Miracle-dz/UniFAR-FTUs huggingface dataset:
Self-adaptive admission control policies for resource-sharing systems

We consider the problem of admission control in resource sharing systems, such as web servers and transaction processing systems, when the job size distribution has high variability, with the aim of minimizing the mean response time. It is well known that in such resource sharing systems, as the number of tasks concurrently sharing the resource is increased, the server throughput initially increases, due to more efficient utilization of resources, but starts falling beyond a certain point, due to resource contention and thrashing. Most admission control mechanisms solve this problem by imposing a fixed upper bound on the number of concurrent transactions allowed into the system, called the Multi-Programming-Limit (MPL), and making the arrivals which find the server full queue up. Almost always, the MPL is chosen to be the point that maximizes server efficiency. In this paper we abstract such resource sharing systems as a Processor Sharing (PS) server with state-dependent service rate and a First-Come-First-Served (FCFS) queue, and we analyze the performance of this model from a queueing theoretic perspective. We start by showing that, counter to the common wisdom, the peak efficiency point is not always optimal for minimizing the mean response time. Instead, significant performance gains can be obtained by running the system at less than the peak efficiency. We provide a simple expression for the static MPL that achieves near-optimal mean response time for general distributions. Next we present two traffic-oblivious dynamic admission control policies that adjust the MPL based on the instantaneous queue length while also taking into account the variability of the job size distribution. The structure of our admission control policies is a mixture of fluid control when the number of jobs in the system is high, with a stochastic component when the system is near-empty. We show via simulations that our dynamic policies are much more robust to unknown traffic intensities and burstiness in the arrival process than imposing a static MPL.
The European Union and neoliberal governmentality: Twinning in Tunisia and Egypt

As a response to the Arab uprisings that started in 2010, the European Union has emphasised, more determinated than ever, the urgency of inclusive and sustainable socio-economic development in the Arab region. The central objective of this article is to understand the nature and operation of European Union support for development following Arab mass movements. More specifically, it examines the European Union’s Twinning instrument in Egypt and Tunisia through a neoliberal governmentality framework, with a major focus on visualisations, technologies and subject formation. This approach enables us to observe the application of an agenda through which Twinning intervenes into non-economic domains of governance in the target countries and aims at shaping these spheres by economic rationalities and techniques. By constructing change around local governance capabilities, the Twinning programme acts upon individual skills, institutional arrangements and relationships, deploys benchmarking techniques, and empowers subjects and government behaviour in order to bring conduct to certain economic logics and exercises. The outcome is the rendering of Tunisian and Egyptian socio-economic development open to enterprise-based, calculative and professionalised operations that make local conditions serviceable to neoliberal governing patterns, linkages and practices of business, capital production and investment.
Impact of family responsibilities on career success among employees working in the semi-government sector in the state of Qatar

Qatar is among rapidly growing countries in the GCC region. There has been an encouraging involvement of the people in the Qatari society from the both genders. This paper presents a survey followed by a detailed analysis about how the work and family relations are related, further to this how the family responsibilities impact the career success. The research contributes a valuable insight into both work-family relations and career success studies by being one of the first to address the effects of family responsibilities on career success among residents of the state of Qatar. The analysis presented uses Structural Equation Model (SEM) to interpret the relationships between career success and family responsibilities. The research supports that the work centrality is a factor that has significant relationship with family responsibilities which also indirectly impact objective career success. The objective career success and subjective career success are independent factors.
The Effect of Testing on Achievement: Meta-Analyses and Research Summary, 1910–2010. Source List, Outcomes, and References for Qualitative Studies

The text of this study can be found in the International Journal of Testing. The study summarizes the research literature on the effect of testing on student achievement, which comprises several hundred studies conducted from the early 20th century to the present day. Only quantitative studies are listed here (N studies = 177; N effects = 640). Mean effect sizes range from a moderate d ˜ 0.55 to a fairly large d ˜ 0.88 depending on the way effects are aggregated or effect sizes are adjusted for study artifacts. Testing with feedback produces the strongest positive effect on achievement. Adding stakes or testing with greater frequency also strongly and positively affects achievement. The evidence from a century’s worth of quantitative studies shows the effect of testing on achievement to be moderately to strongly positive. Smaller-scale studies, however, tend to produce stronger effects than do large-scale studies. Those who judge the effect of testing on achievement exclusively from large-sample multivariate studies deprive themselves of the most focused, clear, and precise evidence. Some prominent researchers in economics and education, for example, have claimed that no studies of “test-based accountability” had been conducted before theirs in the early 2000s. But, this list includes 24 studies completed before 2000 whose primary focus was to measure the effect of “test-based accountability. ” A few dozen more pre-2000 studies also measured the effect of test-based accountability although such was not their primary focus. Include qualitative and program evaluation studies of test-based accountability, and the count of pre-2000 studies rises into the hundreds.
Genome Sequences of 12 Cluster AN Arthrobacter Phages

ABSTRACT Twelve siphoviral phages isolated using Arthrobacter sp. strain ATCC 21022 were sequenced. The phages all have relatively small genomes, ranging from 15,319 to 15,556 bp. All 12 phages are closely related to previously described cluster AN Arthrobacter phages.
Activity detection and causal interaction analysis among independent EEG components from memory related tasks

Over the past few years there has been an increased interest in studying the underlying neural mechanism of cognitive brain activity related to memory. In this direction, we study the brain activity based on its independent components instead of the EEG signal itself aiming towards identifying and analyzing induced responses being attributed to oscillatory bursts from local or distant neural assemblies, with variable latency and frequency, in an auditory working memory paradigm. The contribution and functional coupling of independent components to evoked and/or induced oscillatory activities is investigated through the concept of the recently introduced partial directed coherence method, which can also reveal the direction of the statistically significant relationships. The results on read data from an oddball experiment are in accordance with previous psychophysiology studies suggesting increased phase locked activity most prominently in the delta/ theta band, while alpha is also apparent in measures of non phase-locked activity. Dynamic synchronization is inferred between the alpha and delta bands, whereas some influence of the theta band is also detected. This study indicates that functional connectivity during cognitive processes may be successfully assessed using spectral power measures applied on independent components, which reflect distinct spatial patterns of activity.
The Roles of Customer Expectation and Emotion in Service Experience

This research advanced the development for a theoretical framework of service experience in Service Science discipline. Service experience is composed of a series of complicated services and influenced by many factors. Customer psychological status is the important one to be investigated. Accordingly, we proposed a theoretical framework of service experience based on the perspectives of customer expectation and emotion. Good customer expectation management for service providers will increase the opportunity of customer satisfaction of service experience. In order to ensure that customers can have positive behaviors and responses during service experience delivery, developing an atmospheric service context to generate positive customer emotion is also important. Three hypothetical propositions are provided to illustrate the theoretical framework of service experience. This study evaluated the theoretical framework of service experience by using the multi-method. The analysis results from interviews and questionnaires are the solid evidences to support the theoretical framework of service experience.
Information Diffusion Techniques and Small-Sample Problem

Strong interests in the small-sample problem have been given towards for establishing several information diffusion techniques for pattern recognition. In this paper, we review and formalize three techniques: the soft histogram, the self-study discrete regression, and the interior-outer-set model. To promote the development of this area, in this paper we suggest two open topics: the anti-accuracy principle and the digital image compression technique based on the fuzzy if-then rules extracted by using information matrix technique.
Profound Peripheral Insulin Resistance, Independent of Obesity, in Polycystic Ovary Syndrome

Hyperinsulinemia secondary to a poorly characterized disorder of insulin action is a feature of the polycystic ovary syndrome (PCO). However, controversy exists as to whether insulin resistance results from PCO or the obesity that is frequently associated with it. Thus, we determined in vivo insulin action on peripheral glucose utilization (M) and hepatic glucose production (HGP) with the euglycemic glucose-clamp technique in obese (n = 19) and nonobese (n = 10) PCO women and age- and body-composition-matched normal ovulatory women (n = 11 obese and n = 8 nonobese women). None had fasting hyperglycemia. Two obese PCO women had diabetes mellitus, established with an oral glucose tolerance test; no other women had impairment of glucose tolerance. However, the obese PCO women had significantly increased fasting and 2-h glucose levels after an oral glucose load and increased basal HGP compared with their body-composition-matched control group. There were statistically significant interactions between obesity and PCO in fasting glucose levels and basal HGP (P < .05). Steady-state insulin levels of ∼100 μU/ml were achieved during the clamp. Insulin-stimulated glucose utilization was significantly decreased in both PCO groups whether expressed per kilogram total weight (P < .001) or per kilogram fat free mass (P < .001) or when divided by the steady-state plasma insulin (I) level (M/I, P < .001). There was residual HGP in 4 of 15 obese PCO, 0 of 11 obese normal, 2 of 10 nonobese PCO, and 0 of 8 nonobese normal women. The metabolic clearance rate of insulin did not differ in the four groups. We conclude that 1) PCO women have significant insulin resistance that is independent of obesity, changes in body composition, and impairment of glucose tolerance, 2) PCO and obesity have a synergistic deleterious effect on glucose tolerance, 3) hyperinsulinemia in PCO is not the result of decreased insulin clearance, and 4) PCO is associated with a unique disorder of insulin action.
Robust Volume Assessment of Brain Tissues for 3-Dimensional Fourier Transformation MRI via a Novel Multispectral Technique

A new TRIO algorithm method integrating three different algorithms is proposed to perform brain MRI segmentation in the native coordinate space, with no need of transformation to a standard coordinate space or the probability maps for segmentation. The method is a simple voxel-based algorithm, derived from multispectral remote sensing techniques, and only requires minimal operator input to depict GM, WM, and CSF tissue clusters to complete classification of a 3D high-resolution multislice-multispectral MRI data. Results showed very high accuracy and reproducibility in classification of GM, WM, and CSF in multislice-multispectral synthetic MRI data. The similarity indexes, expressing overlap between classification results and the ground truth, were 0.951, 0.962, and 0.956 for GM, WM, and CSF classifications in the image data with 3% noise level and 0% non-uniformity intensity. The method particularly allows for classification of CSF with 0.994, 0.961 and 0.996 of accuracy, sensitivity and specificity in images data with 3% noise level and 0% non-uniformity intensity, which had seldom performed well in previous studies. As for clinical MRI data, the quantitative data of brain tissue volumes aligned closely with the brain morphometrics in three different study groups of young adults, elderly volunteers, and dementia patients. The results also showed very low rates of the intra- and extra-operator variability in measurements of the absolute volumes and volume fractions of cerebral GM, WM, and CSF in three different study groups. The mean coefficients of variation of GM, WM, and CSF volume measurements were in the range of 0.03% to 0.30% of intra-operator measurements and 0.06% to 0.45% of inter-operator measurements. In conclusion, the TRIO algorithm exhibits a remarkable ability in robust classification of multislice-multispectral brain MR images, which would be potentially applicable for clinical brain volumetric analysis and explicitly promising in cross-sectional and longitudinal studies of different subject groups.
Family of origin influences on the parenting of men with co‐occurring substance abuse and intimate partner violence

Purpose – Research indicates significant associations between intimate partner violence (IPV), substance abuse (SA) and childhood experiences of abuse. Yet few studies have interviewed fathers with co‐occurring IPV and SA about their experiences in their own families and how that impacts their parenting. The purpose of this paper is to fill that gap and explore the ways in which fathers with co‐occurring IPV and SA describe the parenting of their own parents and how it is related to the ways they parent. Design/methodology/approach – In total, 40 fathers with co‐occurring IPV and SA were interviewed about their experiences of childhood abuse and the ways they are like and unlike their parents for this qualitative study using thematic analysis. Findings – A large percentage of the fathers experienced childhood abuse and reported negative images of their fathers and mothers most commonly due to father absence and abusive/harsh parenting by both parents. Most fathers indicated a wish to be more present, available and warm with their children. Fathers did not draw associations between their childhood histories and their own behaviors. Practical implications – Multigenerational transmission of IPV, SA, and child maltreatment may be important areas to focus on in interventions with fathers with co‐occurring IPV and SA issues. Originality/value – This study is one of the first to specifically interview fathers with co‐occurring IPV and SA about their experiences of being parented and how that is related to their own parenting.
Comparison of Active Contour and Active Shape Approaches for Corpus Callosum Segmentation

The corpus callosum is the largest connective structure in the brain, and its shape and size are correlated to sex, age, brain growth and degeneration, handedness, musical ability, and neurological diseases. Manually segmenting the corpus callosum from brain magnetic resonance (MR) image is time consuming, error prone, and operator dependent In this paper, two semi-automatic segmentation methods are present: the active contour model-based approach and the active shape model-based approach. We tested these methods on an MR image of the human brain and found that the active contour approach had better segmentation accuracy but was slower than the active shape approach.
Relation of physical fitness to brain aging and cognition in older adults

Level of physical fitness may be an important factor influencing the effects of brain aging and age-related cognitive decline. Multiple measures of aerobic fitness were used in a cohort of healthy older adults 50-89 years of age to identify how individual differences in fitness relate to brain aging and age-associated cognitive decline. Healthy adults (n=123; 65 F and 58 M; mean ± sd age = 67.9 ± 10.0; Mini-Mental State Exam = 29.1 ± 1.2) were screened to exclude neurological, psychiatric, and medical illnesses that could affect cognitive function, including hypertension. The Scaled Subprofile Model (SSM) with voxel-based morphometry and Statistical Parametric Mapping version 8 (VBM; SPM8 Dartel) were performed on T1-weighted 3T volumetric magnetic resonance imaging (MRI) scans to identify a gray matter pattern associated with brain aging. Performance on aerobic fitness measures, assessed during a graded exercise treadmill test (GXT), was evaluated in relation to the age-associated MRI gray matter network pattern and indices of neuropsychological function. Multivariate SSM VBM network analysis identified a linear combination of patterns that predicted age (R = 0.48, p = 8.71e-19). This combined pattern was characterized by reductions in bilateral lateral and medial frontal, parietal, lateral temporal, and cerebellar regions with relative preservations in thalamic, occipital, and medial temporal regions including the hippocampus. Higher expression of the age-related network pattern was associated with poorer performance on multiple fitness indices. The best combination of fitness measures in predicting brain aging included overall treadmill exercise time, ventilatory efficiency, and the difference between basal and maximal respiratory rate (p = 6.67e-7). A higher
β-Defensin Genomic Copy Number Does Not Influence the Age of Onset in Huntington's Disease.

BACKGROUND Huntington's disease (HD) is an autosomal dominant neurodegenerative disorder caused by the abnormal expansion of a CAG triplet repeat tract in the huntingtin gene. While the length of this CAG expansion is the major determinant of the age of onset (AO), other genetic factors have also been shown to play a modulatory role. Recent evidence suggests that neuroinflammation is a pivotal factor in the pathogenesis of HD, and that targeting this process may have important therapeutic ramifications. The human β-defensin 2 (hBD2) - encoded by DEFB4 - is an antimicrobial peptide that exhibits inducible expression in astrocytes during inflammation and is an important regulator of innate and adaptive immune response. Therefore, DEFB4 may contribute to the neuroinflammatory processes observed in HD. OBJECTIVE In this study we tested the hypothesis that copy number variation (CNV) of the β-defensin region, including DEFB4, modifies the AO in HD. METHODS AND RESULTS We genotyped β-defensin CNV in 490 HD individuals using the paralogue ratio test and found no association between β-defensin CNV and onset of HD. CONCLUSIONS We conclude that it is unlikely that DEFB4 plays a role in HD pathogenesis.
Toward the construction of a profession’s boundaries: Creating a networking agenda

Attention to the boundaries of an organization or profession is an essential precursor to facilitating boundary-spanning activities. We follow a four-stage process model of constructing boundaries to delimit a profession’s membership and domain prior to its recognition as an institutionalized entity. A set of networking activities forms the basis of boundary construction, yet identifying and prioritizing which activities to pursue is a challenge that can jeopardize the success of an aspiring group. We use a case study of the emerging Jewish legal profession in pre-state Israel to analyze how an agenda for creating membership and domain boundaries implicitly surfaces through interactions among members of the new group. We employ content analysis of a key meeting transcript and network analytical methods to reveal a shared cognitive map of priorities. The study adds to the literature on professional boundaries and demonstrates the utility of an innovative qualitative-quantitative research approach.
Responses to climate change: exploring organisational learning across internationally networked organisations for development

Drawing from the organisational learning and governance literature, this paper assesses four internationally networked governmental and non‐governmental organisations in the UK addressing climate change. We analyse how those concerned understand the climate change crisis, what mechanisms are put in place to address information flows, and what evidence there is of learning through sharing information between the organisational headquarters and their regional offices. The most striking finding is the evidence of learning that largely depends on ad‐hoc informal processes and shadow networks.
Correlational Neural Networks

Common representation learning (CRL), wherein different descriptions (or views) of the data are embedded in a common subspace, has been receiving a lot of attention recently. Two popular paradigms here are canonical correlation analysis (CCA)–based approaches and autoencoder (AE)–based approaches. CCA-based approaches learn a joint representation by maximizing correlation of the views when projected to the common subspace. AE-based methods learn a common representation by minimizing the error of reconstructing the two views. Each of these approaches has its own advantages and disadvantages. For example, while CCA-based approaches outperform AE-based approaches for the task of transfer learning, they are not as scalable as the latter. In this work, we propose an AE-based approach, correlational neural network (CorrNet), that explicitly maximizes correlation among the views when projected to the common subspace. Through a series of experiments, we demonstrate that the proposed CorrNet is better than AE and CCA with respect to its ability to learn correlated common representations. We employ CorrNet for several cross-language tasks and show that the representations learned using it perform better than the ones learned using other state-of-the-art approaches.
We Trust You, But Not That Much: Examining Police–Black Clergy Partnerships to Reduce Youth Violence

This paper examines activist black clergy involvement in local youth violence reduction initiatives and efforts to improve police-minority community relations in Boston, Massachusetts. In-depth interviews were conducted with activist black clergy, community organizers, and Boston Police Department (BPD) managers. Study findings highlight how the work of a specific group of black ministers supports that of BPD and vice versa. The research suggests that police-black clergy partnerships can improve police legitimacy in minority communities and enhance informal social control elements of youth violence prevention strategies.