Miracle-dz/UniFAR-FTUs huggingface dataset:
The impact of user-browser interaction on web performance

The user interaction with the current web contents is a major concern when defining web workloads in order to precisely estimate system performance. However, the intrinsic difficulty to represent this behavior in a workload model leads many research works to still use workloads non representative of the current web navigations. In contrast, in previous works we demonstrated that the use of an accurate workload model that considers user's dynamism when navigating the web clearly affects system performance metrics. In this paper we analyze, for the first time, the effect of considering the User-Browser Interaction (UBI) as a part of user's dynamic behavior on web workload characterization in performance studies. To this end, we evaluate a typical e-commerce scenario and compare the obtained results for different UBI behaviors, such as the use of the back button and parallel browsing originated by using browser tabs or opening new windows when surfing a website.
High level quantitative hardware prediction modeling using statistical methods

With the increasing proliferation of heterogeneous and reconfigurable computing, it has become essential to have efficient prediction models to drive early HW-SW partitioning and co-design. In this paper, we present a high level quantitative prediction modeling approach that accurately models the relation between hardware and software metrics, based on several statistical techniques. The proposed approach generates models that predict hardware performance indicators for reconfigurable components, such as the number of slices, the number of flip-flops, and the number of wires. It utilizes automatic model selection, artificial neural networks, (logistic) regression, and data transformations. These models take a high-level language description as input, enabling hardware prediction in the early design stages. We calibrate the models for two sets of tools targeting Xilinx and Altera FPGAs, where we report, for example, and error of 14% for the number of multipliers in case of Xilinx and an error of only 18% for the number of wires in case of Altera. To provide a realistic evaluation, we validate the approach using 181 kernels, contrary to the majority of the existing techniques, which use libraries of tens of kernels at most.
Neuropsychological rehabilitation specific to anorexia nervosa: A critical review of the literature on executive functioning symptomatology and cognitive remediation treatment applications tailored to this patient population

Engaging, maintaining, and treating patients with anorexia nervosa (AN) remains a significant challenge for clinicians, hypothesized explanations for which are thought to involve specific executive functioning impairments. The neuropsychological treatment paradigm Cognitive Remediation Therapy (CRT) represents the translation of neurocognitive research into practice, and is thought to remediate neuropsychological symptoms and associated maladaptive cognitive processes. Additionally, the etiological model of AN related to executive functioning provides a conceptual framework for this novel approach to treatment. This study identifies and examines such a model, in addition to CRT protocols. Methodology involved a comprehensive synthesis and critical analysis of the literature pertaining to these domains. A variety of promising findings attributed to CRT are discussed, including an increase in participant BMI, improved neuropsychological performance, reduced perseveration, increased capacity for global processing, decreased eating disorder and depressive symptomatology, increased motivation, and confidence in patients’ ability to change and begin subsequent therapies. Numerous important methodological limitations are also elucidated, as many studies utilized small sample sizes resulting in low statistical power and poor generalizability, neglected to identify or consider demographic and cultural variables, failed to assess general intelligence or reference the normative data used, did not identify or discuss potential cohort or practice effects, provided limited details influencing studies’ reproducibility, and introduced a variety of biases. Nevertheless, this groundwork illuminated promising results in the treatment of a diagnostically complex and challenging disorder. Accordingly, a number of suggested future directions and clinical applications are elaborated upon.
Poor Sleep Quality of Third-Trimester Pregnancy is a Risk Factor for Postpartum Depression

Background The aim of this study was to investigate whether poor sleep quality of third-trimester pregnancy is a risk factor for postpartum depression. Material/Methods Third-trimester pregnant women (T0, n=293) were tested using the first socio-demographic, Pittsburgh Sleep Quality Index, and Edinburgh Postnatal Depression Scale assessments, and received a diagnosis of depression. Three months (T1, n=223) after delivery, scale filling was finished and the structured interview was performed again. Results We found that 73 persons (32.7%) were low income, 84 persons (37.7%) were middle-income, and 66 persons (29.6%) were higher income. The overall prevalence of postpartum depression was 9.4% (21 persons). After controlling for other factors, age, household income, marital satisfaction, and sleep quality were significantly related to postpartum depression, in which age and sleep quality scores (a higher score was associated with poorer sleep quality) were positively related to postpartum depression, and household income and marital satisfaction were negatively related to postpartum depression. Moreover, third-trimester sleep quality score was positively related to postpartum depressive symptoms. Conclusions Poor third-trimester subjective sleep quality is a risk factor for postpartum depression.
Dimensions of corporate social responsibility (CSR) skepticism and their impacts on public evaluations toward CSR

ABSTRACT This study attempts to examine the dimensions of corporate social responsibility (CSR) skepticism and to identify the strongest predictor by testing the relationships between the skepticism constructs and public responses. The study further examines the role of cynicism either as an antecedent, a moderator, or a component of CSR skepticism. Through a series of model tests, three factors of CSR skepticism were identified to better predict public responses to CSR: (a) skepticism toward a company’s altruism, (b) disbelief of CSR messages and CSR activities, and (c) skepticism toward CSR informativeness. Skepticism toward a company’s altruism was identified as the strongest predictor in determining negative public response to CSR, whereas cynicism did not have much predictive power to explain public response to CSR; as a result, it was excluded from the final dimensions of CSR skepticism.
A delinqüência juvenil em São Paulo; mitos, imagens e fatos : Reflexões sobre a violência na sociedade contemporânea: educação, juventude, trabalho, memória

The aim of this essay is to examine the role of the adolescents in urban crime in the city of Sao Paulo, Brazil, from 1988 to 1996, and is based on completed research, the final report of which was published in 1999. I focus my analysis on one specific problem: the emergency of public and collective concern regarding the role of children and adolescents in the world of crime, particularly that of violent and organized crime. In additional to analyzing the evolution of urban juvenile delinquency in the metropolis of Sao Paulo, I seek to expose the way in which the relationship between youths, violence, and crime has been problematized within diverse social discourses, mainly those that negotiate public policies of social control and often appear in the newspapers and on television.
Minichromosome maintenance 7 protein is a reliable biological marker for human cervical progressive disease

Objective This study focused on comparing the expression levels of p16, Ki-67, and minichromosome maintenance 7 (MCM7) protein in normal and affected cervical epithelium to ascertain the biological significance of these markers in detecting progressive cervical disease. Methods A quantitative and based on-scanning-microscopy analysis of the three markers expression was performed in normal and cervical intraepithelial neoplasia (CIN) I, II, and III tissues. p16 area as well as p16, Ki-67, and MCM7 positive cells or nuclei were evaluated according to their distribution and extent through the cervical epithelium. Results A clear p16 over-expression was observed in all the dysplastic epithelium tissue samples. The quantitative analysis of p16 area as well as the number of p16 positive cells was able to better discriminate the CIN lesions grades than the usual semi-quantitative analysis. The average Ki-67 labeling indexes for the normal epithelium, CIN I, CIN II, and CIN III groups were 19.8%, 27.3%, 32.8%, and 37.1%, respectively, whereas the mean MCM7 labeling indexes for the correspondent grades were 27.0%, 30.4%, 50.5%, and 67.2%. The Ki-67 and MCM7 labeling indexes were closely correlated with the CIN histological grade, with higher labeling indexe values obtained from the more severe lesions (p<0.05), being the MCM7 labeling indexes the highest values in all the CIN categories (p<0.05). Conclusion We observed a good correlation among the p16, Ki-67, and MCM7 data. In addition, MCM7 demonstrated to be a more efficient and sensitive marker to assess disease progression in the uterine cervix.
Skeletonization: A Technique for Trimming the Fat from a Network via Relevance Assessment

This paper proposes a means of using the knowledge in a network to determine the functionality or relevance of individual units, both for the purpose of understanding the network's behavior and improving its performance. The basic idea is to iteratively train the network to a certain performance criterion, compute a measure of relevance that identifies which input or hidden units are most critical to performance, and automatically trim the least relevant units. This skeletonization technique can be used to simplify networks by eliminating units that convey redundant information; to improve learning performance by first learning with spare hidden units and then trimming the unnecessary ones away, thereby constraining generalization; and to understand the behavior of networks in terms of minimal "rules. "
A Mixed Methods Study of the Effects of Clicker Use on Math Anxiety and Achievement in Mathematics

Many large lecture classes at undergraduate institutions have started to utilize technology to engage students. A mixed methods design was used in this dissertation research to build a comprehensive understanding of the statistical relationships among mathematics anxiety, math self-efficacy, and achievement in mathematics among students in a large lecture, undergraduate calculus class taught using clickers. The purpose of this study was to develop an understanding of the statistical relationships and of the students’ experiences and perspectives on the relationships among mathematics self-efficacy, math anxiety, and achievement, along with the effect of clicker use on these variables, with attention given to changes in student perceptions during the semester. Statistical analysis was conducted utilizing quantitative survey data, and qualitative methods were used to analyze student interview data. Pairwise statistical relationships identified in previous research were confirmed among math anxiety, mathematics self-efficacy, and achievement in mathematics. Findings also revealed the potential for clickers to help promote desired learning outcomes when used effectively by students and instructors. Future research on the effect of clicker use in other types of mathematics courses besides calculus, in classes with students representing a more diverse range of racial/ethnic backgrounds, and with smaller class sizes will help build on the knowledge gained from this study.
Emotion and attitude conveyed in speech by means of prosody

In order to adapt a dialogue-system to its users and their needs, the information provided by the speech of the user constitutes useful input for a model of the user. Generating an adequate system’s response involves synthesizing speech in an appropriate expression style. This paper focuses on methodological issues concerning the study of speech variations conveying emotion and attitude. First, such a study considered in the context of spoken communication involves expression as well as perception. It is argued that production studies are optimally supplemented with perception studies. Second, it is argued that interpreting speech data in the framework of a model of intonation provides a methodological background for investigating intonation phenomena conveying emotion and attitude in speech, against the background of intonation phenomena relevant to speech communication.
Self-Efficacy in Retrieving Positive Emotional Experience and Using Humor: A Validation Study of a New Instrument in Three Countries

Recent research has pointed to the benefits of positive emotions and their appropriate modulation in buffering the impact of negative experience, and in promoting well-being. Two studies examined the psychometric properties of a new scale that was designed to assess perceived self-efficacy in using memories of positive emotional experiences and humor to face challenges and to cope with stressful experiences. In the first study, we examined the factor structure and internal validity of two scales in youths from the United States (N = 1,277), Italy (N = 363), and Spain (N = 223). In the second study, we examined correlations of the two scales with positive affect, as well as other indicators of well-being and adjustment in the three countries (US: N = 499; Italian and Spanish samples of Study 1). The results of the exploratory and confirmatory factor analyses supported two distinct factors and showed acceptable partial invariance of the scales across countries. Correlations supported the scales’ construct and discriminant validity. Overall, the findings corroborated the psychometric properties of the two scales and the view of retrieval of positive emotional experiences and humor as distinct self-regulatory strategies.
The Relationship between Leadership Styles and Job Performance: The Role of Work Engagement as a Mediator: Review Article

Job performance of managers is affected by so many factors in business organizations. Job performance stands on different factors; few of them are personal or individual traits and opportunities or system factors. This all is related to the work, which have significant relationship on employees’ task and contextual performance. Good leadership acts as a very vital part and leading towards better performance and accomplishment of organizational goals. On the other hand, a large number of performance measures were infertile as a result of factors such as unsuccessful leadership styles of the leaders. This paper proposes that transactional leadership and transformational leadership styles have direct relationship on the job performance of managers. The paper further incorporates the work engagement as mediator between leadership styles and job performance of managers. It is mainly targeted to improve the strength of leaders. Consequently they take up on those leadership styles which refine abilities of the leaders and assist them to obtain job performance. The paper finally suggests future research direction in view of leader member exchange theory and equity fairness and justice theory.
Decadal–Interdecadal Climate Variability over Antarctica and Linkages to the Tropics: Analysis of Ice Core, Instrumental, and Tropical Proxy Data

AbstractThe Antarctic continent contains the majority of the global ice volume and plays an important role in a changing climate. The nature and causes of Antarctic climate variability are, however, poorly understood beyond interannual time scales due to the paucity of long, reliable meteorological observations. This study analyzes decadal–interdecadal climate variability over Antarctica using a network of annually resolved ice core records and various instrumental and tropical proxy data for the nineteenth and twentieth centuries. During the twentieth century, Antarctic ice core records indicate strong linkages to sea surface temperature (SST) variations in the tropical Pacific and Atlantic on decadal–interdecadal time scales. Antarctic surface temperature anomalies inferred from the ice cores are consistent with the associated changes in atmospheric circulation and thermal advection. A set of atmospheric general circulation model experiments supports the idea that decadal SST variations in the tropics f.
2 Evidence for the Default Network's Role in Spontaneous Cognition 3 4 5

35 36 A set of brain regions known as the default network increases its activity when 37 focus on the external world is relaxed. During such moments, participants change their 38 focus of external attention and engage in spontaneous cognitive processes including 39 remembering the past and imagining the future. However, the functional contributions of 40 the default network to shifts in external attention versus internal mentation have been 41 difficult to disentangle because the two processes are correlated under typical 42 circumstances. To address this issue, the present study manipulated factors that promote 43 spontaneous cognition separately from those that change the scope of external attention. 44 Results revealed that the default network increased its activity when spontaneous 45 cognition was maximized but not when participants increased their attention to 46 unpredictable foveal or peripheral stimuli. To examine the nature of participants’ 47 spontaneous thoughts, a second experiment used self-report questionnaires to quantify 48 spontaneous thoughts during extended fixation epochs. Thoughts about one’s personal 49 past and future comprised a major focus of spontaneous cognition with considerable 50 variability. Activity correlations between the medial temporal lobe and distributed 51 cortical regions within the default network predicted a small, but significant, portion of 52 the observed variability. Collectively, these results suggest that during passive states, 53 activity within the default network reflects spontaneous, internally-directed cognitive 54 processes. 55 56
SVP-like MADS Box Genes Control Dormancy and Budbreak in Apple

The annual growth cycle of trees is the result of seasonal cues. The onset of winter triggers an endodormant state preventing bud growth and, once a chilling requirement is satisfied, these buds enter an ecodormant state and resume growing. MADS-box genes with similarity to Arabidopsis SHORT VEGETATIVE PHASE (SVP) [the SVP-like and DORMANCY ASSOCIATED MADS-BOX (DAM) genes] have been implicated in regulating flowering and growth-dormancy cycles in perennials. Here, we identified and characterized three DAM-like (MdDAMs) and two SHORT VEGETATIVE PHASE-like (MdSVPs) genes from apple (Malus × domestica ‘Royal Gala’). The expression of MdDAMa and MdDAMc indicated they may play a role in triggering autumn growth cessation. In contrast, the expression of MdDAMb, MdSVPa and MdSVPb suggested a role in maintaining bud dormancy. Consistent with this, ectopic expression of MdDAMb and MdSVPa in ‘Royal Gala’ apple plants resulted in delayed budbreak and architecture change due to constrained lateral shoot outgrowth, but normal flower and fruit development. The association of MdSVPa and MdSVPb expression with floral bud development in the low fruiting ‘Off’ trees of a biennial bearing cultivar ‘Sciros’ suggested the SVP genes might also play a role in floral meristem identity.
Protein Secondary Structure Prediction Using Cascaded Convolutional and Recurrent Neural Networks

Protein secondary structure prediction is an important problem in bioinformatics. Inspired by the recent successes of deep neural networks, in this paper, we propose an end-to-end deep network that predicts protein secondary structures from integrated local and global contextual features. Our deep architecture leverages convolutional neural networks with different kernel sizes to extract multiscale local contextual features. In addition, considering long-range dependencies existing in amino acid sequences, we set up a bidirectional neural network consisting of gated recurrent unit to capture global contextual features. Furthermore, multi-task learning is utilized to predict secondary structure labels and amino-acid solvent accessibility simultaneously. Our proposed deep network demonstrates its effectiveness by achieving state-of-the-art performance, i.e., 69.7% Q8 accuracy on the public benchmark CB513, 76.9% Q8 accuracy on CASP10 and 73.1% Q8 accuracy on CASP11. Our model and results are publicly available.
Wavelet Estimators in Nonparametric Regression: A Comparative Simulation Study

Wavelet analysis has been found to be a powerful tool for the nonparametric estimation of spatially-variable objects. We discuss in detail wavelet methods in nonparametric regression, where the data are modelled as observations of a signal contaminated with additive Gaussian noise, and provide an extensive review of the vast literature of wavelet shrinkage and wavelet thresholding estimators developed to denoise such data. These estimators arise from a wide range of classical and empirical Bayes methods treating either individual or blocks of wavelet coefficients. We compare various estimators in an extensive simulation study on a variety of sample sizes, test functions, signal-to-noise ratios and wavelet filters. Because there is no single criterion that can adequately summarise the behaviour of an estimator, we use various criteria to measure performance in finite sample situations. Insight into the performance of these estimators is obtained from graphical outputs and numerical tables. In order to provide some hints of how these estimators should be used to analyse real data sets, a detailed practical step-by-step illustration of a wavelet denoising analysis on electrical consumption is provided. Matlab codes are provided so that all figures and tables in this paper can be reproduced.
Challenges of academic healthcare leaders in a higher education context in South Africa

Universities are in a highly competitive environment, needing strong academic leadership. Some heads of departments have been appointed into leadership positions in a healthcare faculty after having been mere academics for a few years. They are more likely to experience challenges. This study aimed to explore the views and understanding of heads of departments in a healthcare faculty on being appointed as academic leaders in a higher education context in South Africa. A qualitative design using 12 individual unstructured interviews was conducted with all the heads of departments in a health sciences faculty. Open coding was conducted and two themes emerged, focusing on the varied skills needed for academic leadership positions and developing leadership skills amongst senior academics. The findings indicated that development of senior academics in leadership should be undertaken by a knowledgeable professional in formal or informal settings, to encourage mentorship and more regular group meetings, while addressing the core role of a leader. Implications of these findings for a faculty of health sciences and suggestions for leadership succession in future are discussed.