Miracle-dz/UniFAR-FTUs huggingface dataset:
Evidence for an Independent and Cumulative Effect of Postprandial Hypertriglyceridemia and Hyperglycemia on Endothelial Dysfunction and Oxidative Stress Generation: Effects of Short- and Long-Term Simvastatin Treatment

Background—Postprandial hypertriglyceridemia and hyperglycemia are considered risk factors for cardiovascular disease. Evidence suggests that postprandial hypertriglyceridemia and hyperglycemia induce endothelial dysfunction through oxidative stress; however, the distinct role of these two factors is a matter of debate. Methods and Results—Thirty type 2 diabetic patients and 20 normal subjects ate 3 different meals: a high-fat meal; 75 g glucose alone; and high-fat meal plus glucose. Glycemia, triglyceridemia, nitrotyrosine, and endothelial function were assayed during the tests. Subsequently, diabetics took 40 mg/d simvastatin or placebo for 12 weeks. The 3 tests were performed again at baseline, between 3 to 6 days after the start, and at the end of each study. High-fat load and glucose alone produced a decrease of endothelial function and an increase of nitrotyrosine in normal and diabetic subjects. These effects were more pronounced when high fat and glucose were combined. Short-term simvastatin treatment had no effect on lipid parameters but reduced the effect on endothelial function and nitrotyrosine observed during each different test. Long-term simvastatin treatment was accompanied by a lower increase in postprandial triglycerides, which was followed by smaller variations of endothelial function and nitrotyrosine during the tests. Conclusions—This study shows an independent and cumulative effect of postprandial hypertriglyceridemia and hyperglycemia on endothelial function, suggesting oxidative stress as common mediator of such effect. Simvastatin shows a beneficial effect on oxidative stress and endothelial dysfunction, which may be ascribed to a direct effect as well as the lipid-lowering action of the drug.
Global Methylation Profiling for Risk Prediction of Prostate Cancer

Purpose: The aim of this study was to investigate the promoter hypermethylation as diagnostic markers to detect malignant prostate cells and as prognostic markers to predict the clinical recurrence of prostate cancer. Experimental Design: DNA was isolated from prostate cancer and normal adjacent tissues. After bisulfite conversion, methylation of 14,495 genes was evaluated using the Methylation27 microarrays in 238 prostate tissues. We analyzed methylation profiles in four different groups: (i) tumor (n = 198) versus matched normal tissues (n = 40), (ii) recurrence (n = 123) versus nonrecurrence (n = 75), (iii) clinical recurrence (n = 80) versus biochemical recurrence (n = 43), and (iv) systemic recurrence (n = 36) versus local recurrence (n = 44). Group 1, 2, 3, and 4 genes signifying biomarkers for diagnosis, prediction of recurrence, clinical recurrence, and systemic progression were determined. Univariate and multivariate analyses were conducted to predict risk of recurrence. We validated the methylation of genes in 20 independent tissues representing each group by pyrosequencing. Results: Microarray analysis revealed significant methylation of genes in four different groups of prostate cancer tissues. The sensitivity and specificity of methylation for 25 genes from 1, 2, and 4 groups and 7 from group 3 were shown. Validation of genes by pyrosequencing from group 1 (GSTP1, HIF3A, HAAO, and RARβ), group 2 (CRIP1, FLNC, RASGRF2, RUNX3, and HS3ST2), group 3 (PHLDA3, RASGRF2, and TNFRSF10D), and group 4 (BCL11B, POU3F3, and RASGRF2) confirmed the microarray results. Conclusions: Our study provides a global assessment of DNA methylation in prostate cancer and identifies the significance of genes as diagnostic and progression biomarkers of prostate cancer. Clin Cancer Res; 18(10); 2882–95. ©2012 AACR.
Increasing Coverage of Translation Memories with Linguistically Motivated Segment Combination Methods

Translation memories (TMs) used in computer-aided translation (CAT) systems are the highest-quality source of parallel texts since they consist of segment translation pairs approved by professional human translators. The obvious problem is their size and coverage of new document segments when compared with other parallel data. In this paper, we describe several methods for expanding translation memories using linguistically motivated segment combining approaches concentrated on preserving the high translational quality. The evaluation of the methods was done on a medium-size real-world translation memory and documents provided by a Czech translation company as well as on a large publicly available DGT translation memory published by European Commission. The asset of the TM expansion methods were evaluated by the pre-translation analysis of widely used MemoQ CAT system and the METEOR metric was used for measuring the quality of fully expanded new translation segments.
Combining zonotopes and support functions for efficient reachability analysis of linear systems

Reachability analysis is an important technique for formally verifying continuous systems, as well as for guaranteed state estimation, stability analysis, and controller synthesis. We present a detailed assessment of the computational efficiency for the reachability analysis of linear systems with respect to the two most scalable set representations: zonotopes and support functions. As a result, we propose representing reachable sets as a combination of support functions and zonotopes. This mix of representations can be converted to polyhedra of desired (directional) precision, at a higher precision compared to exclusively using support functions or zonotopes. The benefits are shown by an in-depth analysis of computational complexity and by numerical experiments.
Impacts on attention with Computer-Supported Learning Devices

Attention has been supported to predict later effortful control [1]. Vohs & Baumeister proposed that stability in effortful control also been found from early childhood to adolescence [2]. Attention plays an important role in child development. In this paper, we are interested in modeling preschoolers' focus of attention by Computer-Supported Learning Devices (CSLD). The methodology of the study applied an experimental study on young children attention with and without CSLD. We have developed a system to estimate preschoolers' focus of attention by providing visual cues for actions. We invited five preschoolers with RFID-tagged gloves standing behind five tangible objects designed instant feedback technique to estimate their attention. In addition, we employ database to assess each individual's learning effectiveness. The system predicts preschoolers' focus of attention according to each individual's learning effectiveness. The system then presents each individual's learning outcomes on a projected screen in which the teacher simultaneously received an instant feedback of effective teaching. We have evaluated the system using the triangular data out of database, learning sheet, and in-depth interview. Results show that there are significant differences between group and gender. With CSLD, frequency analysis on attention is significantly more than control group children do (p=.001).
Two-Person Neuroscience and Naturalistic Social Communication: The Role of Language and Linguistic Variables in Brain-Coupling Research

Social cognitive neuroscience (SCN) seeks to understand the brain mechanisms through which we comprehend others’ emotions and intentions in order to react accordingly. For decades, SCN has explored relevant domains by exposing individual participants to predesigned stimuli and asking them to judge their social (e.g., emotional) content. Subjects are thus reduced to detached observers of situations that they play no active role in. However, the core of our social experience is construed through real-time interactions requiring the active negotiation of information with other people. To gain more relevant insights into the workings of the social brain, the incipient field of two-person neuroscience (2PN) advocates the study of brain-to-brain coupling through multi-participant experiments. In this paper, we argue that the study of online language-based communication constitutes a cornerstone of 2PN. First, we review preliminary evidence illustrating how verbal interaction may shed light on the social brain. Second, we advance methodological recommendations to design experiments within language-based 2PN. Finally, we formulate outstanding questions for future research.
Local pursuit as a bio-inspired computational optimal control tool

This work explores the use of a cooperative optimization algorithm, known as “local pursuit”, as a numerical tool for computing optimal control-trajectory pairs. Local pursuit is inspired by the foraging activities of ant colonies and has been the focus of recent work on cooperative control. We present a hybrid approach to numerical optimization that combines local pursuit with existing methods, and solves an optimal control problem in many small pieces, in a manner to be made precise. Our approach can overcome some important limitations of traditional nonlinear programming based techniques, leading to the ability to handle larger problems with the same resources, while avoiding difficulties due to ill-conditioning. The performance of our method is illustrated in a numerical example involving optimal orbit transfer of a simple satellite.
Implications of WMAP Observations on Li Abundance and Stellar Evolution Models

The Wilkinson Microwave Anisotropy Probe (WMAP) determination of the baryon-to-photon ratio implies, through big bang nucleosynthesis, a cosmological Li abundance larger, by a factor of 2-3, than the Li abundance plateau observed in the oldest Population II stars. It is, however, inescapable that there be a reduction by a factor of at least 1.6-2.0 of the surface Li abundance during the evolution of Population II field stars with [Fe/H] ≤ -1.5. That the observed Li should be lower than cosmologically produced Li is expected from stellar evolution models. Since at turnoff most of the Li abundance reduction is caused by gravitational settling, the presence of 6Li in some turnoff stars is also understood. Given that the WMAP implications for Li cosmological abundance and the Li Spite plateau can be naturally explained by gravitational settling in the presence of weak turbulence, there appears little need for exotic physics as suggested by some authors. Instead, there is a need for a better understanding of turbulent transport in the radiative zones of stars. This requires simulations from first principles. Rather strict upper limits to turbulent transport are determined for the Sun and Population II stars.
Configurable declare : designing customisable flexible models

Declarative languages are becoming more popular for modelling business processes with a high degree of variability. Unlike procedural languages, where the models define what is to be done, a declarative model specifies what behaviour is not allowed, using constraints on process events. In this paper, we study how to support configurability in such a declarative setting. We take Declare as an example of a declarative process modelling language and introduce Configurable Declare. Configurability is achieved by using configuration options for event hiding and constraint omission. We illustrate our approach using a case study, based on process models of ten Dutch municipalities. A Configurable Declare model is constructed supporting the variations within these municipalities.
BH 1 ( NWGR ) Domain of Bcl-2 Family Galectin-3 : A Novel Antiapoptotic Molecule with A Functional Updated

Galectin-3, a @-galactoside-bindingprotein, has been shown to be involved in tumor progression and metastasis. Here, we demonstrate that expression of galectin-3 in human breast carcinoma BT549 cells inhibits cis-dlamminedichloroplatinum (cisplatin)-induced poly(ADP-ribose) po lymerase degradation and apoptosis, without altering Bcl-2, Bcl-XL, or Bax expressions. Galectin-3 contains the NWGR amino acid sequence highly conserved in the BH1 domain of the bcl-2 gene family, and a substitution of glycine to alanine in this motif abrogated its antiapoptotic activity. Our findings demonstrate that galectin-3 inhibits apoptosis through a cysteine protease pathway and highlight the functional signif icance of the NWGR motif in apoptosis resistance of a non-Bcl-2 protein.
A noise reduction method for discrete chaotic signals and its application in communication

This paper addresses the issue for filtering noisy contaminated discrete chaotic signals. A modified cubature Kalman filter combined with QR decomposition is proposed for estimating a nonlinear discrete system. Simulation results show the proposed method can effectively reduce noise on discrete chaotic signals. In comparison with other Kalman filters, the proposed method has a better filtering performance in the case of low signal to noise ratios (SNR), and has the similar performance in the case of high SNR. In addition, it is indicated by simulations that the proposed filtering method can also effectively implement chaos-based communication when message signals are modulated by additive chaos masking.
Quadratic approximate dynamic programming for input‐affine systems

We consider the use of quadratic approximate value functions for stochastic control problems with input‐affine dynamics and convex stage cost and constraints. Evaluating the approximate dynamic programming policy in such cases requires the solution of an explicit convex optimization problem, such as a quadratic program, which can be carried out efficiently. We describe a simple and general method for approximate value iteration that also relies on our ability to solve convex optimization problems, in this case, typically a semidefinite program. Although we have no theoretical guarantee on the performance attained using our method, we observe that very good performance can be obtained in practice.Copyright © 2012 John Wiley & Sons, Ltd.
Evaluating the Domain Specificity of Mental Health–Related Mind-Sets

Mind-sets are beliefs regarding the malleability of self-attributes. Research suggests they are domain-specific, meaning that individuals can hold a fixed (immutability) mind-set about one attribute and a growth (malleability) mind-set about another. Although mind-set specificity has been investigated for broad attributes such as personality and intelligence, less is known about mental health mind-sets (e.g., beliefs about anxiety) that have greater relevance to clinical science. In two studies, we took a latent variable approach to examine how different mind-sets (anxiety, social anxiety, depression, drinking tendencies, emotions, intelligence, and personality mind-sets) were related to one another and to psychological symptoms. Results provide evidence for both domain specificity (e.g., depression mind-set predicted depression symptoms) and generality (i.e., the anxiety mind-set and the general mind-set factor predicted most symptoms). These findings may help refine measurement of mental health mind-sets and suggest that beliefs about anxiety and beliefs about changeability in general are related to clinically relevant variables.
On Twisted Forms and Relative Algebraic K‐Theory

This paper introduces a new approach to the study of certain aspects of Galois module theory by combining ideas arising from the study of the Galois structure of torsors of finite group schemes with techniques coming from relative algebraic K‐theory. 2000 Mathematics Subject Classification 11‐XX, 19‐XX.
Emotion recognition using anatomical information in facial expressions

This paper shows a work done under Affective Computing umbrella and in the field of emotion recognition. The paper explores the anatomy of a human face and builds the classification model based on it. The anatomical information of face is used to locate several points on the face and to extract the features. The features are in form of distance vectors which can be of specific person or group of persons. Canny edge detection algorithm is used to refine the extracted features and make them suitable for classifications. For classification two approaches (one vs. rest and one vs. one) of SVM (Support Vector Machine) classification for multiple classes (happy, sad, disgust, anger and surprise) have been incorporated. The paper shows the results and analysis of both these methods.
Extending classic telecommunication addressing schemes for Home Gateway based user content and services discovery

With the explosion of broadband penetration and residential gateways, users' interest in offering user generated content and services from their own home has become more and more pronounced. Home Area Networks (HANs) with rich user content are therefore emerging at the “edge” of the telecom and Internet service providers' networks. Home consumer devices such as Home Gateways (HGs) and femto base stations act as gateways for end user generated content and services. In this context, our paper addresses the important issue of how to address these devices and the users' content and services with ease, without introducing yet another addressing scheme, but instead building on top of widely used telecom network addressing. Our new addressing paradigm is based on a lightweight DHT which augments classic telecommunication addressing schemas such as SS7 and SIP. The experimental results for our prototype are based on simulations conducted on a ModelNet cluster and the results have shown that our implementation scales well while exhibiting good fault tolerant properties. Our implementation has been released to the open source community on sourceforge.net.
Genre Distinctions and Discourse Modes: Text Types Differ in their Situation Type Distributions

In this paper we explore the relationship between the genre of a text and the types of situations introduced by the clauses of the text, working from the perspective of the theory of discourse modes (Smith, 2003). The typology of situation types distinguishes between, for example, events, states, generic statements, and speech acts. We analyze texts of different genres from two English text corpora, the Penn Discourse TreeBank (PDTB) and the Manually Annotated SubCorpus (MASC) of the Open American National Corpus. Texts of different types – genres in the PDTB and subcorpora in MASC – are segmented into clauses, and each clause is labeled with the type of situation it introduces to the discourse. We then compare the distribution of situation types across different text types, finding systematic differences across genres. Our findings support predictions of the discourse modes theory and offer new insights into the relationship between text types and situation type distributions.
Human activities recognition based on poisson equation evaluation and bidirectional 2DPCA

A novel algorithm for the human activities recognition based on the Poisson images and via bidirectional two-dimensional principal component analysis (2DPCA) is presented in this note, where the Poisson images are defined by solving the Poisson equations to re-interpret the motion accumulation image (MAI). More precisely, firstly, object detection based on the Gaussian Mixture Model (GMM) is applied to acquire the binary images including moving human blobs; secondly, the Poisson image is defined to make the features extracted in the sequel robust to possible incomplete human blobs; thirdly, the principal component analysis (PCA), 2DPCA and bidirectional 2DPCA are applied, respectively, to extract the feature vectors; and finally, the nearest neighbour (NN) classifier is used to recognize the human activities. Simulation results on Weizmann database confirm the recognition performance of the proposed algorithm. Comparisons in terms of classification accuracy and time consumption in between the three methods show that the bidirectional 2DPCA is optimal.
Application of chemical reaction based pneumatic power generator to robot finger

In this paper, a pneumatic power generator based on the chemical reaction is newly proposed by using a small piston pump for the injection of the fuel. Based on the understanding of chemical reaction property, the piston pump is designed by crank-slider mechanism. The piston pump allows compact size and light weight of the entire power generation system compared to the conventional approaches using blow-down tank. In order to verify the effectiveness of the proposed power generation system, we theoretically and experimentally analyze the performance of the system. In addition, we realize the power generator and applies it to an underactuated robot finger for the feasibility test.
Support Vector Machine Soft Margin Classifiers: Error Analysis

The purpose of this paper is to provide a PAC error analysis for the q-norm soft margin classifier, a support vector machine classification algorithm. It consists of two parts: regularization error and sample error. While many techniques are available for treating the sample error, much less is known for the regularization error and the corresponding approximation error for reproducing kernel Hilbert spaces. We are mainly concerned about the regularization error. It is estimated for general distributions by a K-functional in weighted Lq spaces. For weakly separable distributions (i.e., the margin may be zero) satisfactory convergence rates are provided by means of separating functions. A projection operator is introduced, which leads to better sample error estimates especially for small complexity kernels. The misclassification error is bounded by the V-risk associated with a general class of loss functions V. The difficulty of bounding the offset is overcome. Polynomial kernels and Gaussian kernels are used to demonstrate the main results. The choice of the regularization parameter plays an important role in our analysis.
Climacteric Lowers Plasma Levels of Platelet-Derived Microparticles: A Pilot Study in Pre- versus Postmenopausal Women

Background: Climacteric increases the risk of thrombotic events by alteration of plasmatic coagulation. Up to now, less is known about changes in platelet- (PMP) and endothelial cell-derived microparticles (EMP). Methods: In this prospective study, plasma levels of microparticles (MP) were compared in 21 premenopausal and 19 postmenopausal women. Results: No altered numbers of total MP or EMP were measured within the study groups. However, the plasma values of CD61-exposing MP from platelets/megakaryocytes were higher in premenopausal women (5,364 × 106/l, range 4,384–17,167) as compared to postmenopausal women (3,808 × 106/l, range 2,009–8,850; p = 0.020). This differentiation was also significant for the subgroup of premenopausal women without hormonal contraceptives (5,364 × 106/l, range 4,223–15,916; p = 0.047; n = 15). Furthermore, in premenopausal women, higher plasma levels of PMP exposing CD62P were also present as compared to postmenopausal women (288 × 106/l, range 139–462, vs. 121 × 106/l, range 74–284; p = 0.024). This difference was also true for CD63+ PMP levels (281 × 106/l, range 182–551, vs. 137 × 106/l, range 64–432; p = 0.015). Conclusion: Climacteric lowers the level of PMP but has no impact on the number of EMP in women. These data suggest that PMP and EMP do not play a significant role in enhancing the risk of thrombotic events in healthy, postmenopausal women.
Vermont - A Versatile Monitoring Toolkit for IPFIX and PSAMP

In this paper, we present Vermont, a flexible network monitoring toolkit for packet filtering and packet sampling, flow accounting, and flow aggregation. This toolkit supports the export and collection of IPFIX/PSAMP compliant monitoring data. Packet capturing is based on the well-known pcap library, which enables deployment on various hardware platforms and operating systems. Apart from an overview to Vermont’s architecture, we present evaluation results with regard to performance, interoperability, and robustness. Furthermore, we compare Vermont to other open-source implementations of monitoring probes with respect to supported features and functionality.