Hepatic damage produced by long-term alcohol consumption in well-nourished rats

A study of the effect of long-term alcohol consumption on the liver of well-nourished rats is described. Rats fed for 16 weeks on a semipurified diet supplemented with high levels of vitamins and lipotropic factors and alcohol corresponding to 35% of the total caloric intake developed marked fatty changes of the liver. Mild fatty changes were observed in pair-fed controls receiving as isoenergetic equivalent of sucrose instead of alcohol. Intracellular hyaline bodies, corresponding ultrastructurally to giant mitochondria were abundantly found in the hepatocytes of alcoholic rats, while in the controls they were not seen. Te findings in this investigation are postulated to provide further evidence that the long-term intake of alcohol exerts a direct causative role in the pathogenesis of liver damage.     

Bücherschau

Ohne Zusammenfassung VDI     

Energieinformatik

Due to the increasing importance of producing and consuming energy more sustainably, Energy Informatics (EI) has evolved into a thriving research area within the CS/IS community. The article attempts to characterize this young and highly dynamic field of research by describing current EI research topics and methods and provides an outlook of how the field might evolve in the future. It is shown that two general research questions have received the most attention so far and are likely to dominate the EI research agenda in the coming years: How to leverage information and communication technology (ICT) to (1) improve energy efficiency, and (2) to integrate decentralized renewable energy sources into the power grid. Selected EI streams are reviewed, highlighting how the respective research questions are broken down into specific research projects and how EI researchers have made contributions based on their individual academic background.     

Modeling of Filtration Combustion of Carbon

The kinetics of the overall reactions of carbon gasification at temperatures up to 1600 K is studied. The kinetic characteristics of the reactions are taken into account in a distributed mathematical model of filtration combustion of carbon. By computational experiment at different values of process control parameters (the gas flow rate, the fraction of the oxidant in the gas, and the mass ratio of carbon to the inert material in the combustible mixture), it is found that, in the wave of filtration combustion of carbon under superadiabatic conditions, carbon gasification can predominately yield either CO₂ or CO.     

MPaaS: Mobility prediction as a service in telecom cloud

Mobile applications and services relying on mobility prediction have recently spurred lots of interest. In this paper, we propose mobility prediction based on cellular traces as an infrastructural level service of telecom cloud. Mobility Prediction as a Service (MPaaS) embeds mobility mining and forecasting algorithms into a cloud-based user location tracking framework. By empowering MPaaS, the hosted 3rd-party and value-added services can benefit from online mobility prediction. Particularly we took Mobility-aware Personalization and Predictive Resource Allocation as key features to elaborate how MPaaS drives new fashion of mobile cloud applications. Due to the randomness of human mobility patterns, mobility predicting remains a very challenging task in MPaaS research. Our preliminary study observed collective behavioral patterns (CBP) in mobility of crowds, and proposed a CBP-based mobility predictor. MPaaS system equips a hybrid predictor fusing both CBP-based scheme and Markov-based predictor to provide telecom cloud with large-scale mobility prediction capacity.     

Temporal evolution of contacts and communities in networks of face-to-face human interactions

Temporal dynamics of social interaction networks as well as the analysis of communities are key aspects to gain a better understanding of the involved processes, important influence factors, their effects, and their structural implications. In this article, we analyze temporal dynamics of contacts and the evolution of communities in networks of face-to-face proximity. As our application context, we consider four scientific coil- ferences. On a structural level, we focus on static and dynamic properties of the contact graphs. Also, we analyze the resulting community structure using state-of-the-art automatic community detection algorithms. Specifically, we analyze tile evolution of contacts and communities over time to consider the stability of the respective conmmnities. Furthermore, we assess different factors which have an influence on the quality of com- munity prediction. Overall, we provide first important insights into the evolution of contacts and communities in face-to-face contact networks.     

Business process compliance checking – applying and evaluating a generic pattern matching approach for conceptual models in the financial sector

Given the strong increase in regulatory requirements for business processes the management of business process compliance becomes a more and more regarded field in IS research. Several methods have been developed to support compliance checking of conceptual models. However, their focus on distinct modeling languages and mostly linear (i.e., predecessor-successor related) compliance rules may hinder widespread adoption and application in practice. Furthermore, hardly any of them has been evaluated in a real-world setting. We address this issue by applying a generic pattern matching approach for conceptual models to business process compliance checking in the financial sector. It consists of a model query language, a search algorithm and a corresponding modelling tool prototype. It is (1) applicable for all graph-based conceptual modeling languages and (2) for different kinds of compliance rules. Furthermore, based on an applicability check, we (3) evaluate the approach in a financial industry project setting against its relevance for decision support of audit and compliance management tasks.     

Approximate variational inference based on a finite sample of Gaussian latent variables

Variational methods are employed in situations where exact Bayesian inference becomes intractable due to the difficulty in performing certain integrals. Typically, variational methods postulate a tractable posterior and formulate a lower bound on the desired integral to be approximated, e.g. marginal likelihood. The lower bound is then optimised with respect to its free parameters, the so-called variational parameters. However, this is not always possible as for certain integrals it is very challenging (or tedious) to come up with a suitable lower bound. Here, we propose a simple scheme that overcomes some of the awkward cases where the usual variational treatment becomes difficult. The scheme relies on a rewriting of the lower bound on the model log-likelihood. We demonstrate the proposed scheme on a number of synthetic and real examples, as well as on a real geophysical model for which the standard variational approaches are inapplicable.     

Sparkle measurement revisited: A closer look at the details

Four years after introduction of the first instrument for measurement of sparkle, the foundations have been reconsidered, and the pool of practical experience has been analyzed to provide a more detailed and complete picture of the subject matter. The following aspects are introduced and discussed: observation conditions and resulting requirements for imaging (sampling) and filtering, analysis of spatial periods and frequencies as a basis for filtering, spatial filtering concepts, sparkle in the frequency domain, sparkle evaluation based on analysis of single images and difference images, origins of unwanted sparkle components, scaling and offset in sparkle evaluation, and verification of the method.