Miracle-dz/UniFAR-FTUs huggingface dataset:
A service-oriented architecture (SOA) framework for choreography verification

Service composition is fundamental in the SOA paradigm. It is oriented to build complex applications from smaller components. The design of composing service-based applications is mainly carried out throughout two composition techniques namely choreography and orchestration. Although these two composition models are different in nature, they are complementary. Choreography presents an abstract description of protocols. It offers a top view of the management rules which govern the interactions between the services involved in a decentralized application. On the other hand, orchestration provides details of the executable process at single peers which are necessary for the implementation of choreography. In this context, one open research problem, is the correct transformation of choreography specifications to orchestration specifications since orchestration provides more details to choreography specification. The choreography transformation has been the subject of several research works. Nevertheless, the existing works have considered that the choreography, on which their transformations are based, is correct by default. So, they have not sought to verify whether it is free of any error or not. Actually, due to the message passing nature of web services interaction, many subtle errors can occur. So, it is crucial to implement a checking process oriented to identify eventual incompatibilities that may arise. For this purpose, we present a formal verification approach based on the SPIN model-checker. The approach automatically transforms WS-CDL choreography specifications to Promela code for verification purposes. We verify non-functional properties that are expressed with linear temporal logic.
Employing Personality Feature to Rank the Influential Users in Signed Networks

Social networks are an important part of the everyday activities of a big part of people. Different type of socialbased activities (e.g. online product shopping, question answering forums and etc.) create a vast connection between users. One of the most important features of these networks is knowledge sharing. This knowledge usually provides better insight for the users and consequently has a direct impact on the decision made by them. For example, online shopping members usually take their decision based on this shared information. But the main issue is there are a huge amount of shared knowledge without an accurate mechanism to determine their validity. One approach is to count more on the influential users opinions in the system and toward this end, several ranking algorithms have been proposed. But the existing algorithms for users ranking don't consider the personality features of users in their methodology. In this paper, we use this new feature of personality in the ranking algorithm for influential user detection in signed networks. We used Optimism and Pessimism scores as personality features of each user and employ it in the PageRank algorithm as a sample ranking algorithm and evaluated the new ranking results by using a new metric of credibility. To assess the performance of the proposed method, we applied it to a large dataset of Epinions signed networks. The results are compared with state-of-the-art expert finding algorithms which indicate that the personality feature can effectively improve the ranking and influential user detection accuracy.
Does HR Add Value? Diverse Perspectives on Human Capital Management

The human resources (HR) function has evolved significantly over the past several decades. It has grown in maturity and influence while simultaneously enduring great criticism from employees and managers. Meanwhile, environmental pressures have forced business leaders and academics to call for the elevation of HR to a level of strategic primacy. This thesis examines the relationship between organizational human capital and the professional HR function, looking at the history and current state of HR, perceptions of HR’s efficacy, trends in innovative organizational design and leadership, and the future of human capital management. I explore these issues in the academic and popular literature, survey managers and experts in the field, and present an intra-industry study across several biotechnology firms. Thesis Advisor: John Van Maanen Title: Erwin H. Schell Professor of Organization Studies
The Association between Anomalous Self-experiences, Self-esteem and Depressive Symptoms in First Episode Schizophrenia

Background: Anomalous self-experiences (ASEs) aggregate in schizophrenia spectrum disorders, but the relationship between ASEs, and depression has been studied to a limited extent. Lower self-esteem has been shown to be associated with depression in early psychosis. Our hypothesis is that ASEs in early phases of schizophrenia are linked to lower levels of self-esteem, which in turn is associated with depression. Aim: The aim is to examine the relationship between ASEs, self-esteem and depression in first-episode schizophrenia spectrum disorders. Method: ASEs were assessed in 55 patients with first-episode schizophrenia by means of the Examination of anomalous Self-Experience (EASE) instrument. Assessment of depression was based on the Calgary Depression Scale for Schizophrenia (CDSS). Self-esteem was measured using the Rosenberg Self-Esteem Scale (RSES). Symptom severity was assessed using the Structured Clinical Interview for the Positive and Negative Syndrome Scale (SCI-PANSS). Substance misuse was measured with the Drug Use Disorder Identification Test (DUDIT), and alcohol use was measured with the Alcohol Use Disorder Identification Test (AUDIT). Data on childhood adjustment were collected using the Premorbid Adjustment Scale (PAS). Data on childhood trauma were collected using the Norwegian version of the Childhood Trauma Questionnaire, short form (CTQ-SF). Results: Analyses detected a significant association between current depression and ASEs as measured by the EASE in women, but not in men. The effect of ASEs on depression appeared to be mediated by self-esteem. No other characteristics associated with depression influenced the relationship between depression, self-esteem and ASEs. Conclusion: Evaluating ASEs can assist clinicians in understanding patients' experience of self-esteem and depressive symptoms. The complex interaction between ASEs, self-esteem, depression and suicidality could be a clinical target for the prevention of suicidality in this patient group.
Exaggerating Character Motion by Anticipation and Reaction ∗

We present a method to exaggerate a character motion by anticipation and reaction. Exaggerating a motion is frequently observed in traditional cartoon-style character animations. According to the principles of traditional 2D animation techniques, the anticipation, reaction, and exaggeration of a motion make an animation quite expressive. The anticipation and reaction of a motion play a role in exagger-ating the motion, since they enlarge the length of the motion path and the amount of movement. We ﬁrst analyze the rotation of each joint and the movement of the center of mass during a given motion, where the anticipatory and reaction motions are added. Altering the direction of rotation and translation by extrapolation of the motion, we can obtain initially guessed anticipatory and reaction poses. By means of a nonlinear optimization technique, we can obtain consequent anticipatory and reaction poses to place the centers of mass at proper locations. Finally, we can generate the anticipatory and reaction motions by composing the poses with a given motion, while considering the continuities at junctions and preserving the high frequency components of the given motion.
Relevance of Non-communicable Comorbidities for the Development of the Severe Forms of Dengue: A Systematic Literature Review

Patients with dengue fever and comorbidities seem to be at higher risk of developing complications and/or severe dengue compared to healthier individuals. This study systematically reviews the evidence related to comorbidities and dengue. A systematic literature review was performed in five databases (EMBASE, PUBMED, Global Health, SciELO, Cochrane) and grey literature for full-text articles since its inceptions until October 10, 2015. A total of 230 articles were retrieved. Sixteen studies were analysed after applying all inclusion and exclusion criteria. Seven case control studies and nine retrospective cohort studies showed that comorbidities may contribute to severe dengue, especially 1) cardiovascular disease, 2) stroke, 3) diabetes, 4) respiratory disease and 5) renal disease, as well as old age. However, due to heterogeneity in studies, the real estimate effect of comorbidities as modifiers of dengue severity could not be established. Further research in regions with high prevalence of dengue infection would contribute to a better understanding of the relevance of comorbidities in severe dengue, especially with a standardised protocol, for outcomes, specific comorbidities, study design—best using prospective designs—and sample sizes.
Computational modeling of H channel currents in rat layer V pyramidal neurons

In layer V pyramidal neurons, neurons that project across the corpus callosum have different electrophysiological properties compared to neurons that project down to the pons. Hyperpolarization activated cyclic nucleotide gated (HCN) channels are thought to be the basis of this difference. Characterizing how HCN channel influence these electrophysiological differences may be key in determining how neurons perform memory tasks. To determine the role of HCN in these neuronal cells, these cells are injected with biotin, fixed and visualized under a microscope. After tracing these cells using the Neurolucida program, the cell parameters are imported into NEURON and modeled with any hypothetical channel. We use these tracings or reconstructions as well as cylinder representations of our cell measurements to determine the effect of HCN channels on input resistance, time constant and resonance. Our data from our model is consistent with our hypothesis that the presence of HCN channels decrease the input resistance and time constant. However we cannot establish that HCN channels are the basis for the electrophysiological differences between layer V pyramidal neurons as changes to the morphology of corticopontine neurons can produce the same electrophysiological differences.
A Regularized Approach for Geodesic-Based Semisupervised Multimanifold Learning

Geodesic distance, as an essential measurement for data dissimilarity, has been successfully used in manifold learning. However, most geodesic distance-based manifold learning algorithms have two limitations when applied to classification: 1) class information is rarely used in computing the geodesic distances between data points on manifolds and 2) little attention has been paid to building an explicit dimension reduction mapping for extracting the discriminative information hidden in the geodesic distances. In this paper, we regard geodesic distance as a kind of kernel, which maps data from linearly inseparable space to linear separable distance space. In doing this, a new semisupervised manifold learning algorithm, namely regularized geodesic feature learning algorithm, is proposed. The method consists of three techniques: a semisupervised graph construction method, replacement of original data points with feature vectors which are built by geodesic distances, and a new semisupervised dimension reduction method for feature vectors. Experiments on the MNIST, USPS handwritten digit data sets, MIT CBCL face versus nonface data set, and an intelligent traffic data set show the effectiveness of the proposed algorithm.
Towards Adaptive Learning Support on the Basis of Behavioural Patterns in Learning Activity Sequences

Monitoring and interpreting sequential user activities contributes to enhanced, more fine-grained user models in e-learning systems. We present in this paper different behavioural patterns from the domain of problem-solving that can be determined by targeted, ultimately automated clustering. For the identification of these patterns, we apply a new approach - based on the modeling of activity sequences - to real-world learning activity sequence data, monitored via an Intelligent Tutoring System. This paper describes the identified behavioural patterns, explains the process used for their detection, and compares the patterns to related ones in earlier literature. It further discusses implications of the patterns themselves, and of the employed approach, on adaptively supporting individual and group-based collaborative learning.
A Framework for the Analysis and Evaluation of Algebraic Fault Attacks on Lightweight Block Ciphers

Algebraic fault analysis (AFA), which combines algebraic cryptanalysis with fault attacks, has represented serious threats to the security of lightweight block ciphers. Inspired by an earlier framework for the analysis of side-channel attacks presented at EUROCRYPT 2009, a new generic framework is proposed to analyze and evaluate algebraic fault attacks on lightweight block ciphers. We interpret AFA at three levels: 1) the target; 2) the adversary; and 3) the evaluator. We describe the capability of an adversary in four parts: 1) the fault injector; 2) the fault model describer; 3) the cipher describer; and 4) the machine solver. A formal fault model is provided to cover most of current fault attacks. Different strategies of building optimal equation set are also provided to accelerate the solving process. At the evaluator level, we consider the approximate information metric and the actual security metric. These metrics can be used to guide adversaries, cipher designers, and industrial engineers. To verify the feasibility of the proposed framework, we make a comprehensive study of AFA on an ultra-lightweight block cipher called LBlock. Three scenarios are exploited, which include injecting a fault to encryption, to key scheduling, or modifying the round number or counter. Our best results show that a single fault injection is enough to recover the master key of LBlock within the affordable complexity in each scenario. To verify the generic feature of the proposed framework, we apply AFA to three other block ciphers, i.e., Data Encryption Standard, PRESENT, and Twofish. The results demonstrate that our framework can be used for different ciphers with different structures.
A Functional Model of SystemC-Based MPEG-2 Decoder with Heterogeneous Multi-IP-Cores and Hybrid-Interconnections Architecture

In this paper, a functional model of SystemC-Based MPEG-2 decoder is presented, which is of heterogeneous multi- IP-cores and hybrid-interconnections. Considering the application-specific features into the design flow, three important aspects are analyzed, including function partition, parameter sharing, and interconnection topology, which are the key technical difficulties in the system level design of a video decoder. A kind of function unit determination is proposed on account of the balance of traffic load on the communication sub-system on- chip. At the same time, to be able to charge with the heavy transmission burden, a hybrid interconnection with bus and point-to-point (P2P) is applied. Additionally, in order to enhance the decoder performance, high-frequently transmitted and updated parameters are extracted to store in on-chip shared memories. The presented application-specific architecture is proofed to be efficient with a system level model on SystemC- based environments. More, the topology and design flow would be a guideline for the design of such application-specific System- on-Chip (SoC), and set up a quick evaluation method.
Bwt Based Lossless Reversible Transformation Algorithms – An Analysis

This paper presents and analyzes the benefits provided in lossless compression by using various preprocessing methods that takes advantage of redundancy of the source file. Textual data holds a number of properties that can be taken into account in order to improve compression. Pre-processing deals with these properties by applying a number of transformations that make the redundancy “more visible” to the compressor. Here our focus is on the Burrows-Wheeler Transformation (BWT), Star Transformation, Intelligent Dictionary Based Encoding (IDBE), Enhanced Intelligent Dictionary Based Encoding (EIDBE) and Improved Intelligent Dictionary Based Encoding (IIDBE). The algorithms are briefly explained before calling attention to their analysis.
Sequence‐based study of two related proteins with different folding behaviors

ZSPA–1 is an engineered protein that binds to its parent, the three‐helix‐bundle Z domain of staphylococcal protein A. Uncomplexed ZSPA–1 shows a reduced helix content and a melting behavior that is less cooperative, compared with the wild‐type Z domain. Here we show that the difference in folding behavior between these two sequences can be partly understood in terms of an off‐lattice model with 5–6 atoms per amino acid and a minimalistic potential, in which folding is driven by backbone hydrogen bonding and effective hydrophobic attraction. Proteins 2004;54:000–000. © 2003 Wiley‐Liss, Inc.
Periodic travelling waves in the theta model for synaptically connected neurons

We study periodic travelling waves in the Theta model for a linear continuum of synaptically-interacting neurons. We prove that when the neurons are oscillatory, at least one periodic travelling of every wave number always exists. In the case of excitable neurons, we prove that no periodic travelling waves exist when the synaptic coupling is weak, and at least two periodic travelling waves of each wave-number, a `fast' one and a `slow' one, exist when the synaptic coupling is sufficiently strong. We derive explicit upper and lower bounds for the `critical' coupling strength as well as for the wave velocities. We also study the limits of large wave-number and of small wave-number, in which results which are independent of the form of the synaptic-coupling kernel can be obtained. Results of numerical computations of the periodic travelling waves are also presented.
A Linear Feature Extraction for Multiclass Classification Problems Based on Class Mean and Covariance Discriminant Information

A parametric linear feature extraction method is proposed for multiclass classification. The skeleton of the proposed method consists of two types of schemes that are complementary to each other with regard to the discriminant information used. The approximate pairwise accuracy criterion (aPAC) and the common-mean feature extraction (CMFE) are chosen to exploit the discriminant information about class mean and about class covariance, respectively. Choosing aPAC rather than the linear discriminant analysis (LDA) can also resolve the problem of overemphasized large distances introduced by LDA, while maintaining other decent properties of LDA. To alleviate the suboptimum problem caused by a direct cascading of the two different types of schemes, there should be a mechanism for sorting and merging features based on their effectiveness. Usage of a sample-based classification error estimation for evaluation of effectiveness of features usually costs a lot of computational time. Therefore, we develop a fast spanning-tree-based parametric classification accuracy estimator as an intermediary for the aPAC and CMFE combination. The entire framework is parametric-based. This avoids paying a costly price in computation, which normally happens to the sample-based approach. Our experiments have shown that the proposed method can achieve a satisfactory performance on real data as well as simulated data.
The Impact of Inertia , Particle Increment & Global Increment on Swarms in a Dynamic Environment

The purpose of this paper and the experiments condu cte herein is to assess the impact of variation in particle inertia (w), particle increment ( c1) and global increment ( c2), on the fitness of particles and there impact upo n particle swarm optimization in a dynamic environmen t. I this paper a 3-dimensional parabolic function is utilized to illustrate an example of a dynamic environment. Results show that the impact of PSO in this environm e t will not be significantly enhanced by the alteration of w, c1 or c2.
Topical antibiotics on tracheostoma prevents exogenous colonization and infection of lower airways in children.

INTRODUCTION Patients requiring long-term ventilation are at high risk of lower airway infections, generally of endogenous development. Patients on long-term ventilation, in particular via a tracheostomy, may develop tracheobronchitis or pneumonia of exogenous pathogenesis, ie, caused by microorganisms not carried in the oropharynx. The frequency of exogenous colonization or infection has previously been reported to be as high as 33%. A prospective observational cohort study of 2 years was undertaken to evaluate the efficacy of topical antibiotics in the prevention of exogenous colonization or infection of the lower airways. The antibiotic combination of polymyxin E and tobramycin in a 2% paste was applied four times a day on the tracheostoma. MATERIALS AND METHODS A total of 23 children (median age, 4.1 months; range, 0 to 215 months) were enrolled in the study from September 1, 1996, until August 30, 1998. Surveillance samples of the oropharynx were obtained before tracheostomy and thereafter twice weekly. Diagnostic samples of the lower airways were taken once weekly and on clinical indication. RESULTS Fourteen children (61%) had a total of 16 episodes of tracheal colonization or infection with 20 potentially pathogenic microorganisms. Only one child had tracheobronchitis with Streptococcus pneumoniae and Haemophilus influenzae during the 2-year study. Of the 16 colonization episodes, 12 (75%) were of primary endogenous pathogenesis, ie, caused by microorganisms present in the oropharynx at the time of tracheostomy. Community microorganisms including S pneumoniae, H influenzae, Moraxella (Branhamella) catarrhalis, and Staphylococcus aureus were the predominating bacteria. Three patients acquired nosocomial bacteria Pseudomonas aeruginosa and Hafnia alvei in the oropharynx, subsequently followed by secondary colonization of the lower airways. There was one failure of the prophylaxis: one patient (4%) had exogenous colonization with Pseudomonas pickettii. CONCLUSION Topical antibiotics applied to the tracheostoma were found to be effective in reducing the exogenous route of colonization of the lower respiratory tract, compared with clinical experience and the literature. This promising technique requires further evaluation in randomized trials.
Finite-time control for formation flying spacecraft with coupled attitude and translational dynamics

This paper investigates a distributed coordination control scheme using terminal sliding mode for formation flying spacecraft with coupled attitude and translational dynamics. A six Degree-of-Freedom (6DOF) coupled model in Euler-Lagrange form is established. A continuous controller is proposed to alleviate the chattering phenomenon of a terminal sliding mode control. Theoretical analysis shows that the controller can guarantee the finite-time stability of the overall closed-loop system.