97 research outputs found

    Tax Compliance and Public Goods Provision -- An Agent-based Econophysics Approach

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    We calculate the dynamics of tax evasion within a multi-agent econophysics model which is adopted from the theory of magnetism and previously has been shown to capture the main characteristics from agent-based based models which build on the standard Allingham and Sandmo approach. In particular, we implement a feedback of public goods provision on the decision-making of selfish agents which aim to pursue their self interest. Our results imply that such a feedback enhances the moral attitude of selfish agents thus reducing the percentage of tax evasion. Two parameters govern the behavior of selfish agents, (i) the rate of adaption to changes in public goods provision and (ii) the threshold of perception of public goods provision. Furtheron we analyze the tax evasion dynamics for different agent co mpositions and under the feedback of public goods provision. We conclude that policymakers may enhance tax compliance behavior via the threshold of perception by means of targeted public relations.Comment: 28 pages, 3 figures, accepted for publication in the Central European Journal of Economic Modelling and Econometric

    An agent-based approach to integrated assessment modelling of climate change

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    There is an ongoing discussion concerning the relationship between social welfare and climate change, and thus the required level and type of measures needed to protect the climate. Integrated assessment models (IAMs) have been extended to incorporate technological progress, heterogeneity and uncertainty, making use of a (stochastic) dynamic equilibrium approach in order to derive a solution. According to the literature, the IAM class of models does not take all the relationships among economic, social and environmental factors into account. Moreover, it does not consider these interdependencies at the micro-level, meaning that all possible consequences are not duly examined. Here, we propose an agent-based approach to analyse the relationship between economic welfare and climate protection. In particular, our aim is to analyse how the decisions of individual agents, allowing for the trade-off between economic welfare and climate protection, influence the aggregated emergent economic behaviour. Using this model, we estimate a damage function, with values in the order 3% - 4%for 2 C temperature increase and having a linear (or slightly concave) shape. We show that the heterogeneity of the agents, technological progress and the damage function may lead to lower GDP growth rates and greater temperature-related damage than what is forecast by models with solely homogeneous (representative) agents

    Optimal temperature overshoot profile found by limiting global sea level rise as a lower-cost climate target

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    The global temperature targets of limiting surface warming to below 2.0°C or even to 1.5°C have been widely accepted through the Paris Agreement. However, limiting surface warming has previously been proven insufficient to control sea level rise (SLR). Here, we explore a sea level target that is closer to coastal planning and associated adaptation measures than a temperature target. We find that a sea level target provides an optimal temperature overshoot profile through a physical constraint of SLR. The allowable temperature overshoot leads to lower mitigation costs and more effective long-term sea level stabilization compared to a temperature target leading to the same SLR by 2200. With the same mitigation cost as the temperature target, a SLR target could bring surface warming back to the targeted temperatures within this century, lead to a reduction of surface warming of the next century, and reduce and slow down SLR in the centuries thereafter

    CD10−/ALDH− cells are the sole cisplatin-resistant component of a novel ovarian cancer stem cell hierarchy

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    It is long established that tumour-initiating cancer stem cells (CSCs) possess chemoresistant properties. However, little is known of the mechanisms involved, particularly with respect to the organisation of CSCs as stem-progenitor-differentiated cell hierarchies. Here we aimed to elucidate the relationship between CSC hierarchies and chemoresistance in an ovarian cancer model. Using a single cell-based approach to CSC discovery and validation, we report a novel, four-component CSC hierarchy based around the markers cluster of differentiation 10 (CD10) and aldehyde dehydrogenase (ALDH). In a change to our understanding of CSC biology, resistance to chemotherapy drug cisplatin was found to be the sole property of CD10−/ALDH− CSCs, while all four CSC types were sensitive to chemotherapy drug paclitaxel. Cisplatin treatment quickly altered the hierarchy, resulting in a three-component hierarchy dominated by the cisplatin-resistant CD10−/ALDH− CSC. This organisation was found to be hard-wired in a long-term cisplatin-adapted model, where again CD10−/ALDH− CSCs were the sole cisplatin-resistant component, and all CSC types remained paclitaxel-sensitive. Molecular analysis indicated that cisplatin resistance is associated with inherent- and adaptive-specific drug efflux and DNA-damage repair mechanisms. Clinically, low CD10 expression was consistent with a specific set of ovarian cancer patient samples. Collectively, these data advance our understanding of the relationship between CSC hierarchies and chemoresistance, which was shown to be CSC- and drug-type specific, and facilitated by specific and synergistic inherent and adaptive mechanisms. Furthermore, our data indicate that primary stage targeting of CD10−/ALDH− CSCs in specific ovarian cancer patients in future may facilitate targeting of recurrent disease, before it ever develops

    ApiDB: integrated resources for the apicomplexan bioinformatics resource center

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    ApiDB () represents a unified entry point for the NIH-funded Apicomplexan Bioinformatics Resource Center (BRC) that integrates numerous database resources and multiple data types. The phylum Apicomplexa comprises numerous veterinary and medically important parasitic protozoa including human pathogenic species of the genera Cryptosporidium, Plasmodium and Toxoplasma. ApiDB serves not only as a database in its own right, but as a single web-based point of entry that unifies access to three major existing individual organism databases (, and CryptoDB.org), and integrates these databases with data available from additional sources. Through the ApiDB site, users may pose queries and search all available apicomplexan data and tools, or they may visit individual component organism databases

    EzArray: A web-based highly automated Affymetrix expression array data management and analysis system

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    <p>Abstract</p> <p>Background</p> <p>Though microarray experiments are very popular in life science research, managing and analyzing microarray data are still challenging tasks for many biologists. Most microarray programs require users to have sophisticated knowledge of mathematics, statistics and computer skills for usage. With accumulating microarray data deposited in public databases, easy-to-use programs to re-analyze previously published microarray data are in high demand.</p> <p>Results</p> <p>EzArray is a web-based Affymetrix expression array data management and analysis system for researchers who need to organize microarray data efficiently and get data analyzed instantly. EzArray organizes microarray data into projects that can be analyzed online with predefined or custom procedures. EzArray performs data preprocessing and detection of differentially expressed genes with statistical methods. All analysis procedures are optimized and highly automated so that even novice users with limited pre-knowledge of microarray data analysis can complete initial analysis quickly. Since all input files, analysis parameters, and executed scripts can be downloaded, EzArray provides maximum reproducibility for each analysis. In addition, EzArray integrates with Gene Expression Omnibus (GEO) and allows instantaneous re-analysis of published array data.</p> <p>Conclusion</p> <p>EzArray is a novel Affymetrix expression array data analysis and sharing system. EzArray provides easy-to-use tools for re-analyzing published microarray data and will help both novice and experienced users perform initial analysis of their microarray data from the location of data storage. We believe EzArray will be a useful system for facilities with microarray services and laboratories with multiple members involved in microarray data analysis. EzArray is freely available from <url>http://www.ezarray.com/</url>.</p

    InnateDB: facilitating systems-level analyses of the mammalian innate immune response

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    Although considerable progress has been made in dissecting the signaling pathways involved in the innate immune response, it is now apparent that this response can no longer be productively thought of in terms of simple linear pathways. InnateDB (www.innatedb.ca) has been developed to facilitate systems-level analyses that will provide better insight into the complex networks of pathways and interactions that govern the innate immune response. InnateDB is a publicly available, manually curated, integrative biology database of the human and mouse molecules, experimentally verified interactions and pathways involved in innate immunity, along with centralized annotation on the broader human and mouse interactomes. To date, more than 3500 innate immunity-relevant interactions have been contextually annotated through the review of 1000 plus publications. Integrated into InnateDB are novel bioinformatics resources, including network visualization software, pathway analysis, orthologous interaction network construction and the ability to overlay user-supplied gene expression data in an intuitively displayed molecular interaction network and pathway context, which will enable biologists without a computational background to explore their data in a more systems-oriented manner

    Effect of Stress on Viral–Bacterial Synergy in Bovine Respiratory Disease: Novel Mechanisms to Regulate Inflammation

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    The severity of bovine respiratory infections has been linked to a variety of factors, including environmental and nutritional changes, transportation, and social reorganization of weaned calves. Fatal respiratory infections, however, usually occur when a primary viral infection compromises host defences and enhances the severity of a secondary bacterial infection. This viral–bacterial synergy can occur by a number of different mechanisms and disease challenge models have been developed to analyse host responses during these respiratory infections. A primary bovine herpesvirus-1 (BHV-1) respiratory infection followed by a secondary challenge with Mannheimia haemolytica results in fatal bovine respiratory disease (BRD) and host responses to these two pathogens have been studied extensively. We used this disease model to demonstrate that stress significantly altered the viral–bacterial synergy resulting in fatal BRD. Functional genomic analysis revealed that BHV-1 infection enhanced toll-like receptors (TLR) expression and increased pro-inflammatory responses which contribute to the severity of a Mannheimia haemolytica infection. TLRs play a critical role in detecting bacterial infections and inducing pro-inflammatory responses. It is difficult to understand, however, how stress-induced corticosteroids could enhance this form of viral–bacterial synergy. Nuclear translocation of the glucocorticoid receptor activates cell signalling pathways which inhibit both TLR signalling and pro-inflammatory responses. The apparent conundrum between stress-induced corticosteroids and enhanced BRD susceptibility is discussed in terms of present data and previous investigations of stress and respiratory disease

    Identification of the Regulatory Logic Controlling Salmonella Pathoadaptation by the SsrA-SsrB Two-Component System

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    Sequence data from the past decade has laid bare the significance of horizontal gene transfer in creating genetic diversity in the bacterial world. Regulatory evolution, in which non-coding DNA is mutated to create new regulatory nodes, also contributes to this diversity to allow niche adaptation and the evolution of pathogenesis. To survive in the host environment, Salmonella enterica uses a type III secretion system and effector proteins, which are activated by the SsrA-SsrB two-component system in response to the host environment. To better understand the phenomenon of regulatory evolution in S. enterica, we defined the SsrB regulon and asked how this transcription factor interacts with the cis-regulatory region of target genes. Using ChIP-on-chip, cDNA hybridization, and comparative genomics analyses, we describe the SsrB-dependent regulon of ancestral and horizontally acquired genes. Further, we used a genetic screen and computational analyses integrating experimental data from S. enterica and sequence data from an orthologous regulatory system in the insect endosymbiont, Sodalis glossinidius, to identify the conserved yet flexible palindrome sequence that defines DNA recognition by SsrB. Mutational analysis of a representative promoter validated this palindrome as the minimal architecture needed for regulatory input by SsrB. These data provide a high-resolution map of a regulatory network and the underlying logic enabling pathogen adaptation to a host
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