Miracle-dz/UniFAR-FTUs huggingface dataset:
New onset diabetes after transplantation in renal transplant recipients at Tygerberg Hospital

New Onset Diabetes after Transplantation (NODAT) is a common complication of renal transplantation worldwide.However, there is very little data available regarding this condition in Sub-Saharan Africa. This study was thereforeconducted in order to determine the incidence of NODAT and its associated risk factors in a South African renaltransplant population. A retrospective analysis was conducted on 221 patients who underwent renal transplants atTygerberg Hospital during the period January 1st 1995 to December 31st 2008. Specific information was retrieved from patient files in order to determine the study outcomes. Fifty of the 221 patientswere found to have NODAT reflecting an incidence of 22.6% (95% CI 0.17-0.28). The cumulative incidences of NODATat three, 12 and 36 months were 9%, 12% and 17% respectively. The mean time to onset of NODAT was 18 monthsafter transplantation (95% CI 11.3-25.3) and the mean age at diagnoses of NODAT was 41 years (95% CI 38.9-44.8). Transplantation at the age of 40 years (odds ratio = 1.05) as well the usage of tacrolimus (odds ratio = 0.43) was foundto increase the risk of developing NODAT. The development of NODAT did not have any effect on graft or patientsurvival in this study. The incidence of NODAT in a South African population appears to be as high as it is worldwide with the first year posttransplantationcarrying the greatest risk for its development. The risk for development of NODAT is increased as thetime post-transplantation increases. Transplantation from the age of 40 years and the use of tacrolimus appear to be themost significant risk factors.
The Direct Assessment of Writing Skill: A Measurement Review

·· Introduction . 'JYpes of Direct Assessment. 2 Task 'JYpes . 2 Evaluation Methods. 3 Reliability of Direct Assessments . 4 Factors Influencing Reliability Estimates . 4 Reading Reliability Estimates . 6 Score Reliability Estimates . 9 Reliabilities of Analytic Subscales . 11 Summary of Reliability Evidence . 12 Validity of Direct Assessments . 12 Concurrent Validity . 12 Predictive Validity . 14 Incremental Validity. 14 Validity of Analytic Subscores . 16 Construct Validity . 17 Content Validity . 18 Summary of Validity Evidence . 18 Technological Developments . 18 Summary and Conclusions . 19 References . 21
Cardio-cerebral diseases

The connection between Cardio-vascular diseases (CVD) and CNS (Central nervous system) diseases is well known. Here we review most of the well-known and studied diseases connecting both systems to get a better view of that spectrum of diseases. When we discuss that kind of diseases, we mean that one organ is originally healthy and would function normally until it is affected by the other diseased system. Previously known, cardiovascular diseases usually cause CNS disorders by interrupted blood flow to the CNS, while the CNS disorders disrupt the cardiovascular autonomic functions leading to the excessive sympathetic discharge and catecholamines release. In our review article, we focus mainly on the brain disorders when CNS is mentioned, not the spinal cord disorders.
Natural frequencies and Bayesian reasoning: the impact of formal education and problem context

Research suggests that children and adults are able to solve Bayesian problems when natural frequencies are used, but most studies have involved only students or academics. The present research focuses on random samples from the general population. Experiments 1 and 2 showed that the natural-frequency format resulted in more Bayesian responses than the probability format. Results of Experiment 3 showed that when the task is not framed as a medical problem and the numbers are not too difficult, about 40% of the general population could correctly solve the problems. More importantly, the natural-frequency format resulted in a substantial increase in correct answers in the lower level of formal education group. Experiment 4 suggests that the context of a problem influences people’s ability to solve a Bayesian problem. Participants were twice as likely to solve a social problem compared with a medical problem. The results of the four experiments show that natural frequency resulted in much better estimates than probabilities. It should be emphasized, however, that even when natural frequencies were used, a majority of participants were not able to solve the problems correctly.
University students’ food consumption assessment and the relation with their academic profile

Objective: The purpose of this research is to assess the quality of the diet taken by the students of Universidad Alfonso X El Sabio (Madrid) and to learn whether having a specific knowledge about nutrition produce positive effects in food behavior. Methods: 390 students were tested, 72.63% of them studied degrees in relation to health sciences whereas the remaining 27.37% did not. The students were between 18 and 25 years old. The information was gathered through a questionnaire. This information dealt with frequency of food consumption as well as weight and height in order to get the body mass index. Results: The breakdown of the population according to their body mass index was the following: 75.54% normal weight, 11.06% low weight, 13.4% obesity. These figures are considered normal and they are similar to other groups of students. Both groups (health science students and the others) showed a lower cereal, vegetable and fruit consumption in comparison with the recommended percentage; whereas the consumption of pulses was higher than the average in Spain and the average from other groups, almost reaching the recommendable minimum. In addition, both groups showed a high consumption of dairies. No striking differences have been found between both groups. When comparing both of them in relation to gender, women showed better food behavior since they ate more fruit, vegetables and white fish. Conclusion: No differences have been found between the group studying health sciences and the students studying other kind of degree. The obtained results show that the food consumption of the population is far from the stipulated recommendations; therefore, it would be necessary to design a new action plan regarding nutrition.
SSALTO/DUACS and operational altimetry

The SSALTO/DUACS multiple altimeter processing system provides MERCATOR, GODAE, and climate forecasting centers with directly usable, high quality near real time altimeter data. Commercial applications for the fishery and offshore industries are also developed. An overview of the SSALTO/DUACS system is given and its main applications and users are described.
Novel Rate Control Scheme for Low Delay Video Coding of HEVC

In this paper, a novel rate control scheme for low delay video coding of High Efficiency Video Coding (HEVC) is proposed. The proposed scheme is developed by considering a new temporal prediction structure of HEVC. In the proposed scheme, the relationship between bit rate and quantization step is exploited firstly to formulate an accurate quadratic rate‐quantization (R‐Q) model. Secondly, a method of determining the quantization parameters (QPs) for the first frames within a group of pictures is proposed. Thirdly, an accurate frame‐level bit allocation method is proposed for HEVC. Finally, based on the proposed R‐Q model and the target bit allocated for the frame, the QPs are predicted for coding tree units by using rate‐distortion (R‐D) optimization. We compare our scheme against that of three other state‐of‐the‐art rate control schemes. Experimental results show that the proposed rate control scheme can increase the Bjøntegaard delta peak signal‐to‐noise ratio by 0.65 dB and 0.09 dB on average compared with the JCTVC‐I0094 and JCTVC‐M0036 schemes, respectively, both of which have been implemented in an HEVC test model encoder; furthermore, the proposed scheme achieves a similar R‐D performance to Wang's scheme, as well as obtaining the smallest bit rate mismatch error of all the schemes.
Impact of pharmacist’s intervention on improving quality of life in patients with diabetes mellitus

1.1. Introduction:Diabetes mellitus is a chronic disease affecting multiple organ systems leading to significant morbidity and mortality. 1.2. Objectives:To assess the impact of pharmacist led interventions in the quality of life in patients with type 2 diabetes mellitus. 1.3. Methods:A prospective, interventional study carried over a period of 12 months from October 2014 – September 2015 in general medicine outpatient department of a tertiary care teaching hospital. A total of 106 Patients who fulfilled the study criteria were randomized into intervention group (55 patients) and usual care groups (51 patients) and completed the study. Patient information leaflet and medication counselling was provided to intervention group by the clinical pharmacist. Quality of life scores were collected by using Audit of diabetes dependent quality of life questionnaire to both the groups at the beginning and at the end of the study. In a group of 30 patients in the intervention group glycosylated haemoglobin was recorded at baseline and final follow up. These quality of life scores and glycaemic levels (fasting plasma glucose and post prandial plasma glucose) were obtained and compared between both groups at the end of the study. 1.4. Results:The intervention group showed an improvement in the quality of life score from -2.69±1.53 at the baseline to -1.92±0.59 at the final visit (p<0.05). The average HbA1c values decreased from 9.15± 1.37 to 7.21± 0.844 in the intervention group (p<0.05). There was a significant decrease in the post prandial blood glucose from 260.30± 93.43 to 165.19± 33.44 and fasting blood glucose from 163.45 ± 56.03 to 114.45± 18.87 from the baseline value to the final follow up in the intervention group (p<0.05). 1.5. Conclusion:The study shows that clinical pharmacist guided appropriate interventions were found to be effective in achieving better glycaemic control and better quality of life in patients with diabetes mellitus.
Chronic Diarrhea in Hypogammaglobulinemia: A Case Report of Immunodeficiency

Introduction: Common variable immunodeficiency (CVID) or acquired hypogammaglobulinemia is the most common primary antibody deficiency which leads to lymphocytic dysfunction. CVID is not related to gender and can affect the person at any age, but the peaks of onset are the first and the third decades of life. CVID presents with various manifestations, which can obscure the proper diagnosis of the disease based on broad non-specific presentations. In this report, we describe a case of refractory chronic diarrhea secondary to underlying CVID disease without recurring bacterial infections. Case Presentation: A 31 year old woman with a chief complaint of persistent diarrhea and weight loss for five years. She did not complain of anysymptoms until the age of 26 when she started having several episodes of semi-solid diarrhea per day. Despite dietary and additional interventions, symptoms were persistent during a 5 year course of the disease and worsened in the last 2 months, with significantincrease in volume and frequency of diarrhea and associated weight loss of 10 kilograms. Several work-ups were inconclusive and she was referred to us for evaluation of CVID enteropathy. Discussion: Chronic diarrhea is considered one of the most common clinical manifestations of CVID. More than half of patients present with diarrhea and 10% develop idiopathic malabsorption associated with weight loss. This case report presents gastrointestinal manifestation of CVID as the only presentation during 5 years, which led to exhaustive diagnostic studies without definitive diagnosis or effective management. This report signifies the importance of early diagnosis of CVID, and the need to improve physicians’ general awareness of manifestations of the disease.
Multi-Objects Detection in Remote Sensing Images Using Multiple Kernel Learning

The objective of this work is multiple objects detection in remote sensing images. Many classifiers have been proposed to detect military objects. In this paper, we demonstrate that linear combination of kernels can get a better classification precision than product of kernels. Starting with base kernels, we obtain different weights for each class through learning. Experiment on Caltech-101 dataset shows the learnt kernels yields superior classification results compared with single-kernel SVM. While such a powerful classifier act as a sliding-window detector to search planes in images collected from Google Earth, results shows the effectiveness of using MKL detector to locate military objects in remote sensing images.
Distributed Spectral Graph Methods for Analyzing Large-Scale Unstructured Biomedical Data

There is an ever-expanding body of biological data, growing in size and complexity, out- stripping the capabilities of standard database tools or traditional analysis techniques. Such examples include molecular dynamics simulations, drug-target interactions, gene regulatory networks, and high-throughput imaging. Large-scale acquisition and curation biological data has already yielded results in the form of lower costs for genome sequencing and greater cov- erage in databases such as GenBank, and is viewed as the future of biocuration. The “big data” philosophy and its associated paradigms and frameworks have the potential to uncover solutions to problems otherwise intractable with more traditional investigative techniques. Here, we focus on two biological systems whose data form large, undirected graphs. First, we develop a quantitative model of ciliary motion phenotypes, using spectral graph methods for unsupervised latent pattern discovery. Second, we apply similar techniques to identify a mapping between physiochemical structure and odor percept in human olfaction. In both cases, we experienced computational bottlenecks in our statistical machinery, necessitating the creation of a new analysis framework. At the core of this framework is a distributed hierarchical eigensolver, which we compare directly to other popular solvers. We demon- strate its essential role in enabling the discovery of novel ciliary motion phenotypes and in identifying physiochemical-perceptual associations.
Honey and Cupping for Leg Ulcer Healing in Rheumatoid Arthritis Patients, Data Supporting their Use in Clinical Practice

Introduction: Patients with rheumatoid arthritis are predisposed to developing chronic leg ulcers. These ulcers must be treated as early as possible as it is substantial regarding the fate of the patient specially in spectrum of that most of treated ulcers for a long time with conventional treatment have little if any signs of healing. Honey as a natural, widely available product had been investigated with promising results as an effective factor with many benefits in promoting healing of various wounds & ulcers. Meanwhile many studies were conducted on cupping as healing measures used in many cultures & still used, enhancing blood supply to the affected area & removing exudates to prepare the wound for sound healing. Materials and Methods: In this prospective study, patients with rheumatoid arthritis leg ulcers refractory to conventional therapies were treated with cupping & honey application for three months until either healing or failure of treatment was achieved. Results: 93.3% of ulcers showed signs of healing while failure of treatment was observed in only 6.7% of ulcers that needed surgical intervention. Conclusion: Honey combined with cupping suction had considerable therapeutic effects on leg ulcers in rheumatoid arthritis patients.
The image : a guide to pseudo-events in America

First Published In 1962, This Wonderfully Provocative Book Introduced The Notion Of 'pseudo-events' -- Events Such As Press Conferences And Presidential Debates, Which Are Manufactured Solely In Order To Be Reported -- And The Contemporary Definition Of Celebrity As 'a Person Who Is Known For His Well-knownness. ' Since Then Daniel J. Boorstin's Prophetic Vision Of An America Inundated By Its Own Illusions Has Become An Essential Resource For Any Reader Who Wants To Distinguish The Manifold Deceptions Of Our Culture From Its Few Enduring Truths.
Minimally-invasive, direct coronary artery bypass grafting.

BACKGROUND Minimally-invasive, direct vision coronary artery bypass grafting (MIDCAB) is a new surgical technique performed via limited thoracotomy in a beating heart without cardiopulmonary bypass. METHODS From June 1996 to December 1996, MIDCAB was performed in 12 patients (all male, average age, 65.9 years). In 11 patients with left anterior descending coronary artery lesions, thoracotomy was performed via the left, fourth intercostal space and the pericardium was incised to identify the target site. About 8 cm of the left internal mammary artery was harvested. Bilateral anterolateral thoractomy was performed in one patient with left anterior descending and right coronary artery lesions. Anastomosis was performed under direct vision in the beating heart without cardiopulmonary bypass. RESULTS MIDCAB was performed successfully without morbidity. The patients' average stay in the intensive care unit was 1.8 days. No patient had any early cardiac event requiring additional surgery or percutaneous transluminal coronary angioplasty. Postoperatively, all patients were asymptomatic and their recovery was uneventful. CONCLUSIONS Our initial experience indicates that MIDCAB offers good results and is a treatment option for selected patients with left anterior descending and/or right coronary artery lesions.
Optimization of Growth Conditions for Purification and Production of L-Asparaginase by Spirulina maxima

L-asparaginase (L-AsnA) is widely distributed among microorganisms and has important applications in medicine and in food technology sectors. Therefore, the ability of the production, purification, and characterization of AsnA from Spirulina maxima (SM) were tested. SM cultures grown in Zarrouk medium containing different N2 (in NaNO3 form) concentrations (1.25, 2.50, and 5.0 g/L) for 18 days contained a significant various quantity of dry biomass yields and AsnA enzyme levels. MS L-AsnA activity was found to be directly proportional to the N2 concentration. The cultures of SM at large scales (300 L medium, 5 g/L N2) showed a high AsnA enzyme activity (898 IU), total protein (405 mg/g), specific enzyme activity (2.21 IU/mg protein), and enzyme yield (51.28 IU/L) compared with those in low N2 cultures. The partial purification of crude MS AsnA enzyme achieved by 80% ammonium sulfate AS precipitated and CM-Sephadex C-200 gel filtration led to increases in the purification of enzyme with 5.28 and 10.91 times as great as that in SM crude enzymes. Optimum pH and temperature of purified AsnA for the hydrolyzate were 8.5 and 37 ± 0.2°C, respectively. To the best of our knowledge, this is the first report on L-asparaginase production in S. maxima.
Anthropometrical Parameters and Physical Fitness of College Going Adolescent Girls Residing in Mumbai

Impaired physical fitness and malnutrition are important causes of overweight and obesity across the age and gender groups. Moreover, the increasing incidence of obesity is associated with complications such as diabetes, cardiovascular diseases and hypertension and hence is a serious cause of concern especially among younger generations including adolescents. The present study has been conducted to understand the influence of body composition on physical fitness among adolescent girls in the age group of 16-19 yrs. 110 adolescent girls in the age group of 16–19 years were selected using purposive sampling technique. The participants were categorized as per their BMI WHO, [1] into 4 groups; i.e. underweight (26.4%), normal (33.7%), Over-weight (10%) and obese (30%). They were assessed for anthropometric parameters (height, weight, waist circumference, hip circumference and waist to hip ratio), total body fat percent, physical fitness (aerobic capacity, muscular endurance and flexibility testing), and physical activity pattern. Highly significant difference was seen between the groups in the BMI, WHR and total body fat percent (p<0.01). There was a decrease in physical fitness with increased BMI. The study suggested a strong need to create awareness among the adolescents about the importance of regular physical activity and to maintain healthy body composition.
AVD: Adversarial Video Distillation

In this paper, we present a simple yet efficient approach for video representation, called Adversarial Video Distillation (AVD). The key idea is to represent videos by compressing them in the form of realistic images, which can be used in a variety of video-based scene analysis applications. Representing a video as a single image enables us to address the problem of video analysis by image analysis techniques. To this end, we exploit a 3D convolutional encoder-decoder network to encode the input video as an image by minimizing the reconstruction error. Furthermore, weak supervision by an adversarial training procedure is imposed on the output of the encoder to generate semantically realistic images. The encoder learns to extract semantically meaningful representations from a given input video by mapping the 3D input into a 2D latent representation. The obtained representation can be simply used as the input of deep models pre-trained on images for video classification. We evaluated the effectiveness of our proposed method for video-based activity recognition on three standard and challenging benchmark datasets, i.e. UCF101, HMDB51, and Kinetics. The experimental results demonstrate that AVD achieves interesting performance, outperforming the state-of-the-art methods for video classification.
On the Conjugacy of Off-Line and On-Line Sequential Monte Carlo Samplers

Sequential Monte Carlo (SMC) methods are widely used for filtering purposes of non-linear economic or financial models. Nevertheless the SMC scope encompasses wider applications such as estimating static model parameters so much that it is becoming a serious alternative to Markov- Chain Monte-Carlo (MCMC) methods. Not only SMC algorithms draw posterior distributions of static or dynamic parameters but additionally provide an estimate of the normalizing constant. The tempered and time (TNT) algorithm, developed in the paper, combines (off-line) tempered SMC inference with on-line SMC inference for estimating many slightly different distributions. The method encompasses the Iterated Batch Importance Sampling (IBIS) algorithm and more generally the Resample Move (RM) algorithm. Besides the number of particles, the TNT algorithm self-adjusts its calibrated parameters and relies on a new MCMC kernel that allows for particle interactions. The algorithm is well suited for efficiently back-testing models. We conclude by comparing in-sample and out-of-sample performances of complex volatility models.