Miracle-dz/UniFAR-FTUs huggingface dataset:
Genetic Determinants of Sudden Cardiac Death

Sudden cardiac death (SCD) is the final common end point of multiple disease processes. It results from a complex interplay of structural, metabolic, and genetic determinants. Although epidemiological risk factors such as age, prior myocardial infarction, and low ejection fraction are well established, this syndrome also has a strong genetic component. An understanding of the genetic contributions to risk could add substantially to the prediction and prevention of SCD. In this review, we explore the epidemiology, heritability, and allelic architecture of SCD and provide a detailed overview of the genetics of inherited electrophysiological and structural heart diseases that are potent risk factors for SCD. Each year, SCD claims >300 000 lives in the United States.1 Most cases, ≈80%, are related to underlying coronary artery disease. Fewer cases, ≈10% to 15%, are associated with an underlying nonischemic myopathic process such as hypertrophic cardiomyopathy (HCM) or dilated cardiomyopathy (DCM). Approximately 5% are estimated to have a primary defect of cardiac electrophysiology (eg, long-QT syndrome [LQTS] or Brugada syndrome [BS]). 2 At the population level, the conventional cardiac risk factors are powerful risk factors for SCD. For example, diabetes mellitus is associated with a marked increase in risk of SCD (odds ratio=1.7 without microvascular disease; odds ratio=2.7 with microvascular disease). 3 Among subjects with known coronary artery disease, smoking is linked to an increase in risk of SCD (hazard ratio=2.5). 4 In a multivariate analysis from the Paris Prospective Study, a 42-mg/dL increase in total cholesterol (1 SD of the sample variation) was associated with a 23% increased risk of SCD. In the same analysis, an increase of 20 mm Hg in systolic blood pressure was associated with a 23% increase in the risk of SCD.5 Furthermore, data from the Framingham Heart Study demonstrate that left ventricular hypertrophy is a risk …
Casual conversation as logical constraint satisfaction

Casual conversation seems to be the last domain in which logic may be successfully applied. We want to demonstrate here that this intuition is incorrect. On the contrary, logic offers a new perspective on conversation, not at the behavioural level, but at the argumentative level. By studying the way arguments are logically linked together, we can observe new phenomena, like conflicting beliefs or conflicting desires that are shared by participants, and strategies to escape from such situations. From this new perspective, conversation emerges as a logical constraint satisfaction process.
Hand gesture recognition using RGB-D cues

In this paper, we propose a hand gesture recognition method in the clutter background by fusing the RGB-D cues. Since the hand localization is the key issue, we propose a coarse-to-fine procedure to detect hand accurately, which combines the statistic skin model using color information with depth prior knowledge. By detecting the skin candidate regions on the color image with Gaussian Mixture Model (GMM) skin model, hand region is obtained by compounding the depth information with the assumption that hands are at the closest position to the camera in all skin regions. Then, a new descriptor based on saliency point is used to represent the binary hand properly. A new hand model containing the wrist is proposed and the gesture recognition based on special points is applied. The experiment results demonstrate that our method performs better than NMI and moment based methods with a 96.2% recognition rate.
Nitrogen‐stable isotope signatures in estuarine food webs: A record of increasing urbanization in coastal watersheds

Nutrient enrichment as a result of anthropogenic activity concentrated along the land‐sea margin is increasing eutrophication of near‐shore waters across the globe. Management of eutrophication in the coastal zone has been hampered by the lack of a direct method to trace nitrogen sources from land into coastal food webs. Stable isotope data from a series of estuaries receiving nitrogen loads from 2 to 467 kg N ha−1 yr−1 from the Waquoit Bay watershed, Cape Cod, Massachusetts, indicate that producer and consumer 15N‐to‐14N ratios record increases in wastewater nitrogen inputs. Nitrate from groundwater‐borne wastewater introduces a 15N‐enriched tracer to estuaries. This study explicitly links anthropogenically derived nitrogen from watersheds to nitrogen in estuarine plants and animals, and suggests that wastewater nitrogen may be detectable in estuarine biota at relatively low loading rates, before eutrophication leads to major changes in species composition and abundance within estuarine food webs.
Identification of cis Elements Directing Termination of Yeast Nonpolyadenylated snoRNA Transcripts

ABSTRACT RNA polymerase II (Pol II) termination is triggered by sequences present in the nascent transcript. Termination of pre-mRNA transcription is coupled to recognition of cis-acting sequences that direct cleavage and polyadenylation of the pre-mRNA. Termination of nonpolyadenylated [non-poly(A)] Pol II transcripts in Saccharomyces cerevisiae requires the RNA-binding proteins Nrd1 and Nab3. We have used a mutational strategy to characterize non-poly(A) termination elements downstream of the SNR13 and SNR47 snoRNA genes. This approach detected two common RNA sequence motifs, GUA[AG] and UCUU. The first motif corresponds to the known Nrd1-binding site, which we have verified here by gel mobility shift assays. We also show that Nab3 protein binds specifically to RNA containing the UCUU motif. Taken together, our data suggest that Nrd1 and Nab3 binding sites play a significant role in defining non-poly(A) terminators. As is the case with poly(A) terminators, there is no strong consensus for non-poly(A) terminators, and the arrangement of Nrd1p and Nab3p binding sites varies considerably. In addition, the organization of these sequences is not strongly conserved among even closely related yeasts. This indicates a large degree of genetic variability. Despite this variability, we were able to use a computational model to show that the binding sites for Nrd1 and Nab3 can identify genes for which transcription termination is mediated by these proteins.
Architecture of a natural disasters management framework and its application to risk assessment

In this paper, the service-based architecture of a framework for the management of natural disasters is presented. This proposal combines last trends in the design of Geographic Information Systems, namely web service technologies and OGC standards (including the Sensor Web), with Multicriteria Decision Analysis techniques, which enable the incorporation of the expert's knowledge into the system. The framework becomes this way a real Spatial Decision Support System. Research needs identified during the design of the architecture are described in the paper. Finally, the forest fire risk assessment in Galicia is considered as a real scenario for the application of the proposed framework.
Regulation of mitochondrial morphology and inheritance by Mdm10p, a protein of the mitochondrial outer membrane

Yeast cells with the mdm10 mutation possess giant spherical mitochondria and are defective for mitochondrial inheritance. The giant mitochondria display classical features of mitochondrial ultrastructure, yet they appear incapable of movement or division. Genetic analysis indicated that the mutant phenotypes resulted from a single nuclear mutation, and the isolated MDM10 gene restored wild-type mitochondrial distribution and morphology when introduced into mutant cells. MDM10 encodes a protein of 56.2 kD located in the mitochondrial outer membrane. Depletion of Mdm10p from cells led to a condensation of normally extended, tubular mitochondria into giant spheres, and reexpression of the protein resulted in a rapid restoration of normal mitochondrial morphology. These results demonstrate that Mdm10p can control mitochondrial morphology, and that it plays a role in the inheritance of mitochondria.
Cross-layer analysis of malware datasets for malicious campaigns identification

In this paper, we investigate the problem of detecting correlations among datasets containing malicious data concerned with various types of network attacks and related events of the infections taken from a numerous sources and organizations. We propose a graph based technique to depict relationships between malicious data based on values of attributes related both to attackers and victims, and referred to different layers of the OSI model. The presented model can be used to fast, automatic identification of malware campaigns. The case study described in the paper demonstrates the performance of our method.
3D reconstruction of synaptic and nuclear corticosteroid receptors distribution density in the amygdala: a feasibility study

This project tested a new way of looking at different types of stress receptors (corticosteroid receptors) in the brain. The method used fluorescent markers to label the stress receptors in brain tissue, and reconstructed microscope images in 3D by using computer software. The thesis details this new method, and demonstrates how it can be used to compare different types of stress receptors, at different locations in the amygdala.
Baeyer-Villiger monooxygenases, an emerging family of flavin-dependent biocatalysts

Baeyer-Villiger monooxygenases (BVMOs) are flavoenzymes that catalyze a remarkably wide variety of oxidative reactions such as regio- and enantioselective Baeyer-Villiger oxidations and sulfoxidations. Several of these conversions are difficult to achieve using chemical approaches. Due to their selectivity and catalytic efficiency, BVMOs are highly valuable biocatalysts for the synthesis of a broad range of fine chemicals. For a long time, only one member of this class of flavin-containing biocatalysts had been cloned and overexpressed which has limited their application for synthetic processes. Recently a number of new genes that encode BVMOs have been sequenced and overexpressed. In this paper the biocatalytic properties of recently cloned BVMOs are reviewed. Furthermore, the potential for obtaining novel BVMOs from sequenced genomes will be discussed.
Reconstructing Single Field Inflationary Actions From CMBR Data

This paper describes a general program for deriving the action of single field inflation models with nonstandard kinetic energy terms using CMBR power spectrum data. This method assumes that an action depends on a set of undetermined functions, each of which is a function of either the inflaton wave function or its time derivative. The scalar, tensor and non-gaussianity of the curvature perturbation spectrum are used to derive a set of reconstruction equations whose solution set can specify up to three of the undetermined functions. The method is then used to find the undetermined functions in various types of actions assuming power law type scalar and tensor spectra. In actions that contain only two unknown functions, the third reconstruction equation implies a consistency relation between the non-gaussianty, sound speed and slow roll parameters. In particular we focus on reconstructing a generalized DBI action with an unknown potential and warp factor. We find that for realistic scalar and tensor spectra, the reconstructed warp factor and potential are very similar to the theoretically derived result. Furthermore, physical consistency of the reconstructed warp factor and potential imposes strict constraints on the scalar and tensor spectral indices.
Optimizing boosting with discriminative criteria

We describe the use of discriminative criteria to optimize Boosting based ensembles. Boosting algorithms may create hundreds of individual classifiers in order to fit the training data. However, this strategy isn’t feasible and necessary for complex classification problems, such as real-time continuous speech recognition, in which only the combination of a few of acoustic models is practical. How to improve the classification accuracy for small size of ensemble is the focus of this paper. Two discriminative criteria that attempt to minimize the true Bayes error rate are investigated. Improvements are observed over a variety of datasets including image and speech recognition, indicating the prospective utility of these two criteria.
Ieee/acm Transactions on Computational Biology and Bioinformatics 1 towards Verified Biological Models

The last several decades have witnessed a vast accumulation of biological data and data analysis. Many of these data sets represent only a small fraction of the system's behavior, making the visualization of full system behavior difficult. A more complete understanding of a biological system is gained when different types of data (and/or conclusions drawn from the data) are integrated into a larger-scale representation or model of the system. Ideally, this type of model is consistent with all available data about the system, and it is then used to generate additional hypotheses to be tested. Computer-based methods intended to formulate models that integrate various events and to test the consistency of these models with respect to the laboratory-based observations on which they are based are potentially very useful. In addition, in contrast to informal models, the consistency of such formal computer-based models with laboratory data can be tested rigorously by methods of formal verification. We combined two formal modeling approaches in computer science that were originally developed for non-biological system design. One is the inter-object approach using the language of live sequence charts (LSCs) with the Play-Engine tool, and the other is the intra-object approach using the language of statecharts and Rhapsody as the tool. Integration is carried out using InterPlay, a simulation engine coordinator. Using these tools, we constructed a combined model comprising three modules. One module represents the early lineage of the somatic gonad of C. elegans in LSCs, while a second more detailed module in statecharts represents an interaction between two cells within this lineage that determine their developmental outcome. Using the advantages of the tools, we created a third module representing a set of key experimental data using LSCs. We tested the combined statechart-LSC model by showing that the simulations were consistent with the set of experimental LSCs. This small-scale modular example demonstrates the potential for using similar approaches for verification by exhaustive testing of models by LSCs. It also shows the advantages of these approaches for modeling biology.
Evolutionary algorithms for nurse scheduling problem

The nurse scheduling problem (NSPs) represents a difficult class of multi-objective optimisation problems consisting of a number of interfering objectives between the hospitals and individual nurses. The objective of this research is to investigate difficulties that occur during the solution of NSP using evolutionary algorithms, in particular genetic algorithms (GA). As the solution method a population-less cooperative genetic algorithm (CGA) is taken into consideration. Because contrary to competitive GAs, we have to simultaneously deal with the optimization of the fitness of the individual nurses and also optimization of the entire schedule as the final solution to the problem in hand. To confirm the search ability of CGA, first a simplified version of NSP is examined. Later we report a more complex and useful version of the problem. We also compare CGA with another multi-agent evolutionary algorithm using pheromone style communication of real ants. Finally, we report the results of computer simulations acquired throughout the experiments.
The 5S rRNA maturase, ribonuclease M5, is a Toprim domain family member

The maturation of 5S ribosomal RNA in low G+C Gram-positive bacteria is catalyzed by a highly conserved, ∼190 residue, enzyme, called ribonuclease M5 (RNase M5). Sequence alignment had predicted that the N-terminal half of RNase M5 would consist of a Toprim domain, a protein fold found in type IA and type II topoisomerases, DnaG-like primases, OLD family nucleases and RecR proteins [L. Aravind, D. D. Leipe and E. V. Koonin (1998) Nucleic Acids Res., 26, 4205–4213]. Here, we present structural modelling data and a mutational analysis of RNase M5 that confirms this hypothesis. The N-terminal half of RNase M5 can be fitted to the Toprim domain of the DnaG catalytic core. Mutation of amino acid residues highly conserved among RNase M5 enzymes and members of the Toprim domain family showed that alteration of residues critical for topoisomerase and primase activity also had a dramatic effect on the cleavage of 5S rRNA precursor by RNase M5 both in vivo and in vitro. This suggests that the mechanisms of double-stranded RNA cleavage by RNase M5 and double-stranded DNA cleavage by members of the topoisomerase family are related.
1 . 1 Jeffress ’ s localization model

delay lines gating neurons Jeffress (1948) model of auditory localization. (a) Elementary delay line and coincidence counting neuron. (b) Array of coincidence counters organized tonotopically and by interaural delay (correlation lag). (c) Pattern evoked by a wideband sound source displaced from the axis. A ridge occurs at the internal delay that compensates for the external interaural delay of 0.2 ms. The topmost curve represents the sum of cross-correlation functions over frequency ("summary crosscorrelation function"). This paper reviews models of auditory signal processing that operate in the . This is in contrast with the traditional view that the cochlea performs a Fourier transformation, and that subsequent processing is carried out in the frequency domain. We classify models into parameter , channel , and within-channel models. Phenomena accounted for are sound localization, pitch perception, vowel timbre identification, and various aspects of sound segregation ("cocktail-party") effects. Most models may be implemented based on a time-domain stochastic neural representation (spike trains) such as found in the auditory nerve. Processing involves "neural filters" based on delay lines and gating neurons (coincidence counters), that select or delete certain spikes, thereby modifying the statistics of the spike train in a way that strengthens or weakens the representation of parts of the sound environment. In particular "cancellation filters", in which the interaction is mainly inhibitory, are suggested as a likely ingredient for models of auditory processing.
Defining Statistical Timing Sensitivity for Logic Circuits With Large-Scale Process and Environmental Variations

The large-scale process and environmental variations for today's nanoscale ICs require statistical approaches for timing analysis and optimization. In this paper, we demonstrate why the traditional concept of slack and critical path becomes ineffective under large-scale variations and propose a novel sensitivity framework to assess the ldquocriticalityrdquo of every path, arc, and node in a statistical timing graph. We theoretically prove that the path sensitivity is exactly equal to the probability that a path is critical and that the arc (or node) sensitivity is exactly equal to the probability that an arc (or a node) sits on the critical path. An efficient algorithm with incremental analysis capability is developed for fast sensitivity computation that has linear runtime complexity in circuit size. The efficacy of the proposed sensitivity analysis is demonstrated on both standard benchmark circuits and large industrial examples.
Depth from Flash Depth from Flash

Digital camera technology has recently seen substantial improvements in image quality while lower prices have made it a(cid:11)ordable to the average consumer. Camera manufacturers, however, are not taking full advantage of this new medium for image capture. By (cid:12)ltering the already digitized image produced by these cameras through on-board image processing algorithms we can dramatically increase the power of digital cameras. For example, according to experts in the photographic industry, most people simply take bad pictures. Classic examples of this phenomenon are photographs taken indoors with a point-and-shoot style camera using its built-in (cid:13)ash. The subjects of these photographs often seem to have a spotlight on them, making them look bright and washed out while the rest of the photograph is dark and indistinct. This can primarily be accounted for by a well known property of point light sources: fallo(cid:11) in brightness is inversely proportional to the square of the distance between the light and the object being illuminated. A technique (cid:12)rst introduced in the (cid:12)eld of computer vision has been shown to successfully recover information about the distance between the light source and objects in the world [4]. We propose using this technique, which is readily implementable in hardware, to correct for a variety of poorly illuminated digital images.
Design and Application of RuBee-Based Telemedicine Data Acquisition System

Telemedicine can be defined as the delivery of health care and sharing of medical knowledge over a distance using telecommunication. This paper introduced the new technology of RuBee, RuBee fills the drawback of RFID tags which have no network and cannot be programmable, which has made tremendous progress for the development of the telemedicine. A brief introduction of the RuBee protocol, and analyzed the design of RuBee Router and its application in the Telemedicine System. Provide a snapshot of the applications of electronic patient record, emergency telemedicine and home monitoring etc. in wireless telemedicine systems.
Une approche uniﬁée reposant sur l’information mutuelle pour l’estimation du mouvement 2D et l’asservissement visuel

Dans reposant d’algorithmes de suivi différentiel (dans la lignée du que d’une alternative originale et robuste à l’utilisation d’informations visuelles géométriques en asservissement visuel. L’information mutuelle est une mesure de recalage introduite dans le cadre de la théorie de l’information et utilisée, principalement, dans le domaine de l’imagerie médicale pour le recalage multimodal. Utilisée récemment pour le suivi, cette mesure de similarité est reconnue pour sa robustesse par rapport aux changements d’illumination ainsi qu’aux occlusions. Nous proposons un cadre général permettant de considérer cette mesure dans le cadre d’un processus d’estimation du mouvement 2D dans une séquence d’images. La fonction de similarité reposant sur l’entropie des images étant non-linéaire, une attention particulière sera portée à l’estimation efﬁcace des paramètres du mouvement. Enﬁn, la problématique de l’estimation du mouvement étant très similaire à celui de l’asservissement visuel, nous montrerons que la même approche peut être utilisée pour réaliser des tâches de positionnement en robotique. Différents résultats valideront les développements proposés. ;
Multi-objective optimal HIV therapy based on a new model of infection dynamics

Different types of models have been introduced and utilized to analyze the AIDS dynamics. Combining the properties of previous basic models, in this paper, a new model of infection is proposed. It is assumed that HAART is available for treatment of AIDS. Amount of drug usage and the quality of treatment, are defined as two objectives of a bi-objective optimization problem, and NSGA-II is used to solve this problem. Pareto frontier, resulted from the optimization process, suggests a set of treatment strategies, which all are optimal from a perspective, and can be used in different medical and economical situations.