Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimizing Expatriates’ Contributions to Organizational Learning1 Expatriate managers acquire a wide and deep range of knowledge while living

Organizational learning theories suggest that organizations tend to know less than the sum of the knowledge of their members. In light of trends towards globalization with concomitant localization, the knowledge gained by international managers is a crucial resource for organizations seeking to understand and influence their multiple stakeholders in diverse environments. Expatriate managers return from overseas assignments with a wealth of different kinds of knowledge, but active strategies are needed in order for this individual resource to become embedded into the organization. This study of two German-based multinational companies found little evidence of strategic use of returned expatriates for organizational learning. To the extent that knowledge was transformed from a purely individual resource into an organizational asset (e.g., change in method or policy), the learning was driven by the returned expatriates rather than by the organization itself. The research suggests that if organizations are to optimize their learning from their international managers, a conscious knowledge-management approach to the entire expatriation cycle is needed. Using the data from the interviews and the insights from organizational learning theory, improvements on the frequently used expatriation cycle are proposed.
Variation in the strength of selected codon usage bias among bacteria

Among bacteria, many species have synonymous codon usage patterns that have been influenced by natural selection for those codons that are translated more accurately and/or efficiently. However, in other species selection appears to have been ineffective. Here, we introduce a population genetics-based model for quantifying the extent to which selection has been effective. The approach is applied to 80 phylogenetically diverse bacterial species for which whole genome sequences are available. The strength of selected codon usage bias, S, is found to vary substantially among species; in 30% of the genomes examined, there was no significant evidence that selection had been effective. Values of S are highly positively correlated with both the number of rRNA operons and the number of tRNA genes. These results are consistent with the hypothesis that species exposed to selection for rapid growth have more rRNA operons, more tRNA genes and more strongly selected codon usage bias. For example, Clostridium perfringens, the species with the highest value of S, can have a generation time as short as 7 min.
Forcing Versus Feedback: Epidemic Malaria and Monsoon Rains in Northwest India

Malaria epidemics in regions with seasonal windows of transmission can vary greatly in size from year to year. A central question has been whether these interannual cycles are driven by climate, are instead generated by the intrinsic dynamics of the disease, or result from the resonance of these two mechanisms. This corresponds to the more general inverse problem of identifying the respective roles of external forcings vs. internal feedbacks from time series for nonlinear and noisy systems. We propose here a quantitative approach to formally compare rival hypotheses on climate vs. disease dynamics, or external forcings vs. internal feedbacks, that combines dynamical models with recently developed, computational inference methods. The interannual patterns of epidemic malaria are investigated here for desert regions of northwest India, with extensive epidemiological records for Plasmodium falciparum malaria for the past two decades. We formulate a dynamical model of malaria transmission that explicitly incorporates rainfall, and we rely on recent advances on parameter estimation for nonlinear and stochastic dynamical systems based on sequential Monte Carlo methods. Results show a significant effect of rainfall in the inter-annual variability of epidemic malaria that involves a threshold in the disease response. The model exhibits high prediction skill for yearly cases in the malaria transmission season following the monsoonal rains. Consideration of a more complex model with clinical immunity demonstrates the robustness of the findings and suggests a role of infected individuals that lack clinical symptoms as a reservoir for transmission. Our results indicate that the nonlinear dynamics of the disease itself play a role at the seasonal, but not the interannual, time scales. They illustrate the feasibility of forecasting malaria epidemics in desert and semi-arid regions of India based on climate variability. This approach should be applicable to malaria in other locations, to other infectious diseases, and to other nonlinear systems under forcing.
A 2 : Universal basic services for parallel systems

Basic services like, e.g., routing, load balancing, or data management are essential for efficient usage of parallel and distributed systems. Therefore, the subproject A2 of our CRC376 has focused on design, analysis and implementation of such services. In this report we briefly survey the work of this subproject from 1995 until today. The main part of the report gives more detailed surveys on three of our very recent topics: Dynamic page migration for mobile wireless networks, selfish routing in non-cooperative networks, and exact graph partitioning for process management in parallel systems.
A MULTI-AGENT FRAMEWORK FOR SUPPORTING WEB-BASED INTELLIGENT FOURTH PARTY LOGISTICS

A distributed intelligent agent-based framework that supports fourth-party logistics optimization under a web-based e-Commerce environment has been proposed in this paper. In the framework, customer job requests come through an e-Procurement service. These requests are consolidated and pushed to the e-Market Place service periodically. The e-Market Place then serves as a broker that allows intelligent agents to bid to serve these requests optima lly in real-time by solving multiple instances of underlying logistics optimization problem. The resulting system was implemented based on the Java 2 Enterprise Edition (J2EE) platform using distributed system technology for communication between objects.
LAS PROPUESTAS DE LA PSICOLOGÍA POSITIVA. ¿UNIVERSALES PSICOLÓGICOS O PARTICULARES DE UNA VISIÓN CULTURAL? pROpOSalS FROM pOSiTiVe pSYCHOlOgY ¿ pSYCHOlOgiCal UniVeRSalS OR paRTiCUlaR COnCepTS FROM a CUlTURal peRSpeCTiVe?

The paper presents, in the first place, a list of advances on design and adaptation of instruments to assess variables derived from Positive Psychology. This paradigm focuses on protective factors which preserve persons from psychological disease. On the other hand, the potential universality of these concepts is analyzed, facing the goal to take into account the possible validity of generalizations.
Generative Models for Clustering: The Next Generation

Clustering social information is challenging when both attributes and relations are present. Many approaches commonly used today ignore one aspect of the data or the other. Relation-only algorithms are typically limited because the sparseness of relations in social information makes finding strong patterns difficult. Feature-only algorithms have the limitation that the most interesting (and useful) aspect of social information is the set of relations between objects. Recently, there has been a surge in interest in simultaneously considering both features and relations in the operation of a clustering algorithm. Several of these approaches are based on a generative model, which corresponds to an assumption that the data exists as part of some unobserved probability distribution. Each of the approaches discussed in this paper have good initial results. After discussing each in turn, we discuss in broad terms what has been accomplished thus far with generative models, what open problems remain, and how the development of generative models for relational data can contribute to the field of social information processing.
An Integrated Epigenetic and Genetic Analysis of DNA Methyltransferase Genes (DNMTs) in Tumor Resistant and Susceptible Chicken Lines

Both epigenetic alterations and genetic variations play essential roles in tumorigenesis. The epigenetic modification of DNA methylation is catalyzed and maintained by the DNA methyltransferases (DNMT3a, DNMT3b and DNMT1). DNA mutations and DNA methylation profiles of DNMTs themselves and their relationships with chicken neoplastic disease resistance and susceptibility are not yet defined. In the present study, we analyzed the complexity of the DNA methylation variations and DNA mutations in the first exon of three DNMTs genes over generations, tissues, and ages among chickens of two highly inbred White Leghorn lines, Marek's disease-resistant line 63 and -susceptible line 72, and six recombinant congenic strains (RCSs). Among them, tissue-specific methylation patterns of DNMT3a were disclosed in spleen, liver, and hypothalamus in lines 63 and 72. The methylation level of DNMT3b on four CpG sites was not significantly different among four tissues of the two lines. However, two line-specific DNA transition mutations, CpG→TpG (Chr20:10203733 and 10203778), were discovered in line 72 compared to the line 63 and RCSs. The methylation contents of DNMT1 in blood cell showed significant epimutations in the first CpG site among the two inbred lines and the six RCSs (P<0.05). Age-specific methylation of DNMT1 was detected in comparisons between 15 month-old and 2 month-old chickens in both lines except in spleen samples from line 72. No DNA mutations were discovered on the studied regions of DNMT1 and DNMT3a among the two lines and the six RCSs. Moreover, we developed a novel method that can effectively test the significance of DNA methylation patterns consisting of continuous CpG sites. Taken together, these results highlight the potential of epigenetic alterations in DNMT1 and DNMT3a, as well as the DNA mutations in DNMT3b, as epigenetic and genetic factors to neoplastic diseases of chickens.
H2 and Brγ Narrowband Imaging of Bipolar Planetary Nebulae

We present near-IR narrowband continuum-subtracted images in the H2 2.122 μm, and Brγ 2.166 μm emission lines for a sample of 15 bipolar planetary nebulae (PNe). H2 emission was definitely detected for most of the objects in this sample (13 of 15). The very high H2 detection rate supports the idea that bipolar PNe have important reservoirs of molecular material and offer suitable physical conditions for the excitation of H2. The strength of the H2 emission and the H2/Brγ flux ratio are found to correlate with the morphology of the bipolar PNe observed. Bipolar PNe with broad and bright rings exhibit stronger H2 emission than bipolar PNe with narrow twists. High-quality (subarcsec) [N II] and Hα optical images have been used to compare the distribution of the ionized and molecular material. The H2 emission lies just outside the optical [N II] emission zone.
Out‐of‐the‐loop performance problems and the use of intermediate levels of automation for improved control system functioning and safety

Human supervisory control and monitoring of automated systems, as well as, passive system(s) information processing can all be classified as forms of out‐of‐the‐loop (OOTL) performance. Whether the operator's task is to decide if process control intervention is necessary, detect a critical system event, or accept or reject the actions of a computer controller, he or she is removed from direct, real‐time control of the system. OOTL performance is a critical issue in overall automated systems functioning because it is associated with numerous negative consequences including: (a) operator failure to observe system parameter changes and intervene when necessary (vigilance decrements); (b) human over‐trust in computer controllers (complacency); (c) operator loss of system or situation awareness; and (d) operator direct/manual control skill decay. These consequences have been found to impact human performance under both normal operating conditions and system failure modes, with a greater effect on the latter [15] leading to serious problems in operator ability to perform their assigned tasks when working with automated systems.
Interprocedural parallelization analysis in SUIF

As shared-memory multiprocessor systems become widely available, there is an increasing need for tools to simplify the task of developing parallel programs. This paper describes one such tool, the automatic parallelization system in the Stanford SUIF compiler. This article represents a culmination of a several-year research effort aimed at making parallelizing compilers significantly more effective. We have developed a system that performs full interprocedural parallelization analyses, including array privatization analysis, array reduction recognition, and a suite of scalar data-flow analyses including symbolic analysis. These analyses collaborate in an integrated fashion to exploit coarse-grain parallel loops, computationally intensive loops that can execute on multiple processors independently with no cross-processor synchronization or communication. The system has successfully parallelized large interprocedural loops over a thousand lines of code completely automatically from sequential applications.This article provides a comprehensive description of the analyses in the SUIF system. We also present extensive empirical results on four benchmark suites, showing the contribution of individual analysis techniques both in executing more of the computation in parallel, and in increasing the granularity of the parallel computations. These results demonstrate the importance of interprocedural array data-flow analysis, array privatization and array reduction recognition; a third of the programs spend more than 50&percent; of their execution time in computations that are parallelized with these techniques. Overall, these results indicate that automatic parallelization can be effective on sequential scientific computations, but only if the compiler incorporates all of these analyses.
Gaze pattern analysis for video contents with different frame rates

This paper presents a study investigating the viewing behavior of human subjects for video contents having different frame rates. Frame rate variability arises when temporal video scalability is considered for adaptive video transmission, and the gaze pattern variation due to the frame rate variability would eventually affect the visual perception, which needs to be considered during perceptual optimization of such a system. We design an eye-tracking experiment using several high definition contents having a wide range of content characteristics. By comparing the gaze points for a normal frame rate condition and a low frame rate condition, it is shown that, although the overall viewing pattern remains quite similar, statistically significant difference is also observed for some time intervals. The difference is analyzed in terms of two factors, namely, overall gaze paths and subject-wise variability.
Morphological and Embedded Computation in a Self-contained Soft Robotic Hand

We present a self-contained, soft robotic hand composed of soft pneumatic actuator modules that are equipped with strain and pressure sensing. We show how this data can be used to discern whether a grasp was successful. Colocating sensing and embedded computation with the actuators greatly simplifies control and system integration. Equipped with a small pump, the hand is self-contained and needs only power and data supplied by a single USB connection to a PC. We demonstrate its function by grasping a variety of objects ranging from very small to large and heavy objects weighing more than the hand itself. The presented system nicely illustrates the advantages of soft robotics: low cost, low weight, and intrinsic compliance. We exploit morphological computation to simplify control, which allows successful grasping via underactuation. Grasping indeed relies on morphological computation at multiple levels, ranging from the geometry of the actuator which determines the actuator’s kinematics, embedded strain sensors to measure curvature, to maximizing contact area and applied force during grasping. Morphological computation reaches its limitations, however, when objects are too bulky to self-align with the gripper or when the state of grasping is of interest. We therefore argue that efficient and reliable grasping also requires not only intrinsic compliance, but also embedded sensing and computation. In particular, we show how embedded sensing can be used to detect successful grasps and vary the force exerted onto an object based on local feedback, which is not possible using morphological computation alone.
Homing strategies of the Australian desert ant Melophorus bagoti II. Interaction of the path integrator with visual cue information

SUMMARY Individually foraging ants are known to return to their nest by using path-integration and recording visual information present in the environment. The interaction between the path integrator and the information provided by the visual cues in an Australian desert ant are reported here. Ants were trained to travel in a 1-m wide and 20-m long corridor of cylinders. Homeward paths of trained ants were recorded in the presence and absence of vector information and route cues in both the familiar training field and in an unfamiliar test field. Homing ants used route cue information only in a familiar context. The route cues were not essential but served to reduce the deviation of the homing trajectory from the nest–feeder line. When displaced locally, homebound ants initially oriented towards the nest using distant cues and then headed in a direction intermediate between that dictated by the path integrator and the distant cues. If in the course of travel ants encountered the familiar path they adhered to it. If not, they travelled on average half the distance of the outbound journey and initiated a search directed towards the nest. Following the search, ants headed in a direction intermediate between that dictated by the route cues and the distant cues. In an unfamiliar context neither vector nor route cue information could steer a homing ant towards the nest. The dominance of distant cues, the importance of familiar context and the interaction between different navigation strategies are discussed here.
Estimating Probabilities of Default with Support Vector Machines

This paper proposes a rating methodology that is based on a non-linear classification method, the support vector machine, and a non-parametric technique for mapping rating scores into probabilities of default. We give an introduction to underlying statistical models and represent the results of testing our approach on Deutsche Bundesbank data. In particular we discuss the selection of variables and give a comparison with more traditional approaches such as discriminant analysis and the logit regression. The results demonstrate that the SVM has clear advantages over these methods for all variables tested.
Geometric characterization of intermittency in the parabolic Anderson model

We consider the parabolic Anderson problem @tu = u + (x)u on R+ Z d with localized initial condition u(0;x) = 0(x) and random i.i. d. potential . Under the assumption that the distribution of (0) has a double-exponential, or slightly heavier, tail, we prove the following geometric characterisation of intermittency: with probability one, as t ! 1, the overwhelming contribution to the total mass P x u(t;x) comes from a slowly increasing number of 'islands' which are located far from each other. These 'islands' are local regions of those high exceedances of the eld in a box of side length 2t log 2 t for which the (local) principal Dirichlet eigenvalue of the random operator + is close to the top of the spectrum in the box. We also prove that the shape of in these regions is non-random and that u(t; ) is close to the corresponding positive eigenfunction. This is the geometric picture suggested by localization theory for the Anderson Hamiltonian.
Regulators of Rho GTPases in Neuronal Development

The formation and elaboration of axonal and dendritic morphologies are fundamental aspects of neuronal polarization critical for information processing. In general, developing CNS neurons elaborate one axon and multiple dendrites in response to intracellular and extracellular cues, so as to transmit and receive information, respectively. The molecular mechanisms underlying axon–dendrite polarity are complex and involve the integration of numerous signaling pathways that impinge on the cytoskeleton. One group of proteins, the Rho GTPases, has emerged as key integrators of environmental cues to regulate the underlying axonal and dendritic cytoskeletons. Here, we discuss the role of regulators of the Rac1 GTPase in axon development and highlight the importance of both actin and microtubule remodeling in this process.
A Study on the Relationship Between Organization Reciprocity Behaviors and Job Satisfaction, Turnover Intention

This paper explores that how the three kinds of reciprocity behaviors impact job satisfaction and turnover intention by using the scale developed based on background of Chinese culture and 423 employees samples from 27 enterprises in five cities. The results demonstrate that there are positive correlation between generalized reciprocity, balanced and job satisfaction, and negative correlation between negative reciprocity and job satisfaction, that there are negative correlation between generalized reciprocity, balanced reciprocity and turnover intention, and positive correlation between negative reciprocity and turnover intention. Based on the research finding, recommendations are listed in the hope of providing helps and supports to enterprises incentive mechanisms.
Training the Genre Classifier for Automatic Classification of Web Pages

This paper presents experiments on classifying web pages by genre. Firstly, a corpus of 1539 manually labeled web pages was prepared. Secondly, 502 genre features were selected based on the literature and the observation of the corpus. Thirdly, these features were extracted from the corpus to obtain a data set. Finally, two machine learning algorithms, one for induction of decision trees (J48) and one ensemble algorithm (bagging), were trained and tested on the data set. The ensemble algorithm achieved on average 17% better precision and 1.6% better accuracy, but slightly worse recall; F-measure did not vary significantly. The results indicate that classification by genre could be a useful addition to search engines.
Expanding the Knowledge Acquisition Bottleneck for Intelligent Tutoring Systems

The first conference workshop on authoring tools for intelligent tutoring systems (ITSs) was held at the AI and Education conference in 1995. Since then a number of workshops and symposia on ITS authoring, cost-effective production, and reusability have been offered and well attended (see "Related worksh ops and symposia" at the end of this article). The field has come a long way in the last decade, and the time is right to take stock of where we are. Submissions to this special issue were numerous enough to require that it be organized into two parts. We expect to have Part II of this special issue published within a year. In Part II this introductory paper will be expanded into a more complete overview of the state of the art in ITS authoring tools.