Miracle-dz/UniFAR-FTUs huggingface dataset:
Cardiovascular Effect of Incretin-Based Therapy in Patients with Type 2 Diabetes Mellitus: Systematic Review and Meta-Analysis

Background To assess the cardiovascular (CV) risk associated with the use of incretin-based therapy in adult patients with type 2 diabetes mellitus (T2DM) primary prevention group with low CV risks. Methods The clinical studies on incretin-based therapy published in medical journals until August 2014 were comprehensively searched using MEDLINE, EMBASE and CENTRAL with no language restriction. The studies were systemically reviewed and evaluated for CV risks using a meta-analysis approach and where they meet the following criteria: clinical trial, incidence of predefined CV disease, T2DM with no comorbidities, age > 18 years old, duration of at least 12 weeks, incretin-based therapy compared with other antihyperglycaemic agents or placebo. Statistical analyses were performed using a Mantel-Haenszel (M-H) test. The odds ratios (OR) and their 95% confidence interval (CI) were estimated and displayed for comparison. Results A total of 75 studies comprising 45,648 patients with T2DM were selected. The pooled estimate demonstrated no significance in decreased CV risk with incretin-based therapy versus control (M-H OR, 0.90; 95% CI, 0.81–1.00). Conclusions This meta-analysis suggests that incretin-based therapy show no significant protective effect on CV events in T2DM primary prevention group with low CV risks. Prospective randomized controlled trials are required to confirm the results of this analysis.
Performance of MIMO System with Receiver Employing Phased Array Antennas

This paper presents the results of computer simulation of a MIMO system comprising phased array antennas (PAA) in all receiving branches. Values of baseband channel impulse responses were calculated by the ray-tracing simulator in order to examine the system performance under relatively realistic conditions. An applicability of PAAs was investigated by means of comparison of a bit error rate (BER) of two MIMO systems working in the same environment. Receiver of the first one employed PAAs, while receiver of the latter one was provided with simple omnidirectional radiators. Additionally, each receiver was assumed to utilize two different detection methods: V-BLAST and simple matrix inversion.
Rapid development of knowledge-based systems via integrated knowledge acquisition

This paper presents a novel approach, which is based on integrated (automatic/interactive) knowledge acquisition, to rapidly develop knowledge-based systems. Linguistic rules compatible with heuristic expert knowledge are used to construct the knowledge base. A fuzzy inference mechanism is used to query the knowledge base for problem solving. Compared with the traditional interview-based knowledge acquisition, our approach is more flexible and requires a shorter development cycle. The traditional approach requires several rounds of interviews (both structured and unstructured). However, our method involves an optional initial interview, followed by data collection, automatic rule generation, and an optional final interview/rule verification process. The effectiveness of our approach is demonstrated through a benchmark case study and a real-life manufacturing application.
Who is eating where? Findings from the SocioEconomic Status and Activity in Women (SESAW) study

Abstract Objective Foods prepared outside of the home have been linked to less-than-ideal nutrient profiles for health. We examine whether the locations where meals are prepared and consumed are associated with socio-economic predictors among women. Design A cross-sectional study using self-reported data. We examined multiple locations where meals are prepared and consumed: (i) at home; (ii) fast food eaten at home; (iii) fast food eaten at the restaurant; (iv) total fast food; (v) non-fast-food restaurant meals eaten at home; (vi) non-fast-food restaurant meals eaten at the restaurant; and (vii) all non-fast-food restaurant meals. Multilevel logistic regression was used to determine whether frequent consumption of meals from these sources varied by level of education, occupation, household income and area-level disadvantage. Setting Metropolitan Melbourne, Australia. Subjects A total of 1328 women from forty-five neighbourhoods randomly sampled for the SocioEconomic Status and Activity in Women study. Results Those with higher educational qualifications or who were not in the workforce (compared with those in professional employment) were more likely to report frequent consumption of meals prepared and consumed at home. High individual- and area-level socio-economic characteristics were associated with a lower likelihood of frequent consumption of fast food and a higher likelihood of frequent consumption of meals from non-fast-food sources. The strength and significance of relationships varied by place of consumption. Conclusions The source of meal preparation and consumption varied by socio-economic predictors. This has implications for policy makers who need to continue to campaign to make healthy alternatives available in out-of-home food sources.
Energy-efficient data storage solutions under sink failures

In challenging environment, sensory data must be stored inside the network in case of sink failures. Since all sensor nodes have limited storage capacity and energy, not all the data can be stored. In order to preserve more data, we need to redistribute partial data items from storage-depleted source nodes to sensor nodes with available storage space and residual energy. In this paper, we study the data redistribution and retrieval with priority problem (DRRP) and try to preserve data that maximizing the total preserved data priorities, while minimizing data redistribution and retrieval costs. By utilizing graph transformation, we convert this problem into a minimum cost maximum weighted flow problem. In order to find the optimal solution, we propose an improved linear programming algorithm named E2 DP2 ( energy-efficient data preservation with priority). Through extensive simulations, we show that the proposed algorithm outperforms the other two traditional algorithms in terms of energy consumption.
A Sticky Wage, Limited Participation Model of Monetary Transmission

This paper studies to what extent surprise money growth may affect output, employment,and real wages from the supply side. Under nominal wage contracts, we analyze the effects of monetary shocks in a limited participation model. We observe that unanticipated money growth increases real wages, employment and output while decreasing prices. This modelling approach to the monetary transmission mechanism, while different from the more traditional demand side explanations, is consistent with empirical findings like procyclical real wages and countercyclical prices.
A robust speech rate estimation based on the activation profile from the selected acoustic unit dictionary

A typical solution for the speech rate estimation consists of two stages, which involves first computing a short-time feature contour such that most of peaks of the contour correspond to the syllable nuclei followed by the detection of the peaks of the contour corresponding to the syllable nuclei. Temporal correlation selected subband correlation (TCSSBC) is often used as a feature contour for the speech rate estimation in which correlation within and across a few selected sub-band energies are computed. In this work, instead of a fixed set of sub-bands, we learn them in a data-driven manner using a dictionary learning approach. Similarly, instead of the energy contours, we use the activation profile from the learned dictionary elements. We found that the peaks detected from the data-driven approach significantly improve the speech rate estimation when combined with the traditional TCSSBC approach using a proposed peak-merging strategy. Experiments are performed separately using Switchboard, TIMIT and CTIMIT corpora. Except Switchboard, the correlation coefficient for the speech rate estimation using the proposed approach is found to be higher than those by the TCSSBC technique - 3.1% and 5.2% (relative) improvements for TIMIT and CTIMIT respectively.
Toward a Narrative Comprehension Model of Cinematic Generation for 3D Virtual Environments

Most systems for generating cinematic shot sequences for virtual environments focus on the low-level problems of camera placement. While this approach will create a sequence of camera shots which film individual events in a virtual environment, it does not account for the high-level effects shot sequences have on viewer inferences. There are systems which are based on well known cinematography principles such as the rule of thirds and other framing principals, however these usually utilize schemas or predefined shots and do not reason about the high level cognitive effects on the viewer. In this paper a system is proposed which can reason directly about these high-level cognitive and narrative effects of a shot sequence on the viewer’s mental state.
The communities of practice in an innovative enterprise.

The emergence of the Web has brought proximity and favored partnership among different groups viewing to cooperate in the generation of knowledge and in the process of innovation. Among the organizational forms of cooperation, the communities of practice (COPs) have been notable as a propitious activity for joining work groups aiming at creating and sharing knowledge as well as problem solving (Wenger et al., 2002). For some authors, communities of practice have always been part of the informal structure of any organization. However, IT has made it possible to exchange knowledge and ideas at an unprecedented pace. The aim of this paper is to analyze the formation and performance of communities of practice as a tool for enterprise innovation. The methodology used in this paper is based on a case study of a multinational company whose performance as an innovative enterprise has been outstanding.
Design Aspects of An Energy-Efficient, Lightweight Medium Access Control Protocol for Wireless Sensor Networks

This document gives an overview of the most relevant design aspects of the lightweight medium access control (LMAC) protocol [16] for wireless sensor networks (WSNs). These aspects include selfconfiguring and localized operation of the protocol, time synchronization in multi-hop networks, network setup and strategies to reduce latency. The main goal in designing a MAC protocol for WSNs is to minimize energy waste - due to collisions of messages and idle listening - , while limiting latency and loss of data throughput. It is shown that the LMAC protocol performs well on energy-efficiency and delivery ratio [19] and can ensure a long-lived, self-configuring network of battery-powered wireless sensors. The protocol is based upon scheduled access, in which each node periodically gets a time slot, during which it is allowed to transmit. The protocol does not depend on central managers to assign time slots to nodes. WSNs are assumed to be multi-hop networks, which allows for spatial reuse of time slots, just like frequency reuse in GSM cells. In this document, we present a distributed algorithm that allows nodes to find unoccupied time slots, which can be used without causing collision or interference to other nodes. Each node takes one time slot in control to carry out its data transmissions. Latency is affected by the actual choice of controlled time slot. We present time slot choosing strategies, which ensure a low latency for the most common data traffic in WSNs: reporting of sensor readings to central sinks.
Principals, Agents and Prisoners: An Economical Perspective on Information Systems Development Practice

Information systems development takes place within an economical context. However, the economical conditions, which shape systems development in practice, are hardly researched. In this paper we are investigating the question how a given price structure influences systems development projects. Our analysis is based on a multi case study and a Grounded Theory inspired research approach. Our work is informed by economic theories, which deal with the relationship of suppliers and customers and their mutual dependency. We thus apply principal-agent theory and economic game theory in form of the prisoner’s dilemma. As a result we provide three interlinked models for understanding the impact of pricing structure on systems development practice. The main elements of these models are pricing structure, risk distribution and price level, and opportunistic behavior. We discuss how these elements are interrelated and examine their impact on information systems development in practice.
Langevin dynamics simulations of biomolecules on graphics processors

Due to the very long timescales involved (us-s), theoretical modeling of fundamental biological processes including folding, misfolding, and mechanical unraveling of biomolecules, under physiologically relevant conditions, is challenging even for distributed computing systems. Graphics Processing Units (GPUs) are emerging as an alternative programming platform to the more traditional CPUs as they provide high raw computational power that can be utilized in a wide range of scientific applications. Using a coarse-grained Self Organized Polymer (SOP) model, we have developed and tested the GPU-based implementation of Langevin simulations for proteins (SOP-GPU program). Simultaneous calculation of forces for all particles is implemented using either the particle based or the interacting pair based parallelization, which leads to a ~30-fold acceleration compared to an optimized CPU version of the program. We assess the computational performance of an end-to-end application of the SOP-GPU program, where all steps of the algorithm are running on the GPU, by profiling the associated simulation time and memory usage for a number of small proteins, long protein fibers, and large-size protein assemblies. The SOP-GPU package can now be used in the theoretical exploration of the mechanical properties of large-size protein systems to generate the force-extension and force-indentation profiles under the experimental conditions of force application, and to relate the results of single-molecule experiments in vitro and in silico.
Parallel-Inverter System With Failure Isolation and Hot-Swap Features

This paper presents the analysis, design, and implementation of a parallel-inverter system with failure isolation and hot-swap features. The system is controlled with a system control unit to achieve output voltage regulation, inverter synchronization, and the aforementioned features. By incorporating a current- weighting-distribution control, the system allows inverters with identical or different power ratings. The failure isolation feature is achieved with a scanning circuit, a resistor-capacitor filter, and transistors, which are also used in achieving the hot-swap one. In the proposed system, power capacity can be readily expanded, and inverter-failure disturbance can be correspondingly reduced. Experimental results that are obtained from a six-inverter system have illustrated the discussed features and significantly demonstrated its feasibility, improving system reliability, and stability.
Complex and degraded color document image binarization

We present a document binarization scheme that is intended at consistently binarizing a range of degraded color document images. The proposed solution makes use of a mean-shift algorithm based segmentation applied at different scales of the image and a contrast enhanced version of the popular Niblack's thresholding method. The solution has been evaluated using standard metrics used in a prominent binarization competition and has also been subject to an end-to-end evaluation by use in an OCR system. The proposed solution was found to perform at par or better than existing state of the art binarization solutions and was found to always be more consistent in performance than the state of the art.
Test suite reduction for fault detection and localization: A combined approach

The relation of test suites and actual faults in a software is of critical importance for timely product release. There are two particularily critical properties of test suites to this end: fault localization capability, to characterize the effort of finding the actually defective program elements, and fault detection capability which measures how probable is their manifestation and detection in the first place. While there are well established methods to predict fault detection capability (by measuring code coverage, for instance), characterization of fault localization is an emerging research topic. In this work, we investigate the effect of different test reduction methods on the performance of fault localization and detection techniques. We also provide new combined methods that incorporate both localization and detection aspects. We empirically evaluate the methods first by measuring detection and localization metrics of test suites with various reduction sizes, followed by how reduced test suites perform with actual faults. We experiment with SIR programs traditionally used in fault localization research, and extend the case study with large industrial software systems including GCC and WebKit.
The Effect of Common Sources of Regression Error on Benefit Estimates

Discussions of the sources of error in recreation demand analysis are common in the existing literature. The most traditional line of thought (e.g., Gum and Martin) considers the error component in predicting the individual's recreation behavior to arise from unmeasured socioeconomic factors. Others (e.g., Hanemann) attribute at least some of this error to fundamental randomness in human behavior. Applied statisticians (e.g., Hiett and Worrall) on the other hand, suggest that recall of annual number of recreational trips (i.e., the quantity demanded) is subject to substantial error. Still others (e.g., Brown, et al.) have argued that recall of explanatory variables, such as travel expenses, contains error. Despite the discussion of potential error sources, there is no work which relates the sources of error in the demand relationship with benefit measurement.1 Of practical importance in recreational demand estimation is whether error assumptions have an influence on welfare measures, since it is for public policy decision purposes that recreational demand estimation is usually undertaken. Will the estimated consumer surplus derived from demand analysis be independent of the assumed source of the error in the regression? The purpose of this paper is to explore how the assumptions about sources of error influence estimates of recreation benefits. A discussion of the various sources of error in de-
UNLocBoX A matlab convex optimization toolbox using proximal splitting methods

Convex optimization is an essential tool for machine learning, as many of its problems can be formulated as minimization problems of specific objective functions. While there is a large variety of algorithms available to solve convex problems, we can argue that it becomes more and more important to focus on efficient, scalable methods that can deal with big data. When the objective function can be written as a sum of "simple" terms, proximal splitting methods are a good choice. UNLocBoX is a MATLAB library that implements many of these methods, designed to solve convex optimization problems of the form $\min_{x \in \mathbb{R}^N} \sum_{n=1}^K f_n(x). $ It contains the most recent solvers such as FISTA, Douglas-Rachford, SDMM as well a primal dual techniques such as Chambolle-Pock and forward-backward-forward. It also includes an extensive list of common proximal operators that can be combined, allowing for a quick implementation of a large variety of convex problems.
Inferring Multiple Regulation Networks

Gaussian Graphical Models provide a convenient framework for representing dependencies between variables. Recently, this tool has received a high interest for the discovery of biological networks. The literature focuses on the case where a single network is inferred from a set of measurements, but, as data is typically scarce, several assays, where the experimental conditions affect interactions, are usually merged to infer a single network. In this paper, we describe an approach for estimating several related networks, by rendering the closeness assumption into group penalties. We provide quantitative results demonstrating the benefits of the proposed approach on artificial and real data.
Letters to friends

Cicero was a prodigious letter writer, and happily a splendid treasury of his letters has come down to us: collected and in part published not long after his death, over 800 of them were rediscovered by Petrarch and other humanists in the fourteenth century. Among classical texts this correspondence is unparalleled; nowhere else do we get such an intimate look at the life of a prominent Roman and his social world, or such a vivid sense of a momentous period in Roman history. The 435 letters collected here represent Cicero's correspondence with friends and acquaintances over a period of 20 years, from 62 B.C., when Cicero's political career was at its peak, to 43 B.C., the year he was put to death by the victorious Triumvirs. They range widely in substance and style, from official dispatches and semi-public letters of political importance to casual notes that chat with close friends about travels and projects, domestic pleasures and books, and questions currently debated. This new Loeb Classical Library edition of the Letters to Friends, in three volumes, brings together D. R. Shackleton Bailey's standard Latin text, now updated, and a revised version of his much admired translation first published by Penguin. This authoritative edition complements the new Loeb edition of Cicero's Letters to Atticus, also translated by Shackleton Bailey.
Iron Supplementation Effects on Redox Status following Aseptic Skeletal Muscle Trauma in Adults and Children

Exercise-induced skeletal muscle microtrauma is characterized by loss of muscle cell integrity, marked aseptic inflammatory response, and oxidative stress. We examined if iron supplementation would alter redox status after eccentric exercise. In a randomized, double blind crossover study, that was conducted in two cycles, healthy adults (n = 14) and children (n = 11) received daily either 37 mg of elemental iron or placebo for 3 weeks prior to and up to 72 h after an acute eccentric exercise bout. Blood was drawn at baseline, before exercise, and 72 h after exercise for the assessment of iron status, creatine kinase activity (CK), and redox status. Iron supplementation at rest increased iron concentration and transferrin saturation (p < 0.01). In adults, CK activity increased at 72 h after exercise, while no changes occurred in children. Iron supplementation increased TBARS at 72 h after exercise in both adults and children; no changes occurred under placebo condition. Eccentric exercise decreased bilirubin concentration at 72 h in all groups. Iron supplementation can alter redox responses after muscle-damaging exercise in both adults and children. This could be of great importance not only for healthy exercising individuals, but also in clinical conditions which are characterized by skeletal muscle injury and inflammation, yet iron supplementation is crucial for maintaining iron homeostasis. This study was registered at Clinicaltrials.gov Identifier: NCT02374619.