Miracle-dz/UniFAR-FTUs huggingface dataset:
Nonsustained ventricular tachycardia in the setting of acute myocardial infarction: tachycardia characteristics and their prognostic implications.

BACKGROUND Nonsustained ventricular tachycardia (NSVT) has significant prognostic implications in the setting of healing and healed myocardial infarction (MI), but only limited information is available on its importance in the setting of acute MI. We evaluated the prognostic significance of NSVT characteristics in the setting of acute MI. METHODS AND RESULTS A prospective database was used to identify 112 patients with NSVT within 72 hours of acute MI. A control group was identified matched for age, sex, type of MI, and thrombolytic treatment. Mean age was 64 to 65 years in the 2 groups with 71% to 72% men. Q-wave MI was noted in 52% to 53%, and thrombolytic therapy was administered to 31% to 32% of patients in each group. In-hospital ventricular fibrillation occurred more frequently in the NSVT group (9% versus 0% in the control group; P<0. 001), but total in-hospital (10% versus 4%) and follow-up mortality (10% versus 17%) did not differ between the 2 groups. With a Cox regression model, specific NSVT characteristics were predictive of mortality. The strongest predictor was time from presentation to occurrence of NSVT. Shortest RR interval during NSVT was also a univariate predictor of mortality. Multivariate analysis identified time from presentation to occurrence of NSVT as the strongest predictor of mortality (P<0.0001). The increased relative risk of NSVT was first significant when it occurred 13 hours from presentation and continued to increase as the time from presentation to occurrence of NSVT increased, plateauing at approximately 24 hours with a relative risk of 7.5. CONCLUSIONS Contrary to prevailing clinical opinion, NSVT that occurs in the setting of acute MI does have important prognostic significance. Specifically, the currently accepted notion that NSVT that occurs within 48 hours of acute MI has no prognostic significance needs to be adjusted. Although NSVT that occurs within the first several hours of presentation does not have an associated adverse prognosis, NSVT that occurs beyond the first several hours after presentation is associated with significant increases in relative risk.
Achieving the desired dynamic behavior in multi-robot systems interacting with the environment

In this paper we consider the problem of controlling the dynamic behavior of a multi-robot system while interacting with the environment. In particular, we propose a general methodology that, by means of locally scaling interrobot coupling relationships, leads to achieving a desired interactive behavior. The proposed method is shown to guarantee passivity preservation, which ensures a safe interaction. The performance of the proposed methodology is evaluated in simulation, over large-scale multi-robot systems.
Application of implication operators versus regression analysis: A case study of factors influencing differentials in price levels among counties in Florida

The article constitutes an additional case study of the application of implication operators and this time their performance is evaluated in comparison to the performance of linear regression techniques. Both methodologies are applied for the purpose of determining what factors are influencing price level differentials among counties of Florida. Eleven variables were selected as explanatory variables. In the process of applying both methodologies, the advantages as well as disadvantages of each are examined. Utilizing both methodologies, the analysis involved 12 annual cross section runs, as well as one pooled cross section‐time series run. the analysis consisted of using traditional linear regression methodologies on the one hand, and four different implication operators, on the other hand. Tables I through XXXV display the results of this empirical case study. the major conclusions could be briefly summarized as follows: Both methodologies show some consistency of results from year to year, but that consistency is limited‐as could be expected. The variables utilized in this study are not expected to explain 100% of the variations in price levels. In other words, it could be expected that other factors in addition to the eleven explanatory variables could have impact on the price levels of various counties. The results of pooled regression analysis display a substantial difference in comparison to annual cross section results. In contrast, the results of year‐to‐year application of implication operators are fairly consistent with the corresponding pooled results. As the research progressed, it became apparent that conceptual advantages of implication operator methodologies over the regression methods Some very restrictive conditions are required for an appropriate application of regression methods1‐3 but not for the use of implication operators.4‐7 are countered by the incompleteness of research in that area (of implication operators) as reflected by the unavailability of significance indicators. Thus, both methods have some advantages and some disadvantages. The methodology of implication operators has a potential to become the superior method of the two, Because it does not require restrictions on the applications of the implication operators methods in contrast to the regression methods. once the research and development of these techniques is complete, and the problem of significance tests is solved. But until then, the preferred approach is to utilize both methods to extract maximum information about phenomena under investigation, and then to apply common sense to sort out and interpret the results. As a greater number of relevant but independent methods of analysis are applied to the investigation process, the results could either reinforce one another‐if they at least approximately point in the same direction, or call for some caution in the case of contradictory outcome.
Characterization of Variability in Deeply-Scaled Fully Depleted SOI Devices by Aikaterini Papadopoulou Research Project

Scaling of CMOS technology into the deep submicron regime gives rise to process variability, which in turn compromises circuit yield. One of the main sources of variability is random dopant fluctuation (RDF) in the channel. Fully Depleted Silicon on Insulator technology has been proposed as a promising alternative to bulk CMOS, due to it’s undoped channel which reduces RDF, as well as due to its better electrostatic control of the channel. A testchip for measurement and analysis of variability in a 22nm FDSOI process has been designed. Among other experiments, the tetstchip features an array of 11x11 tiles with variability measurement structures. Each tile contains circuits to measure IV and CV device characteristics, RO frequencies and resistor values. Scan chains and multiplexing are employed to enable analysis of a large number of DUTs with a limited pad count. The goal of this testchip is to characterize variability in FDSOI. This will be achieved by extracting systematic and random variation data from specifically designed test structures. The focus of this testchip is to decouple different sources of random variation in order to electrically measure line edge roughness and silicon thickness variation due to surface roughness, characterize the effects of source and drain doping, and quantify the contribution of ground planes and back-biasing in FDSOI variability.
Compact Representations by Finite-State Transducers

Finite-state transducers give efficient representations of many Natural Language phenomena. They allow to account for complex lexicon restrictions encountered, without involving the use of a large set of complex rules difficult to analyze. We here show that these representations can be made very compact, indicate how to perform the corresponding minimization, and point out interesting linguistic side-effects of this operation.
Interactive lecturing

Background: Lectures can vary from being entirely teacher‐centred through to those that value learner–teacher and learner–learner interaction. Advocates of the exclusively didactic (teacher‐centred) lecture aim to maximise the amount of lecture time available to their delivery of content, and regard other activities as ‘lost’ lecture time. Educational research has, however, identified the potential benefit of interactivity that promotes mentally active learning and improved learning outcomes. This article reviews the notion of ‘active learning’, outlines how active learning is promoted by interactivity and concludes with strategies for including interactivity within lectures.
Application of mathematical morphological operator in power fault signal detection

Mathematical morphology is a recently developed the typical nonlinear image processing and analysis theory. Its development is receiving more and more attention, this paper systematically introduces the application of mathematical morphological operator in power fault signal detection. This paper expounds the basic theory of mathematical morphology, morphological operator tectonic filters and morphological signal singularity detection, etc. The simulation results show that the structural elements in the choice of appropriate conditions, the mathematical morphology operators not only have excellent filter capability for various kinds of noises, but also the testing of abrupt signals has several merits, such as quick speed, low delay and easy to distinguish, etc.
Normal form based analytical investigation of nonlinear power system dynamics under excitation

The increase of power exchanges through long lines makes power systems exhibiting predominant nonlinear inter-area or local oscillations, for which the conventional linear analysis fails to offer an accurate picture. Existing 2nd Order and 3rd Order Normal Form methods make possible to do analytical investigations of the nonlinear interactions by including higherorder terms. However, those methods can only study the power system dynamics under free oscillations, usually used to study the effect of disturbances apply to the state variables, e.g the post-fault cases. When the system is subject to excitation, as variable power references or variable loads, there is no available Normal Form method in the literature making possible to study the higher-order oscillations. In this paper, for the first time to the author's knowledge, a methodology based on the Normal Form theory is proposed to give an analytical description of power system nonlinear dynamic response of excited power systems. The proposed method makes possible to simplify the initial problem by decomposing the complex power system dynamics into a set of simpler normal dynamics. The proposed analytical normal dynamics are validated using time-domain simulations and open the way to new analyzing tools for power grids.
Acute Effects of Exogenous Hormone Administration on Postprandial Acylation Stimulating Protein Levels in Ovariectomized Rats after a Fat Load

Background. ASP, a potent lipogenic factor, was linked to female fat metabolism in association studies. Aim. To investigate acute effects of sex hormone treatment on postprandial ASP levels in vivo. Methods. 24 female rats were randomly divided into 4 groups including controls. The rats were ovariectomized and injected with progesterone, estrogen, or testosterone. An hour later, olive oil was administered orally. Plasma ASP and triglycerides were measured at several postprandial time points. Area under the curve (TG-AUC) represented TG clearance. Results. Only the progesterone treated group had a significant postprandial ASP increase at two hours compared to basal levels (439.8 ± 62.4 versus 253.4 ± 59.03 μg/mL, P = 0.04). Interestingly, increased ASP levels coordinated negatively with corresponding TG levels and TG-AUC postprandially, mostly evident in the opposite effects in the progesterone and testosterone treated groups. ASP levels increased 3-fold in the progesterone versus testosterone treated groups, whereas TG-AUC was significantly lower. Conclusion. These findings suggest that progesterone enhances ASP production and TG clearance simultaneously, supporting the notion of a stimulatory role for progesterone on ASP-mediated TG clearance. This is the first functional study demonstrating a cause-effect relationship between hormone treatment and ASP levels in vivo and may contribute to understanding the mechanism of progesterone function as a female lipogenic hormone.
Predicting Instructor’s Intervention in MOOC forums

Instructor intervention in student discussion forums is a vital component in Massive Open Online Courses (MOOCs), where personalized interaction is limited. This paper introduces the problem of predicting instructor interventions in MOOC forums. We propose several prediction models designed to capture unique aspects of MOOCs, combining course information, forum structure and posts content. Our models abstract contents of individual posts of threads using latent categories, learned jointly with the binary intervention prediction problem. Experiments over data from two Coursera MOOCs demonstrate that incorporating the structure of threads into the learning problem leads to better predictive performance.
The eFIP system for text mining of protein interaction networks of phosphorylated proteins

Protein phosphorylation is a central regulatory mechanism in signal transduction involved in most biological processes. Phosphorylation of a protein may lead to activation or repression of its activity, alternative subcellular location and interaction with different binding partners. Extracting this type of information from scientific literature is critical for connecting phosphorylated proteins with kinases and interaction partners, along with their functional outcomes, for knowledge discovery from phosphorylation protein networks. We have developed the Extracting Functional Impact of Phosphorylation (eFIP) text mining system, which combines several natural language processing techniques to find relevant abstracts mentioning phosphorylation of a given protein together with indications of protein–protein interactions (PPIs) and potential evidences for impact of phosphorylation on the PPIs. eFIP integrates our previously developed tools, Extracting Gene Related ABstracts (eGRAB) for document retrieval and name disambiguation, Rule-based LIterature Mining System (RLIMS-P) for Protein Phosphorylation for extraction of phosphorylation information, a PPI module to detect PPIs involving phosphorylated proteins and an impact module for relation extraction. The text mining system has been integrated into the curation workflow of the Protein Ontology (PRO) to capture knowledge about phosphorylated proteins. The eFIP web interface accepts gene/protein names or identifiers, or PubMed identifiers as input, and displays results as a ranked list of abstracts with sentence evidence and summary table, which can be exported in a spreadsheet upon result validation. As a participant in the BioCreative-2012 Interactive Text Mining track, the performance of eFIP was evaluated on document retrieval (F-measures of 78–100%), sentence-level information extraction (F-measures of 70–80%) and document ranking (normalized discounted cumulative gain measures of 93–100% and mean average precision of 0.86). The utility and usability of the eFIP web interface were also evaluated during the BioCreative Workshop. The use of the eFIP interface provided a significant speed-up (∼2.5-fold) for time to completion of the curation task. Additionally, eFIP significantly simplifies the task of finding relevant articles on PPI involving phosphorylated forms of a given protein. Database URL: http://proteininformationresource.org/pirwww/iprolink/eFIP.shtml
Integrated system development process for high-precision motion control systems

A cost-efficient way to achieve high-accuracy motion control is the utilization of complex control algorithms. Hence advanced motion control constitutes a class of real-time applications, for which the technical feasibility strongly depends on the achievable execution performance on the embedded processing platform. The presented modular controller structure defines a set of advanced control algorithms able minimize the tracking error, even for friction affected kinematics. Transferring the controller design to an implementation-oriented modelling level focuses on minimizing the processing latency in order to realize the required high sample rate. The utilization or even the custom development of a parallel platform becomes inevitable, which is why it is necessary to integrate both, control and embedded platform development processes. The presented process includes controller design, platform mapping and architecture optimization to address the challenge of tailoring an application-specific modular embedded processing platform already on the modelling level before interfacing state-of-the-art tool chains.
Activation of LPS-inducible genes by the antitumor agent 5,6-dimethylxanthenone-4-acetic acid in primary murine macrophages. Dissection of signaling pathways leading to gene induction and tyrosine phosphorylation.

The synthetic flavone analogue 5,6-dimethylxanthenone-4-acetic acid (5,6-MeXAA) has shown promise as an antitumor agent and is currently a candidate for clinical trials. Because 5,6-MeXAA has been shown in a murine macrophage and a human myelomonocytic cell line to induce TNF-alpha mRNA and to activate macrophages to become tumoricidal, actions that are shared with bacterial LPS, we sought to determine the level of LPS mimetic activity exhibited by this low m.w. macrophage-activating agent. To elucidate its mechanisms of action, the capacity to induce a panel of LPS-inducible genes was assessed. 5,6-MeXAA was found to induce a subset of LPS-inducible genes within the panel in both Lpsn and Lpsd primary murine macrophages. Of the six LPS-inducible genes examined, there was marked induction of IP-10, D8, and D3; low induction of TNF-alpha gene expression; and insignificant induction of TNFR-2 and IL-1 beta genes. 5,6-MeXAA was also found to be a potent inducer of IFNs in macrophages of both strains, and of increased expression of the genes that encode the IFN regulatory factors IRF-1, IRF-2, and ICSBP. In contrast with LPS, 5,6-MeXAA failed to induce significantly any of the 40- to 45-kDa tyrosine phosphoproteins induced by LPS. These data suggest that 5,6-MeXAA shares with LPS certain biochemical pathways that lead to gene induction and allow for the additional dissection of the relationship of tyrosine phosphorylation and the expression of specific genes.
Separation of Line Drawings Based on Split Faces for 3D Object Reconstruction

Reconstructing 3D objects from single line drawings is often desirable in computer vision and graphics applications. If the line drawing of a complex 3D object is decomposed into primitives of simple shape, the object can be easily reconstructed. We propose an effective method to conduct the line drawing separation and turn a complex line drawing into parametric 3D models. This is achieved by recursively separating the line drawing using two types of split faces. Our experiments show that the proposed separation method can generate more basic and simple line drawings, and its combination with the example-based reconstruction can robustly recover wider range of complex parametric 3D objects than previous methods.
Nitration of Hsp90 induces cell death

Oxidative stress is a widely recognized cause of cell death associated with neurodegeneration, inflammation, and aging. Tyrosine nitration in these conditions has been reported extensively, but whether tyrosine nitration is a marker or plays a role in the cell-death processes was unknown. Here, we show that nitration of a single tyrosine residue on a small proportion of 90-kDa heat-shock protein (Hsp90), is sufficient to induce motor neuron death by the P2X7 receptor-dependent activation of the Fas pathway. Nitrotyrosine at position 33 or 56 stimulates a toxic gain of function that turns Hsp90 into a toxic protein. Using an antibody that recognizes the nitrated Hsp90, we found immunoreactivity in motor neurons of patients with amyotrophic lateral sclerosis, in an animal model of amyotrophic lateral sclerosis, and after experimental spinal cord injury. Our findings reveal that cell death can be triggered by nitration of a single protein and highlight nitrated Hsp90 as a potential target for the development of effective therapies for a large number of pathologies.
Hierarchical Maximum Margin Learning for Multi-Class Classification

Due to myriads of classes, designing accurate and efficient classifiers becomes very challenging for multi-class classification. Recent research has shown that class structure learning can greatly facilitate multi-class learning. In this paper, we propose a novel method to learn the class structure for multi-class classification problems. The class structure is assumed to be a binary hierarchical tree. To learn such a tree, we propose a maximum separating margin method to determine the child nodes of any internal node. The proposed method ensures that two classgroups represented by any two sibling nodes are most separable. In the experiments, we evaluate the accuracy and efficiency of the proposed method over other multi-class classification methods on real world large-scale problems. The results show that the proposed method outperforms benchmark methods in terms of accuracy for most datasets and performs comparably with other class structure learning methods in terms of efficiency for all datasets.
Determinant of Sovereign Default — Does Political Factors Matter ?

In this paper, I study the impact of political risk on sovereign default. An extended model of Alesina and Tabellini (1990) shows that political instability increases the likelihood of default. To test the theoretical implication, a panel logit model is adopted to estimate the effect of political factors, along with other macroeconomic variables on the probability of default. Data from 68 countries in the period of 1970 to 2010 is used to conduct the study, including both developed and developing countries. Some key findings suggest that a country is more likely to default when i) it has a relatively younger political regime in place; ii) it faces a higher chance of political turnover; and iii) it has a less democratic political system. Economic and liquidity factors are also vital as a country with stronger growth and less external debt is less likely to experience sovereign debt crisis. Robustness tests using alternative measures of political risk and EMBI sovereign bond spreads also support the baseline findings.
Le Balanced Scorecard au filtre d'une PME française

Confrontees a la necessite d’une prise de decision rapide dans un environnement concurrentiel et incertain, de plus en plus de PME ont desormais besoin de mettre en place des systemes de management de leur performance strategique. Bien que concu a l’origine pour les grandes entreprises, le Balanced Scorecard pourrait offrir une reponse a ce besoin. Une etude de cas conduite dans une PME francaise questionne d’une part, l’applicabilite de ce modele normatif dans un contexte specifique de redressement et esquisse d’autre part, le portrait d’un tableau de bord strategique « sur-mesure » modele sur les besoins du dirigeant de cette PME.
Going on-line on a shoestring: An experiment in concurrent development of requirements and architecture

A number of on-line applications were built for a small university using a micro-sized development team. Four ideas were tested during the project: the Twin Peaks development model, using fully functional prototypes in the requirements elicitation process, some core practices of Extreme Programming, and the use of open-source software in a production environment. Certain project management techniques and their application to a micro-sized development effort were also explored. These ideas and techniques proved effective in developing many significant Internet and networked applications in a short time and at very low cost.