-40) and molecular data (QM9) and demonstrate a significant improvement in performance compared to standard Steerable CNNs

Kostbare Koggen: seltene Bilder aus illuminierten Manuskripten und gotischen Kirchen

The modern history of the Bremen cog of 1380 begins in October 1962 with pictures of cogs on the seals of medieval Hanseatic cities. Cogs are also known to us today from miniatures in illuminated manuscripts and frescoes in churches. For the German Maritime Museum book "Die Kogge: Sternstunde der deutschen Schiffsarchäologie" (The cog - a defining moment in German maritime archaeology) I succeeded in assembling a large number of images, several of them unknown until now. The aim of my search was to make the book visually attractive. After its publication in 2003, I continued with my search - this time for a twenty-seven-metre-long illuminated wall in the museum's cog exhibition, which was opened in the summer of 2005, and can now present nineteen new finds. As a result, sixty cog pictures - on miniatures, frescoes and etchings - are currently known, and the number prompts me to seek initial answers to two questions: Do the pictures' times and places of origin match the construction times and origins of the archaeological cog finds? And: What role did the vessel type known as the Hansa cog play in the awareness of contemporaries, and in what context were cogs portrayed? Images of cogs in manuscripts and churches existed from the early thirteenth to early fifteenth centuries - roughly the time from which the discovered wreckage dates. I have been able to trace cog pictures to all countries in the Hanseatic region apart from Poland and the Baltic countries. The miniatures show that cogs were probably familiar in the countries where archaeologists found no wrecks: Indeed, most of the manuscripts in this collection come from England and France. Analysis of the pictures of cogs clearly shows that this type of ship was certainly familiar to contemporaries, and that it is certainly no mere scientist's invention. People at that time knew this vessel well. Whether they always called it a cog, however, or associated this type of ship with the word ‘cog’ is something we cannot ascertain from the pictures that survive. Today, cogs are considered to be the ships used by Hanseatic merchants: No other type of ship is mentioned as frequently in the records of the Hanseatic towns, and we also see cogs on the cities' official seals. Yet miniatures in manuscripts dealing with cogs generally show people of entirely different social origins: kings, priests and the aristocracy. Those among the nobility who commissioned pictures had themselves portrayed in the process of carrying out grand military deeds of the past and in the most recent ship of the time - the cog. The leaders of the church and the landed nobility also commissioned images of saints that included cogs. Those who were important and had money in the fourteenth century used cogs and derived prestige from them - or at least from a portrayal of them

Kapazitiver Sensor zur präzisen Ortsbestimmung von Phasengrenzen in mikrofluidischen Strukturen

Das Ziel dieser Doktorarbeit ist die Entwicklung und Charakterisierung eines Sensors zur Überwachung der Flüssigkeitsbewegung in mikrofluidischen Analysegeräten. Je nach Position der Probenflüssigkeit im Mikrokanal müssen z.B. Mischer und Ventile angesteuert werden, um ein richtiges Ablaufen der hochkomplexen chemischen und biologischen Prozesse in dem Analysegerät zu ermöglichen. Zum Zweck der präzisen Positionsbestimmung wird in dieser Arbeit eine einfache, planare Elektrodenstruktur zur kontaktfreien, kapazitiven Messung von flüssig/gas Grenzflächen vorgestellt. Der Sensor liegt außerhalb der Einwegkartusche und zeichnet sich, gegenüber den bisher eingesetzten Lichtschranken, zum einen durch seine Unempfindlichkeit gegenüber Benetzungen der Kanalwände aus und zum anderen ist er einfacher am Kanal anzubringen. Der Moving Plug Sensor (MPS) arbeitet auf Basis der kapazitiv gekoppelten, kontaktfreien Leitfähigkeitsmessung, kurz C 4 D (engl. Contactless Capacitively Coupled Conductivity Detection). Außerhalb des Kanals angebracht, detektiert der MPS eine vorbeifließende Phasengrenze zweier Stoffe durch den Unterschied der Permittivität beider Medien. Von gängigen Füllstandsensoren unterscheidet sich der MPS durch ein System von drei kapazitiv gekoppelten Elektroden. Zwei rechteckige Messelektroden werden von einer rahmenförmigen Schirmelektrode umgeben. Dieses System dreier kapazitiv gekoppelter Elektroden erzeugt ein charakteristisches Signal gekennzeichnet durch zwei Extrema. Das von Kondensatoren bekannte Stufensignal weist einen Unter- gefolgt von einem Überschwinger auf. Die Extrema treten auf, wenn sich die Phasengrenze an zwei spezifischen Punkten im Bereich des Sensors befindet. Dadurch ermöglicht der Sensor eine sehr präzise Positionsbestimmung der Phasengrenze an zwei Stellen und dadurch auch die Bestimmung der Flussrate mit nur einem Sensor. Die Vorteile der neuen Sensorgeometrie gegenüber den bisher verwendeten Lichtschrankensystemen werden sowohl durch Simulationen wie auch durch Messungen bestätigt, die sowohl die Geometrieparameter der Elektroden, als auch die Lage des Sensors zum Kanal und die elektrischen Materialeigenschaften der Flüssigkeit betrachten. Die Signalcharakteristik ist für die kontaktfreie, präzise Positionsbestimmung von Flüssigkeitssäulen in Mikrokanälen optimiert und der Sensor ist für ein breites Spektrum permittiver und gering leitfähiger Flüssigkeiten einsetzbar. Zusammenfassend stellt diese Dissertation eine robuste und präzise messende elektrische Sensorkonfiguration vor, die im Vergleich zu herkömmlichen Messverfahren wie Lichtschranken oder in der Kartusche integrierten Elektroden einige Vorteile aufweist: minimierter Platzbedarf unter der Kartusche, berührungslose Messung, geeignet für opake Kartuschen, kombinierte und präzise Messung der Fluidposition (±50μm) und Geschwindigkeit (< 2%), kostengünstige Fertigung, Kalibrierung basierend auf Geometriefaktoren und dadurch eine einfache Montage. Darüber hinaus lässt sich die Messgenauigkeit durch Geometrieparameter der Elektrodenanordnung an die Lage des Sensors zur Kartusche anpassen

Post-Translational Inhibition of IP-10 Secretion in IEC by Probiotic Bacteria: Impact on Chronic Inflammation

Peer reviewedPublisher PD

ПЕРШИЙ ЮВІЛЕЙ КАТЕРИНОСЛАВА ЯК ІСТОРІОГРАФІЧНЕ ЯВИЩЕ

У статті здійснена спроба вивчення історіографічного процесу у регіональному вимірі на прикладі Катеринослава.The article deals with the investigation of historiographic process in the second of XIX – at the beginning of ХХ century in a regional view on the materials of Katerinoslav

Exploration of machine learning methods for the classification of infrared limb spectra of polar stratospheric clouds

Polar stratospheric clouds (PSCs) play a key role in polar ozone depletion in the stratosphere. Improved observations and continuous monitoring of PSCs can help to validate and improve chemistry–climate models that are used to predict the evolution of the polar ozone hole. In this paper, we explore the potential of applying machine learning (ML) methods to classify PSC observations of infrared limb sounders. Two datasets were considered in this study. The first dataset is a collection of infrared spectra captured in Northern Hemisphere winter 2006/2007 and Southern Hemisphere winter 2009 by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) instrument on board the European Space Agency's (ESA) Envisat satellite. The second dataset is the cloud scenario database (CSDB) of simulated MIPAS spectra. We first performed an initial analysis to assess the basic characteristics of the CSDB and to decide which features to extract from it. Here, we focused on an approach using brightness temperature differences (BTDs). From both the measured and the simulated infrared spectra, more than 10 000 BTD features were generated. Next, we assessed the use of ML methods for the reduction of the dimensionality of this large feature space using principal component analysis (PCA) and kernel principal component analysis (KPCA) followed by a classification with the support vector machine (SVM). The random forest (RF) technique, which embeds the feature selection step, has also been used as a classifier. All methods were found to be suitable to retrieve information on the composition of PSCs. Of these, RF seems to be the most promising method, being less prone to overfitting and producing results that agree well with established results based on conventional classification methods