Miracle-dz/UniFAR-FTUs huggingface dataset:
Nutritionists’ Health Study cohort: a web-based approach of life events, habits and health outcomes

Introduction Non-communicable chronic diseases (NCCDs) represent a burden for public health. Alongside the established cardiometabolic risk factors such as high blood pressure and disorders of glucose and lipid metabolism, living habits and nutritional status at different stages of life are seen as contributors to this scenario. Gut microbiota composition and subclinical inflammation have been pointed out as underlying mechanisms of NCCDs. Studies involving health professionals have brought relevant contributions to the knowledge about risk factors. Technological advances facilitate data collection and analysis for big samples. A web-based survey addressed to collect data from a cohort study, which is able to identify NCCDs risk factors, is highly desirable. The objective of the Brazilian Nutritionists’ Health Study (NutriHS) is to gather online information on early life events, daily habits, emergent cardiometabolic risk factors and health outcomes of a specific subset of the Brazilian population. Methods and analysis NutriHS, developed at the School of Public Health—University of Sao Paulo, Brazil, is a research initiative that enrols undergraduates of nutrition courses from Brazilian universities and graduated volunteers. A web-based self-administered system was designed to collect health-related data. After fulfilling online questionnaires (socioeconomic, early life events and lifestyle data), participants are invited to a clinical visit for physical examination and laboratory procedures (blood sampling, faeces collection and body composition). At a 3-year interval, they will be invited to repeat similar procedures. Ethics and dissemination The NutriHS research protocol was approved by the Institutional Ethics Committee and is providing promising data which contribute to the understanding of pathophysiological links between early life events, body composition, gut microbiota, and inflammatory and metabolic risk profile. The combination of a friendly tool with the innovative purposes of NutriHS offers a remarkable resource for testing hypotheses about mechanisms of nutrition-related diseases and further planning of preventive programmes in public health.
Correlation of Gleason Scores with Diffusion-Weighted Imaging Findings of Prostate Cancer

The purpose of our study was to compare the apparent diffusion coefficient (ADC) derived from diffusion-weighted imaging (DWI) of prostate cancer (PCa) patients with three classes of pathological Gleason scores (GS). Patients whose GS met these criteria (GS 3 + 3, GS 3 + 4, and GS 4 + 3) were included in this study. The DWI was performed using b values of 0, 50, and 400 s/mm2 in 44 patients using an endorectal coil on a 1.5T MRI scanner. The apparent diffusion coefficient (ADC) values were calculated from the DWI data of patients with three different Gleason scores. In patients with a high-grade Gleason score (4 + 3), the ADC values were lower in the peripheral gland tissue, pathologically determined as tumor compared to low grade (3 + 3 and 3 + 4). The mean and standard deviation of the ADC values for patients with GS 3 + 3, GS 3 + 4, and GS 4 + 3 were 1.135 ± 0.119, 0.976 ± 0.103 and 0.831 ± 0.087 mm2/sec. The ADC values were statistically significant (P < 0.05) between the three different scores with a trend of decreasing ADC values with increasing Gleason scores by one-way ANOVA method. This study shows that the DWI-derived ADC values may help differentiate aggressive from low-grade PCa.
FROM METABOLIC NETWORKS TO MINIMAL DYNAMIC BIOREACTION MODELS

Abstract The paper deals with the design of minimal dynamic bioreaction models in the situation where (a) the model is based on the knowledge of a detailed underlying metabolic network, (b) measurements of extra-cellular species in the reactor are the only available measurements. A brief but rigorous presentation of the theory is first given. Then the approach is illustrated with the example of chinese hamster ovary cells cultivated in stirred flasks.
Construct, Predictive Validity, and Measurement Equivalence of the Race-Based Traumatic Stress Symptom Scale for Black Americans

The current study was designed to determine the construct and predictive validity of the Race-Based Traumatic Stress Symptom Scale (RBTSSS) using structural equation modeling (SEM) and confirmatory factor analysis (CFA) with Black adults. The study involved 527 Black American adults who completed the RBTSSS and various measures of psychological functioning. Analyses included CFA, test of measurement invariance across gender and socioeconomic status, and test of predictive validity employing canonical correlation analysis (CCA). Two separate CCAs were conducted: one for the total sample of participants completing both measures and one with a subset of the sample identified as meeting criteria for race-based stress–trauma. The structure of the RBTSSS was confirmed through tests of the first order model and construct invariance using CFA. A second order SEM supported the RBTS construct. Canonical correlation analyses indicated that the RBTSS scales were significantly associated with psychological outcomes, including anxiety, depression, and loss of emotional and behavioral control. The analyses found support for the construct and predictive validity for the RBTSSS for Blacks.
Plasmablastic lymphoma

Background: Plasmablastic lymphoma (PBL) is a B-cell malignancy associated with human immunodeficiency virus (HIV). PBL could also influence the HIV-negative patients. The study aimed to identify prognostic factors for survival among Chinese PBL patients. Materials and methods: Eligible patients from literature and Peking Union Medical College Hospital (PUMCH) were included in this study. Clinical characteristics and immunophenotypic data were extracted. Kaplan–Meier curve was used to describe the survival status. Cox regression was used for multivariate analysis. Results: A total of 60 Chinese PBL patients were included, including 54 patients from 36 published articles and 6 new patients that have not been reported. The median overall survival was 7 months (95% confidence interval 3.853–10.147 months). An overwhelming majority (79.31%) of the included cases were Ann Arbor stage IV patients. All the Chinese PBL patients were HIV-negative; 46.81% were Epstein-Barr virus-positive. CD38, CD138, or MUM1 was positively expressed in more than 80% of patients; CD20 expression was also found in 22.03% of cases. Kaplan–Meier curve revealed obvious differences in patient survival between patients in primary stages and advanced stages, as well as between patients with kidney involvement and those without kidney involvement. Cox regression analysis indicated that stage and age were 2 prognostic factors for patient survival. Conclusions: Advanced stage might be associated with poor prognosis among PBL HIV-negative patients in Chinese.
Silhouette Analysis for Human Action Recognition Based on Supervised Temporal t-SNE and Incremental Learning

This paper develops a human action recognition method for human silhouette sequences based on supervised temporal t-stochastic neighbor embedding (ST-tSNE) and incremental learning. Inspired by the SNE and its variants, ST-tSNE is proposed to learn the underlying relationship between action frames in a manifold, where the class label information and temporal information are introduced to well represent those frames from the same action class. As to the incremental learning, an important step for action recognition, we introduce three methods to perform the low-dimensional embedding of new data. Two of them are motivated by local methods, locally linear embedding and locality preserving projection. Those two techniques are proposed to learn explicit linear representations following the local neighbor relationship, and their effectiveness is investigated for preserving the intrinsic action structure. The rest one is based on manifold-oriented stochastic neighbor projection to find a linear projection from high-dimensional to low-dimensional space capturing the underlying pattern manifold. Extensive experimental results and comparisons with the state-of-the-art methods demonstrate the effectiveness and robustness of the proposed ST-tSNE and incremental learning methods in the human action silhouette analysis.
Children’s choice: motivation after successful completion of a mathematics task

ABSTRACT The purpose of this study was to examine kindergarten children’s motivation choice after successfully completing a mathematical task. Three succeeding measurements took place in two-week intervals. In each measurement a different choice dyad was presented to participating children. After the successful completion of a mathematical activity, participants were asked to make one choice from among three dyads: social reward-tangible reward, social reward-harder task and tangible reward-harder task. Results revealed that children preferred the tangible reward (candy) over other choices and the social reward over the harder task. Logistic regression analyses revealed that children’s choice of a tangible reward cannot be predicted by their mothers’ and fathers’ education and income levels, their mathematical level or their teachers’ reward practices. Educators should be aware of practices that would harm the learner’s inner process in order to avoid those applications in their classroom.
The Francisella Tularensis Proteome and its Recognition by Antibodies

Francisella tularensis is the causative agent of a spectrum of diseases collectively known as tularemia. The extreme virulence of the pathogen in humans, combined with the low infectious dose and the ease of dissemination by aerosol have led to concerns about its abuse as a bioweapon. Until recently, nothing was known about the virulence mechanisms and even now, there is still a relatively poor understanding of pathogen virulence. Completion of increasing numbers of Francisella genome sequences, combined with comparative genomics and proteomics studies, are contributing to the knowledge in this area. Tularemia may be treated with antibiotics, but there is currently no licensed vaccine. An attenuated strain, the Live Vaccine Strain (LVS) has been used to vaccinate military and at risk laboratory personnel, but safety concerns mean that it is unlikely to be licensed by the FDA for general use. Little is known about the protective immunity induced by vaccination with LVS, in humans or animal models. Immunoproteomics studies with sera from infected humans or vaccinated mouse strains, are being used in gel-based or proteome microarray approaches to give insight into the humoral immune response. In addition, these data have the potential to be exploited in the identification of new diagnostic or protective antigens, the design of next generation live vaccine strains, and the development of subunit vaccines. Herein, we briefly review the current knowledge from Francisella comparative proteomics studies and then focus upon the findings from immunoproteomics approaches.
Maximum-Minimum Eigenvalue Detection for Cognitive Radio

Sensing (signal detection) is a fundamental problem in cognitive radio. In this paper, a new method is proposed based on the eigenvalues of the covariance matrix of the received signal. It is shown that the ratio of the maximum eigenvalue to the minimum eigenvalue can be used to detect the signal existence. Based on some latest random matrix theories (RMT), we can quantize the ratio and find the threshold. The probability of false alarm is also found by using the RMT. The proposed method overcomes the noise uncertainty difficulty while keeps the advantages of the energy detection. The method can be used for various sensing applications without knowledge of the signal, the channel and noise power. Simulations based on randomly generated signals and captured ATSC DTV signals are presented to verify the methods.
The Effect of Affect Regulation on the Relationship between Attachment and Internalizing/Externalizing Behavior Problems in Male Adolescents who have Sexually Offended

It is important to better understand those who perpetrate sexually; however, much of the available research has been conducted with adult sex offenders. Since research has found that these adults frequently report perpetrating sexual abuse for the first time during childhood/adolescence, this study examines adolescents who have committed a sexual offense. Findings have shown that adolescents who sexually offend are most often insecurely attached to caregivers, have difficulty regulating their emotions, and display numerous internalizing and externalizing behavior problems (in addition to sexual offending). Research has shown that attachment insecurity is highly related to internalizing/externalizing behaviors and poor affect regulation skills. However, no studies have examined the relationships among attachment, affect regulation, and internalizing/externalizing behaviors in the population of adolescents who sexually offend. The purpose of this study is to identify how affect regulation ability might mediate or possibly moderate the relationship between attachment and internalizing/externalizing behaviors in this population. Sixty-two incarcerated adolescents completed self-report questionnaires regarding demographic information, internalizing/externalizing behavior problems, attachment, and affect regulation. Path analysis was the chosen method of analysis. In addition, mediation and moderation hypotheses were tested. This study found that attachment was related to internalizing and externalizing behaviors, as well as, emotion regulation. Maladaptive affect regulation appeared to have a stronger influence on problem behaviors than adaptive affect regulation in this study. Affect regulation was not found to moderate the
Remifentanil Preconditioning Protects against Ischemic Injury in the Intact Rat Heart

Background:Opioid receptors mediate cardiac ischemic preconditioning. Remifentanil is a new, potent ultra-short-acting phenylpiperidine opioid used in high doses for anesthesia. The authors hypothesize that pretreatment with this drug confers cardioprotection. Methods:Male Sprague-Dawley rats were anesthetized and the chest was opened. All animals were subjected to 30 min of occlusion of the left coronary artery and 2 h of reperfusion. Before the 30-min occlusion, rats received either preconditioning by ischemia (ischemic preconditioning, 5-min occlusion, 5-min reperfusion × 3) or pretreatment with remifentanil, performed with the same regime (3 × 5-min infusions) using 0.2, 0.6, 2, 6, or 20 μg·kg−1·min−1 intravenously. The experiment was repeated with naltrindole (a selective Δ-opioid receptor antagonist, 5 mg/kg), nor-binaltorphimine (a selective &kgr;-OR antagonist, 5 mg/kg), or CTOP (a selective μ-opioid receptor antagonist, 1 mg/kg) administered before remifentanil-induced preconditioning or ischemic preconditioning, respectively. Infarct size, as a percentage of the area at risk, was determined by 2,3,5-triphenyltetrazolium staining. Results:There was a dose-related reduction in infarct size/area at risk after treatment with remifentanil that was similar to that seen with ischemic preconditioning. This effect was prevented or significantly attenuated by coadministration of a μ, &kgr;, or Δ-opioid antagonist. The infarct-sparing effect of ischemic preconditioning was abolished by blockade of &kgr;-opioid receptors or Δ-opioid receptors but not by μ-opioid receptors. Conclusion:Remifentanil mimics cardioprotection via all three opioid receptors. This differs from ischemic preconditioning, which confers cardioprotection via &kgr;- and Δ-, but not μ-opioid receptors. Part of the protective effect of remifentanil may be produced by μ-agonist activity outside the heart.
Why Most Developing Countries Should Not Try New Zealand's Reforms

Developing and transitional countries have an understandable desire to accelerate public sector reform by adopting the most advanced innovations devised by developed countries. In many countries, interest has been stimulated by the New Zealand (NZ) model which gives public managers broad discretion to operate within an accountability framework that specifies the results to be achieved and closely monitors performance. Despite the interest and the sales efforts, only a few developed countries (such as Iceland and Singapore) have adopted selected features of the NZ system; others (such as Sweden and the United Kingdom) have embraced a managerial ethic, without subscribing to the hard-edged contractualism that differentiates New Zealand's reforms from those tried elsewhere. To the author's knowledge, however, not a single developing or transitional country has installed the full NZ model, though quite a few have been enchanted by the prospect of leapfrogging to the front ranks in the international reform sweepstakes. It is his belief there are important preconditions for successfully implementing the new public management (NPM) approach; these should not be ignored by countries striving to uplift themselves. While arguments that managerial deficiencies should be the driving factor in determining the suitability of NZ-type reforms, this article argues that they should be deterring factors. The greater the shortcomings in a country's established management practices, the less suitable the reforms are. In his view, significant progress can be made through a logical sequence of steps that diminishes the scope of informality, while building managerial capacity, confidence, and experience, and outlines some of the key steps. First, progress in the public sector requires parallel advances in the market sector. Second, modernizing the public sector means establishing reliable, workable, external controls. Third, in the process of developing skills, confidence, trust, and public-regarding values, politicians and officials must concentrate on the basic process of public management. Finally, once the basics have been mastered, the public sector should be organized according to the principles of internal control.
Relative entropy and the Bekenstein bound

Elaborating on a previous work by Marolf et al, we relate some exact results in quantum field theory and statistical mechanics to the Bekenstein universal bound on entropy. Specifically, we consider the relative entropy between the vacuum and another state, both reduced to a local region. We propose that, with the adequate interpretation, the positivity of the relative entropy in this case constitutes a well-defined statement of the bound in flat space. We show that this version arises naturally from the original derivation of the bound from the generalized second law when quantum effects are taken into account. In this formulation the bound holds automatically, and in particular it does not suffer from the proliferation of the species problem. The results suggest that while the bound is relevant at the classical level, it does not introduce new physical constraints semiclassically.
RASTER DATA PARTITIONING FOR SUPPORTING DISTRIBUTED GIS PROCESSING

Abstract. In the geospatial sector big data concept also has already impact. Several studies facing originally computer science techniques applied in GIS processing of huge amount of geospatial data. In other research studies geospatial data is considered as it were always been big data (Lee and Kang, 2015). Nevertheless, we can prove data acquisition methods have been improved substantially not only the amount, but the resolution of raw data in spectral, spatial and temporal aspects as well. A significant portion of big data is geospatial data, and the size of such data is growing rapidly at least by 20% every year (Dasgupta, 2013). The produced increasing volume of raw data, in different format, representation and purpose the wealth of information derived from this data sets represents only valuable results. However, the computing capability and processing speed rather tackle with limitations, even if semi-automatic or automatic procedures are aimed on complex geospatial data (Krist´of et al., 2014). In late times, distributed computing has reached many interdisciplinary areas of computer science inclusive of remote sensing and geographic information processing approaches. Cloud computing even more requires appropriate processing algorithms to be distributed and handle geospatial big data. Map-Reduce programming model and distributed file systems have proven their capabilities to process non GIS big data. But sometimes it’s inconvenient or inefficient to rewrite existing algorithms to Map-Reduce programming model, also GIS data can not be partitioned as text-based data by line or by bytes. Hence, we would like to find an alternative solution for data partitioning, data distribution and execution of existing algorithms without rewriting or with only minor modifications. This paper focuses on technical overview of currently available distributed computing environments, as well as GIS data (raster data) partitioning, distribution and distributed processing of GIS algorithms. A proof of concept implementation have been made for raster data partitioning, distribution and processing. The first results on performance have been compared against commercial software ERDAS IMAGINE 2011 and 2014. Partitioning methods heavily depend on application areas, therefore we may consider data partitioning as a preprocessing step before applying processing services on data. As a proof of concept we have implemented a simple tile-based partitioning method splitting an image into smaller grids (NxM tiles) and comparing the processing time to existing methods by NDVI calculation. The concept is demonstrated using own development open source processing framework.
An Evaluation of Gamified Training: Using Narrative to Improve Reactions and Learning

Background and Aim. Gamification is growing in popularity in education and workplace training, but it is unclear which game elements are conducive to learning. The theory of gamified learning suggests that one type of gamification, the addition of game fiction/narrative, can be used to improve learning outcomes, and the Technology-Enhanced Training Effectiveness Model (TETEM) suggests individual differences impact the strength of this effect. From this theoretical basis, this study gamified a training module with game fiction in order to improve outcomes over the original training. Results and Conclusion. In a study of 273 learners, trainees were significantly more satisfied with training enhanced with game fiction over the control text (d = 0.65) but did not differ in declarative knowledge scores by condition. Further, trainees in the control condition scored higher on procedural knowledge than trainees in the game fiction condition, although the effect was smaller (d = −0.40). Thus, the use of narrative improved reactions to training but at some cost to training effectiveness. Attitudes toward game-based learning were also tested as a moderator of the condition-outcome relationship.