Miracle-dz/UniFAR-FTUs huggingface dataset:
The Choice of Organizational Form for Collaborative Innovation

It is commonplace for firms to collaborate with others to gain access to technological components for innovation. This paper examines the choice of organizational form for such activities: when should a firm hire a technological expert as a temporary employee, transact through consulting spot markets, or engage in a long-term employment or supply relationship with the expert? Property rights theory is applied to examine the incentives and commitment created by different organization forms when the property rights of knowledge assets are incomplete. The model highlights the role of fallback options in sustaining socially efficient implicit contracts. Comparison of long-term employment and supply relationships shows that, contrary to received wisdom, an employment relationship is a less robust arrangement than a supply relationship in the presence of large knowledge spillovers. Nevertheless, the employment relationship is relatively more sustainable when there are complementarities between the parties’ cooperation investments. Empirical implications for structuring R&D and consulting arrangements are discussed.
Simulation and parameter optimization of PCV in shift hydraulic system

It is well-known that the shift hydraulic system plays a major role in the operation of the stepped automatic transmission. The main functions of the shift hydraulic system are to generate and maintain desired fluid pressures for transmission operation, as well as to initiate gear shifts and control shift quality. Generally, the widely used hydraulic control system in automatic transmissions is a pulse width modulation (PWM) type. It consists of a solenoid valve and a reducing type second stage valve, the so called pressure control valve (PCV), to control the oncoming and off-going clutches. This paper presents a simulation model of the shift control system based on the AMESim software. A simulation analysis is conducted to study the working principle and performance of the pressure control valve, and is validated against experimental data. The effects of such parameters as spring stiffness, spool diameter and under lap are analyzed and optimized based on genetic algorithms. The results confirm that simulation analysis and structure parameter optimization with AMESim are instructive to the designing of the pressure control valve of shift hydraulic system.
La Batterie de tâches de Théorie de l’esprit : Validation de la version francophone

Cet article presente deux etudes de validation de la version francophone de la Theory of Mind Task Battery (Hutchins, Prelock, & Chace, 2008) ou Batterie ToM-vf (Houssa & Nader- Grosbois, 2012), menees aupres d’enfants d’âge prescolaire. Dans l’etude 1, 209 enfants et dans l’etude 2, 82 enfants ont ete evalues au moyen de la Batterie-ToM-vf et des epreuves ToM-emotions et croyances (Nader-Grosbois & Thirion-Marissiaux, 2011). Les parents et enseignants ont complete l’inventaire de la Theorie de l’esprit (ToMI-vf, Houssa, Mazzone, & Nader-Grosbois, 2014) et les Echelles d’Adaptation Sociale pour Enfants (EASE, Hughes, Soares-Boucaud, Hochmann, & Fritz, 1997) et le Profil Socio-Affectif (Lafreniere, Dumas, Capuano, & Durning, 1997). L’etude 1 revele une bonne coherence interne pour l’ensemble des enonces. L’analyse factorielle en composantes principales avec rotation varimax aboutit a une structure en trois facteurs « reconnaissance des emotions », « prise de perspective » et « inference complexe ». Le score varie en fonction de l’âge. Des correlations positives significatives confirment la validite convergente entre les scores de la Batterie-ToM-vf et ceux des epreuves ToM-emotions et croyances, du ToMI-vf et de la sous-echelle EASE-ToM. L’etude 2 revele des correlations positives elevees pour la fiabilite test-retest et pour l’accord interjuges. Des correlations positives significatives sont obtenues entre les scores a la Batterie ToM-vf et les scores aux dimensions « prosociale » et cooperative, et l’adaptation du PSA, et a la sous-echelle de capacites sociales de l’EASE. En conclusion, la Batterie ToM-vf presente de bonnes qualites psychometriques et son applicabilite a des enfants d’âge prescolaire est confirmee.
Reflective function as a mediator between childhood adversity, personality disorder and symptom distress.

A growing body of literature has indicated the central role of childhood adversity for the development in later life of personality disorder (PD) and psychiatric distress. In this investigation, we examine the role of reflective function (RF) as a mediator between childhood adversity, subsequent development of PD and psychiatric morbidity. We tested the hypothesis that adversity leads to decreased RF, which in turn is associated with PD, and both increase the likelihood of psychiatric distress. The study sample consisted of 234 individuals, drawn from a clinical PD group (n = 112) and one demographically matched non-psychiatric group (n = 122) using a shared battery of measures, which included the Structured Clinical Interview for DSM-IV, the Symptom Checklist-90-R and the Adult Attachment Interview, which was used to assess RF levels. The results indicated that childhood adversity predicted low level of RF, which in turn was associated with PD onset later in life. A combination of different early adverse experiences had a significantly greater impact on lowering RF scores than experiencing either neglect or abuse alone. Mediation analyses confirmed that RF was a significant mediator between adversity and PD diagnoses and between adversity and psychiatric distress.
Classification and Ranking of Questions in Microblog

This paper gives brief idea about new approach towards E learning in Micro-blogging supported classroom. Micro-blogging is a technology used in social networking applications which can be used in classroom for the communication between student and teacher. Nowadays from research it is observed that it has numerous benefits. Its major advantage is that the number of questions asked is much more than that of questions asked in certain time period of lecture. It is beneficial for student to get there doubts cleared not only in classroom but also outside. But it can happen that questions not related to particular topic can furthermore be raised. To overcome such a problem, questions should be classified as relevant and irrelevant questions using classification technique and classified question should get tagged on the basis of concept which is called as Concept Tagging. After classification question should be ranked using ranking techniques.
Advantages and limitations of cell-based assays for GTPase activation and regulation

Small GTPases of the Ras superfamily are important regulators of many cellular functions, including signal transduction, cytoskeleton assembly, metabolic regulation, organelle biogenesis and intracellular transport. Most GTPases act as binary switches, being “on” in the active, GTP-bound state and “off” in the inactive, GDP-bound state, and cycle between the two states with the aid of accessory proteins, referred to as guanine nucleotide exchange factors (GEFs) and GTPase-activating proteins (GAPs). This review will focus on the ADP-ribosylation factors (Arfs), a family of G-proteins that are essential regulators of carrier vesicle formation during vesicular transport. As for most other GTPases, the Arfs themselves are vastly outnumbered by the proteins that regulate them, and a major focus in the field has been to define the functional relationships between individual GEFs and GAPs and their substrates at the cellular level. Over the years, a variety of methods have been developed to measure GTPase activation in vitro and in vivo. In vitro analysis will be discussed in the accompanying article by Randazzo and colleagues. Here we will focus on cell- and tissue-based assays and their advantages/disadvantages relative to cell-free systems.
Dependability in dynamic, evolving and heterogeneous systems: the connect approach

The EU Future and Emerging Technologies (FET) Project Connect aims at dropping the heterogeneity barriers that prevent the eternality of networking systems through a revolutionary approach: to synthesise on-the-fly the Connectors via which networked systems communicate. The Connect approach, however, comes at risk from the standpoint of dependability, stressing the need for methods and tools that ensure resilience to faults, errors and malicious attacks of the dynamically Connected system. We are investigating a comprehensive approach, which combines dependability analysis, security enforcement and trust assessment, and is centred around a lightweight adaptive monitoring framework. In this project paper, we overview the research that we are undertaking towards this objective and propose a unifying workflow process that encompasses all the Connect dependability/security/trust concepts and models.
A possible explanation for the radio afterglow of GRB 980519: the dense medium effect

GRB 980519 is characterized by its rapidly declining optical and X-ray afterglows. Explanations of this behaviour include models invoking a dense medium environment, which makes the shock wave evolve quickly into the subrelativistic phase, a jet-like outflow, and a wind-shaped circumburst medium environment. Recently, Frail et al. found that the latter two cases are consistent with the radio afterglow of this burst. Here, by considering the transrelativistic shock hydrodynamics, we show that the dense medium model can also account for the radio light curve quite well. The potential virtue of the dense medium model for GRB 980519 is that it implies a smaller angular size of the afterglow, which is essential for interpreting the strong modulation of the radio light curve. Optical extinction arising from the dense medium is not important if the prompt optical-UV flash accompanying the gamma-ray emission can destroy dust by sublimation out to an appreciable distance. Comparisons with some other radio afterglows are also discussed.
Executive Functions and Substance Use: Relations in Late Adolescence and Early Adulthood

Poor executive functions (EFs) have been linked to substance use and abuse across multiple substances. However, it is unclear whether these associations are stronger for some EFs over others and/or some stages of substance use over others (e.g., ever using substances vs. dependence). It is also unknown whether such patterns change from adolescence to early adulthood, a transition that is characterized by changes to both EFs and substance use behaviors. In this longitudinal study of approximately 850 twins, we examined the relations between multiple EF abilities (including a common EF factor predicting 9 EF tasks) and measures of general substance use and dependence/abuse in late adolescence (mean age 17 years) and early adulthood (mean age 23 years). At the phenotypic level, common EF in adolescence was negatively related to the number of substances ever used and to last 6-month frequency of use, but not to dependence/abuse vulnerability (i.e., the number of dependence and abuse symptoms endorsed per substance that had been repeatedly used). However, in the same participants in early adulthood, common EF was only weakly related to the number of substances used, and not related to concurrent frequency of use nor dependence/abuse vulnerability. Twin analyses revealed that these associations were primarily genetic in origin, and that the genetic correlations were relatively stable over time. These results suggest that low common EF is a genetic risk factor for increased polysubstance use in late adolescence, but that non-EF factors play a larger role in the progression to substance dependence/abuse.
Cross-Loop Optimization of Arithmetic Intensity for Finite Element Local Assembly

We study and systematically evaluate a class of composable code transformations that improve arithmetic intensity in local assembly operations, which represent a significant fraction of the execution time in finite element methods. Their performance optimization is indeed a challenging issue. Even though affine loop nests are generally present, the short trip counts and the complexity of mathematical expressions, which vary among different problems, make it hard to determine an optimal sequence of successful transformations. Our investigation has resulted in the implementation of a compiler (called COFFEE) for local assembly kernels, fully integrated with a framework for developing finite element methods. The compiler manipulates abstract syntax trees generated from a domain-specific language by introducing domain-aware optimizations for instruction-level parallelism and register locality. Eventually, it produces C code including vector SIMD intrinsics. Experiments using a range of real-world finite element problems of increasing complexity show that significant performance improvement is achieved. The generality of the approach and the applicability of the proposed code transformations to other domains is also discussed.
Oxytocin Attenuates Affective Evaluations of Conditioned Faces and Amygdala Activity

Social relations between humans critically depend on our affective experiences of others. Oxytocin enhances prosocial behavior, but its effect on humans' affective experience of others is not known. We tested whether oxytocin influences affective ratings, and underlying brain activity, of faces that have been aversively conditioned. Using a standard conditioning procedure, we induced differential negative affective ratings in faces exposed to an aversive conditioning compared with nonconditioning manipulation. This differential negative evaluative effect was abolished by treatment with oxytocin, an effect associated with an attenuation of activity in anterior medial temporal and anterior cingulate cortices. In amygdala and fusiform gyrus, this modulation was stronger for faces with direct gaze, relative to averted gaze, consistent with a relative specificity for socially relevant cues. The data suggest that oxytocin modulates the expression of evaluative conditioning for socially relevant faces via influences on amygdala and fusiform gyrus, an effect that may explain its prosocial effects.
Robust Decoding of H.264 Encoded Video Transmitted over Wireless Channels

Due to its high compression efficiency, the H.264 video coder is very sensitive to impairments due to transmission over noisy channels. Most error resilience/concealment techniques provided in the H.264 standard were dealing with packet losses. In wireless environments, the proportion of corrupted packets (and thus considered as lost) may become very high. This paper shows that the H.264 decoder may be seen as a parity check decoder able to detect erroneous packets. Combined with soft estimation techniques, it allows to correct transmission errors and to reduce significantly the number of packets deemed lost. The proposed solution is compatible with the error-resilience features of H.264
NK cells regulate CXCR2+ neutrophil recruitment during acute lung injury

A critical step in the pathogenesis of acute lung injury (ALI) is excessive recruitment of polymorphonuclear neutrophils (PMNs) into the lungs, causing significant collateral tissue damage. Defining the molecular and cellular steps that control neutrophil infiltration and activation during ALI is therefore of important therapeutic relevance. Based on previous findings implicating the transcription factor Tbet in mucosal Th1‐inflammation, we hypothesized a detrimental role for Tbet during ALI. In line with our hypothesis, initial studies of endotoxin‐induced lung injury revealed a marked protection of Tbet−/− mice, including attenuated neutrophilia compared to WT counterparts. Surprisingly, subsequent studies identified natural killer (NK) cells as the major source of pulmonary Tbet during ALI. In addition, a chemokine screen suggested that mature Tbet+ NK‐cells are critical for the production of pulmonary CXCL1 and ‐2, thereby contributing to pulmonary PMN recruitment. Indeed, both NK‐cell Ab depletion and adoptive transfer studies provide evidence for NK cells in the orchestration of neutrophil recruitment during endotoxin‐induced ALI. Taken together, these findings identify a novel role for Tbet+ NK‐cells in initiating the early events of noninfectious pulmonary inflammation.
Non-universal gaugino masses: a signal-based analysis for the Large Hadron Collider

We discuss the signals at the Large Hadron Collider (LHC) for scenarios with non-universal gaugino masses in supersymmetric (SUSY) theories. We perform a multichannel analysis, and consider the ratios of event rates in different channels such as $jets + {E}_T/ $, $same$ - and $opposite$-$sign dileptons$ $+jets+ {E}_T/ $, as well as $single-lepton$ and $trilepton$ final states together with $jets + {E}_T/ $ . Low-energy SUSY spectra corresponding to high-scale gaugino non-universality arising from different breaking schemes of SU(5) as well as SO(10) Grand Unified (GUT) SUSY models are considered, with both degenerate low-energy sfermion masses and those arising from a supergravity scenario. We present the numerical predictions over a wide range of the parameter space using the event generator {\tt Pythia}, specifying the event selection criteria and pointing out regions where signals are likely to be beset with backgrounds. Certain broad features emerge from the study, which may be useful in identifying the signatures of different GUT breaking schemes and distinguishing them from a situation with a universal gaugino mass at high scale. The absolute values of the predicted event rates for different scenarios are presented together with the various event ratios, so that these can also be used whenever necessary.
Network coding-aware data aggregation for a distributed Wireless Sensor Network

Wireless Sensor Networks (WSNs) are immensely deployed for monitoring information like humidity, temperature and soil fertility. As the sensor nodes sense data and floods them in the network, the network traffic increases and may result in congestion which leads to broadcast storm problem. This paper addresses the utility of network coding to optimize data aggregation and to decrease the number of transmitted messages in a WSN. A coding-aware deployment strategy is presented which create opportunity for network coding at aggregate sensor nodes. Our deployment strategy leads to a topology which supports many-to-many network flows (multiple sources and multiple sink network flow). It also gives protection against multiple failures in the network. Furthermore, we propose a heuristic that restricts unnecessary transmissions.
Vectorizing Face Images by Interleaving Shape and Texture Computations

The correspondence problem in computer vision is basically a matching task between two or more sets of features. In this paper, we introduce a vectorized image representation, which is a feature-based representation where correspondence has been established with respect to a reference image. This representation has two components: (1) shape, or (x, y) feature locations, and (2) texture, defined as the image grey levels mapped onto the standard reference image. This paper explores an automatic technique for ``vectorizing'''' face images. Our face vectorizer alternates back and forth between computation steps for shape and texture, and a key idea is to structure the two computations so that each one uses the output of the other. A hierarchical coarse-to-fine implementation is discussed, and applications are presented to the problems of facial feature detection and registration of two arbitrary faces.
A Distributed SDP Approach for Large-Scale Noisy Anchor-Free Graph Realization with Applications to Molecular Conformation

We propose a distributed algorithm for solving Euclidean metric realization problems arising from large 3-D graphs, using only noisy distance information and without any prior knowledge of the positions of any of the vertices. In our distributed algorithm, the graph is first subdivided into smaller subgraphs using intelligent clustering methods. Then a semidefinite programming relaxation and gradient search method are used to localize each subgraph. Finally, a stitching algorithm is used to find affine maps between adjacent clusters, and the positions of all points in a global coordinate system are then derived. In particular, we apply our method to the problem of finding the 3-D molecular configurations of proteins based on a limited number of given pairwise distances between atoms. The protein molecules, all with known molecular configurations, are taken from the Protein Data Bank. Our algorithm is able to reconstruct reliably and efficiently the configurations of large protein molecules from a limited number of pairwise distances corrupted by noise, without incorporating domain knowledge such as the minimum separation distance constraints derived from van der Waals interactions.
A Constructive Geometrical Approach to the Uniqueness of Markov Stationary Equilibrium in Stochastic Games of Intergenerational Altruism

We provide sufficient conditions for existence and uniqueness of a monotone, Lipschitz continuous Markov stationary Nash equilibrium (MSNE) and characterize its associated Stationary Markov equilibrium in a class of intergenerational paternalistic altruism models with stochastic production. Our methods are constructive, and emphasize both order-theoretic and geometrical properties of nonlinear fixed point operators, and relate our results to the construction of globally stable numerical schemes that construct approximate Markov equilibrium in our models. Our results provide a new catalog of tools for the rigorous analysis of MSNE on minimal state spaces for OLG economies with stochastic production and limited commitment.
Neural network ensembles for video game AI using evolutionary multi-objective optimization

Recently, there has been an increasing interest in game artificial intelligence (AI). Game AI is a system that makes the game characters behave like human beings that is able to make smart decisions to achieve the target in a computer or video game. Thus, this study focuses on an automated method of generating artificial neural network (ANN) controller that is able to display good playing behaviors for a commercial video game. In this study, we create neural-based game controller for screen-capture of Ms. Pac-Man using a multi-objective evolutionary algorithm (MOEA) for training or evolving the architectures and connection weights (including biases) in ANN corresponding to conflicting goals of minimizing complexity in ANN and maximizing Ms. Pac-man game score. In particular, we have chosen the commonly-used Pareto Archived Evolution Strategy (PAES) algorithm for this purpose. After the entire training process is completed, the controller is tested for generalization using the optimized networks in single network (single-net) and neural network ensemble (multi-net) environments. The multi-net model is compared to single-net model, and the results reveal that neural network ensemble is able learn to play with good strategies in a complex, dynamic and difficult game environment which is not achievable by the individual neural network.