Miracle-dz/UniFAR-FTUs huggingface dataset:
Intangible assets and decline: a population ecology perspective

Abstract This paper investigates the effects of environmental pressure, human capital, and social capital on organizational effectiveness and decline using a population ecology perspective. Panel data with 1,553 observations from 398 companies spanning 4 years in Taiwan were used for analyses. Research results indicate that several environmental pressure indicators significantly affect organization effectiveness and decline. Although human capital and social capital did not predict our outcome variables, human capital plays a moderating role in explaining the variation of the relationship between environmental pressure and organizational effectiveness. This paper provides a new perspective that suggests that organizations should accumulate intangible assets to resist the threat of external environmental pressure. The leading consumer electronics company Samsung is a good example supporting our argument that investment in human capital can produce commercial benefits, especially in tough economic times.
Visuomotor delay in interceptive actions

Abstract Neural delays, which are generally defined as visuomotor delays in interceptive actions, must be compensated to enable accurate timing in movement. Visuomotor delays can depend on the kind of task, the use of information, and the skill of the performer. The compensation for such delays does not necessarily require prediction or representation but can be made by an attunement of some parameters in what is called a law of control.
MRE11-Deficiency Associated with Improved Long-Term Disease Free Survival and Overall Survival in a Subset of Stage III Colon Cancer Patients in Randomized CALGB 89803 Trial

Purpose Colon cancers deficient in mismatch repair (MMR) may exhibit diminished expression of the DNA repair gene, MRE11, as a consequence of contraction of a T11 mononucleotide tract. This study investigated MRE11 status and its association with prognosis, survival and drug response in patients with stage III colon cancer. Patients and Methods Cancer and Leukemia Group B 89803 (Alliance) randomly assigned 1,264 patients with stage III colon cancer to postoperative weekly adjuvant bolus 5-fluorouracil/leucovorin (FU/LV) or irinotecan+FU/LV (IFL), with 8 year follow-up. Tumors from these patients were analyzed to determine stability of a T11 tract in the MRE11 gene. The primary endpoint was overall survival (OS), and a secondary endpoint was disease-free survival (DFS). Non-proportional hazards were addressed using time-dependent covariates in Cox analyses. Results Of 625 tumor cases examined, 70 (11.2%) exhibited contraction at the T11 tract in one or both MRE11 alleles and were thus predicted to be deficient in MRE11 (dMRE11). In pooled treatment analyses, dMRE11 patients showed initially reduced DFS and OS but improved long-term DFS and OS compared with patients with an intact MRE11 T11 tract. In the subgroup of dMRE11 patients treated with IFL, an unexplained early increase in mortality but better long-term DFS than IFL-treated pMRE11 patients was observed. Conclusions Analysis of this relatively small number of patients and events showed that the dMRE11 marker predicts better prognosis independent of treatment in the long-term. In subgroup analyses, dMRE11 patients treated with irinotecan exhibited unexplained short-term mortality. MRE11 status is readily assayed and may therefore prove to be a useful prognostic marker, provided that the results reported here for a relatively small number of patients can be generalized in independent analyses of larger numbers of samples. Trial Registration ClinicalTrials.gov NCT00003835
Rebel Manhood

Southern men occupy a contradictory place in U.S. culture as the rest of the country stereotypes them as backwards and deviant, yet simultaneously celebrates Southern males as quintessential exemplars of American manhood. I explore this contradiction using interviews with musicians, participant observation of concerts, and an ethnographic content analysis of contemporary Southern rock lyrics and websites. I find marginalized men embrace a Southern rebel identity to meet hegemonic masculine ideals shared across social classes and geographic regions. Rebels reject the middle class roles and cultural capital most men use to signify their manhood by accruing authority and resources through education, career, and family. Instead, southern rebels empower the masculine self by protesting authority figures, dominating women and signifying their independence by drinking, using drugs, and brawling. While rebels define their selves in contrast to middle-class morals and practices, dismissing them as deviant and backward overlooks how rebels use the symbolic resources they have at their disposal to meet the hegemonic masculine ideals celebrated throughout the country.
Identification of emotional facial expressions among behaviorally inhibited adolescents with lifetime anxiety disorders

The current study examined differences in emotion expression identification between adolescents characterised with behavioural inhibition (BI) in childhood with and without a lifetime history of anxiety disorder. Participants were originally assessed for BI during toddlerhood and for social reticence during childhood. During adolescence, participants returned to the laboratory and completed a facial emotion identification task and a clinical psychiatric interview. Results revealed that behaviorally inhibited adolescents with a lifetime history of anxiety disorder displayed a lower threshold for identifying fear relative to anger emotion expressions compared to non-anxious behaviorally inhibited adolescents and non-inhibited adolescents with or without anxiety. These findings were specific to behaviorally inhibited adolescents with a lifetime history of social anxiety disorder. Thus, adolescents with a history of both BI and anxiety, specifically social anxiety, are more likely to differ from other adolescents in their identification of fearful facial expressions. This offers further evidence that perturbations in the processing of emotional stimuli may underlie the aetiology of anxiety disorders.
Optimal Charging Scheduling of Electric Vehicles in Smart Grids by Heuristic Algorithms

Transportation electrification has become an important issue in recent decades and the large scale deployment of electric vehicles (EVs) has yet to be achieved. The smart coordination of EV demand addresses an improvement in the flexibility of power systems and reduces the costs of power system investment. The uncertainty in EV drivers’ behaviour is one of the main problems to solve to obtain an optimal integration of EVs into power systems. In this paper, an optimisation algorithm to coordinate the charging of EVs has been developed and implemented using a Genetic Algorithm (GA), where thermal line limits, the load on transformers, voltage limits and parking availability patterns are taken into account to establish an optimal load pattern for EV charging-based reliability. This methodology has been applied to an existing residential low-voltage system. The results indicate that a smart charging schedule for EVs leads to a flattening of the load profile , peak load shaving and the prevention of the aging of power system elements.
When Paradigms Meet: Interacting Perspectives on Evaluation in the Non‐Profit Sector

This study examines a public debate in Australia, arising from a national government report, around how social contribution in the nonprofit sector should be assessed. Guided by several meta-perspectives on evaluation, we identify connections between foundational assumptions and normative positions on evaluation espoused by non-profit organizations (NPOs), and examine the ways in which the inter-paradigmatic context of the non-profit sector contributes to the emergence of NPOs’ different normative positions on evaluation. We conclude that particular paradigmatic orientations of NPOs (positivism, interpretivism, constructivism) lead to particular perspectives on how NPOs should engage with alternative paradigms (monism, impartial pluralism, radical pluralism).
Neural correlates of trust

Trust is a critical social process that helps us to cooperate with others and is present to some degree in all human interaction. However, the underlying brain mechanisms of conditional and unconditional trust in social reciprocal exchange are still obscure. Here, we used hyperfunctional magnetic resonance imaging, in which two strangers interacted online with one another in a sequential reciprocal trust game while their brains were simultaneously scanned. By designing a nonanonymous, alternating multiround game, trust became bidirectional, and we were able to quantify partnership building and maintenance. Using within- and between-brain analyses, an examination of functional brain activity supports the hypothesis that the preferential activation of different neuronal systems implements these two trust strategies. We show that the paracingulate cortex is critically involved in building a trust relationship by inferring another person's intentions to predict subsequent behavior. This more recently evolved brain region can be differently engaged to interact with more primitive neural systems in maintaining conditional and unconditional trust in a partnership. Conditional trust selectively activated the ventral tegmental area, a region linked to the evaluation of expected and realized reward, whereas unconditional trust selectively activated the septal area, a region linked to social attachment behavior. The interplay of these neural systems supports reciprocal exchange that operates beyond the immediate spheres of kinship, one of the distinguishing features of the human species.
From Big Data to Smart Data with the K-Nearest Neighbours Algorithm

The k-nearest neighbours algorithm is one of the most widely used data mining models because of its simplicity and accurate results. However, when it comes to deal with big datasets, with potentially noisy and missing information, this technique becomes ineffective and inefficient. Due to its drawbacks to tackle large amounts of imperfect data, plenty of research has aimed at improving this algorithm by means of data preprocessing techniques. These weaknesses have turned out as strengths and the k-nearest neighbours rule has become a core model to actually detect and correct imperfect data, eliminating noisy and redundant data, as well as correcting missing values. In this work, we delve and review the role of the k nearest neighbour algorithm can play to come up with smart data from big datasets. We analyse how this model is affected by the big data problem, but at the same time, how it can be used to transform raw data into useful data. Concretely, we discuss the benefits of recent big data technologies (Hadoop and Spark) to enable this model to address large amounts of data, as well as the usefulness of prototype reduction and missing values imputation techniques based on it. As a result, guidelines on the use of the k-nearest neighbour to obtain Smart data are provided and new potential research trends are discussed.
Evaluación de ansiedad ante exámenes: Datos de aplicación y fiabilidad de un cuestionario CAEX

Se presenta un cuestionario de evaluacion de problemas de ansiedad ante examenes. Los datos se han obtenido entre estudiantes universitarios, justo antes de realizar los examenes correspondientes. Los sujetos informar sobre sus respuestas fisiologicas, cognitivas y conductuales, asi como su ansiedad ante diferentes tipos de pruebas. Se presentan los datos sobre los grupos, items, fiabilidad y diferencias entre las escalas de frecuencia y ansiedad utilizadas.
Vulnerable story telling: narrative research in nursing

The aim of this paper is to explore the notion of the vulnerable in telling their stories. There are many reasons for vulnerable people to tell their stories, some of which are described here. Through stories, participants in research come to understand their experience, legitimise their behaviour and share their emotional experience with others in holistic form which is not `fractured' or disrupted by researchers. Stories of people in physical or mental pain, or of those who experience illness and disability, are not often heard; narrative inquiry centres on their perspectives and perceptions. The authors attempt to show that in the telling of stories, research participants have the potential to regain the power to shape their own world and identity. It also demonstrates that there is more than one reality, beyond the beliefs and perspectives of health professionals. The focus of the paper is on the role of narrative research in nursing and the way in which it enhances the understanding of professionals in order to engage with vulnerability and assist vulnerable people.
A Methodology to Identify Complex Network Attacks

are attacked on a daily basis. Identifying these attacks is a crucial task for network managers. Tools exist to assist in this task. One of the more common tools used is an Intrusion Detection System. These systems may fall short in identifying all attacks that have occurred on a network. Often an attack consists of a sequence of simple attacks. These complex attacks are more difficult to identify. The proposed methodology identified a family of complex attacks to aid in the understanding of these attacks to improve their detection. A reusable representation of these attacks was developed using ontology. Lastly, an algorithm was developed to utilize the ontological representations to extend the knowledge of complex attacks and allow for better detection of such attacks by taking advantage of the advanced reasoning inherit in ontology.
Identifying safety challenges related to major change processes

In this paper we have tried to identify the main safety challenges in a major change processes. We have explored actual large‐scale changes during deregulation of aviation and rail, and we have explored large‐scale changes in the oil and gas industry. Based on the main safety challenges we have tried to develop a framework to assess the safety of a general change process. The framework consists of key issues to be discussed among the actors involved in the change process. The actors are operators (management and workforce), safety authorities and suppliers. The use of the framework should help assess the status of the change process. We are suggesting that the status of the change process can be categorized as satisfactory (continue), not satisfactory (adjust but continue with caution) or unacceptable (halt, major adjustments must be implemented). The status of the change process can be evaluated prior to the change and during the change. The evaluation of the change prior to the change could be used as a proactive/leading indicator of the change process. The framework is going to be used in several large change processes to gather more experience and to validate and verify the framework
HistoneDB 2.0: a histone database with variants—an integrated resource to explore histones and their variants

Compaction of DNA into chromatin is a characteristic feature of eukaryotic organisms. The core (H2A, H2B, H3, H4) and linker (H1) histone proteins are responsible for this compaction through the formation of nucleosomes and higher order chromatin aggregates. Moreover, histones are intricately involved in chromatin functioning and provide a means for genome dynamic regulation through specific histone variants and histone post-translational modifications. ‘HistoneDB 2.0 – with variants’ is a comprehensive database of histone protein sequences, classified by histone types and variants. All entries in the database are supplemented by rich sequence and structural annotations with many interactive tools to explore and compare sequences of different variants from various organisms. The core of the database is a manually curated set of histone sequences grouped into 30 different variant subsets with variant-specific annotations. The curated set is supplemented by an automatically extracted set of histone sequences from the non-redundant protein database using algorithms trained on the curated set. The interactive web site supports various searching strategies in both datasets: browsing of phylogenetic trees; on-demand generation of multiple sequence alignments with feature annotations; classification of histone-like sequences and browsing of the taxonomic diversity for every histone variant. HistoneDB 2.0 is a resource for the interactive comparative analysis of histone protein sequences and their implications for chromatin function. Database URL: http://www.ncbi. nlm.nih. gov/projects/HistoneDB2.0
Investigating multitasking in high-functioning adolescents with autism spectrum disorders using the Virtual Errands Task

Using a modified version of the Virtual Errands Task (VET; McGeorge et al., 2001), we investigated the executive ability of multitasking in 18 high-functioning adolescents with ASD and 18 typically developing adolescents. The VET requires multitasking (Law, Logie & Pearson, 2006) because there is a limited amount of time in which to complete the errands. ANCOVA revealed that the ASD group completed fewer tasks, broke more rules and rigidly followed the task list in the order of presentation. Our findings suggest that executive problems of planning inflexibility, inhibition, as well as difficulties with prospective memory (remembering to carry out intentions) may lie behind multitasking difficulties in ASD.
Lipoprotein lipase activity in marasmic type of protein-calorie malnutrition.

Kwashiorkor and marasmus constitute the two major syndromes of protein-calorie malnutrition encountered in infants and young children in many parts of the world. The clinical and metabolic characteristics of these syndromes differ significantly from one another, one difference being the fat metabolism. The increase of free fatty acids (FFA) in plasma has been accepted as the key factor causing fatty liver in kwashiorkor (Korn, 1955; Feigelson et al., 1961; Lewis et al., 1964; Fletcher, 1966; Bar-on and Stein, 1968). The role of lipoprotein lipase (LPL) in the mobilization of FFA is well known. In this paper, plasma FFA and LPL levels, as well as the effect of heparin on the activation of this enzyme and its kinetics in plasma in various stages of marasmus will be presented.
In silico analysis of protein toxin and bacteriocins from Lactobacillus paracasei SD1 genome and available online databases

Lactobacillus paracasei SD1 is a potential probiotic strain due to its ability to survive several conditions in human dental cavities. To ascertain its safety for human use, we therefore performed a comprehensive bioinformatics analysis and characterization of the bacterial protein toxins produced by this strain. We report the complete genome of Lactobacillus paracasei SD1 and its comparison to other Lactobacillus genomes. Additionally, we identify and analyze its protein toxins and antimicrobial proteins using reliable online database resources and establish its phylogenetic relationship with other bacterial genomes. Our investigation suggests that this strain is safe for human use and contains several bacteriocins that confer health benefits to the host. An in silico analysis of protein-protein interactions between the target bacteriocins and the microbial proteins gtfB and luxS of Streptococcus mutans was performed and is discussed here.
A study for improved of speed response characteristic in four-switch three-phase BLDC motor

This paper presents a new speed control method using the acceleration feedforward compensation and using the disturbance torque estimate method. The proposed method improve transition response characteristic of system and has been a robust characteristic in the four-switch three-phase motor drive system in which the gain of speed controller cannot be made large enough. The simulation results prove the validity of the proposed method.
Conception d'un modèle et de frameworks de distribution d'applications sur grappes de PCs avec tolérance aux pannes à faible coût. (Design of a model and frameworks for application distribution on PC clusters with low-overhead fault tolerance)

PC clusters are distributed architectures whose adoption spreads as a result of their low cost but also their extensibility in terms of nodes. In particular, the increase in nodes is responsable for the increase of fail-stop failures which jeopardize distributed applications. The absence of efficient and portable solutions limits their use to non critical applications or without time constraints. MoLOToF is a model for application-level fault tolerance based on checkpointing. To ease the addition of fault tolerance, it proposes to structure applications using fault-tolerant skeletons as well as collaborations between the programmer and the fault tolerance system to gain in efficiency. The application of MoLOToF on SPMD and Master-Worker families of parallel algorithms lead to FT-GReLoSSS and ToMaWork frameworks respectively. Each framework provides faulttolerant skeletons suited to targeted families of algorithms and an original implementation. FTGReLoSSS uses C++ on top of MPI while ToMaWork uses Java on top of virtual shared memory system provided by JavaSpaces technology. The frameworks’ evaluation reveals a reasonable time development overhead and negligible runtime overheads in absence of fault tolerance. Experiments up to 256 nodes on a dualcore PC cluster, demonstrate a better efficiency of FT-GReLoSSS’ fault tolerance solution compared to existing system-level solutions (LAM/MPI and DMTCP).
Recurrent online kernel recursive least square algorithm for nonlinear modeling

In this paper, we proposed a recurrent kernel recursive least square (RLS) algorithm for online learning. In classical kernel methods, the kernel function number grows as the number of training sample increases, which makes the computational cost of the algorithm very high and only applicable for offline learning. In order to make the kernel methods suitable for online learning where the system is updated when a new training sample is obtained, a compact dictionary (support vectors set) should be chosen to represent the whole training data, which in turn reduces the number of kernel functions. For this purpose, a sparsification method based on the Hessian matrix of the loss function is applied to continuously examine the importance of the new training sample and determine the update of the dictionary according to the importance measure. We show that the Hessian matrix is equivalent to the correlation matrix of the training samples in the RLS algorithm. This makes the sparsification method able to be easily incorporated into the RLS algorithm and reduce the computational cost futher. Simulation results show that our algorithm is an effective learning method for online chaotic signal prediction and nonlinear system identification.
Looking on the Dark Side

To understand cognitive bases of self-reported ruminative tendencies, we examined interpretations and subsequent memories of ambiguous situations depicting opportunities for rumination. In Experiment 1, we recruited students, randomly assigned them to a distracting or ruminative concentration task, and then measured their latencies to complete fragments that resolved situational ambiguity in either a ruminative or a benign direction. Students in the ruminative task condition who previously self-identified as brooders were quicker to complete ruminative fragments. In Experiment 2, we simulated this bias to investigate its possible contribution to rumination; nonbrooding students were trained to make ruminative or benign resolutions of ambiguous situations. Ruminative training led to more negative continuations of new, potentially ruminative situations in a subsequent transfer task. Next, ruminative training also caused more negatively valenced errors in recalling the ambiguous transfer situations. Finally, after reflection about a personal experience, state-rumination scores were higher in the ruminative condition. These results establish the causal role of interpretation biases in ruminative patterns of thought.