Miracle-dz/UniFAR-FTUs huggingface dataset:
The influence of organisational commitment, job involvement and utility perceptions on trainees’ motivation to improve work through learning

Workplace training is a key strategy often used by organisations to optimise performance. Further, trainee motivation is a key determinant of the degree to which the material learned in a training programme will be transferred to the workplace, enhancing the performance of the trainee. This study investigates the relationship between several components of the Revised Human Resource Development (HRD) Evaluation and Research Model. This model provides a framework for diagnosing and understanding the causal influences of HRD intervention outcomes on training effectiveness. Data were obtained from an online questionnaire completed by 105 employees of various organisations. Findings revealed that affective organisational commitment, job involvement and utility perceptions are predictors of motivation to learn and transfer learning. An interaction effect was found, with increased affective organisational commitment predicting greater motivation to learn when training was of lower perceived utility. These findings suggest that the design and delivery of training should emphasise the relevance and utility of the programme in order to encourage greater trainee motivation and maximise return on investment. Additionally, implementing strategies aimed at promoting organisational commitment would appear beneficial.
Cognition and Emotion : From Order to Disorder

1. Introduction Part One - Philosophy And Theory 2. The Cognitive Philosophy of Emotion 3. Cognitive Theories of Emotion 4. Cognitive Theories of Emotional Disorder 5. Towards an Integrated Cognitive Theory of Emotion: The Spaars Approach Part Two - Basic Emotions and Their Disorders 6. Fear 7. Sadness 8. Anger 9. Disgust 10. Happiness 11. Overview and Conclusions
Throughput optimization in MU-MIMO systems via exploiting bs antenna tilt

In this paper, we propose a novel framework to enhance the throughput in a single-cell multiuser multiple-input multiple-output (MU-MIMO) system via adaptive base station (BS) antenna tilting. The key idea is to partition the cell into so-called vertical regions and to apply one out of a finite number of tilt and vertical half-power beamwidth (HPBW) pairs at the BS when serving each vertical region. This strategy results in an increased average received signal-to-noise ratio (SNR) over the coverage area. A scheduler is then employed to schedule the transmission to one of the vertical regions at each time-slot with the objective to maximize a suitable utility function of users' achievable throughput. MU-MIMO zero-forcing beamforming in the horizontal plane is used at the BS to serve the users in each vertical region. Simulation results show that the proposed adaptive BS tilting scheme is a promising approach to provide a noticeable throughput gain compared to a conventional scheme employing a fixed tilt at the BS. The proposed framework also achieves a superior performance-complexity tradeoff compared to a conventional system in which the tilt can be adapted to the location of the served users at each time-slot.
Ontology Driven Query Expansion for Better Image Retrieval

As more information becomes available on the Web it is more difficult to provide effective search services for Internet users. Since, it is assumed that users do not always formulate search queries using the best terms. So, search engines invoke query expansion to increase the quality of user search results. Query expansion is useful in reducing query/document mismatch by expanding the query using words or phrases with a similar meaning or some other statistical relation to the set of relevant documents. This paper proposes an approach for ontology driven query expansion for better image retrieval. In this work the association rules; generated by mining web logs and WorldNet have been used for query expansion process. Further, an algorithm has been proposed and the performance has been measured.
Using Technology to Prepare Teachers for the Twenty‐first Century

Abstract Teacher education plays a vital role in the development of a literate, globally informed citizenry. To adequately prepare our teachers, we must ensure that they are aware of global perspectives, are proficient with the information resources and tools of the day and can adapt to the tools of the future. This paper will propose how new technologies can be used to promote global understandings and information literacy as well as the professional development of new teachers. It will conclude with a discussion of the implications for teacher‐preparation institutions and with a caution that the critical element for promoting student learning is not technology access, but good teaching.
Executive Heads and the Role of Intergovernmental Organizations: Expansionist Leadership in the United Nations and the European Union

Despite considerable advances in methods to examine leaders’ personal characteristics using at–a–distance assessment, few studies have applied such techniques outside of the national level. This study reveals that such approaches can provide analytical leverage for examining executive heads of intergovernmental organizations (IGOs). The personal characteristics of six United Nations Secretaries–General and four European Union Commission Presidents were measured via content analysis of their responses to questions. Separately, their behavior in office was measured via historical accounts and analyses. In general, executive heads with higher expansionist leadership style scores displayed a greater willingness to try to enhance the status of their organizations.
Division of labor in a group of robots inspired by ants' foraging behavior

In this article, we analyze the behavior of a group of robots involved in an object retrieval task. The robots' control system is inspired by a model of ants' foraging. This model emphasizes the role of learning in the individual. Individuals adapt to the environment using only locally available information. We show that a simple parameter adaptation is an effective way to improve the efficiency of the group and that it brings forth division of labor between the members of the group. Moreover, robots that are best at retrieving have a higher probability of becoming active retrievers. This selection of the best members does not use any explicit representation of individual capabilities. We analyze this system and point out its strengths and its weaknesses.
Socio-Economic Resources and Differential Ageing

ABSTRACT The Sociology and Social Policy Research Unit of the Berlin Aging Study focuses on four substantive areas: (1) life course antecedents and generational experiences, (2) later phases of the family life course, (3) action resources and social participation, and (4) economic situations and the provision of care. This paper reports results on the relationship between social and economic inequality and differential ageing, using the BASE multidisciplinary Intake Assessment (N = 360). The socio-economic position of older people is measured along three dimensions: economic resources, social status and prestige, and cultural status. Several ageing outcomes are considered, including functional physical health, cognitive functioning and mental health, overall subjective well-being, social autonomy and dependency. First, we show that old people as a group are neither socially nor economically homogeneous: very old women possess unusually low economic resources; and cohort differences in educational attainment are carried into old age. Second, cognitive functioning and mental health are positively correlated with socio-economic resources, while functional physical health is not. For women, socio-economic resources slightly affect overall subjective well-being, and are linked to the likelihood of living in a nursing home. We speculate that the wide availability of compulsory health insurance reduces social differentials in physical health and that these inequalities may determine who survives into old age.
Bi-directional astrocytic regulation of neuronal activity within a network

The concept of a tripartite synapse holds that astrocytes can affect both the pre- and post-synaptic compartments through the Ca2+-dependent release of gliotransmitters. Because astrocytic Ca2+ transients usually last for a few seconds, we assumed that astrocytic regulation of synaptic transmission may also occur on the scale of seconds. Here, we considered the basic physiological functions of tripartite synapses and investigated astrocytic regulation at the level of neural network activity. The firing dynamics of individual neurons in a spontaneous firing network was described by the Hodgkin–Huxley model. The neurons received excitatory synaptic input driven by the Poisson spike train with variable frequency. The mean field concentration of the released neurotransmitter was used to describe the presynaptic dynamics. The amplitudes of the excitatory postsynaptic currents (PSCs) obeyed the gamma distribution law. In our model, astrocytes depressed the presynaptic release and enhanced the PSCs. As a result, low frequency synaptic input was suppressed while high frequency input was amplified. The analysis of the neuron spiking frequency as an indicator of network activity revealed that tripartite synaptic transmission dramatically changed the local network operation compared to bipartite synapses. Specifically, the astrocytes supported homeostatic regulation of the network activity by increasing or decreasing firing of the neurons. Thus, the astrocyte activation may modulate a transition of neural network into bistable regime of activity with two stable firing levels and spontaneous transitions between them.
StereoPasting: Interactive Composition in Stereoscopic Images

We propose "StereoPasting,” an efficient method for depth-consistent stereoscopic composition, in which a source 2D image is interactively blended into a target stereoscopic image. As we paint "disparity” on a 2D image, the disparity map of the selected region is gradually produced by edge-aware diffusion, and then blended with that of the target stereoscopic image. By considering constraints of the expected disparities and perspective scaling, the 2D object is warped to generate an image pair, which is then blended into the target image pair to get the composition result. The warping is formulated as an energy minimization, which could be solved in real time. We also present an interactive composition system, in which users can edit the disparity maps of 2D images by strokes, while viewing the composition results instantly. Experiments show that our method is intuitive and efficient for interactive stereoscopic composition. A lot of applications demonstrate the versatility of our method.
An evolutionary controllers' placement algorithm for reliable SDN networks

SDN controllers placement in TelCo networks are generally multi-objective and multi-constrained problems. The solutions proposed in the literature usually model the placement problem by providing a mixed integer linear program (MILP). Their performances are, however, quickly limited for large sized networks, due to the significant increase in the computational delays. In order to avoid the inherent complexity of optimal approaches and the lack of flexibility of heuristics, we propose in this paper a genetic algorithm designed from the NSGA II framework that aims to deal with the controller placement problem. Genetic algorithms can, indeed, be both multi-objective, multi-constraints and can be designed to be computed in parallel. They constitute a real opportunity to find good solutions to this category of problems. Furthermore, the proposed algorithm can be easily adapted to manage dynamic placements scenarios. The goal chosen, in this work, is to maximize the clusters average connectivity and to balance the control's load between clusters, in a way to improve the networks' reliability. The evaluation results on a set of network topologies demonstrated very good performances, which achieve optimal results for small networks.
Visualization of Dynamic Trafficking of a Protein Kinase C βII/Green Fluorescent Protein Conjugate Reveals Differences in G Protein-coupled Receptor Activation and Desensitization*

Protein kinase C (PKC) links various extracellular signals to intracellular responses and is activated by diverse intracellular factors including diacylglycerol, Ca2+, and arachidonic acid. In this study, using a fully functional green fluorescent protein conjugated PKCβII (GFP-PKCβII), we demonstrate a novel approach to study the dynamic redistribution of PKC in live cells in response to G protein-coupled receptor activation. Agonist-induced PKC translocation was rapid, transient, and selectively mediated by the activation of Gqα- but not Gsα- or Giα-coupled receptors. Interestingly, although the stimuli were continuously present, only one brief peak of PKC membrane translocation was observed, consistent with rapid desensitization of the signaling pathway. Moreover, when GFP-PKCβII was used to examine cross-talk between two Gqα-coupled receptors, angiotensin II type 1A receptor (AT1AR) and endothelin A receptor (ETAR), activation of ETARs resulted in a subsequent loss of AT1AR responsiveness, whereas stimulation of AT1ARs did not cause desensitization of the ETAR signaling. The development of GFP-PKCβII has allowed not only the real time visualization of the dynamic PKC trafficking in live cells in response to physiological stimuli but has also provided a direct and sensitive means in the assessment of activation and desensitization of receptors implicated in the phospholipase C signaling pathway.
Human emotion recognition from motion using a radial basis function network architecture

A radial basis function network architecture is developed that learns the correlation of facial feature motion patterns and human emotions. We describe a hierarchical approach which at the highest level identifies emotions, at the mid level determines motion of facial features, and at the low level recovers motion directions. Individual emotion networks were trained to recognize the 'smile' and 'surprise' emotions. Each emotion network was trained by viewing a set of sequences of one emotion for many subjects. The trained neural network was then tested for retention, extrapolation and rejection ability. Success rates were about 88% for retention, 73% for extrapolation, and 79% for rejection. <<ETX>>
SEMIPARAMETRIC BAYESIAN INFERENCE FOR DYNAMIC TOBIT PANEL DATA MODELS WITH UNOBSERVED HETEROGENEITY

This paper develops semiparametric Bayesian methods for inference of dynamic Tobit panel data models. Our approach requires that the conditional mean dependence of the unobserved heterogeneity on the initial conditions and the strictly exogenous variables be specified. Important quantities of economic interest such as the average partial effect and average transition probabilities can be readily obtained as a by-product of the Markov chain Monte Carlo run. We apply our method to study female labor supply using a panel data set from the National Longitudinal Survey of Youth 1979. Copyright © 2008 John Wiley & Sons, Ltd.
Measuring Divergent Thinking Attitudes Related to Creative Problem Solving and Innovation Management

In an increasingly complex and changing business environment, creativity is becoming recognized as a critical success factor for organizations. The identification of attitudes toward creativity and the subsequent development of creative thinking are important mechanisms for organizations to encourage creativity across all employees. Employee attitudes toward creativity can indicate their potential for behaving in a creative manner, and organizations that can incorporate creativity into their organizational culture can further encourage creative thinking. This research extended previous research that had identified 2 divergent thinking attitudes related to organizational creativity. Three additional attitudes were identified as "valuing new ideas," "creative individual stereotypes," and "too busy for new ideas," using various psychometric and substantive analyses with 2 large samples including both business students and employees of industrial organizations. Basic scales were established to measure all 3 a.
The Role of Affect in Public Support and Opposition to Wolf Management

Individuals process information through two systems: the experiential system, containing affect and emotion, and the analytic system, containing logic and normative rules. Both are involved in decision making, and expected to help explain choices to support or oppose wildlife-related policies. In the present study, an Internet survey of motivated, informed individuals is used to investigate the role of both systems in wolf recovery policy choices. Integral affect measures serve as the experiential component in our model, while objective knowledge and beliefs about outcomes of wolf recovery serve as the analytic component. Results indicate that affect has a greater effect than knowledge on beliefs, and is more important for explaining intentions to oppose than to support wolf recovery. Knowledge of differences in information processing between those that support versus oppose wolf recovery allows managers to design outreach that motivates greater analytic processing, potentially mitigating the effects of experiential processing.
Automatic detection of optimal azimuth widths for sound source separation using Adress

The Adress algorithm has proved successful as a means of separating sound sources from stereo mixtures. The algorithm has two main parameters, azimuth position and azimuth width, and these are typically set by the user for each source individually. For the separation of large amounts of audio material, such as in an audio archive, a method of automatically setting these parameters would be of use. This paper proposes a method of automatically obtaining the azimuth widths for the sources in a mixture by balancing the reconstruction error between the original spectrograms and the resynthesised spectrograms with the sparseness of the recovered sources, using an L-curve type approach.
Adaptive divergence within and between ecotypes of the terrestrial garter snake, Thamnophis elegans, assessed with FST‐QST comparisons

Populations of the terrestrial garter snake (Thamnophis elegans) around Eagle Lake in California exhibit dramatic ecotypic differentiation in life history, colouration and morphology across distances as small as a few kilometres. We assayed the role of selection in ecotypic differentiation in T. elegans using FST‐QST analysis and identified selective agents using direct and indirect observations. We extended the conventional implementation of the FST‐QST approach by using three‐level analyses of genetic and phenotypic variance to assess the role of selection in differentiating populations both within and between ecotypes. These results suggest that selection has driven differentiation between as well as within ecotypes, and in the presence of moderate to high gene flow. Our findings are discussed in the context of previous correlational selection analyses which revealed stabilizing and correlational selection for some of the traits examined.
Hypothalamic miRNAs: emerging roles in energy balance control

The hypothalamus is a crucial central nervous system area controlling appetite, body weight and metabolism. It consists in multiple neuronal types that sense, integrate and generate appropriate responses to hormonal and nutritional signals partly by fine-tuning the expression of specific batteries of genes. However, the mechanisms regulating these neuronal gene programmes in physiology and pathophysiology are not completely understood. MicroRNAs (miRNAs) are key regulators of gene expression that recently emerged as pivotal modulators of systemic metabolism. In this article we will review current evidence indicating that miRNAs in hypothalamic neurons are also implicated in appetite and whole-body energy balance control.
Evaluating battery aging on mobile devices

Battery-related problems in mobile devices have been extensively investigated in both industry and literature. In particular, battery aging is a critical issue, since battery lifetime decreases as usage time increases. Battery aging primarily causes inconvenience to users by necessitating frequent recharging, and also affects the accuracy of power estimations for mobile devices. Evaluating battery aging and its effects has rarely been addressed in prior works. In this paper, we propose an online scheme to quantify the battery aging of mobile devices. Specifically, we estimate the degree of battery aging as a ratio metric based on patterns of charging time. For example, an estimate of 50% indicates that the battery capacity is only half of full capacity, meaning that the battery usage time is only approximately half that of the new battery's. Our scheme works autonomously on mobile devices and does not require any external equipment. The extensive experiments demonstrated that the proposed scheme quantifies battery aging accurately.
Accurate collision response on polygonal meshes

We present a very general geometrical correction method for enforcing collisions and other geometrical constraints between polygonal mesh surfaces. It is based on a global resolution scheme that takes advantage of an efficient use of the conjugate gradient algorithm to find the appropriate displacement of the mesh vertices that would satisfy all the constraints simultaneously, and according to momentum conservation laws. This method has been implemented in a cloth simulation system along with a collision response model that enforces a minimum "thickness" distance between cloth surfaces, which can be efficiently integrated in an simulation scheme based on implicit integration. Some provided examples illustrate the efficiency of the method.
Comparison of EMG activity during stable and unstable push-up protocols

Abstract This experiment examined muscle activation measured using electromyography (EMG) during a standardized push-up performed on stable and unstable surfaces. Fifteen highly trained participants performed four push-ups: standard (hands and feet on the floor), either the hands or feet on an unstable surface (single instability), and with both hands and feet on unstable surfaces (dual instability). Unstable surfaces were created using a stability ball and an extreme balance board. EMG activity was recorded from three core stabilizers (erector spinae, rectus abdominus and internal obliques), one prime mover (triceps), and one lower body stabilizer (soleus). The EMG time series were smoothed using a 10-point moving average and root mean squares (RMS) were calculated for the entire time series. The results showed that push-ups performed with dual instability had significantly greater EMG activation compared to single instability or the stable push-up. In addition, as instability increased, there was a greater amount of muscle activation for the core stabilizers, prime movers and lower body stabilizers. The findings are consistent with the position that unstable surfaces in conjunction with standard exercises can be used to increase activation of core trunk stabilizers. This may in turn provide increased trunk strength and greater resistance to injury.
Complete Genome Sequence for the Fusarium Head Blight Antagonist Bacillus amyloliquefaciens Strain TrigoCor 1448

ABSTRACT We present the complete genome sequence for Bacillus amyloliquefaciens TrigoCor 1448 (ATCC 202152), a bacterial biological control agent for Fusarium head blight in wheat. We compare it to its closest relative, B. amyloliquefaciens strain AS43.3.