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     

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.     

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.     

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.     

Adaptive water management in Israel: structure and policy options

Difficulties in integrating technical, economic and institutional factors present a major gap in analytical capacity to guide water policy. This article presents an integrated framework to support water policy and guide water management choices, with application to Israel. That framework rests on the theory of economic policy originally developed by Tinbergen. It sees national water challenges as consisting of external factors, constraints, policy instruments and targets. The need for a modern implementation of the theory of economic policy is motivated by emerging environmental requirements, scarce water, growing demands for domestic use, and ongoing needs to implement existing and potential peace agreements.     

Performance and reliability prediction for evolving service-oriented software systems

During software system evolution, software architects intuitively trade off the different architecture alternatives for their extra-functional properties, such as performance, maintainability, reliability, security, and usability. Researchers have proposed numerous model-driven prediction methods based on queuing networks or Petri nets, which claim to be more cost-effective and less error-prone than current practice. Practitioners are reluctant to apply these methods because of the unknown prediction accuracy and work effort. We have applied a novel model-driven prediction method called Q-ImPrESS on a large-scale process control system from ABB consisting of several million lines of code. This paper reports on the achieved performance prediction accuracy and reliability prediction sensitivity analyses as well as the effort in person hours for achieving these results.