Miracle-dz/UniFAR-FTUs huggingface dataset:
ontinuous administration of polyphenols from aqueous rooibos ( Aspalathus inearis ) extract ameliorates dietary-induced metabolic disturbances in yperlipidemic mice

The incidence of obesity and related metabolic diseases is increasing globally. Current medical treatments often fail to halt the progress of such disturbances, and plant-derived polyphenols are increasingly being investigated as a possible way to provide safe and effective complementary therapy. Rooibos (Aspalathus linearis) is a rich source of polyphenols without caloric and/or stimulant components. We have tentatively characterized 25 phenolic compounds in rooibos extract and studied the effects of continuous aqueous rooibos extract consumption in mice. The effects of this extract, which contained 25% w/w of total polyphenol content, were negligible in animals with no metabolic disturbance but were significant in hyperlipemic mice, especially in those in which energy intake was increased via a Western-type diet that increased the risk of developing metabolic complications. In these mice, we found hypolipemiant activity when given rooibos extract, with significant reductions in serum cholesterol, triglyceride and free fatty acid concentrations. Additionally, we found changes in adipocyte size and number as well as complete prevention of dietary-induced hepatic steatosis. These effects were not related to changes in insulin resistance. Among other possible mechanisms, we present data indicating that the activation of AMP-activated protein kinase (AMPK) and the resulting regulation of cellular energy homeostasis may play a significant role in these effects of rooibos extract. Our findings suggest that adding polyphenols to elp i the daily diet is likely to h
The G 243 D mutation ( afsB mutation ) in the principal sigma factor s HrdB alters intracellular ppGpp level and antibiotic production in Streptomyces coelicolor A 3 ( 2 )

Deficient antibiotic production in an afsB mutant, BH5, of Streptomyces coelicolor A3(2) was recently shown to be due to a mutation (G243D) in region 1.2 of the primary sigma factor s. Here we show that intracellular ppGpp levels during growth, as well as after amino acid depletion, in the mutant BH5 are lower than those of the afsB parent strain. The introduction of certain rifampicin resistance (rif) mutations, which bypassed the requirement of ppGpp for transcription of pathway-specific regulatory genes, actII-ORF4 and redD, for actinorhodin and undecylprodigiosin, respectively, completely restored antibiotic production by BH5. Antibiotic production was restored also by introduction of a new class of thiostrepton-resistance (tsp) mutations, which provoked aberrant accumulation of intracellular ppGpp. Abolition of ppGpp synthesis in the afsB tsp mutant Tsp33 again abolished antibiotic production. These results indicate that intracellular ppGpp level is finely tuned for successful triggering of antibiotic production in the wild-type strain, and that this fine tuning was absent from the afsB mutant BH5, resulting in a failure to initiate antibiotic production in this strain.
A comparative study between 4 H-SiC and silicon power PiN diode having the same breakdown voltage 4 KV

The exploitation of silicon carbide semiconductor devices in power electronic field have made exceptional improvements by their fast switching and low dissipated losses especially at high operating temperatures, However, physical performances of silicon power components have reached their limits. This paper presents a comparative study, through numerical simulation and using the finite element method modeling, between 4H-SiC and silicon power PiN diode having the same breakdown voltage “4KV”. This comparative study highlights the benefits of silicon carbide. Keywords—4H-SiC, Numerical Simulation, Diode PiN
Number Plate Extraction Using K-means Clustering and Weighted Sum Method

In today‟s world automatic vehicle number plate extraction plays a significant role. It is widely used in surveillance systems. In this paper the fast and real time method for number plate extraction has been proposed. In this proposed method, firstly, original image has been taken, and converted into grey scale image. K-means clustering has been applied, vertical and horizontal edges are extracted from the image, morphology operation is used and the feature extraction is done, the correct location of plate has been extracted using weighted sum method (WSM) and if there is any tilt in number plate that tilt is removed away, and extracted number plate is displayed as output. This method has been implemented on images with different background and distances, and as compare to other methods improved results has been obtained. Keywordsedge detection, K-means clustering, number plate extraction, plate tilt correction and weighted sum method.
Relationship of BRCA 2 N 372 H polymorphism and risk of cancer : a systematic meta-analysis under PRISMA guidelines

Objective: Many studies have investigated the association between BRCA2 N372H polymorphism and the risk of several cancers. However, the results were inconsistent. The aim of this meta-analysis was to elucidate whether BRCA2 N372H polymorphism was associated with cancer risk. Methods: We identified eligible studies, published from 2000 through 2016, by searching PubMed, Web of knowledge and Chinese National Knowledge Infrastructure (CNKI). Odds ratios (ORs) and 95% confidence interval (CI) were used to assess the strength of association between BRCA2 N372H polymorphism and cancer risk. Heterogeneity among studies was evaluated using Cochran’s Q and I2 statistics. Results: A total of forty six case-control studies were included in the meta-analysis. The pooled analysis indicated that BRCA2 N372H polymorphism was significantly associated with an increased risk of overall cancer (dominant model: OR = 1.06, 95% CI = 1.01-1.12; recessive model: OR = 1.13, 95% CI = 1.03-1.17). In subgroup analysis, we also found significantly increased risk of BRCA2 N372H polymorphism with ovarian cancer, non-Hodgkin lymphoma, population-based controls and Africans. Conclusions: This research study showed a major role of polymorphism in shaping over cancer risk. Future large-scale studies performed in multiple populations are warranted to confirm the results.
Towards a more symmetrical approach to the zone of proximal development in teacher education

This article focuses on relations between a new teacher and a teacher educator as these played themselves out in the course of a two-year study of a teaching education program. Ordinarily, the concept of the zone of proximal development is used to theorize the learning that occurs in such a relation in asymmetrical terms, where the teacher educator would be placed in the leading position whereas the new teacher in training in the learning position. Our case study shows, however, that learning occurs for both participants in the relation and that the very question of who is in the know—that is, who becomes “the more competent peer”—arises from the relation that constitutes a zone of proximal development. Therefore, there are dialectical inversions, whereby the actual roles of teacher and learner no longer coincide with the institutionally designated positions of particular individuals: the institutionally designated teacher becomes the student and the institutionally designated student becomes a teacher. This then requires an approach to the zone of proximal development that allows for the changes in the relation such that who teaches and who learns is itself the result of the social relation.
Chapter 13 FFX : FAST , SCALABLE , DETERMINISTIC SYMBOLIC REGRESSION TECHNOLOGY

Symbolic regression is a common application for genetic programming (GP). This paper presents a new non-evolutionary technique for symbolic regression that, compared to competent GP approaches on real-world problems, is orders of magnitude faster (taking just seconds), returns simpler models, has comparable or better prediction on unseen data, and converges reliably and deterministically. I dub the approach FFX, for Fast Function Extraction. FFX uses a recentlydeveloped machine learning technique, pathwise regularized learning, to rapidly prune a huge set of candidate basis functions down to compact models. FFX is verified on a broad set of real-world problems having 13 to 1468 input variables, outperforming GP as well as several state-of-the-art regression techniques.
A Model-Based Scheduling Framework for Enhancing Robustness

Scheduling algorithms used for dynamic scheduling of tasks in a distributed system are generally evaluated on their performance, i.e., their degree of achieving a desired outcome or metric. They may also be evaluated on the basis of their robustness, which is the degree to which the scheduling algorithm is able to achieve similar performance in the present of error in the task requirements or system resource availability. In this paper, a modelbased framework for evaluating and improving scheduling algorithms’ performance and robustness is proposed. We also demonstrate through simulated results how system feedback can be incorporated to increase robustness of four evaluated scheduling algorithms.
Paying for Private School Education : Maternal Employment and Savings over the Life-cycle

This paper builds and estimates a dynamic life-cycle model to investigate how mothers change their work and savings behavior in order to pay for private schooling for their children. The model incorporates the choice of private or public school for the child and allows risk aversion and savings to capture how mothers can plan for children’s schooling in advance. Results show that mother’s time with the child and private schooling are complements in producing child’s cognitive skills and that the availability of private schooling leads to more work and savings among women with children of school-going age. Counterfactual simulations show that relaxing liquidity constraints for mothers increases private school enrollment, with larger effects for low-education women. I also find that subsidizing private schooling can reduce inequality in children’s outcomes. However, these subsidies affect work and saving incentives of mothers, and lead to lower wages and asset accumulation among less educated females.
Introduction: Discourse Analysis as a New Cross-Discipline

Discourse analysis is both an old and a new discipline. Its origins can be traced back to the study of language, public speech, and literature more than 2000 years ago. One major historical source is undoubtedly classical rhetoric, the art of good speaking. Whereas the grammatica, the historical antecedent of linguistics, was concerned with the normative rules of correct language use, its sister discipline of rhetorica dealt with the precepts for the planning, organization, specific operations, and performance of public speech in political and legal settings. Its crucial concern, therefore, was persuasive effectiveness. In this sense, classical rhetoric both anticipates contemporary stylistics and structural analyses of discourse and contains intuitive cognitive and social psychological notions about memory organization and attitude change in communicative contexts. After some important revivals in the Middle Ages and the seventeenth and eighteenth centuries, however, rhetoric lost much of its importance in the curricula of schools and in academic research. The emergence of historical and comparative linguistics at the beginning of the nineteenth century and the birth of structural analysis of language at the beginning of the twentieth century replaced rhetoric as the primary discipline of the humanities. Fragments of rhetoric survived only in school textbooks of speech and communication, on one hand, and in stylistics or the study of literary language, on the other. Yet, parallel to this decline of rhetoric as an independent academic discipline, new developments in several fields of the humanities and the social sciences took place that would eventually lead to the emergence handbook
THE EDUCATIONAL AND PSYCHOLOGICAL SUPPORT OF EDUCATORS TO INCLUDE LEARNERS FROM CHILD-HEADED HOMES IN URBAN CLASSROOMS

The purpose of this study was to comprehensively capture teachers’ classroom experiences and establish what educational and psychological support would help them as they were trying to include learners from child-headed homes in their classrooms and schools. The sample of teachers from two different Gauteng districts included members from the school management and school-based support teams. Data were collected through individual and focus group interviews, in addition to collages made by the teachers, survey questionnaires in which they were respondents, observations of their practice and concomitant field notes. Firstly, the findings indicate that teachers are not always aware that learner’s are orphans or head their own households. They do not know how to assist learners in coping with the effects of orphanhood, which include: increased learning difficulties, incomplete schoolwork, failure to participate, school absenteeism, hunger, concentration difficulties, signs of sexual abuse, and accelerated adulthood. The efforts of teachers to create supportive learning environments include; impartial treatment, learning support provision, accessing support services and meeting their learners’ basic needs for food, clothing, love, belonging, reassurance, motivation and encouragement.
Comparison of Ion Release Chromium Soaked in Artificial Saliva and Extract the Starfruit Wuluh ( Averrhoa Bilimbi L . )

The Orthodontic Wire has a stainless steel metal content that can undergo corrosion on the inside of the mouth. Corrosion can be influential, bad for the human body and can release ions that can affect the process of corrosion. Stainless steel wire can release chromium ion and ways to reduce the rate of corrosion of materials by using inhibitors. Inhibitors can be extracts from natural materials and are not harmful to the environment. One of them is the extract of star fruit wuluh that has active content can stabilize ions of chromium on the surface of the stainless steel wire and can form a passive layer so that corrosion can be inhibited. To know the ability of inhibition the star fruit wuluh extract power to prevent corrosion on Stainless Steel wire. Materials used artificial saliva and fluid extract of star fruit wuluh. The research was conducted in experimental laboratories with 4 sample treatment group using the extract of star fruit wuluh and 4 sample control group using artificial saliva fluids. The release of chromium ion Atomic Absorption Spectrophotometric instruments used. Cr metal ion release Occurs with the amount of discharge varies from the treatment group and the control group on day 1, 3, 7 and 14 days. An increase in the amount of deposition of chromium ion on each sample research. The release of chromium ion from Stainless Steel wire that is soaked in the extract of star fruit wuluh less than immersed in artificial saliva. Extract of starfruit wuluh have corrosion inhibition against stainless steel wire. Clinical Article (J Int Dent Med Res 2018; 11(2): pp. 556-566)
Experiments of Phase Errors Estimation and Correction for High-resolution Airborne SAR Imaging

For the lack of high precision inertial measurement system, the experimental airborne L-band SAR system was badly affected by random phase error induced by motion instability. The resultant SAR images derived from the L-SAR system were out of focus by conventional SAR signal processing and imaging method. It is necessary to estimate and correct phase errors for high resolution SAR imaging. As a prospective scheme to refocus these images, the phase gradient autofocus (PGA) algorithm was studied in the SAR imaging processing. This paper focused on the calculation process of phase error estimation, which was first derived mathematically in detail. Then, the effectiveness of PGA algorithm was tested not only for isolated point scatter scene, but also for various distributed-object scenes to verify its performance. Particularly, a near-range scene, a mid-range scene, and a far-range scene were tested. Experiments show that the imaging algorithm based on phase gradient autofocus can effectively measure and compensate the phase error, thus obtain an obviously improved airborne SAR image in azimuth resolution. The processing results prove the effectiveness of the proposed procedure for highresolution airborne SAR imaging. Copyright © 2013 IFSA.
Bit-Vector Approximations of Floating-Point Arithmetic

conflict driven clause learning The abstract conflict driven clause learning algorithm (ACDCL) can be used to reason about floating-point numbers. It does not reason about floating-point numbers directly but about intervals instead. ACDCL have shown to be e cient for reasoning about floatingpoint arithmetic [18]. Martin Brain et al. gives an explanation of how ACDCL solve floating-point formulas in Deciding floating-point logic with abstract conflict driven clause learning [3]. UppSAT is capable to use ACDCL as a back-end. Other approximations in UppSAT Aleksandar Zeljic et al. presents other approximations of floating-point arithmetic than the one touched upon here in Exploring Approximations for Floating-Point Arithmetic using UppSAT [19]. One approximating using the real numbers and one staying in the theory of floating-point numbers but using a smaller amount of bits.
Tapestry : En hancing In-depth Text Analysis at Document Le vel

Modeling text corpus into key topics is good for exploratory analysis. For analyses facilitating decision making, keeping information of individual documents intact is also important. In this paper, I propose the design of an interactive visual analysis interface that combines topic summarization with document information preservation. A series of example analysis activities and use scenarios show its strength in supporting decision making through in-depth analysis at document level.
Tutorial 9: Introduction to Deep Learning

So far in this class, we’ve covered a wide range of classical computer vision techniques, including edge detection, clustering methods, classifiers, and feature detectors/descriptors. While these techniques are still highly relevant to computer vision in research and industry, they share one major drawback: they rely on humans to hand-design features and choose classifiers that work well for the specific problem they’re trying to solve. As a result, computer vision methods designed to solve one problem are often not readily adaptable to solving other problems, significant human effort and experimentation is required to build reasonably accurate vision pipelines, and even the best-designed pipelines are limited in the accuracy they can achieve simply because they were designed by humans and can therefore only pick up on patterns that human designers have picked up on first.
Enhanced Image Initialized Shape EDT EDT EDT Segmented Liver Distance Field Distance FieldTarget Boundary Translation Thresholding Model Adaptation Preprocessing Model Initialization Deformable

Liver segmentation is still a challenging task in medical image processing area due to the complexity of the liver’s anatomy, low contrast with adjacent organs and presence of pathologies. This investigation was used to develop and validate an automated method to segment livers in CT images. The proposed framework consists of three steps: preprocessing, initialization and segmentation. In the first step, statistical shape model is constructed based on principal component analysis and the input image is smoothed using curvature anisotropic diffusion filtering. In the second step, the mean shape model is moved by using thresholding and Euclidean distance transformation to obtain a coarse position in a test image, and then the initial mesh is locally and iteratively deformed to the coarse boundary, which is constrained to stay close to a subspace of shapes describing the anatomical variability. Finally, in order to accurately detect the liver surface, deformable graph cut was proposed, which effectively integrates the properties and inter-relationship of the input images and initialized surface. The proposed method was evaluated on 50 CT scan images, which are publicly available in two databases Sliver07 and 3Dircadb. The experimental results showed that the proposed method was effective and accurate for detection of the liver surface.
DC-SIGN ( CD 209 ) gene promoter polymorphisms in a Brazilian population and their association with human T-cell lymphotropic virus type 1 infection

IP: 54.70. 40.11 On: Tue, 19 Feb 2019 19:29:27 DC-SIGN (CD209) gene promoter polymorphisms in a Brazilian population and their association with human T-cell lymphotropic virus type 1 infection Simone Kashima,3 Evandra Strazza Rodrigues,3 Rochele Azevedo, Erick da Cruz Castelli, Celso Teixeira Mendes-Junior, France Keiko Nascimento Yoshioka, Israel Tojal da Silva, Osvaldo Massaiti Takayanagui and Dimas Tadeu Covas
SAFE Working Paper No. 102

Research on interbank networks and systemic importance is starting to recognise that the web of exposures linking banks balance sheets is more complex than the single-layer-of-exposure approach. We use data on exposures between large European banks broken down by both maturity and instrument type to characterise the main features of the multiplex structure of the network of large European banks. This multiplex network presents positive correlated multiplexity and a high similarity between layers, stemming both from standard similarity analyses as well as a core-periphery analyses of the different layers. We propose measures of systemic importance that fit the case in which banks are connected through an arbitrary number of layers (be it by instrument, maturity or a combination of both). Such measures allow for a decomposition of the global systemic importance index for any bank into the contributions of each of the sub-networks, providing a useful tool for banking regulators and supervisors in identifying tailored policy instruments. We use the dataset of exposures between large European banks to illustrate that both the methodology and the specific level of network aggregation matter in the determination of interconnectedness and thus in the policy making process.
Long term effects of various therapies on the metabolic risk factors in prostate carcinoma patients

The objective is to investigate the long term effects of androgen deprivation therapy and non-androgen deprivation therapy on various metabolic risk factors in prostate carcinoma patients. It was a hospital based prospective study consisted of eighty eight subjects with diagnosed prostate carcinoma and twenty five aged matched healthy controls for the comparison of basic parameters at the initial level. The prostate carcinoma subjects were divided into two groups on the basis of metastatic prostate carcinoma and locally confined prostate carcinoma viz. androgen deprivation therapy (n=51) and non-androgen deprivation therapy (n=37). The subjects were examined for Adult Treatment Panel III criteria for metabolic syndrome. Anthropometric parameters were measured and biochemical parameters estimated at baseline and after 12 and 18 months of therapy. The anthropometric and biochemical parameters were significantly increased and insulin sensitivity was significantly decreased in androgen deprivation therapy group after the therapy of 18 months. However, in non-androgen deprivation group this change was non-significant. The results of the present study suggest that men with prostate carcinoma who receive androgen deprivation therapy develop insulin resistance and hyperglycemia as compared to those who received non androgen deprivation therapy. Hence, it may be stated that androgen deprivation therapy increases the metabolic burden. However, the level of high density lipoprotein also increases significantly in androgen deprivation therapy group which shows the difference with classical metabolic syndrome.