Conjunctive Query Answering for the Description Logic SHIQ

Conjunctive queries play an important role as an expressive query language for Description Logics (DLs). Although modern DLs usually provide for transitive roles, conjunctive query answering over DL knowledge bases is only poorly understood if transitive roles are admitted in the query. In this paper, we consider unions of conjunctive queries over knowledge bases formulated in the prominent DL SHIQ and allow transitive roles in both the query and the knowledge base. We show decidability of query answering in this setting and establish two tight complexity bounds: regarding combined complexity, we prove that there is a deterministic algorithm for query answering that needs time single exponential in the size of the KB and double exponential in the size of the query, which is optimal. Regarding data complexity, we prove containment in co-NP

The Complexity of Reasoning with Boolean Modal Logics: Extended Version

Since Modal Logics are an extension of Propositional Logic, they provide Boolean operators for constructing complex formulae. However, most Modal Logics do not admit Boolean operators for constructing complex modal parameters to be used in the box and diamond operators. This asymmetry is not present in Boolean Modal Logics, in which box and diamond quantify over arbitrary Boolean combinations of atomic model parameters.This is an extended version of the article in: Advances in Modal Logic (AiML), Volume

Interactions of Tumor Necrosis Factor–Related Apoptosis-Inducing Ligand (TRAIL) with the Immune System: Implications for Inflammation and Cancer

Tumor necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL) is a member of the TNF superfamily. TRAIL has historically been distinct from the Fas ligand and TNFα in terms of selective apoptosis induction in tumor cells and has a nearly non-existent systemic toxicity. Consequently, in the search for an ideal drug for tumor therapy, TRAIL rapidly drew interest, promising effective tumor control with minimal side effects. However, euphoria gave way to disillusionment as it turned out that carcinoma cells possess or can acquire resistance to TRAIL-induced apoptosis. Additionally, studies on models of inflammation and autoimmunity revealed that TRAIL can influence immune cells in many different ways. While TRAIL was initially found to be an important player in tumor defense by natural killer cells or cytotoxic T cells, additional effects of TRAIL on regulatory T cells and effector T cells, as well as on neutrophilic granulocytes and antigen-presenting cells, became focuses of interest. The tumor-promoting effects of these interactions become particularly important for consideration in cases where tumors are resistant to TRAIL-induced apoptosis. Consequently, murine models have shown that TRAIL can impair the tumor microenvironment toward a more immunosuppressive type, thereby promoting tumor growth. This review summarizes the current state of knowledge on TRAIL’s interactions with the immune system in the context of cancer

Keys, Nominals, and Concrete Domains

Many description logics (DLs) combine knowledge representation on an abstract, logical level with an interface to 'concrete' domains such as numbers and strings with built-in predicates such as <, +, and prefix-of. These hybrid DLs have turned out to be quite useful for reasoning about conceptual models of information systems, and as the basis for expressive ontology languages. We propose to further extend such DLs with key constraints that allow the expression of statements like 'US citizens are uniquely identified by their social security number'. Based on this idea, we introduce a number of natural description logics and perform a detailed analysis of their decidability and computational complexity. It turns out that naive extensions with key constraints easily lead to undecidability, whereas more careful extensions yield NEXPTIME-complete DLs for a variety of useful concrete domains

Humidity Considerations in Filter Testing Based on Analysis of Filters from Gas Turbine Applications

Depth filters used in multistage filter systems adeptly clean the intake air of gas turbines, preventing damage and increasing performance. However, estimation of their service life is based on empirical data and/or standardized testing procedures, e.g., ISO 16890. By applying standardized synthetic test dusts at constant reference humidity, these testing procedures do not reflect application-typical loading conditions. Based on a direct comparison with field data, the influence of temporary exposure to high relative humidity on differential pressure and particle deposit structure is investigated. The results indicate that simulating humidity variations of the ambient atmosphere during filter tests leads to particle deposits, which more accurately reflect the actual behavior during operation

Experimental and Numerical analysis of a Solar Rotary Kiln for Continuous Treatment of Particle Material

Several energy intensive industrial processes, such as cement production, require particulate material to be treated at high temperatures. Renewable energy could be used to remove the reliance upon fossil fuels in such processes, and of the available technologies concentrated solar energy is perfectly adapted to provide a high temperature energy source. With this objective, the present study focuses on a solar reactor continuously transferring concentrated solar radiation to a bed of flowing particles. Rotary kilns are the chosen concept due to their technical maturity, easy control and simple design. The feasibility of a solar driven rotary kiln has already been proven at lab-scale, with the successful calcination of materials up to a scale of kg/h. The present work describes a large solar rotary kiln able to heat particles to over 1000 °C at flow rates of up to 20 kg/h. The thermal performance of the reactor was evaluated through an on-sun experimental campaign, performed in the high flux solar simulator at the DLR. During one test, 17 kg/h of particles were heated up to 990 °C, with a thermal efficiency of 45 %. An improvement of the efficiency can be obtained by optimizing the reactor. To do this, a numerical model was developed and its parameters fit to the measured data. Simulations were used to quantify the different heat loss mechanisms, and to explore ways of reducing them. The promising experimental results, together with the mprovements suggested by the model, provide the basis for an upcoming chemical campaign, where the calcination of CaCO3 and the effect of endothermic reactions on the temperature distribution will be investigated

Evaluating the drivers of and obstacles to the willingness to use cognitive enhancement drugs: the influence of drug characteristics, social environment, and personal characteristics

Sattler S, Mehlkop G, Graeff P, Sauer C. Evaluating the drivers of and obstacles to the willingness to use cognitive enhancement drugs: the influence of drug characteristics, social environment, and personal characteristics. Substance Abuse Treatment, Prevention, and Policy. 2014;9(1): 8.Background The use of cognitive enhancement (CE) by means of pharmaceutical agents has been the subject of intense debate both among scientists and in the media. This study investigates several drivers of and obstacles to the willingness to use prescription drugs non-medically for augmenting brain capacity. Methods We conducted a web-based study among 2,877 students from randomly selected disciplines at German universities. Using a factorial survey, respondents expressed their willingness to take various hypothetical CE-drugs; the drugs were described by five experimentally varied characteristics and the social environment by three varied characteristics. Personal characteristics and demographic controls were also measured. Results We found that 65.3% of the respondents staunchly refused to use CE-drugs. The results of a multivariate negative binomial regression indicated that respondents’ willingness to use CE-drugs increased if the potential drugs promised a significant augmentation of mental capacity and a high probability of achieving this augmentation. Willingness decreased when there was a high probability of side effects and a high price. Prevalent CE-drug use among peers increased willingness, whereas a social environment that strongly disapproved of these drugs decreased it. Regarding the respondents’ characteristics, pronounced academic procrastination, high cognitive test anxiety, low intrinsic motivation, low internalization of social norms against CE-drug use, and past experiences with CE-drugs increased willingness. The potential severity of side effects, social recommendations about using CE-drugs, risk preferences, and competencies had no measured effects upon willingness. Conclusions These findings contribute to understanding factors that influence the willingness to use CE-drugs. They support the assumption of instrumental drug use and may contribute to the development of prevention, policy, and educational strategies

Automated workflow-based exploitation of pathway databases provides new insights into genetic associations of metabolite profiles

Background: Genome-wide association studies (GWAS) have identified many common single nucleotide polymorphisms (SNPs) that associate with clinical phenotypes, but these SNPs usually explain just a small part of the heritability and have relatively modest effect sizes. In contrast, SNPs that associate with metabolite levels generally explain a higher percentage of the genetic variation and demonstrate larger effect sizes. Still, the discovery of SNPs associated with metabolite levels is challenging since testing all metabolites measured in typical metabolomics studies with all SNPs comes with a severe multiple testing penalty. We have developed an automated workflow approach that utilizes prior knowledge of biochemical pathways present in databases like KEGG and BioCyc to generate a smaller SNP set relevant to the metabolite. This paper explores the opportunities and challenges in the analysis of GWAS of metabolomic phenotypes and provides novel insights into the genetic basis of metabolic variation through the re-analysis of published GWAS datasets. Results: Re-analysis of the published GWAS dataset from Illig et al. (Nature Genetics, 2010) using a pathway-based workflow (http://www.myexperiment.org/packs/319.html), confirmed previously identified hits and identified a new locus of human metabolic individuality, associating Aldehyde dehydrogenase family1 L1 (ALDH1L1) with serine/glycine ratios in blood. Replication in an independent GWAS dataset of phospholipids (Demirkan et al., PLoS Genetics, 2012) identified two novel loci supported by additional literature evidence: GPAM (Glycerol-3 phosphate acyltransferase) and CBS (Cystathionine beta-synthase). In addition, the workflow approach provided novel insight into the affected pathways and relevance of some of these gene-metabolite pairs in disease development and progression. Conclusions: We demonstrate the utility of automated exploitation of background knowledge present in pathway databases for the analysis of GWAS datasets of metabolomic phenotypes. We report novel loci and potential biochemical mechanisms that contribute to our understanding of the genetic basis of metabolic variation and its relationship to disease development and progression