Miracle-dz/UniFAR-FTUs huggingface dataset:
Anti-Inflammatory Properties of Sirtuin 6 in Human Umbilical Vein Endothelial Cells

A prominent feature of inflammatory diseases is endothelial dysfunction. Factors associated with endothelial dysfunction include proinflammatory cytokines, adhesion molecules, and matrix degrading enzymes. At the transcriptional level, they are regulated by the histone deacetylase sirtuin (SIRT) 1 via its actions on the proinflammatory transcription factor nuclear factor-κB (NF-κB). The role of SIRT6, also a histone deacetylase, in regulating inflammation in endothelial cells is not known. The aim of this study was to determine the effect of SIRT6 knockdown on inflammatory markers in human umbilical vein endothelial cells (HUVECs) in the presence of lipopolysaccharide (LPS). LPS decreased expression of SIRT6 in HUVECs. Knockdown of SIRT6 increased the expression of proinflammatory cytokines (IL-1β, IL-6, IL-8), COX-prostaglandin system, ECM remodelling enzymes (MMP-2, MMP-9 and PAI-1), the adhesion molecule ICAM-1, and proangiogenic growth factors VEGF and FGF-2; cell migration; cell adhesion to leukocytes. Loss of SIRT6 increased the expression of NF-κB, whereas overexpression of SIRT6 was associated with decreased NF-κB transcriptional activity. Taken together, these results demonstrate that the loss of SIRT6 in endothelial cells is associated with upregulation of genes involved in inflammation, vascular remodelling, and angiogenesis. SIRT6 may be a potential pharmacological target for inflammatory vascular diseases.
A Novel Approach for Color Image Enhancement Using Double Window Concept

In this paper, a new approach for the enhancement of color image using luminance and contrast enhancement based on double window concept has been presented. The proposed method exploits Hue-Saturation-Value (HSV) color space since the HSV space separates color from intensity. The hue and saturation components have been kept constant in order to avoid color distortion. In this work, the value component of the HSV has been modified in two steps. First, the non-linear transfer function is applied on the overlapping and non-overlapping window in order to enhance luminance part of the image. Further, the 2-D Gaussian filter has been used for contrast enhancement. The Gaussian filter enhances the darker pixel while neutralizing the over enhanced pixel. The modified value is combined with preserved hue and saturation components in order to obtain enhanced HSV image. Finally, the image from HSV color space is converted into RGB color space. The experimental results presented show that the color image enhanced by this algorithm is clearer, vivid and efficient.
Access to the Published Version May Require Subscription. Published with Permission From: World Scientific Gene Ontology-based Semantic Alignment of Biological Pathways by Evolutionary Search

This is an author produced version of a paper published in Journal of Bioinformatics and Computational Biology. This paper has been peer-reviewed but does not include the final publisher proof-corrections or journal pagination. A large number of biological pathways have been elucidated recently, and there is a need for methods to analyse these pathways. One class of methods compares pathways semantically, in order to discover parts that are evolutionarily conserved between species or to discover intra-species similarites. Such methods usually require that the topologies of the pathways being compared are known, i.e. that a query pathway is being aligned to a model pathway. However, sometimes the query only consists of an unordered set of gene products. Previous methods for mapping sets of gene products onto known pathways have not been based on semantic comparison of gene products using ontologies or other abstraction hierarchies. Therefore, we here propose an approach that uses a similarity function defined over Gene Ontology (GO) terms to find semantic alignments when comparing paths in biological pathways where the nodes are gene products. A known pathway graph is used as a model, and an evolutionary algorithm (EA) is used to evolve putative paths from a set of experimentally determined gene products. The method uses a measure of GO term similarity to calculate a match score between gene products, and the fitness value of each candidate path alignment is derived from these match scores. A statistical test is used to assess the significance of evolved alignments. The performance of the method has been tested using regulatory pathways for S. cerevisiae and M. musculus.
Energy-optimal routes for electric vehicles

We study the problem of electric vehicle route planning, where an important aspect is computing paths that minimize energy consumption. Thereby, any method must cope with specific properties, such as recuperation, battery constraints (over- and under-charging), and frequently changing cost functions (e. g., due to weather conditions). This work presents a practical algorithm that quickly computes energy-optimal routes for networks of continental scale. Exploiting multi-level overlay graphs [25, 30], we extend the Customizable Route Planning approach [7] to our scenario in a sound manner. This includes the efficient computation of profile queries and the adaption of bidirectional search to battery constraints. Our experimental study uses detailed consumption data measured from a production vehicle (Peugeot iOn). It reveals for the network of Europe that a new cost function can be incorporated in about five seconds, after which we answer random queries within 0.3 ms on average. Additional evaluation on an artificial but realistic [21, 35] vehicle model with unlimited range demonstrates the excellent scalability of our algorithm: Even for long-range queries across Europe it achieves query times below 5 ms on average---fast enough for interactive applications. Altogether, our algorithm exhibits faster query times than previous approaches, while improving (metric-dependent) preprocessing time by three orders of magnitude.
Ad hoc network capacity

We study the performance of wireless ad hoc networks in the limit of a large number of nodes. We first define ad hoc networks and their capacity. We then calculate a lower bound on the capacity by constructing a communications scheme that achieves it. We also determine an upper bound on the capacity by investigating the properties of any transmission schedule. Bounds indicate that for a large number of nodes n, the total network capacity increases with a rate between k/sub 1/n/sup 1/3/ and k/sub 2/n/sup 1/2/, while the per-node rate goes to zero.
Macro-Invertebrate Decline in Surface Water Polluted with Imidacloprid: A Rebuttal and Some New Analyses

Imidacloprid, the largest selling insecticide in the world, has received particular attention from scientists, policymakers and industries due to its potential toxicity to bees and aquatic organisms. The decline of aquatic macro-invertebrates due to imidacloprid concentrations in the Dutch surface waters was hypothesised in a recent paper by Van Dijk, Van Staalduinen and Van der Sluijs (PLOS ONE, May 2013). Although we do not disagree with imidacloprid's inherent toxicity to aquatic organisms, we have fundamental concerns regarding the way the data were analysed and interpreted. Here, we demonstrate that the underlying toxicity of imidacloprid in the field situation cannot be understood except in the context of other co-occurring pesticides. Although we agree with Van Dijk and co-workers that effects of imidacloprid can emerge between 13 and 67 ng/L we use a different line of evidence. We present an alternative approach to link imidacloprid concentrations and biological data. We analysed the national set of chemical monitoring data of the year 2009 to estimate the relative contribution of imidacloprid compared to other pesticides in relation to environmental quality target and chronic ecotoxicity threshold exceedances. Moreover, we assessed the relative impact of imidacloprid on the pesticide-induced potential affected fractions of the aquatic communities. We conclude that by choosing to test a starting hypothesis using insufficient data on chemistry and biology that are difficult to link, and by ignoring potential collinear effects of other pesticides present in Dutch surface waters Van Dijk and co-workers do not provide direct evidence that reduced taxon richness and abundance of macroinvertebrates can be attributed to the presence of imidacloprid only. Using a different line of evidence we expect ecological effects of imidacloprid at some of the exposure profiles measured in 2009 in the surface waters of the Netherlands.
Preserving Privacy for Interesting Location Pattern Mining from Trajectory Data

One main concern for individuals participating in the data collection of personal location history records i.e., trajectories is the disclosure of their location and related information when a user queries for statistical or pattern mining results such as frequent locations derived from these records. In this paper, we investigate how one can achieve the privacy goal that the inclusion of his location history in a statistical database with interesting location mining capability does not substantially increase risk to his privacy. In particular, we propose a e, d-differentially private interesting geographic location pattern mining approach motivated by the sample-aggregate framework. The approach uses spatial decomposition to limit the number of stay points within a localized spatial partition and then followed by density-based clustering. The e, d-differential privacy mechanism is based on translation and scaling insensitive Laplace noise distribution modulated by database instance dependent smoothed local sensitivity. Unlike the database independent e-differential privacy mechanism, the output perturbation from a e, d-differential privacy mechanism depends on a lower local sensitivity resulting in a better query output accuracy and hence, more useful at a higher privacy level, i.e., smaller e. We demonstrate our e, d-differentially private interesting geographic location discovery approach using the region quadtree spatial decomposition followed by the DBSCAN clustering. Experimental results on the real-world GeoLife dataset are used to show the feasibility of the proposed e, d-differentially private interesting location mining approach.
Web-Based Phylogenetic Assignment Tool for Analysis of Terminal Restriction Fragment Length Polymorphism Profiles of Microbial Communities

ABSTRACT Culture-independent DNA fingerprints are commonly used to assess the diversity of a microbial community. However, relating species composition to community profiles produced by community fingerprint methods is not straightforward. Terminal restriction fragment length polymorphism (T-RFLP) is a community fingerprint method in which phylogenetic assignments may be inferred from the terminal restriction fragment (T-RF) sizes through the use of web-based resources that predict T-RF sizes for known bacteria. The process quickly becomes computationally intensive due to the need to analyze profiles produced by multiple restriction digests and the complexity of profiles generated by natural microbial communities. A web-based tool is described here that rapidly generates phylogenetic assignments from submitted community T-RFLP profiles based on a database of fragments produced by known 16S rRNA gene sequences. Users have the option of submitting a customized database generated from unpublished sequences or from a gene other than the 16S rRNA gene. This phylogenetic assignment tool allows users to employ T-RFLP to simultaneously analyze microbial community diversity and species composition. An analysis of the variability of bacterial species composition throughout the water column in a humic lake was carried out to demonstrate the functionality of the phylogenetic assignment tool. This method was validated by comparing the results generated by this program with results from a 16S rRNA gene clone library.
Two-domain DNA strand displacement

We investigate the computing power of a restricted class of DNA strand displacement structures: those that are made of double strands with nicks (interruptions) in the top strand. To preserve this structural invariant, we impose restrictions on the single strands they interact with: we consider only two-domain single strands consisting of one toehold domain and one recognition domain. We study fork and join signal processing gates based on these structures, and show that these systems are amenable to formalisation and mechanical verification.
Methods for Combining Travel Cost and Contingent Valuation Data

This research explores flexibility within a two-constraint recreation demand model, which uses combined travel cost and contingent valuation data. Using a survey of California whale watchers, observed preferences are combined with stated preferences for hypothetical increases in gray whale populations. This research builds on existing combined models by deriving demand equations and corresponding willingness to pay equations from a globally flexible expenditure function. The result is a system of equations for joint estimation from a utility-theoretic, consistent recreation demand model. Since the approximating model can accurately represent the true unknown underlying function to an arbitrary degree of precision, estimates are robust and reliable.
Achieving Efficient Reliable Flooding in Low-Duty-Cycle Wireless Sensor Networks

Reliable flooding in wireless sensor networks (WSNs) is desirable for a broad range of applications and network operations. However, relatively little work has been done for reliable flooding in low-duty-cycle WSNs with unreliable wireless links. It is a challenging problem to efficiently ensure 100% flooding coverage considering the combined effects of low-duty-cycle operation and unreliable wireless transmission. In this paper, we propose a novel dynamic switching-based reliable flooding (DSRF) framework, which is designed as an enhancement layer to provide efficient and reliable delivery for a variety of existing flooding tree structures in low-duty-cycle WSNs. The key novelty of DSRF lies in the dynamic switching decision making when encountering a transmission failure, where a flooding tree structure is dynamically adjusted based on the packet reception results for energy saving and delay reduction. DSRF distinguishes itself from the existing works in that it explores both poor links and good links on demand. In addition, we define the optimal wakeup schedule-ranking problem in order to maximize the switching gain in DSRF. We prove the NP-completeness of this problem and present a heuristic algorithm with a low computational complexity. Through comprehensive performance comparisons, including the simulation of large-scale scenarios and small-scale experiments on a WSN testbed, we demonstrate that compared with the flooding protocol without DSRF enhancement, the DSRF effectively reduces the flooding delay and the total number of packet transmission by 12%' 25% and 10%' 15%, respectively. Remarkably, the achieved performance is close to the theoretical lower bound.
In-Work Benets in Search Equilibrium

We study the general equilibrium e¤ects of in-work bene ts in a search framework. Introducing in-work bene ts reduces equilibrium unemployment, moderate wages, and boost participation and search. Total employment increases as a result. Considering in-work bene ts in a general equilibrium setting reveals that employment increases mainly though the impact on job creation. This is in contrast to what is usually stressed, namely that employment increases because individuals are provided with incentives to take a job. JEL codes: J21, J38 Keywords: In-work bene ts, unemployment, participation
Why Clowns Taste Funny: The Relationship between Humor and Semantic Ambiguity

What makes us laugh? One crucial component of many jokes is the disambiguation of words with multiple meanings. In this functional MRI study of normal participants, the neural mechanisms that underlie our experience of getting a joke that depends on the resolution of semantically ambiguous words were explored. Jokes that contained ambiguous words were compared with sentences that contained ambiguous words but were not funny, as well as to matched verbal jokes that did not depend on semantic ambiguity. The results confirm that both the left inferior temporal gyrus and left inferior frontal gyrus are involved in processing the semantic aspects of language comprehension, while a more widespread network that includes both of these regions and the temporoparietal junction bilaterally is involved in processing humorous verbal jokes when compared with matched nonhumorous material. In addition, hearing jokes was associated with increased activity in a network of subcortical regions, including the amygdala, the ventral striatum, and the midbrain, that have been implicated in experiencing positive reward. Moreover, activity in these regions correlated with the subjective ratings of funniness of the presented material. These results allow a more precise account of how the neural and cognitive processes that are involved in ambiguity resolution contribute to the appreciation of jokes that depend on semantic ambiguity.
Can Survival Prediction Be Improved By Merging Gene Expression Data Sets?

Background High-throughput gene expression profiling technologies generating a wealth of data, are increasingly used for characterization of tumor biopsies for clinical trials. By applying machine learning algorithms to such clinically documented data sets, one hopes to improve tumor diagnosis, prognosis, as well as prediction of treatment response. However, the limited number of patients enrolled in a single trial study limits the power of machine learning approaches due to over-fitting. One could partially overcome this limitation by merging data from different studies. Nevertheless, such data sets differ from each other with regard to technical biases, patient selection criteria and follow-up treatment. It is therefore not clear at all whether the advantage of increased sample size outweighs the disadvantage of higher heterogeneity of merged data sets. Here, we present a systematic study to answer this question specifically for breast cancer data sets. We use survival prediction based on Cox regression as an assay to measure the added value of merged data sets. Results Using time-dependent Receiver Operating Characteristic-Area Under the Curve (ROC-AUC) and hazard ratio as performance measures, we see in overall no significant improvement or deterioration of survival prediction with merged data sets as compared to individual data sets. This apparently was due to the fact that a few genes with strong prognostic power were not available on all microarray platforms and thus were not retained in the merged data sets. Surprisingly, we found that the overall best performance was achieved with a single-gene predictor consisting of CYB5D1. Conclusions Merging did not deteriorate performance on average despite (a) The diversity of microarray platforms used. (b) The heterogeneity of patients cohorts. (c) The heterogeneity of breast cancer disease. (d) Substantial variation of time to death or relapse. (e) The reduced number of genes in the merged data sets. Predictors derived from the merged data sets were more robust, consistent and reproducible across microarray platforms. Moreover, merging data sets from different studies helps to better understand the biases of individual studies and can lead to the identification of strong survival factors like CYB5D1 expression.
Patients’ Accounts of Increased “Connectedness” and “Acceptance” After Psilocybin for Treatment-Resistant Depression

Objective: To identify patients’ perceptions of the value of psilocybin as a treatment for depression. Method: Twenty patients enrolled in an open-label trial of psilocybin for treatment-resistant depression participated in a semistructured interview at 6-month follow-up. Thematic analysis was used to identify patients’ experiences of the treatment and how it compared with previous treatments. Results: Two main change processes were identified in relation to the treatment. The first concerned change from disconnection (from self, others, and world) to connection, and the second concerned change from avoidance (of emotion) to acceptance. A third theme concerned comparison between psilocybin and conventional treatments. Patients reported that medications and some short-term talking therapies tended to reinforce their sense of disconnection and avoidance, whereas treatment with psilocybin encouraged connection and acceptance. Conclusions: These results suggest that psilocybin treatment for depression may work via paradigmatically novel means, antithetical to antidepressant medications, and some short-term talking therapies.
Simulating Cardiac Electrophysiology Using Unstructured All-Hexahedra Spectral Elements

We discuss the application of the spectral element method to the monodomain and bidomain equations describing propagation of cardiac action potential. Models of cardiac electrophysiology consist of a system of partial differential equations coupled with a system of ordinary differential equations representing cell membrane dynamics. The solution of these equations requires solving multiple length scales due to the ratio of advection to diffusion that varies among the different equations. High order approximation of spectral elements provides greater flexibility in resolving multiple length scales. Furthermore, spectral elements are extremely efficient to model propagation phenomena on complex shapes using fewer degrees of freedom than its finite element equivalent (for the same level of accuracy). We illustrate a fully unstructured all-hexahedra approach implementation of the method and we apply it to the solution of full 3D monodomain and bidomain test cases. We discuss some key elements of the proposed approach on some selected benchmarks and on an anatomically based whole heart human computational model.
'Galculator': functional prototype of a Galois-connection based proof assistant

Galculator is the name of the prototype of a proof assistant of a special brand: it is solely based on the algebra of Galois connections. When combined with the pointfree transform and tactics such as the indirect equality principle, Galois connections offer a very powerful, generic device to tackle the complexity of proofs in program verification. The paper describes the architecture of the current Galculator prototype, which is implemented in Haskell in order to steer types as much as possible. The prospect of integrating the Galculator with other proof assistants such as e.g. Coq is also discussed