Miracle-dz/UniFAR-FTUs huggingface dataset:
Properties of Rescheduling Size Invariance for Dynamic Rescheduling-Based VLIW Cross-Generation Compatibility

The object-code compatibility problem in VLIW architectures stems from their statically scheduled nature. Dynamic rescheduling (DR) is a technique to solve the compatibility problem in VLIWs. DR reschedules program code pages at first-time page faults, i.e., when the code pages are accessed for the first time during execution. Treating a page of code as the unit of rescheduling makes it susceptible to the hazards of changes in the page size during the process of rescheduling. This paper shows that the changes in the page size are only due to insertion and/or deletion of NOPs in the code. Further, it presents an ISA encoding, called list encoding, which does not require explicit encoding of the NOPs in the code. Algorithms to perform rescheduling on acyclic code and cyclic code are presented, followed by the discussion of the property of rescheduling-size invariance (RSI) satisfied by list encoding.
Dynamic Channel Allocation Using a Genetic Algorithm for a TDD Broadband Fixed Wireless Access Network

Algorithm is evaluated and compared with two existing DCA methods namely the Least Interfered (LI) and Channel Segregation (CS). These three methods are chosen from the same category in the proposed Channel Allocation Matrix. I. INTRODUCTION The rapid increase in the data rate in the Internet backbone is not paralleled with the increase in the data rate in the last mile. This causes a bottleneck for the majority of Internet users that do not enjoy fast access networks. Broadband fixed wireless access (BFWA) networks can be rapidly deployed and provide data rates that current Internet users demand. Typical BFWA network components are the Control Server (CSVR), the Access Point (AP) and the Subscriber Unit (SU) and they are arranged as shown in Fig. 1. The SU is mounted on the subscriber's site and uses a directional antenna with a horizontal beamwidth of 20° to communicate with its corresponding AP. Each AP has an antenna with a horizontal beamwidth of 60°. A CSVR is connected to K APs. The CSVR is a server that provides configuration, authentication and management systems.
Test purpose generation for service evolutions: a symbolic approach

We propose an approach to test service evolution in the context of service oriented systems. Such systems are composed of orchestrations which interact with users and coordinate services to fulfill users' requests. The tester only interacts with services through orchestrations. We propose to use symbolic execution techniques in a model based black box approach to identify test purpose characterizing first class citizen behaviors to be tested. We discuss how test purposes characterized before a service evolution may be qualified as: obsolete test purposes (no more relevant after the evolution) non regression test purposes (not impacted by the evolution) and how to identify new emergent test purposes that reflect behaviors induced by the service evolution.
Brief announcement: distributed contention resolution in wireless networks

We present and analyze simple distributed contention resolution protocols for wireless networks. In our setting, one is given n pairs of senders and receivers located in a metric space. Each sender wants to transmit a signal to its receiver at a prespecified power level, e.g., all senders use the same, uniform power level as it is typically implemented in practice. Our analysis is based on the physical model in which the success of a transmission depends on the Signal-to-Interference-plus-Noise-Ratio (SINR). The objective is to minimize the number of time slots until all signals are successfully transmitted. Our main technical contribution is the introduction of a measure called maximum average affectance enabling us to analyze random contention-resolution algorithms in which each packet is transmitted in each step with a fixed probability depending on the maximum average affectance. We prove that the schedule generated this way is only an O(log2 n) factor longer than the optimal one, provided that the prespecified power levels satisfy natural monontonicity properties. By modifying the algorithm, senders need not to know the maximum average affectance in advance but only static information about the network. In addition, we extend our approach to multi-hop communication achieving the same appoximation factor.
Anatomy of a Resource Management System for HPC-Clusters

Workstation clusters are often not only used for high-throughput computing in time-sharing mode but also for running complex parallel jobs in space-sharing mode. This poses several difficulties to the resource management system, which must be able to reserve computing resources for exclusive use and also to determine an optimal process mapping for a given system topology. On the basis of our CCS software, we describe the anatomy of a modern resource management system. Like Codine, Condor, and LSF, CCS provides mechanisms for the user-friendly system access and management of clusters. But unlike them, CCS is targeted at the effective support of space-sharing parallel computers and even metacomputers. Among other features, CCS provides a versatile resource description facility, topology-based process mapping, pluggable schedulers, and hooks to metacomputer management.
A Conversation Analysis of Social Interaction in the Functional Capacity Interview

This ethnomethodological conversation analysis study investigates how functional capacity interviews are organized in social interaction, thereby documenting recurrent assessment practices. Although interviewing is respected, due to its centrality in knowledge production in contemporary society, little is known about conducting functional capacity interviews per se. Moreover, as demonstrated in the literature review, the notion of functional capacity originates in the works of the sociologists Saad Z. Nagi and Talcott Parsons. It is likely that the very notion of functional capacity therefore conveys their sociological understanding of human functioning. A recent discussion of the social aspects of functional capacity has revealed, however, insurmountable difficulties in their original approach, which attributed functional incapacities to changes in the relationship between humans and their environment, but which was silent on the capacities that are relevant in social interaction. Thus, an alternative sociological understanding of human functioning is required, and this dissertation suggests that instead of focusing on single human subjects, we need to focus on social interaction between humans. That position allows us to elaborate and document the abilities needed in social interaction. The data for this study were drawn from a collection of videotaped welfare interviews (n=57) from three projects run between 2007 and 2009 to research and develop the assessment of functional capacity in central and southern Finland. The interviewers were professional nurses with a background in health care; the interviewees were either unemployed or retired. Each structured interview was naturally occurring and contained an interviewee-interviewer dyad. The videotaping was self-administered by the interviewers and other staff members. The videotaped data were transcribed following conventions developed by Gail Jefferson and analyzed in detail with conversation analysis methods. The results were published in four articles and document how functional capacity interviews are organized in social interaction: (1) Functional capacity interviews are document-driven interactions: there are pre-scripted questions and answer options, (2) Speakers perform the interview as a mutual collaboration. Since displays of incompetence are prominent in this type of interaction, interviewers may need to support interviewees in situ with comforting actions, (3) Social identity is demonstrably relevant and procedurally consequential in the reception of simple positive responses that do not index any answer options, (4) Social relationship can work as a resource for helping the interviewee answer questions on social functional capacity, and (5) Abilities play an important role in how intersubjectivity emerges in interaction. In the light of the analysis, it seems clear that ethnomethodological conversation analysis is a viable sociological approach for understanding human functioning in social interaction.
Markovian source separation

A maximum likelihood (ML) approach is used to separate the instantaneous mixtures of temporally correlated, independent sources with neither preliminary transformation nor a priori assumption about the probability distribution of the sources. A Markov model is used to represent the joint probability density of successive samples of each source. The joint probability density functions are estimated from the observations using a kernel method. For the special case of autoregressive models, the theoretical performance of the algorithm is computed and compared with the performance of second-order algorithms and i.i. d. -based separation algorithms.
GRASP WITH PATH-RELINKING FOR THE MULTI-PLANT CAPACITATED LOT SIZING PROBLEM

This paper addresses the independent multi-plant, multi-period, and multi-item capacitated lot sizing problem where transfers between the plants are allowed. This is an NP-hard combinatorial optimization problem and few solution methods have been proposed to solve it. We develop a GRASP (Greedy Randomized Adaptive Search Procedure) heuristic as well as a pathrelinking intensification procedure to find cost-effective solutions for this problem. In addition to this, the paper addresses applications of the proposed heuristics for the special case of the capacitated lot sizing problem with parallel machines. The results of the computational tests show that the proposed heuristics outperform other heuristics previously described in the literature. The results are confirmed by statistical tests.
Selective maturation of dendritic cells by Nippostrongylus brasiliensis‐secreted proteins drives Th2 immune responses

Helminth infections at mucosal and tissue sites strongly polarize towards Th2 immune responses, following pathways which have yet to be elucidated. We investigated whether dendritic cells (DC) exposed to gastrointestinal nematodes induce Th2 differentiation and, if so, whether this outcome reflects the absence of DC activation (the default hypothesis). We studied secreted proteins from the parasite Nippostrongylus brasiliensis, which induce Th2 development in vivo without live infection. Murine bone marrow‐derived DC pulsed with N. brasiliensis excretory/secretory antigen (NES) can, on transfer to naive recipients, prime mice for Th2 responsiveness. Heat inactivation of NES abolishes both its ability to drive Th2 responses in vivo and its capacity to stimulate DC for Th2 induction. NES, but not heat‐inactivated NES, up‐regulates DC maturation markers associated with Th2 promotion (CD86 and OX40L), with little change to CD80 and MHC class II. Moreover, DC exposed to NES readily produce IL‐6 and IL‐12p40, but not IL‐12p70. LPS induced high IL‐12p70 levels, except in DC that had been pre‐incubated with NES. These data contradict the default hypothesis, demonstrating that a helminth product (NES) actively matures DC, selectively up‐regulating CD86 and OX40L together with IL‐6 production, while blocking IL‐12p70 responsiveness in a manner consistent with Th2 generation in vivo.
Role of nucleolar dysfunction in neurodegenerative disorders: a game of genes?

Within the cell nucleus the nucleolus is the site of rRNA transcription and ribosome biogenesis and its activity is clearly essential for a correct cell function, however its specific role in neuronal homeostasis remains mainly unknown. Here we review recent evidence that impaired nucleolar activity is a common mechanism in different neurodegenerative disorders. We focus on the specific causes and consequences of impaired nucleolar activity to better understand the pathogenesis of neurodegenerative disorders, such as Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD) and amyotrophic lateral sclerosis/frontotemporal dementia (ALS/FTD). In particular, we discuss the genetic and epigenetic factors that might regulate nucleolar function in these diseases. In addition, we describe novel animal models enabling the dissection of the context-specific series of events triggered by nucleolar disruption, also known as nucleolar stress. Finally, we suggest how this novel mechanism could help to identify strategies to treat these still incurable disorders.
Learning Spatiotemporal Gaps between Where We Look and What We Focus on

When we are watching videos, there are spatiotemporal gaps between where we look (points of gaze) and what we focus on (points of attentional focus), which result from temporally delayed responses or anticipation in eye movements. We focus on the underlying structure of those gaps and propose a novel learning-based model to predict where humans look in videos. The proposed model selects a relevant point of focus in the spatiotemporal neighbor- hood around a point of gaze, and jointly learns its salience and spatiotemporal gap with the point of gaze. It tells us "this point is likely to be looked at because there is a point of focus around the point with a reasonable spatiotemporal gap. " Experimental results with a public dataset demonstrate the effectiveness of the model to predict the points of gaze by learning a particular structure of gaps with respect to the types of eye movements and those of salient motions in videos.
Modelling the Usage of Discourse Connectives as Rational Speech Acts

Discourse relations can either be implicit or explicitly expressed by markers, such as ’therefore’ and ’but’. How a speaker makes this choice is a question that is not well understood. We propose a psycholinguistic model that predicts whether a speaker will produce an explicit marker given the discourse relation s/he wishes to express. Based on the framework of the Rational Speech Acts model, we quantify the utility of producing a marker based on the information-theoretic measure of surprisal, the cost of production, and a bias to maintain uniform information density throughout the utterance. Experiments based on the Penn Discourse Treebank show that our approach outperforms stateof-the-art approaches, while giving an explanatory account of the speaker’s choice.
Treatment of hepatitis C: a systematic review.

IMPORTANCE Hepatitis C virus (HCV) infects more than 185 million individuals worldwide. Twenty percent of patients chronically infected with HCV progress to cirrhosis. New, simpler therapeutics using direct-acting antivirals that target various stages of the HCV life cycle are in development to eradicate HCV without concomitant interferon. OBJECTIVES To summarize published evidence on safety, efficacy (measured by a sustained virologic response [SVR], which is the treatment goal of undetectable plasma HCV RNA 12 or 24 weeks after therapy completion), and tolerability of current US Food and Drug Administration-approved interferon-based regimens and oral interferon-free regimens used for treating HCV infection and coinfection with human immunodeficiency virus (HIV) and HCV; to provide treatment recommendations for specialists and generalists based on published evidence. EVIDENCE REVIEW A literature search of Web of Science, Scopus, Embase, Agricola, Cochrane Library, Cinahl Plus, ClinicalTrials.gov, Conference Papers Index, Gideon, PsycINFO, Google Scholar, and Oaister was conducted from January 1, 2009, to May 30, 2014. Publications describing phase 2, 3, and 4 studies evaluating the treatment of HCV were included. Forty-one studies involving 19,063 adult patients were included. Strength of clinical data and subsequent HCV treatment recommendations were graded according to the Oxford Centre for Evidence-Based Medicine. FINDINGS Patients infected with HCV genotype 1 represent 60% to 75% of HCV infections in the United States. Hepatitis C virus genotype 1 is more difficult to cure than genotype 2 or genotype 3. Patients with HCV genotype 1 should receive treatment with sofosbuvir + pegylated interferon + ribavirin because of the shorter duration of therapy and high rates of SVR (89%-90%). Simeprevir + pegylated interferon + ribavirin is an alternative for patients with HCV genotype 1 (SVR, 79%-86%). Patients with HCV genotypes 2 and 3, representing 20% to 29% of US HCV infections, should receive therapy with sofosbuvir + ribavirin alone (SVR for genotype 2, 12 weeks' duration: 82%-93%; SVR for genotype 3, 24 weeks' duration, 80%-95%). Patients with HIV-HCV coinfection and patients with compensated cirrhosis (ie, cirrhosis but preserved synthetic liver function) should receive the same treatment as HCV-monoinfected patients. CONCLUSIONS AND RELEVANCE New, short-duration, simpler therapies result in high SVR rates for HCV-infected patients. In conjunction with increased screening for HCV as suggested by recent Centers for Disease Control and Prevention guidelines, availability of new therapies may lead to the treatment of many more people with chronic HCV infection.
A Micro-Architectural Power-Saving Technique for D-NUCA Caches

caches are cache memories that, thanks to banked organization, broadcast search and promotion/demotion mechanism, are able to tolerate the increasing wire delay effects introduced by technology scaling. As a consequence, they will outperform conventional caches (UCA, Uniform Cache Architectures) in future generation cores. Due to the promotion/demotion mechanism, we observed that the distribution of hits across the ways of a D-NUCA cache varies across applications as well as across different execution phases within a single application. In this work, we show how such a behavior can be leveraged to improve the D-NUCA power efficiency as well as to decrease its access latency. In particular, we propose: 1) A new micro architectural technique to reduce the static power consumption of a D-NUCA cache by dynamically adapting the number of active (i.e. powered-on) ways to the need of the running application; our initial evaluation shows that a strong reduction of the average number of active ways (36.9%) is achievable, without significantly affecting the IPC (-2.97%), leading to a resultant reduction of the Energy Delay Product (EDP) of 30.9%. 2) A strategy to tune the characteristic parameters of the proposed technique. 3) A variant of the technique which leads to a more aggressive power reduction strategy
Bayesian Compressive Sensing Based on Importance Models

To solve the problem that all row signals use the same reconstruction algorithm, a type of Bayesian compressive sensing based on importance models is proposed, which reconstructs more important signals firstly even if losing some unimportant signals. Compared to Bayesian compressive sensing whose performances is not well when sampling ratio is lower, the proposed algorithms can improve reconstruction quality effectively. The importance models include two processes, one is judging whether the signal is important and the other is how to reconstruct important signals better. In this paper, the improved reconstruction algorithm is based on sparse important signal and assigning measures by important weights. The two algorithms give priority to the more important column coefficient signals in the reconstruction process. The experimental results show that the proposed algorithms have better reconstruction effect than the traditional Bayesian compressive sensing, and especially, the performance of reconstruction algorithm based on assigning measures by important weights is improved obviously when the sampling rate is relatively low. Copyright © 2013 IFSA.
Ship detection in port surveillance based on context and motion saliency analysis

This paper presents an automatic ship detection approach for video-based port surveillance systems. Our approach combines context and motion saliency analysis. The context is represented by the assumption that ships only travel inside a water region. We perform motion saliency analysis since we expect ships to move with higher speed compared to the water flow and static environment. A robust water detection is first employed to extract the water region as contextual information in the video frame, which is achieved by graph-based segmentation and region-based classification. After the water detection, the segments labeled as non-water are merged to form the regions containing candidate ships, based on the spatial adjacency. Finally, ships are detected by checking motion saliency for each candidate ship according to a set of criteria. Experiments are carried out with real-life surveillance videos, where the obtained results prove the accuracy and robustness of the proposed ship detection approach. The proposed algorithm outperforms a state-of-the-art algorithm when applied to the same sets of surveillance videos.
Subspace Scores for Feature Selection in Computer Vision

Feature selection has become an essential tool in machine learning – by distilling data vectors to a small set of informative dimensions, it is possible to signiﬁcantly accelerate learning algorithms and avoid overﬁtting. Feature selection is especially important in computer vision, where large image vectors are often combined with huge synthetically generated feature sets. Inspired by recent theoretical work on dimensionality reduction for k -means clustering, we introduce an unsupervised feature selection method and evaluate its performance on fundamental vision tasks. Our approach is based on a new measure for feature importance, ‘subspace scores’, which we derive from statistical leverage scores. Sampling by subspace scores is provably effective for k -means clustering and low rank approximation – it can signiﬁcantly reduce the number of features in a dataset before solving these problems and still get nearly optimal results [11]. We verify this work by applying subspace sampling to clustering handwritten digit and face datasets. Additionally, we address a broader range of applications by proposing subspace scores as a general purpose feature selection tool for vision data, akin to Fisher [18] or Laplacian scores [39]. We provide a theoretical justiﬁcation for subspace scores, in addition to experimental results. Evaluation on a facial recognition task is promising: subspace scoring signiﬁcantly outperforms eigenface methods and a variety of standard unsupervised feature selection algorithms. In fact, it is nearly competitive with popular supervised methods for selection. These preliminary experimental results justify further exploration for vision applications.
Of Rulers, Rebels and Revenue

This paper investigates the relationship between civil war onset and state capacity, including the role that primary commodities play in that relationship. It accomplishes this task by moving the theoretical focus of the civil war literature away from an almost exclusive concern with rebels, to a consideration of both rebels and rulers as rational predators attempting to maximize their revenue. In order to deal with the endogeneity posed by including fiscal measures of state capacity in single equation models of civil war onset, the paper employs a simultaneous equations framework. This framework allows us to capture the effects of civil war onset on state capacity and vice versa, as well as the effects of primary commodities on both endogenous covariates. The main findings from this analysis include: state capacity does not affect civil war onset, but civil war onset reduces state capacity; state capacity reduces civil war incidence, just as civil war incidence reduces state capacity; and that primary products only directly affect state capacity, but they do not directly affect civil war onset or incidence as found in previous contributions to the literature.