Miracle-dz/UniFAR-FTUs huggingface dataset:
Autonomous end to end QoS monitoring

Verifying that each flow in the network satisfies its QoS requirements is one of the biggest scalability challenges in the current DiffServ architecture. This task is usually performed by a centralized allocation entity that monitors the flows' QoS parameters. Efficient detection of problematic flows is even more challenging when considering aggregated information such as the end to end delay suffered by packets belonging to a specific flow. Known oblivious and reactive monitoring techniques do not scale well when the number of flows and the length of their paths increase, and when the network load increases. This is due both to load on the centralized bandwidth allocation entity and to the excessive number of monitoring and control messages needed. We propose a new monitoring paradigm termed autonomous monitoring, in which the network itself (i.e. the routers along the flow path) is responsible to discover when a violation of the SLA occurs (or is soon to occur). Only in such cases the centralized allocation entity is notified, and can take the required actions. We study the performance of this new distributed algorithm through theoretical analysis and extensive simulations. Our results indicate that in addition to dramatically reducing the load from the centralized allocation entity, the amount of network traffic needed is relatively small and thus the new monitoring scheme scales well.
The international workshop on meibomian gland dysfunction: report of the subcommittee on management and treatment of meibomian gland dysfunction.

The goals of the subcommittee were to review the current practice and published evidence of medical and surgical treatment options for meibomian gland dysfunction (MGD) and to identify areas with conflicting, or lack of, evidence, observations, concepts, or even mechanisms where further research is required. To achieve these goals, a comprehensive review of clinical textbooks and the scientific literature was performed and the quality of published evidence graded according to an agreed on standard, using objective criteria for clinical and basic research studies adapted from the American Academy of Ophthalmology Practice Guidelines1 (Table 1). It should be noted that, in many of the clinical textbooks and previous reports, terminology is often interchanged and the management of anterior and posterior blepharitis and/or meibomitis is often considered concurrently. Thus, a broad scope of documents was reviewed in this process. Consistency in terminology and global adoption of the term “meibomian gland dysfunction” would significantly aid clinical research and clinical care in MGD going forward. Table 1. Grading Level of Evidence of Clinical and Basic Research Studies1
Compact weighted composition operators on the Hardy space

A weighted composition operator C ψ,℘ takes an analytic map f on the open unit disk of the complex plane to the analytic map ψf o ℘, where ℘ is an analytic map of the open unit disk into itself and ψ is an analytic map on the open unit disk. This paper studies how the compactness of C ψ,℘ depends on the interaction between the two maps ψ and ℘.
Batch-normalized joint training for DNN-based distant speech recognition

Improving distant speech recognition is a crucial step towards flexible human-machine interfaces. Current technology, however, still exhibits a lack of robustness, especially when adverse acoustic conditions are met. Despite the significant progress made in the last years on both speech enhancement and speech recognition, one potential limitation of state-of-the-art technology lies in composing modules that are not well matched because they are not trained jointly.
Fructose Consumption, Lipogenesis, and Non-Alcoholic Fatty Liver Disease

Increased fructose consumption has been suggested to contribute to non-alcoholic fatty liver disease (NAFLD), dyslipidemia, and insulin resistance, but a causal role of fructose in these metabolic diseases remains debated. Mechanistically, hepatic fructose metabolism yields precursors that can be used for gluconeogenesis and de novo lipogenesis (DNL). Fructose-derived precursors also act as nutritional regulators of the transcription factors, including ChREBP and SREBP1c, that regulate the expression of hepatic gluconeogenesis and DNL genes. In support of these mechanisms, fructose intake increases hepatic gluconeogenesis and DNL and raises plasma glucose and triglyceride levels in humans. However, epidemiological and fructose-intervention studies have had inconclusive results with respect to liver fat, and there is currently no good human evidence that fructose, when consumed in isocaloric amounts, causes more liver fat accumulation than other energy-dense nutrients. In this review, we aim to provide an overview of the seemingly contradicting literature on fructose and NAFLD. We outline fructose physiology, the mechanisms that link fructose to NAFLD, and the available evidence from human studies. From this framework, we conclude that the cellular mechanisms underlying hepatic fructose metabolism will likely reveal novel targets for the treatment of NAFLD, dyslipidemia, and hepatic insulin resistance. Finally, fructose-containing sugars are a major source of excess calories, suggesting that a reduction of their intake has potential for the prevention of NAFLD and other obesity-related diseases.
Phytoremediation Ability of the New Heavy Metal Accumulator Plants

Environmental pollution with heavy metals is a global disaster. This study investigated metal-accumulating ability of plants growing in a lead and zinc mine area located in Hamedan, Iran. Three dominant plants, including Conium maculatum, Stachys inflata, and Reseda lutea, were collected, and the concentrations of Cd, Cu, Pb, Ni, and Zn in the aerial parts of the plants and in the soils, collected from the mine area and out of the mine, were measured via atomic absorption spectrometry. The concentrations of all the metals in the soil of the mine were greater than the control area (1 km out of mine area); Pb, Zn, Cu, Ni, and Cd were 120, 17, 17, 2.6, and 40 times higher than in the control area, respectively. In the studied plants, Pb and Zn were the highest in C. maculatum (1,200 and 820 mg kg−1, respectively). The highest concentrations of Cu, Ni, and Cd were in S. inflata (140, 96, and 20 mg kg−1, respectively). Phytoremediation tests were done using experimental pots, and results indicate that the plant species are effective accumulator plants for the phytoremediation of heavy metal–polluted soils. Specifically, C. maculatum was effective in removing Pb and Zn, S. inflata was effective in reducing Ni, and R. lutea was effective in reducing Cu.
Pulse-type classification for the Large Underground Xenon dark matter search

The Large Underground Xenon (LUX) detector [1] is a particle physics experiment that is searching for dark matter. The main component of the detector is a large vessel filled with liquid xenon that acts a target for dark matter particles. An incoming particle interacts with an atom of xenon and creates an initial burst of photons and liberates electrons. The electrons then drift upwards through the liquid xenon and release a second burst of photons as they cross the liquidgas interface through a process called electroluminescence. The first and second bursts of photons are called S1 and S2. These signals are detected by grids of photomultiplier tubes above and below the liquid xenon. Based on differences between S1 and S2 waveforms, it can be predicted whether the incoming particle interacted with the electron cloud or nucleus of a xenon atom. The key to detecting a dark matter signal is accurately separating these types of events. Therefore, it is imperative that S1 signals, S2 signals, and other pulse types are labeled correctly with high precision. The importance of this task is increased because of the vanishingly small proposed rate of dark matter interaction and the relatively high amount of background events. While the current classification performed by the LUX data-processing software is ∼99% accurate, it has several limitations. For these reasons, I developed a new pulse-type classifier which takes various quantities relating to a pulse waveform, and predicts a class for the pulse. My algorithm is able to match the current LUX classification in accuracy, while providing new insights into the physics of the processes being studied and a confidence level for each classification.
[Epidemiology and genetics of chronic inflammatory bowel disease].

De nombreux facteurs etiologiques suspectes : Les maladies inflammatoires chroniques de l'intestin sont des maladies relativement frequentes dont l'incidence annuelle est de 8,1 pour 100000 habitants dans le nord de la France. Il existe des variations seculaires et geographiques d'incidence de ces maladies qui suggerent le role de facteurs environnementaux qui semblent associes au mode de vie de type « occidental». Parmi ceux-ci, le tabac a un effet bien documente mais oppose selon qu'il s'agit de la maladie de Crohn (qu'il aggrave) ou de la rectocolite hemorragique (ou il parait avoir un effet protecteur). Le role d'agents infectieux, en particulier des mycobacteries ou du virus de la rougeole, bien que fortement suspecte, n'est actuellement demontre pour aucun d'entre eux. - Predisposition genetique : Elle a ete longtemps evoquee devant l'existence d'agregations ethniques et familiales de ces maladies. Cette predisposition genetique semble en partie commune aux deux types de maladies. Ainsi, aussi bien la maladie de Crohn que la rectocolite hemorragique sont plus frequentes dans les populations de souche caucasienne et les deux maladies sont frequement retrouvees dans la meme famille. Le risque relatif de developper l'une ou l'autre maladie pour un apparente au premier degre d'un malade est de l'ordre de 10 a 14 fois plus eleve que celui de la population generale. Deux genes de predisposition, actuellement non encore identifies, ont ete recemment localises. - Genes et environnement : Les maladies inflammatoires chroniques de l'intestin apparaissent donc comme des maladies multifactorielles faisant intervenir sur un terrain genetique predispose, des facteurs environnementaux declenchants. La poursuite des travaux epidemiologiques et genetiques devrait permettre de dissequer le role de chacun de ces facteurs et de fournir, a terme, un schema physiopathologique utile a la comprehension de ces maladies et a la prise en charge des malades.
Learning of Graph Rules for Question Answering

AnswerFinder is a framework for the development of question-answering systems. AnswerFinder is currently being used to test the applicability of graph representations for the detection and extraction of answers. In this paper we briefly describe AnswerFinder and introduce our method to learn graph patterns that link questions with their corresponding answers in arbitrary sentences. The method is based on the translation of the logical forms of questions and answer sentences into graphs, and the application of operations based on graph overlaps and the construction of paths within graphs. The method is general and can be applied to any graph-based representation of the contents of questions and answers.
Enhanced stiffness modeling of serial manipulators with passive joints

The chapter focuses on the enhanced stiffness modeling and analysis of serial kinematic chains with passive joints, which are widely used in parallel robotic systems. In contrast to previous works, the stiffness is evaluated for the loaded working mode corresponding to the static equilibrium of the elastic forces and the external wrench acting upon the manipulator end point. It is assumed that the manipulator elasticity is described by a multidimensional lumped-parameter model, which consists of a chain of rigid bodies connected by 6-dof virtual springs. Each of these springs characterize flexibility of the corresponding link or actuating joint and takes into account both their translational/rotational compliance and the coupling between them. The proposed technique allows finding the full-scale “load-deflection” relation for any given workspace point and to linearise it taking into account variation of the manipulator Jacobian due to the external load. These enable evaluating critical forces that may provoke non-linear behavior of the manipulator, such as sudden failure due to elastic instability (buckling). The advantages of the developed technique are illustrated by several examples that deal with kinematic chains employed in typical parallel manipulators. The purpose of this volume is to encourage and inspire the continual invention of robot manipulators for science and the good of humanity. The concepts of artificial intelligence combined with the engineering and technology of feedback control, have great potential for new, useful and exciting machines. The concept of eclecticism for the design, development, simulation and implementation of a real time controller for an intelligent, vision guided robots is now being explored. The dream of an eclectic perceptual, creative controller that can select its own tasks and perform autonomous operations with reliability and dependability is starting to evolve. We have not yet reached this stage but a careful study of the contents will start one on the exciting journey that could lead to many inventions and successful solutions.
Leptin in Whales: Validation and Measurement of mRNA Expression by Absolute Quantitative Real-Time PCR

Leptin is the primary hormone in mammals that regulates adipose stores. Arctic adapted cetaceans maintain enormous adipose depots, suggesting possible modifications of leptin or receptor function. Determining expression of these genes is the first step to understanding the extreme physiology of these animals, and the uniqueness of these animals presents special challenges in estimating and comparing expression levels of mRNA transcripts. Here, we compare expression of two model genes, leptin and leptin-receptor gene-related product (OB-RGRP), using two quantitative real-time PCR (qPCR) methods: “relative” and “absolute”. To assess the expression of leptin and OB-RGRP in cetacean tissues, we first examined how relative expression of those genes might differ when normalized to four common endogenous control genes. We performed relative expression qPCR assays measuring the amplification of these two model target genes relative to amplification of 18S ribosomal RNA (18S), ubiquitously expressed transcript (Uxt), ribosomal protein 9 (Rs9) and ribosomal protein 15 (Rs15) endogenous controls. Results demonstrated significant differences in the expression of both genes when different control genes were employed; emphasizing a limitation of relative qPCR assays, especially in studies where differences in physiology and/or a lack of knowledge regarding levels and patterns of expression of common control genes may possibly affect data interpretation. To validate the absolute quantitative qPCR methods, we evaluated the effects of plasmid structure, the purity of the plasmid standard preparation and the influence of type of qPCR “background” material on qPCR amplification efficiencies and copy number determination of both model genes, in multiple tissues from one male bowhead whale. Results indicate that linear plasmids are more reliable than circular plasmid standards, no significant differences in copy number estimation based upon background material used, and that the use of ethanol precipitated, linearized plasmid preparation produce the most reliable results.
Improved OSIC decoder for spatially multiplexed system

This paper proposes to use candidate symbol table for the decoding of the first few substreams for spatially multiplexed system. In the new decoding algorithm, we generate candidate symbol table (CST) and do ordered successive interference cancellation (OSIC) for each candidates. At the end, Maximum Likelihood (ML) criteria is used to determine the optimum transmit symbol vector among the estimated candidates. Simulation result shows that the size of CST can be maintained to be small, even if the number of bits per symbol increases. Simulation results show that this algorithm gives us performance close to ML decoder, and outperforms maximum likelihood decision feedback equalizer (ML-DFE) and channel-based adaptive group detection based OSIC (AGD-OSIC).
European Conference on Information Systems ( ECIS ) 5-15-2012 BEYOND EA FRAMEWORKS : TOWARDS AN UNDERSTANDING OF THE ADOPTION OF ENTERPRISE ARCHITECTURE MANAGEMENT

Despite the increasing popularity of enterprise architecture management (EAM) in practice, many EAM initiatives either do not fully meet the expected targets or fail. EAM frameworks have been suggested as guidelines to EAM implementation, but our experience indicates that very few companies follow the steps prescribed by such frameworks. Motivated by the diverse approaches that we have observed in practice, our research strives for a broader understanding of how companies adopt EAM in their organizations. We address two questions: (1) Which approaches do companies take in adopting EAM? (2) What factors influence EAM adoption? To answer these questions, we developed an analysis framework to conceptualize EAM adoption and its contextual factors. Based on a set of eight case studies, we explore situational EAM designs and derive four EAM archetypes, which illustrate very diverse EAM adoption approaches in different situations. Our research helps broaden knowledge of EAM adoption by considering multi-dimensional and context-dependent EAM designs. It thereby relativizes the importance of frameworks and modeling, which we find over-emphasized in existing EA research. Our findings also offer starting points for prescriptive EAM research, supporting the successful introduction of EAM in organizations by taking contingencies into account.
Prevention and management of pain and stress in the neonate

Neonates have blood work for newborn screening in their first days of life, and preterm and sick hospitalized infants often require repeated invasive needle-related procedures over the duration of their hospitalization. Reducing newborn infants' pain during such painful procedures is important and may reduce the risk of negative sequela of poorly treated procedural pain. High-quality synthesized evidence demonstrates analgesic effects of three pain manage- ment strategies: breastfeeding; skin-to-skin care, also referred to as kangaroo care; and small amounts of sweet solutions. These strategies are simple to use, easily accessible, and extremely cost-effective. Published neonatal and infant pain guidelines include recommendations to use these strategies prior to and during painful procedures. Yet, despite the robust evidence and pain management recommendations in guidelines and national and international organizations, knowledge has not been translated into consistent normalized care in diverse maternal newborn, neonatal, and pediatric settings where painful procedures for infants take place. There may be knowledge gaps or barriers impeding consistent use of effective pain management for newborn infants. This paper will present a brief review of methods used to assess neonatal pain, followed by a summary of the evidence supporting breastfeeding, skin-to-skin care, and sweet solutions for procedural pain reduction with a discussion about barriers and facilitators to using these strategies in the clinical setting. Finally, a review of recommendations included in current neo- natal pain guidelines will be presented.
A practically constant-time MPI Broadcast Algorithm for large-scale InfiniBand Clusters with Multicast

An efficient implementation of the MPI_BCAST operation is crucial for many parallel scientific applications. The hardware multicast operation seems to be applicable to switch-based infiniband cluster systems. Several approaches have been implemented so far, however there has been no production-ready code available yet. This makes optimal algorithms to a subject of active research. Some problems still need to be solved in order to bridge the semantic gap between the unreliable multicast and MPI_BCAST. The biggest of those problems is to ensure the reliable data transmission in a scalable way. Acknowledgement-based methods that scale logarithmically with the number of participating MPI processes exist, but they do not meet the supernormal demand of high-performance computing. We propose a new algorithm that performs the MPI_BCAST operation in a practically constant time, independent of the communicator size. This method is well suited for large communicators and (especially) small messages due to its good scaling and its ability to prevent parallel process skew. We implemented our algorithm as a collective component for the Open MPI framework using native infiniband multicast and we show its scalability on a cluster with 116 compute nodes, where it saves up to 41% MPI_BCAST latency in comparison to the "TUNED" OpenMPl collective.
Secure cognitive radio system with cooperative secondary networks

In cognitive radio (CR) systems, we often use jamming schemes to improve the physical-layer security in the presence of passive eavesdroppers. However, it also needs additional signal sources to transmit artificial noise. In this paper, we investigate the multiple-input single-output (MISO) cognitive radio system where two secondary links secure each other's communication. Each secondary transmitter (ST) sends intended messages to its own receiver while acts as a friendly jammer to the other CRN. Our target is to maximize the worst-user's secrecy rate while limiting the interference in the direction of the primary receiver. We solve the problem through a sequence of convex semidefinite programs (SDPs) under individual power constraints. We also introduce two sub-optimal zero-forcing (ZF) beamforming methods, one of which solves the problem based on SDP and the other adopts the approach of Pareto-optimal parameterization in a more computationally efficient way.
Proteomic profiling of human hippocampus

The hippocampus is an important brain region playing a central role in short‐term memory formation. Information on protein expression in human hippocampus is limited and we therefore decided to generate a protein map of this pivotal brain structure thus providing protein building blocks and an analytical tool. Two‐dimensional electrophoresis with in‐gel digestion of protein spots followed by mass spectrometrical identification coupled to the Mascot search program was applied. Matrix‐assisted laser desorption/ionization‐time of flight (MALDI‐TOF) or in special cases MALDI‐TOF/TOF was used in order to warrant unambiguous identification. 266 protein spots representing 165 different proteins and 101 probable isoforms or post‐translational modifications were identified. The identified proteins were categorized into several protein groups as metabolic, cytoskeleton, antioxidant, chaperone, signaling, transcriptional, proteolytic, synaptosomal and neuronal, hypothetical and miscellaneous structures. This human hippocampus protein map provides an analytical tool for hydrophilic and even relatively small‐molecular‐weight proteins and contributes to the knowledge on protein building blocks thus forming the basis for protein‐chemical work in this brain area in health and disease.