Miracle-dz/UniFAR-FTUs huggingface dataset:
Model of Critical Factors for Outsourcing Agile Development

Companies are beginning to combine outsourcing with Agile software engineering techniques with the goal of receiving the benefits of both – faster time to market, greater quality, and smaller costs. Since Agile was originally developed to work principally with small collocated teams, scalability of Agile to the enterprise, and simultaneous use of Agile and outsourcing are questions concerning applicability of Agile techniques to global business environments. This paper first summarizes current experience studies and research in Agile, enterprise Agile and Agile outsourcing, to identify factors likely to affect success on Agile projects. It then extends a model originally developed by Chow and Cao (2007) to account for these factors. Finally it outlines an experiment whose goal is to determine which of these factors drives successful projects that use both Agile and outsourcing.
Kinase-interacting substrate screening is a novel method to identify kinase substrates

A novel method called kinase-interacting substrate screening based on affinity beads coated with the kinase of interest identifies phosphorylation sites for Rho-kinase and others, which reveals that Rho-kinase substrate Scrib plays a crucial role in the regulation of subcellular contractility by assembling with Rho-kinase and Shroom2.
Transfer of Learned Heuristics among Planners *

This paper presents a study on the transfer of learned control knowledge between two different planning techniques. We automatically learn heuristics (usually, in planning, heuristics are also named control knowledge) from one planner search process and apply them to a different planner. The goal is to improve this second planner efficiency solving new problems, i.e. to reduce computer resources (time and memory) during the search, or to improve quality solutions. The learning component is based on a deductive learning method (EBL) that is able to automatically acquire control knowledge by generating bounded explanations of the problem solving episodes in a graph-plan based planner. Then, we transform the learned knowledge so that it can be used by a bidirectional planner.
Cardiac Power During Exercise and the Risk of Stroke in Men

Background and Purpose— Low maximal oxygen uptake (VO2max) has been shown to predict the risk of stroke. However, VO2max does not take into account the differences in cardiac afterload between subjects. The aim of this study was to examine the relationship of exercise cardiac power (ECP), defined as a ratio of VO2max with peak systolic blood pressure (SBP) during exercise, with the risk for stroke. Methods— Population-based cohort study with an average follow-up of 12 years from eastern Finland. A total of 1761 men with no history of stroke or coronary heart disease at baseline participated. Among these men, 91 strokes occurred, of which 69 were attributable to ischemic causes. Results— The relative risk of any stroke in men with low ECP (<10.3 mL/mm Hg) was 2.7 (95% CI, 1.2 to 6.0; P=0.01; P=0.02 for the trend across the quartiles), and the relative risk for ischemic stroke was 2.7 (95% CI, 1.1 to 7.0; P=0.03; P=0.04 for trend across the quartiles) compared with men having high ECP (>14.3 mL/mm Hg) during exercise after adjusting for age, examination year, cigarette smoking, alcohol consumption, body mass index, diabetes, serum total cholesterol level, energy expenditure of physical activity, exercise-induced myocardial ischemia, and the use of antihypertensive medication. After further adjustment for resting SBP, results were statistically nonsignificant. Conclusions— Low ECP provides noninvasive and easily available measure for stroke risk. One of the most potential explanations for the association between ECP and the increased risk of stroke is an elevated afterload and peripheral resistance indicated by elevated SBP.
Engineering cheese sensory texture : using structure-property modeling

Constitutive models for soft solids that relate the stress to the deformation history have the potential to be used in a structure-texture engineering context, but successful examples are scarce. In the present work we define equations for the firmness F , springiness S, and rubberiness R, of semi-soft food gels that exhibit broad power-law stress relaxation over a wide range of timescales. The equations contain only two material properties, which have their origin in the food microstructure: a fractional exponent, which quantifies the frequency and temporal response and secondly a scale factor or “quasi-property”, which sets the magnitude of the stress in the material. Together they form a constitutive element, known as the ‘springpot’ or Scott Blair element. This model correctly predicts the timeand interdependency of the firmness, springiness, and rubberiness of emulsion-filled hydrocolloidal gels such as fulland reduced-fat semi-soft cheeses. Firmness and rubberiness are time-dependent properties, whereas springiness is not. The magnitude of the firmness and springiness are inversely related through the fractional constitutive model. Our equations for F , S and R also correctly predict the effect of changing the magnitude or time-scale of the stress loading on the material even in the case of irreversible flow events, when The contents of this chapter are based on (a) T.J. Faber, A. Jaishankar, and G.H. McKinley. Describing the firmness, springiness and rubberiness of food gels using fractional calculus. Part I: Theoretical framework. In preparation for Food Hydrocolloids, and (b) T.J. Faber, A. Jaishankar, and G.H. McKinley. Describing the firmness, springiness and rubberiness of food gels using fractional calculus. Part II: Measurements on cheese. In preparation for Food Hydrocolloids.
Maximizing the number of polychronous groups in spiking networks

In this paper we investigate the effect of biasing the axonal connection delay values in the number of polychronous groups produced for a spiking neuron network model. We use an estimation of distribution algorithm (EDA) that learns tree models to search for optimal delay configurations. Our results indicate that the introduced approach can be used to considerably increase the number of such groups.
CiteSight: supporting contextual citation recommendation using differential search

A person often uses a single search engine for very different tasks. For example, an author editing a manuscript may use the same academic search engine to find the latest work on a particular topic or to find the correct citation for a familiar article. The author's tolerance for latency and accuracy may vary according to task. However, search engines typically employ a consistent approach for processing all queries. In this paper we explore how a range of search needs and expectations can be supported within a single search system using differential search. We introduce CiteSight, a system that provides personalized citation recommendations to author groups that vary based on task. CiteSight presents cached recommendations instantaneously for online tasks (e.g., active paper writing), and refines these recommendations in the background for offline tasks (e.g., future literature review). We develop an active cache-warming process to enhance the system as the author works, and context-coupling, a technique for augment sparse citation networks. By evaluating the quality of the recommendations and collecting user feedback, we show that differential search can provide a high level of accuracy for different tasks on different time scales. We believe that differential search can be used in many situations where the user's tolerance for latency and desired response vary dramatically based on use.
Private Identification, Authentication and Key Agreement Protocol with Security Mode Setup

Identification, authentication and key agreement protocol of UMTS networks with security mode setup has some weaknesses in the case of mutual freshness of key agreement, DoS-attack resistance, and efficient bandwidth consumption. In this article we consider UMTS AKA and some other proposed schemes. Then we explain the known weaknesses of the previous frameworks suggested for the UMTS AKA protocol. After that we propose a new protocol called private identification, authentication, and key agreement protocol (PIAKAP), for UMTS mobile network. Our suggested protocol combines identification and AKA stages of UMTS AKA protocol while eliminates disadvantages of related works and brings some new features to improve the UMTS AKA mechanism. These features consist of reducing the interactive rounds of the UMTS AKA with security mode setup and user privacy establishment.
Beyond Concern: Understanding Net Users' Attitudes About Online Privacy

People are concerned about privacy, particularly on the Internet. While many studies have provided evidence of this concern, few have explored the nature of the concern in detail, especially for the online environment. With this study, we have tried to better understand the nature of online privacy concerns; we look beyond the fact that people are concerned and attempt to understand how they are concerned. We hope our results will help inform both policy decisions as well as the development of technology tools that can assist Internet users in protecting their privacy. We present results here from the analysis of 381 questionnaires completed between November 6 and November 13, 1998 by American Internet users. The sample was drawn from the FamilyPC magazine/Digital Research, Inc. Family Panel. While this is not a statistically representative sample of US Internet users, our respondents are heavy Internet users, and quite possibly lead innovators. As such, we believe that this sample is important for understanding the future Internet user population.
Urinary neutrophil gelatinase-associated lipocalin for diagnosis and estimating activity in lupus nephritis: a meta-analysis

Urinary neutrophil gelatinase-associated lipocalin (uNGAL) is relatively specific in lupus nephritis (LN) patients. However, its diagnostic value has not been evaluated. The aim of this review was to determine the value of uNGAL for diagnosis and estimating activity in LN. A comprehensive search was performed on PubMed, EMBASE, Web of Knowledge, Cochrane electronic databases through December 2014. Meta-analysis of sensitivity and specificity was performed with a random-effects model. Additionally, summary receiver operating characteristic (SROC) curves and area under the curve (AUC) values were calculated. Fourteen studies were selected for this review. With respect to diagnosing LN, the pooled sensitivity and specificity were 73.6% (95% confidence interval (CI), 61.9–83.3) and 78.1% (95% CI, 69.0–85.6), respectively. The SROC-AUC value was 0.8632. Regarding estimating LN activity, the pooled sensitivity and specificity were 66.2% (95% CI, 60.4–71.7) and 62.1% (95% CI, 57.9–66.3), respectively. The SROC-AUC value was 0.7583. In predicting renal flares, the pooled sensitivity and specificity were 77.5% (95% CI, 68.1–85.1) and 65.3% (95% CI, 60.0–70.3), respectively. The SROC-AUC value was 0.7756. In conclusion, this meta-analysis indicates that uNGAL has relatively fair sensitivity and specificity in diagnosing LN, estimating LN activity and predicting renal flares, suggesting that uNGAL is a potential biomarker in diagnosing LN and monitoring LN activity.
Human-centered rehabilitation robotics

This paper presents new human-centered robotic approaches applied to the rehabilitation of gait and upper-extremity functions in patients with movement disorders. So-called "patient-cooperative" strategies can take into account the patient's intention and efforts rather than imposing any predefined movement. It is hypothesized that such human-centered robotic approaches can improve the therapeutic outcome compared to classical rehabilitation strategies.
Profiling Membrane Lipids in Plant Stress Responses

A sensitive approach based on electrospray ionization tandem mass spectrometry has been employed to profile membrane lipid molecular species in Arabidopsis undergoing cold and freezing stresses. Freezing at a sublethal temperature induced a decline in many molecular species of phosphatidylcholine (PC), phosphatidylethanolamine (PE), and phosphatidylglycerol (PG) but induced an increase in phosphatidic acid (PA) and lysophospholipids. To probe the metabolic steps generating these changes, lipids ofArabidopsis deficient in the most abundant phospholipase D, PLDα, were analyzed. The PC content dropped only half as much, and PA levels rose only half as high in the PLDα-deficient plants as in wild-type plants. In contrast, neither PE nor PG levels decreased significantly more in wild-type plants than in PLDα-deficient plants. These data suggest that PC, rather than PE and PG, is the majorin vivo substrate of PLDα. The action of PLDα during freezing is of special interest because Arabidopsis plants that are deficient in PLDα have improved tolerance to freezing. The greater loss of PC and increase in PA in wild-type plants as compared with PLDα-deficient plants may be responsible for destabilizing membrane bilayer structure, resulting in a greater propensity toward membrane fusion and cell death in wild-type plants.
Practical approach for parameter determinations of interior permanent magnet generator

Recently, there has been a lot of researches on various methods for a sensorless control of permanent magnet generators (PMG) in wind turbines. The sensorless control of the PMG considers estimations of a rotor angle and speed which are based on the PMG parameters estimation. The parameters that have been estimated are stator resistance, rotor flux, d-axis and q-axis inductance. For more precise rotor angle and speed estimation, it is essential to determinate values of the PMG parameters in every operating point as accurately as possible. A change of the operating point (different rotor speed, shaft torque etc.) causes the change of the PMG parameters due to stator currents and temperature variation. Accordingly, the PMG parameters could be measured during a PMG commissioning. In this work, the stator resistance is measured while taking into considering a dead time compensation and voltage drop on a power switching devices. A determination of the d-axis and q-axis inductances is based on PMG voltage equations in a dq synchronous reference frame. Thus, the measurements of the rotor speed, stator currents and voltages are required. The experimental measurements are carried out on a 375 kW interior permanent magnet generator. Finally, the measured values could be saved on a digital signal processor (DSP) as look-up tables and used for the sensorless control of the PMG.
Defining contrast-induced nephropathy.

Contrast-induced nephropathy (CIN) is one of the most common forms of hospital-acquired acute kidney injury (1). The elective or semielective timing of the majority of diagnostic and therapeutic procedures using iodinated contrast allows CIN to be one of the few causes of acute kidney injury that are amenable to implementation of preventive interventions. Numerous potential preventive strategies have been evaluated, including periprocedural administration of saline (2,3) or isotonic bicarbonate solutions (4–7); use of pharmacologic agents including diuretics (2), mannitol (2), natriuretic peptides (8), dopamine (9), fenoldopam (10), theophylline (11,12), and N-acetylcysteine (12–14); and prophylactic renal replacement therapy (15–17). In addition, multiple studies have compared the relative nephrotoxicity of various contrast agents (18–23). In virtually all of these studies, CIN has been defined in terms of small absolute or relative increases in serum creatinine concentration. Implicit in the use of these surrogate end points is the assumption that amelioration of contrast-associated increases in serum creatinine correlates with improved clinical outcomes. The association between CIN and adverse clinical outcomes, including cardiovascular complications and death, has been amply demonstrated in retrospective database analyses and …
BACE1, a Major Determinant of Selective Vulnerability of the Brain to Amyloid-β Amyloidogenesis, is Essential for Cognitive, Emotional, and Synaptic Functions

A transmembrane aspartyl protease termed β-site APP cleavage enzyme 1 (BACE1) that cleaves the amyloid-β precursor protein (APP), which is abundant in neurons, is required for the generation of amyloid-β (Aβ) peptides implicated in the pathogenesis of Alzheimer's disease (AD). We now demonstrate that BACE1, enriched in neurons of the CNS, is a major determinant that predisposes the brain to Aβ amyloidogenesis. The physiologically high levels of BACE1 activity coupled with low levels of BACE2 and α-secretase anti-amyloidogenic activities in neurons is a major contributor to the accumulation of Aβ in the CNS, whereas other organs are spared. Significantly, deletion of BACE1 in APPswe;PS1ΔE9 mice prevents both Aβ deposition and age-associated cognitive abnormalities that occur in this model of Aβ amyloidosis. Moreover, Aβ deposits are sensitive to BACE1 dosage and can be efficiently cleared from the CNS when BACE1 is silenced. However, BACE1 null mice manifest alterations in hippocampal synaptic plasticity as well as in performance on tests of cognition and emotion. Importantly, memory deficits but not emotional alterations in BACE1–/– mice are prevented by coexpressing APPswe;PS1ΔE9 transgenes, indicating that other potential substrates of BACE1 may affect neural circuits related to emotion. Our results establish BACE1 and APP processing pathways as critical for cognitive, emotional, and synaptic functions, and future studies should be alert to potential mechanism-based side effects that may occur with BACE1 inhibitors designed to ameliorate Aβ amyloidosis in AD.
Game design through self-play experiments

The application of self-play experiments to computer games was pioneered by Thompson in 1982 with his chess machine BELLE. Since then the technique has been widely used in a variety of games to train artificial players employing a range of artificial neural network architectures. Of particular note is the TD-learning Backgammon program of Tesauro developed in 1995. When developing artificial game players that learn by experience, it is generally possible to accelerate the training process through self-play. Compared with training by humans, this confers the advantages of greater speed and a precise control of playing strength through parameter variation. In spite of these potential advantages, the use of self-play experiments is considered by many to be a treacherous road fraught with problems. The value of such experiments is unclear and the threshold of learning that can be achieved through self-play alone is unknown. There is the common-sense perception that only limited playing skill can be achieved through machine self-play, a notion that is challenged here. A new application that is immune from the problems associated with machine learning is the use of self-play experiments to test the integrity and fairness of games and modify the rules accordingly. We will show how the rules of a particular game, Perudo, can be analysed for fairness and how the excessive positive feedback that arises when forces become unbalanced can be curbed. We use the notion of fair in the same sense as in a soccer game - if a team loses a goal, neglecting psychological effects, the chance of losing a second goal is not significantly changed. It is recognised that the cumulative growth in advantage is part of many games and that it is inappropriate to alter the rules in these cases. However the rate at which advantages grow can be moderated by rule alterations. We will also consider the application of the technique to a range of traditional games. In chess, for example, White is considered to have an advantage over Black. The imbalance can be determined for different playing strengths and extrapolated. We will show that the principles can be extended to the more complex situations of computer games and propose that the development of unintelligent agents to explore game play is advantageous.
Probabilistic optimized ranking for multimedia semantic concept detection via RVM

We present a probabilistic ranking-driven classifier for the detection of video semantic concept, such as airplane, building, etc. Most existing concept detection systems utilize Support Vector Machines (SVM) to perform the detection and ranking of retrieved video shots. However, the margin maximization principle of SVM does not perform ranking optimization but merely classification error minimization. To tackle this problem, we exploit the sparse Bayesian kernel model, namely the relevance vector machine (RVM), as the classifier for semantic concept detection. Based on automatic relevance determination principle, RVM outputs the posterior probabilistic prediction of the semantic concepts. This inference output is optimal for ranking the target video shots, according to the Probabilistic Ranking Principle. The probability output of RVM on individual uni-modal features also facilitates probabilistic fusion of multi-modal evidences to minimize Bayes risk. We demonstrate both theoretically and empirically that RVM outperforms SVM for video semantic concept detection. The testings on TRECVID 07 dataset show that RVM produces statically significant improvements in MAP scores over the SVM-based methods.
Influence of channel fluctuations on optimal real-time scalable image transmission

Joint source-channel coding systems using scalable source codes and forward error correction allow reliable transmission of multimedia data over noisy channels. The performance of such systems highly depends on the source-channel bit allocation strategy. Rate-based error protection schemes, which maximize the expected source rate are very attractive for real-time applications because the optimization can be done very quickly and is independent of the source. In real-world communication, channel conditions are varying in time. Thus, it is important to frequently update the error protection. For two state-of-the-art joint source-channel coding systems, we show that a channel mismatch can lead to a poor performance. We study theoretically and experimentally the dependency of a rate-based optimal protection on the channel statistics and provide an efficient strategy for adjusting the error protection when a channel mismatch occurs.
What Can the Temporal Social Behavior Tell Us? An Estimation of Vertex-Betweenness Using Dynamic Social Information

The vertex-betweenness centrality index is an essential measurement for analyzing social networks, but the computation time is excessive. At present, the fastest algorithm, proposed by Brandes in 2001, requires O(|V| |E|) time, which is computationally intractable for real-world social networks that usually contain millions of nodes and edges. In this paper, we propose a fast and accurate algorithm for estimating vertex-betweenness centrality values for social networks. It only requires O(b^2|V|) time, where b is the average degree in the network. Significantly, we demonstrate that the local dynamic information about the vertices is highly relevant to the global betweenness values. The experiment results show that the vertex-betweenness values estimated by the proposed model are close to the real values and their rank is fairly accurate. Furthermore, using data from online role-playing games, we present a new type of dynamic social network constructed from in-game chatting activity. Besides using such online game networks to evaluate our betweenness estimation model, we report several interesting findings derived from conducting static and dynamic social network analysis on game networks.