Miracle-dz/UniFAR-FTUs huggingface dataset:
An Alternative Approach for the Rising Challenge of Hypertensive Illness via Helicobacter pylori Eradication

Background The aim of the study was to demonstrate the effect of natural Helicobacter pylori eradication on blood pressure values. The prevalence of hypertension in developing countries has been considered by some reports a consequence of progress and life style changes. In spite of that, traditional risk factors do not appear fully sufficient to explain the rising figures of hypertensive illness which further indicates that attempts to control the problem depending upon traditional measures can never be adequate or decisive. H. pylori could migrate or get forced to migrate to the colon; it will continue producing ammonia for a reason or no reason leading to accumulation of profuse toxic amounts of ammonia, unopposed or buffered by any acidity, which could lead to multiple colonic and a high rectal spasm. A colonic re-absorptive error is established with excessive fluid and salt retention in the body that would definitely lead to hypertension which is supposed to remain inadequately controlled without correction of the underlying etiologic pathological error. It is a prospective study, conducted at Balghsoon Polyclinic, Jeddah, Saudi Arabia. Methods Ninety-nine middle-aged male patients with essential hypertension under medications and positive for H. pylori dyspepsia were included in the study. They were given natural therapy for H. pylori eradication. Results Ninety patients were able to resume normal blood pressure (BP) values and quit their medications. Conclusion The concept of the colonic re-absorptive error considered in this study is not just hypothetical as upon its basis, most patients of the study (90.9%) were able to quit medications and maintain normal BP values.
The diagnostic performance of perfusion MRI for differentiating glioma recurrence from pseudoprogression

Background: The purpose of this meta-analysis was to evaluate the diagnostic accuracy of perfusion magnetic resonance imaging (MRI) as a method for differentiating glioma recurrence from pseudoprogression. Methods: The PubMed, Embase, Cochrane Library, and Chinese Biomedical databases were searched comprehensively for relevant studies up to August 3, 2016 according to specific inclusion and exclusion criteria. The quality of the included studies was assessed according to the quality assessment of diagnostic accuracy studies (QUADAS-2). After performing heterogeneity and threshold effect tests, pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were calculated. Publication bias was evaluated visually by a funnel plot and quantitatively using Deek funnel plot asymmetry test. The area under the summary receiver operating characteristic curve was calculated to demonstrate the diagnostic performance of perfusion MRI. Results: Eleven studies covering 416 patients and 418 lesions were included in this meta-analysis. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were 0.88 (95% confidence interval [CI] 0.84–0.92), 0.77 (95% CI 0.69–0.84), 3.93 (95% CI 2.83–5.46), 0.16 (95% CI 0.11–0.22), and 27.17 (95% CI 14.96–49.35), respectively. The area under the summary receiver operating characteristic curve was 0.8899. There was no notable publication bias. Sensitivity analysis showed that the meta-analysis results were stable and credible. Conclusion: While perfusion MRI is not the ideal diagnostic method for differentiating glioma recurrence from pseudoprogression, it could improve diagnostic accuracy. Therefore, further research on combining perfusion MRI with other imaging modalities is warranted.
Psychopathology and Academic Performance among Nigerian High School Adolescents: The Moderator Effects of Study Behaviour, Self-Efficacy and Motivation

Abstract This study investigated the relationship between psychopathology and students’ academic performance and the moderator effects of study behaviour, self-efficacy and motivation. Participants were 476 SS2 students (228 males, 248 females) randomly selected from ten coeducational secondary schools in Ibadan. Measures of psychopathology, study behaviour, self-efficacy and motivation were administered on the sample. Data collected were analysed using hierarchical multiple regression. Results showed that psychopathology correlated negatively but non-significantly with academic performance. Study behaviour, self-efficacy and motivation correlated significantly with academic performance and moderated the psychopathology – academic performance nexus. The results suggest the need for counsellors to design therapeutic interventions for alleviating the students’ psychopathology, increasing their study skills, self-efficacy and motivation for improved academic performance.
On the Representation and Embedding of Knowledge Bases beyond Binary Relations

The models developed to date for knowledge base embedding are all based on the assumption that the relations contained in knowledge bases are binary. For the training and testing of these embedding models, multi-fold (or n-ary) relational data are converted to triples (e.g., in FB15K dataset) and interpreted as instances of binary relations. This paper presents a canonical representation of knowledge bases containing multi-fold relations. We show that the existing embedding models on the popular FB15K datasets correspond to a sub-optimal modelling framework, resulting in a loss of structural information. We advocate a novel modelling framework, which models multi-fold relations directly using this canonical representation. Using this framework, the existing TransH model is generalized to a new model, m-TransH. We demonstrate experimentally that m-TransH outperforms TransH by a large margin, thereby establishing a new state of the art.
Bounded and almost periodic solutions and evolution semigroups associated with nonautonomous functional differential equations

We study evolution semigroups associated with nonautonomous functional differential equations. In fact, we convert a given functional differential equation to an abstract autonomous evolution equation and then derive a representation theorem for the solutions of the underlying functional differential equation. The representation theorem is then used to study the boundedness and almost periodicity of solutions of a class of nonautonomous functional differential equations.
Robust Identification of Local Adaptation from Allele Frequencies

Comparing allele frequencies among populations that differ in environment has long been a tool for detecting loci involved in local adaptation. However, such analyses are complicated by an imperfect knowledge of population allele frequencies and neutral correlations of allele frequencies among populations due to shared population history and gene flow. Here we develop a set of methods to robustly test for unusual allele frequency patterns and correlations between environmental variables and allele frequencies while accounting for these complications based on a Bayesian model previously implemented in the software Bayenv. Using this model, we calculate a set of “standardized allele frequencies” that allows investigators to apply tests of their choice to multiple populations while accounting for sampling and covariance due to population history. We illustrate this first by showing that these standardized frequencies can be used to detect nonparametric correlations with environmental variables; these correlations are also less prone to spurious results due to outlier populations. We then demonstrate how these standardized allele frequencies can be used to construct a test to detect SNPs that deviate strongly from neutral population structure. This test is conceptually related to FST and is shown to be more powerful, as we account for population history. We also extend the model to next-generation sequencing of population pools—a cost-efficient way to estimate population allele frequencies, but one that introduces an additional level of sampling noise. The utility of these methods is demonstrated in simulations and by reanalyzing human SNP data from the Human Genome Diversity Panel populations and pooled next-generation sequencing data from Atlantic herring. An implementation of our method is available from http://gcbias.org.
The Prevalence of von Willebrand Disease and Significance of in Vitro Bleeding Time (PFA-100) in von Willebrand Disease Screening in the İzmir Region

Objective: von Willebrand disease (vWD) is the most common hereditary bleeding disorder. The purpose of this investigation was to determine the prevalence of vWD among adolescents in İzmir and to assess the sensitivity and specificity of PFA-100 as a screening method in detecting this disease. Material and Methods: Our study was conducted on adolescents in the city of İzmir between October 2006 and March 2007. A total of approximately 1500 high school students between 14 and 19 years of age were planned to be included in the investigation. Survey forms prepared for assessing hemorrhagic diathesis were completed by 1339 individuals (512 males, 827 females). The necessary laboratory tests were performed after having obtained written informed consent from 40 individuals suspected to have hemorrhagic diathesis. Results: Based on the von Willebrand factor antigen (vWF:Ag) and ristocetin cofactor activity (vWF:RCo) levels and bleeding symptoms, vWD type-1 was diagnosed in 14 individuals (4 males, 10 females; prevalence: 1.04%). The most common bleeding symptom in these patients was found to be epistaxis (10/14). Screening with PFA-100 revealed prolongation in both cartridges (Col/ADP and Col/Epi) in 3 of the 14 patients. PFA-100 was determined to exhibit 21.4% sensitivity and 100% specificity in the diagnosis of vWD. Conclusion: The PFA-100 device was found to have high specificity but to have exhibited low sensitivity. Therefore, its utilization as a screening test may be problematic in patients with mild type-1 vWD. Specific tests (vWF:RCo, vWF:Ag) are required for the definite diagnosis of vWD. However, further studies with a large number of patients are needed. Conflict of interest:None declared.
Polyphenols from olive mill waste affect biofilm formation and motility in Escherichia coli K-12

Olive mill wastes are sources of phenolic compounds with a wide array of biological activities, including antimicrobial effects. A potential option for bioremediation to overcome ecological problems is the reutilization of these natural compounds in food production. The aim of this work was to gain a better understanding of the antimicrobial mode of action of a phenols extract from olive vegetation water (PEOVW) at molecular level by studying Escherichia coli as a model microorganism. Genome‐wide transcriptional analysis was performed on E. coli K‐12 exposed to PEOVW. The repression of genes for flagellar synthesis and the involvement of genes linked to biofilm formation and stress response were observed. Sub‐inhibitory concentrations of PEOVW significantly decreased biofilm formation, swarming and swimming motility, thus confirming the gene expression data. This study provides interesting insights on the molecular action of PEOVW on E. coli K‐12. Given these anti‐biofilm properties and considering that biofilm formation is a serious problem for the food industry and human health, PEOVW has proved to be a high‐value natural product.
Projective fluids

We present a new method for particle based fluid simulation, using a combination of Projective Dynamics and Smoothed Particle Hydrodynamics (SPH). The Projective Dynamics framework allows the fast simulation of a wide range of constraints. It offers great stability through its implicit time integration scheme and is parallelizable in large parts, so that it can make use of modern multi core CPUs. Yet existing work only uses Projective Dynamics to simulate various kinds of soft bodies and cloth. We are the first ones to incorporate fluid simulation into the Projective Dynamics framework. Our proposed fluid constraints are derived from SPH and seamlessly integrate into the existing method. Furthermore, we adapt the solver to handle the constantly changing constraints that appear in fluid simulation. We employ a highly parallel matrix-free conjugate gradient solver, and thus do not require expensive matrix factorizations.
On the Typical Statistic Features for Image Blind Steganalysis

Multimedia content is a suitable carrier for secret communication. This paper focuses on the steganalysis technique which aims to get the forensic of secrecy existing in multimedia carriers. A key concern for designing a blind steganalysis algorithm is the selection of statistic features. The Probability Density Function (PDF) moment and Characteristic Function (CF) moment are two typical kinds of statistic features commonly used in blind steganalysis. And generally, the features are computed from the subbands of transform domains, such as the wavelet coefficient subbands, the prediction subbands of wavelet coefficients, the prediction error subbands of wavelet coefficients, the wavelet coefficient subbands of image noise, and the log prediction error subbands of wavelet coefficients. To decide which feature is more sensitive to message embedding and useful for steganalysis is important and urgent. Till now, few works have focused on this topic, and they can only give some experimental results without theoretical analysis. Additionally, few frequency subbands have been investigated. To solve this problem, this paper reviews existing feature computing algorithms, compares the two kinds of features, the PDF moments and the CF moments, by analyzing the change trends of the statistic distribution parameters of various frequency subbands before and after message embedding, and so that provides a theoretical basis for the steganalysis feature selection and extraction. These theoretical results are further confirmed by experimental results. This is the first work to provide thorough theoretical analysis on so many feature computing algorithms. It is expected to provide valuable information to researchers or engineers working in the field of steganography forensics or steganalysis.
Prevalence, correlates, and prognostic significance of QRS prolongation in heart failure with reduced and preserved ejection fraction.

AIMS The independent clinical correlates and prognostic impact of QRS prolongation in heart failure (HF) with reduced and preserved ejection fraction (EF) are poorly understood. The rationale for cardiac resynchronization therapy (CRT) in preserved EF is unknown. The aim was to determine the prevalence of, correlates with, and prognostic impact of QRS prolongation in HF with reduced and preserved EF. METHODS AND RESULTS We studied 25,171 patients (age 74.6 ± 12.0 years, 39.9% women) in the Swedish Heart Failure Registry. We assessed QRS width and 40 other clinically relevant variables. Correlates with QRS width were assessed with multivariable logistic regression, and the association between QRS width and all-cause mortality with multivariable Cox regression. Pre-specified subgroup analyses by EF were performed. Thirty-one per cent had QRS ≥120 ms. Strong predictors of QRS ≥120 ms were higher age, male gender, dilated cardiomyopathy, longer duration of HF, and lower EF. One-year survival was 77% in QRS ≥120 vs. 82% in QRS <120 ms, and 5-year survival was 42 vs. 51%, respectively (P < 0.001). The adjusted hazard ratio for all-cause mortality was 1.11 (95% confidence interval 1.04-1.18, P = 0.001) for QRS ≥120 vs. <120 ms. There was no interaction between QRS width and EF. CONCLUSION QRS prolongation is associated with other markers of severity in HF but is also an independent risk factor for all-cause mortality. The risk associated with QRS prolongation may be similar regardless of EF. This provides a rationale for trials of CRT in HF with preserved EF.
Kazhdan's Property T for Discrete Quantum Groups

We give a simple definition of property T for discrete quantum groups. We prove the basic expected properties: discrete quantum groups with property T are finitely generated and unimodular. Moreover we show that, for "I.C. C. " discrete quantum groups, property T is equivalent to Connes' property T for the dual von Neumann algebra. This allows us to give the first example of a property T discrete quantum group which is not a group using the twisting construction.
Class size effects on mathematics achievement in Cyprus: evidence from TIMSS

ABSTRACT Class size reduction has been viewed as one school mechanism that can improve student achievement. Nonetheless, the literature has reported mixed findings about class size effects. We used 4th- and 8th-grade data from TIMSS 2003 and 2007 to examine the association between class size and mathematics achievement in public schools in Cyprus. We employ instrumental variables methods, and take advantage of a regression discontinuity design to examine causal effects of class size on mathematics achievement. The results indicate a non-significant relationship between class size and mathematics achievement in 8th grades. However, there is evidence of positive class size effects in 4th grade. The gender gap is significant and favoured males in 4th grade and females in 8th grade. SES indexes such as parental education and items in the home are positively and significantly related to mathematics achievement. Teacher and school variables are not significantly related with mathematics achievement.
Trans-Kingdom Transposition of the Maize Dissociation Element

Transposons are very valuable tools for genetic manipulation. However, the number of transposable elements that have been suitably adapted for experimental use is insufficient and the spectrum of heterologous hosts in which they have been deployed is restricted. To date, only transposons from animal hosts have been utilized in heterologous animal species and transposons of plant origin have been used in plant genetics. There has been no experimental evidence that any of the known elements could transpose in hosts belonging to both kingdoms. Here we demonstrate that the maize Dissociation (Ds) element is capable of effective Activator (Ac) transposase-mediated transposition in the zebrafish Danio rerio, yielding remarkable germline transmission rates. In addition, mammalian cells were also found to be conducive to Ds transposition. Furthermore, we demonstrate that nuclear localization of Ac transposase is essential for genomic Ds transposition. Our results support the hypothesis that Ac/Ds elements do not rely on host-specific factors for transposition and that host factors involved in their mobility mechanism are widely conserved. Finally, even in vertebrate cells, the Ac/Ds system displays accurate transposition, large-fragment carrying capacity, high transposition frequencies, efficient germline transmission, and reporter gene expression, all of which are advantageous for various genetic applications and animal biotechnology.
Active Inference and Learning

We present a generalized framework for active inference, the selective acquisition of labels for cases at prediction time in lieu of the estimated labels of a predictive model. We develop techniques within this framework for classifying in an online setting, for example, for classifying the stream of web pages where online advertisements are being served. Stream applications present novel complications because (i) we don’t know at the time of label acquisition what instances we will see, (ii) instances repeat based on some unknown (and possibly skewed) distribution. To address the complications, we combine ideas from decision theory, cost-sensitive learning, online density estimation, and we introduce a method for on-line estimation of the utility distribution that allows us to manage the budget over the stream. The resulting model tells which instances to label so that by the end of each budget period, the budget is best spent (in expectation). We test the method on streams from a real application. The main results show that: (1) our proposed approach to active inference on streams can indeed reduce error costs substantially over alternative approaches, (2) more sophisticated online estimations achieve larger reductions in error. We then discuss the setting of simultaneously conducting active inference and active learning. We argue and provide some support that our expected-utility active inference strategy also selects good examples for learning.
Comparison of 3D interest point detectors and descriptors for point cloud fusion

Abstract. The extraction and description of keypoints as salient image parts has a long tradition within processing and analysis of 2D images. Nowadays, 3D data gains more and more importance. This paper discusses the benefits and limitations of keypoints for the task of fusing multiple 3D point clouds. For this goal, several combinations of 3D keypoint detectors and descriptors are tested. The experiments are based on 3D scenes with varying properties, including 3D scanner data as well as Kinect point clouds. The obtained results indicate that the specific method to extract and describe keypoints in 3D data has to be carefully chosen. In many cases the accuracy suffers from a too strong reduction of the available points to keypoints.
Visualizing Multiple Variables Across Scale and Geography

Comparing multiple variables to select those that effectively characterize complex entities is important in a wide variety of domains - geodemographics for example. Identifying variables that correlate is a common practice to remove redundancy, but correlation varies across space, with scale and over time, and the frequently used global statistics hide potentially important differentiating local variation. For more comprehensive and robust insights into multivariate relations, these local correlations need to be assessed through various means of defining locality. We explore the geography of this issue, and use novel interactive visualization to identify interdependencies in multivariate data sets to support geographically informed multivariate analysis. We offer terminology for considering scale and locality, visual techniques for establishing the effects of scale on correlation and a theoretical framework through which variation in geographic correlation with scale and locality are addressed explicitly. Prototype software demonstrates how these contributions act together. These techniques enable multiple variables and their geographic characteristics to be considered concurrently as we extend visual parameter space analysis (vPSA) to the spatial domain. We find variable correlations to be sensitive to scale and geography to varying degrees in the context of energy-based geodemographics. This sensitivity depends upon the calculation of locality as well as the geographical and statistical structure of the variable.