Miracle-dz/UniFAR-FTUs huggingface dataset:
Trends in mortality from cardiovascular and cerebrovascular diseases in Europe and other areas of the world

Objective: To analyse trends in mortality from coronary heart disease (CHD) and cerebrovascular disease (CVD) over the period 1965 to 1998 in the European Union, other European countries, the USA, and Japan. Methods and results: Data were derived from the World Health Organization database. In the European Union, CHD mortality in men rose from 146/100 000 in 1965–9 to 163/100 000 in 1975–9 and declined thereafter to 99/100 000 in 1995–8 (−39%). In women, the fall was from 70 to 45/100 000 (−36%). A > 55% decline in CVD was registered in both sexes. In eastern Europe, mortality from both CHD and CVD rose up to the early 1990s but has declined over the past few years in Poland and the Czech Republic. In the Russian Federation during 1995–8, mortality rates from CHD reached 330/100 000 men and 154/100 000 women and mortality rates from CVD were 203/100 000 men and 150/100 000 women—that is, they were among the highest rates worldwide. In the USA and Japan, long term trends were favourable for both CHD and CVD. Conclusions: Trends in mortality from CHD and CVD were favourable in several developed areas of the world, but there were major geographical differences. In a few eastern European countries, mortality from CHD and CVD remains exceedingly high.
Caffe2C: A Framework for Easy Implementation of CNN-based Mobile Applications

In this study, we create "Caffe2C" which converts CNN (Convolutional Neural Network) models trained with the existing CNN framework, Caffe, C-language source codes for mobile devices. Since Caffe2C generates a single C code which includes everything needed to execute the trained CNN, csCaffe2C makes it easy to run CNN-based applications on any kinds of mobile devices and embedding devices without GPUs. Moreover, Caffe2C achieves faster execution speed compared to the existing Caffe for iOS/Android and the OpenCV iOS/Android DNN class. The reasons are as follows: (1) directly converting of trained CNN models to C codes, (2) efficient use of NEON/BLAS with multithreading, and (3) performing pre-computation as much as possible in the computation of CNNs. In addition, in this paper, we demonstrate the availability of Caffe2C by showing four kinds of CNN-base object recognition mobile applications.
Formatting a Paper-based Survey Questionnaire: Best Practices

This paper outlines how to use what we know, based in large part on the research of social scientist Don Dillman, regarded as a leader in establishing a scientific basis for survey research methodology, to design and create a paper-based survey questionnaire that will improve its response rate and accuracy. While discussion focuses on best practices for formatting paper-based surveys, and several points apply to online surveys as well.
Expectations of reducing fat intake: The role of perceived need within the theory of planned behaviour

Abstract Dietary fat intake has been implicated in the causation of major diseases including coronary heart disease and cancer. Hence, current recommendatioris to improve health emphasise the reduction of fat intake (COMA, 1991). The present study investigated the effect of perceived need to reduce fat intake and past behaviour on peoples' expectations of reducing fat intake, using the framework of the Theory of Planned Behaviour (TPB) (Ajzen, 1985; 1991). The effects of estimated fat intake and body weight on perceived need to reduce were also investigated. One hundred and fifty-two adults completed a four-day weighed dietary record and completed a questionnaire based on the TPB. Perceived need to reduce fat intake, cognitive and affective components of attitude and past behaviour wm found to be significant predictors of expectation of reducing fat intake. Perceived body weight and estimated fat intake were significant predictors of perceived need to reduce fat intake. The implications of these findings .
Estresse oxidativo: conceito, implicações e fatores modulatórios

O estresse oxidativo decorre de um desequilibrio entre a geracao de compostos oxidantes e a atuacao dos sistemas de defesa antioxidante. A geracao de radicais livres e/ou especies reativas nao radicais e resultante do metabolismo de oxigenio. A mitocondria, por meio da cadeia transportadora de eletrons, e a principal fonte geradora. O sistema de defesa antioxidante tem a funcao de inibir e/ou reduzir os danos causados pela acao deleteria dos radicais livres e/ou especies reativas nao radicais. Esse sistema, usualmente, e dividido em enzimatico (superoxido dismutase, catalase e glutationa peroxidase) e nao-enzimatico. No ultimo caso, e constituido por grande variedade de substâncias antioxidantes, que podem ter origem endogena ou dietetica. Objetivou-se revisar os principais mecanismos de geracao de radicais livres, bem como a acao dos agentes mais relevantes do sistema de defesa antioxidante, ressaltando suas implicacoes sobre os marcadores do estresse oxidativo. Tambem serao abordados os principais fatores exogenos moduladores do estresse oxidativo.
Beyond Sliding Windows: Saliency Prior Based Random Partition for Fast Pedestrian Detection

Recently many powerful complicated features have been used for pedestrian detection successfully but they are not fit for real applications because of heavily consuming time caused by production of complicate feature extraction and millions of candidate object probing. The formal is critical for pedestrian detection, so for solving this problem, effective region proposal strategy was proposed. Such approaches generate candidate regions either by segmentation or by shape classification, and they still generate several thousand regions each image, that is too many for fast pedestrian detection. In this paper, a novel search strategy, saliency prior based random partition, is proposed to generate nearly two hundred regions and consume less time than selective search at the same recall. And we prefer the Deformable Part Model [8], one of the most popular object detectors, as the pedestrian detector. At last, we combine the salient prior and the part based detector by Bayesian inference. Experiment results on INRIA person dataset and Caltech person dataset have demonstrated that our approach has outperformed the selective search method.
Antígenos de histocompatibilidade humanos e dermatologia: da pesquisa para a prática clínica

The participation of the human histocompatibility system (HLA: human leukocyte antigens) in the pathogenesis of autoimmune diseases is well known. Situated on the short arm of chromosome 6, the HLA system is very polymorphic and has the capacity to confer susceptibility or resistance to different diseases. In Dermatology, this system has an important participation in the pathogenesis and natural course of various diseases. The strength and type of association differ with conditions and sometimes with the ethnic-racial group studied. The discovery of molecular methods to typify HLA alleles and recent updates in its nomenclature has contributed to a better understanding of this system. Unfortunately, this information has not been adequately transmitted in the literature, hindering identification of the association of the HLA with skin diseases. In this review, some aspects of the HLA system are discussed, such as methods of detection, nomenclature and association with vitiligo, pemphigus, psoriasis, lupus erythematosus, scabies, cutaneous Leishmaniasis, leprosy, paracoccidiodomycosis and atopic dermatitis.
The everyday life of adult family members of working aged survivors of stroke during the first year after the stroke - an integrative review

The purpose of this integrative review was to describe the everyday life of adult family members of working aged survivors of stroke during the first year after the occurrence of the stroke. The studies were researched from Medline, Cinahl, PsycINFO, Medic and Linda databases. The data consisted of 40 articles which were published in scientific journals during 2007-2012. The quality of the articles were assessed with the critical appraisal tools JBI QARI and JBI MAStARI [1] . The articles were analyzed with thematic analysis. The everyday life of adult family members included initially becoming the family member of a survivor of stroke, living as their family member, and eventually coming to terms with life with the survivor of a stroke . Becoming the family member meant living in a focused state of chaos, trying to be strong for the loved one, and going forward in life. It also emphasized the need to rebuild and find a balance in the shadow of the illness and the needs of this complex situation. Coming to terms with the changed life situation of the family member consisted of trying to stabilize emotional wellbeing amid bouts of anxiety and depression. The results of this research should help nurses to better meet the needs of family members at the right time in order to help them deal with expected problems. There is much evidence about older caregivers’ needs, but only scant evidence about younger caregivers and their working aged relatives, especially just after the stroke. This integrative literature review gives important information about the everyday life of family members of working aged survivors of stroke and helps nurses to better understand them and their needs.
Adaptive artistic stylization of images

In this work, we present a novel non-photorealistic rendering method which produces good quality stylization results for color images. The procedure is driven by saliency measure in the foreground and the background region. We start with generating saliency map and simple thresholding based segmentation to get rough estimation of the foreground-background mask. We improve this mask by using a scribble-based method where the scribbles for foreground-background regions are automatically generated from the previous rough estimation. Followed by the mask generation, we proceed with an iterative abstraction process which involves edge-preserving blurring and edge detection. The number of iterations of the abstraction process to be performed in the foreground and background regions are decided by tracking the changes in saliency measure in the foreground and the background regions. Performing unequal number of iterations helps to improve the average saliency measure in more salient region (foreground) while decreasing the average saliency measure in the non-salient region (background). Implementation results of our method shows the merits of this approach with other competing methods.
Generic TV advertisement detection using progressively balanced perceptron trees

Automatic detection of TV advertisements is of paramount importance for various media monitoring agencies. Existing works in this domain have mostly focused on news channels using news specific features. Most commercial products use near copy detection algorithms instead of generic advertisement classification. A generic detector needs to handle inter-class and intra-class imbalances present in data due to variability in content aired across channels and frequent repetition of advertisements. Imbalances present in data make classifiers biased towards one of the classes and thus require special treatment. We propose to use tree of perceptrons to solve this problem. The training data available for each perceptron node is balanced using cluster based over-sampling and TOMEK link cleaning as we traverse the tree downwards. The trained perceptron node then passes the original unbalanced data to its children. This process is repeated recursively till we reach the leaf nodes. We call this new algorithm as "Progressively Balanced Perceptron Tree". We have also contributed a TV advertisements dataset consisting of 250 hours of videos recorded from five non-news TV channels of different genres. Experimentations on this dataset have shown that the proposed approach has comparatively superior and balanced performance with respect to six baseline methods. Our proposal generalizes well across channels, with varying training data sizes and achieved a top F1-score of 97% in detecting advertisements.
Dating Aggression Among Low Income African American Youth

Prevalence of aggression inflicted and sustained in dating relationships was investigated for 171 low income African American youth. More women were victims of choking, attempted forced intercourse, and hurt feelings. As perpetrators, more women reported making threats, throwing objects, and hitting their partner. However, men perpetrated more serious sexual and psychological aggression, including forced breast fondling, attempted forced intercourse, and making a partner feel inferior and degrading her. Women victims of sexual aggression, when compared to nonvictims, expressed more agreement with adversarial sexual beliefs regarding male-female relationships. More than one third of the participants endorsed antagonistic beliefs concerning Black male-female relationships. Suggestions for intervention are presented.
Pap smear image classification using convolutional neural network

This article presents the result of a comprehensive study on deep learning based Computer Aided Diagnostic techniques for classification of cervical dysplasia using Pap smear images. All the experiments are performed on a real indigenous image database containing 1611 images, generated at two diagnostic centres. Focus is given on constructing an effective feature vector which can perform multiple level of representation of the features hidden in a Pap smear image. For this purpose Deep Convolutional Neural Network is used, followed by feature selection using an unsupervised technique with Maximal Information Compression Index as similarity measure. Finally performance of two classifiers namely Least Square Support Vector Machine (LSSVM) and Softmax Regression are monitored and classifier selection is performed based on five measures along with five fold cross validation technique. Output classes reflects the established Bethesda system of classification for identifying pre-cancerous and cancerous lesion of cervix. The proposed system is also compared with two existing conventional systems and also tested on a publicly available database. Experimental results and comparison shows that proposed system performs efficiently in Pap smear classification.
Detecting unseen anomalies in weight training exercises

In weight training, correct exercise execution is crucial for maximizing its effectiveness and for preventing injuries. However, given the complexity of these movements, it is a challenge for trainees to know whether they are performing the exercise correctly. Considering the fact that wrong moves may result in life long injuries, it is important to design systems that can detect incorrect performances automatically. In this paper, we present a workflow to detect performance anomalies from only observations of the correct performance of an exercise by the trainee. We evaluated our algorithm on a benchmark data set for the biceps curl exercise, and also evaluated our system with a publicly available dataset, and showed that our method detects unseen anomalies in weight lifting exercises with 98 percent accuracy.
Are the patients afraid of opioids? Pilot study of the patients with chronic cancer and non-malignant pain

Background. Chronic pain is a major public health issue. Opioids have an important role in the management of chronic cancer and non-cancer pain. Unfortunately, beliefs and myths about opioids are a serious obstacle to using them in pain relief. Material and methods. The study involved 28 patients who suffered from chronic cancer or non-cancer pain. The functional status was measured using Karnofsky Performance Scale and Edmonton Symptom Assessment System. Each patient was asked to complete a survey consisting of three parts, which determined patients medical characteristics, knowledge of analgesic drugs and the fears of using opioids. Results. Our study showed that over half of the surveyed patients (53%) had doubts about starting the opioids treatment. They were afraid of taking morphine and the patients who used tramadol feared of changing it into morphine. The most common reason given by the patients was the fear of addiction and death, which were believed to be associated with using opioids. Other reasons included: the fear of side effects and/or unsatisfactory result of pain relief. Conclusion. Our research suggests that patients are afraid of taking opioids, especially morphine. The results of this pilot study vote for the need of larger survey on patients' attitude to the treatment with opioids for pain management.
Vaginal health in copper intrauterine device users and non-users

Objective: To compare the cervicovaginal flora, vaginal symptoms , infections and pH between copper intrauterine device (IUD) users and non-IUD, non-hormonal users Materials and Methods: A cross-sectional study was conducted from August 2010 to March 2011 at Ramathibodi Hospital. Ninety-two women at the age of 18-45 yr of whom 46 were copper IUD users while other 46 were nonusers. Each woman was evaluated clinically with direct observation of vaginal secretions, wet mount examination, Whiff test, vaginal pH testing and cervicovaginal culture. The outcomes included prevalence of aerobic and anaerobic bacteria colonization, bacterial vaginosis, vaginal candidiasis, trichomoniasis, vaginal symptoms and vaginal pH. Results: There was no difference in prevalence of aerobic (50% VS 54.3%; P=0.67) and anaerobic (82.6%VS 76.1%; P=0.44) colonization between two groups. Vaginal symptoms, candidiasis and trichomoniasis were not significantly different. Prevalence of bacterial vaginosis was significantly higher among IUD users than non-IUD users. (28.3% VS 10.9%; P=0.03). The mean vaginal pH was significantly higher in IUD group (5.3±0.6 VS 4.8±0.8; P <0.05). Conclusion: Copper intrauterine device altered vaginal pH and bacterial vaginosis was more common among IUD users.
A Base Integer Programming Model and Benchmark Suite for Liner-Shipping Network Design

The liner-shipping network design problem is to create a set of nonsimple cyclic sailing routes for a designated fleet of container vessels that jointly transports multiple commodities. The objective is to maximize the revenue of cargo transport while minimizing the costs of operation. The potential for making cost-effective and energy-efficient liner-shipping networks using operations research OR is huge and neglected. The implementation of logistic planning tools based upon OR has enhanced performance of airlines, railways, and general transportation companies, but within the field of liner shipping, applications of OR are scarce. We believe that access to domain knowledge and data is a barrier for researchers to approach the important liner-shipping network design problem. The purpose of the benchmark suite and the paper at hand is to provide easy access to the domain and the data sources of liner shipping for OR researchers in general. We describe and analyze the liner-shipping domain applied to network design and present a rich integer programming model based on services that constitute the fixed schedule of a liner shipping company. We prove the liner-shipping network design problem to be strongly NP-hard. A benchmark suite of data instances to reflect the business structure of a global liner shipping network is presented. The design of the benchmark suite is discussed in relation to industry standards, business rules, and mathematical programming. The data are based on real-life data from the largest global liner-shipping company, Maersk Line, and supplemented by data from several industry and public stakeholders. Computational results yielding the first best known solutions for six of the seven benchmark instances is provided using a heuristic combining tabu search and heuristic column generation.
Further consideration of Asian medicinal plants in treating common chronic diseases in the West

Ethnopharmacological knowledge is viewed as an increasingly relevant and important source for development of new medicinal products. Historically plants have been the basis of many medicines and are a major resource for human health care. This project critically examined the science-based medical evidence supporting use of traditional Asian medicinal plants for curative, preventive or palliative functions relevant to important chronic ailments in Western countries (eg. cardiovascular disease, cancer, diabetes, arthritis, dementia, asthma). Around 400 medicinal plant species were reviewed through 3,500 scientific references. There were more species associated with anticancer effects than any other chronic disease, suggesting that if Asian medicinal species are to make new impacts on Western health there is a strong chance that this will be as anticancer agents. However, conclusive positive results from randomised, double blind, placebo-controlled experiments with humans were only available for a limited number of crops. Garlic (Allium sativum), turmeric (Curcuma longa), green tea (Camellia sinensis), ginseng (Panax ginseng), Astragalus membranaceus and Ginkgo biloba are important Chinese medicinal plants with strong support from medical efficacy trials. Other species backed by good data include Apocynum venetum, Codonopsis pilosula, Fallopia multiflora, Huperzia serrata, Lycium barbarum, Lycium chinense, Stephania tetrandra and Trichosanthes kirilowii.
A Simulation-Based Evaluation of Premovement Active Surveillance Protocol Options for the Managed Movement of Turkeys to Slaughter During an Outbreak of Highly Pathogenic Avian Influenza in the United States

SUMMARY. Risk management decisions associated with live poultry movement during a highly pathogenic avian influenza (HPAI) outbreak should be carefully considered. Live turkey movements may pose a risk for disease spread. On the other hand, interruptions in scheduled movements can disrupt business continuity. The Secure Turkey Supply (STS) Plan was developed through an industry-government-academic collaboration to address business continuity concerns that might arise during a HPAI outbreak. STS stakeholders proposed outbreak response measure options that were evaluated through risk assessment. The developed approach relies on 1) diagnostic testing of two pooled samples of swabs taken from dead turkeys immediately before movement via the influenza A matrix gene real-time reverse transcriptase polymerase chain reaction (rRT-PCR) test; 2) enhanced biosecurity measures in combination with a premovement isolation period (PMIP), restricting movement onto the premises for a few days before movement to slaughter; and 3) incorporation of a distance factor from known infected flocks such that exposure via local area spread is unlikely. Daily exposure likelihood estimates from spatial kernels from past HPAI outbreaks were coupled with simulation models of disease spread and active surveillance to evaluate active surveillance protocol options that differ with respect to the number of swabs per pooled sample and the timing of the tests in relation to movement. Simulation model results indicate that active surveillance testing, in combination with strict biosecurity, substantially increased HPAI virus detection probability. When distance from a known infected flock was considered, the overall combined likelihood of moving an infected, undetected turkey flock to slaughter was predicted to be lower at 3 and 5 km. The analysis of different active surveillance protocol options is designed to incorporate flexibility into HPAI emergency response plans.