Miracle-dz/UniFAR-FTUs huggingface dataset:
Comitês De Classificadores Para Diagnóstico Automático De Patologias Da Coluna Vertebral: Um Estudo Comparativo

This paper reports a comparative study of learning strategies based on committee machines developed for the diagnostics module of the software platform SINPATCO System for INtelligent Diagnostics of PAThologies of the vertebral COlumn. This module comprises an automatic pattern classifier and is evaluated by its ability in classifying a new patient as belonging to one out of three categories: Normal, Disk Hernia or Spondylolisthesis. First, the MLP and GRNN networks were evaluated individually. In sequel, committee machines composed of MLP and GRNN networks were evaluated. The obtained results suggest that the committee of classifiers presented better generalization performance than individual classifiers. In addition, MLP-based committee machines performed better than the GRNN-based one, obtaining higher recognition rates, higher robustness to outliers and lower false positive and false negative rates. Keywords— Computer Aided Diagnostics, vertebral column, committee machines, pattern classification, robustness. Resumo— Este artigo reporta um estudo comparativo de estratégias de aprendizado baseadas em máquinas de comitê implementadas para o módulo de diagnóstico da plataforma SINPATCO Sistema INteligente para diagnóstico de PATologias da COluna vertebral. Este módulo é composto por um classificador automático de padrões, sendo avaliado quanto à capacidade de categorizar casos cĺınicos em uma das seguintes classes: Normal, Hérnia de Disco e Espondilolistese. Primeiramente, classificadores baseados nas redes MLP e GRNN foram avaliados individualmente, para em seguida, avaliar comitês de máquinas constitúıdos desses classificadores. Os resultados obtidos indicam que comitê de classificadores apresentam melhor generalização que os classificadores tomados individualmente. Entre as máquinas de comitê, o comitê de redes MLP apresenta melhor desempenho, i.e. maior taxa de acerto, maior robustez a outliers e menor número de falsos positivos e falsos negativos. Keywords— Diagnóstico por computador, coluna vertebral, máquinas de comitê, classificação de padrões, robustez a outliers.
Permeability enhancement techniques for poorly permeable drugs: A review.

Need for an oral replacement to parenteral delivery has led to renewed attentiveness in excipients like intestinal permeation enhancers which improve oral drug bioavailability. Delivery of a drug by oral route is predominantly restricted by pre-systemic degradation and poor penetration across the gut wall. The major challenge in the oral drug delivery is the development of novel dosage forms to endorse absorption of poorly permeable drugs across the intestinal epithelium. Fifty years ago research on oral absorption enhancers that increases gut permeability was first commenced yet clinical success yet to be achieved. Development has been troubled by lack of adequate reproducibility interest as well as perceived safety concerns. We reviewed some selected permeation enhancement techniques that are advantageous for increasing permeability of poorly permeable drugs.
The Role That Students' Learning Styles Play in Complex Problem Solving Over Time while Implementing a Case-Based E-Learning Environment in a Lecture-Oriented Anesthesiology Class

This study explores how students’ learning styles influence students’ learning performance in solving complex problems in an Anesthesiology class over a three-week period as a case-based e-learning environment is implemented in a conventional lectureoriented classroom in a dental school. Seventy students from an Anesthesiology class participated in this study. Five learning-outcomes tests and two course-satisfaction surveys were implemented during the case-based instruction using a blended approach (online and face-to-face). The results revealed that students’ learning styles seemed to influence their learning outcomes slightly at an earlier time during the case-based learning implementation; however, as time passed, learning styles no longer influenced their learning at all. Thus, learning styles may be considered only in the early stages of instructional implementation in order to facilitate the students’ transition to the new learning environment. Learning Style and Case-Based E-Learning 3
COST-EFFECTIVENESS ANALYSIS IN THE MANAGEMENT OF STROKE

Objective: Stroke is one of the leading causes of death and disabilities worldwide. Cost-effectiveness analysis helps identify neglected opportunities by highlighting interventions that are relatively inexpensive, yet have the potential to reduce the disease burden substantially. In India, there are wide social and economic disparities. Socioeconomic environment influences occupation, lifestyle, and nutrition of social classes which in turn would influence the prevalence and profile of stroke. By reduction of delays in access to hospital and improving provision of affordable treatments can reduce morbidity and mortality in patients with stroke in India. This study is designed to measure and compare the costs (resources consumed) and consequences (clinical, economic, and humanistic) of pharmaceutical products and services and their impact on individuals, healthcare systems and society.Methods: The purpose of this study is to analyze and conduct a cost-effectiveness analysis for the treatment of stroke in Guntur City Hospitals. The patients were treated either with aspirin or clopidogrel. The health outcomes were measured using Modified Rankin Scale, A prominent risk assessment scale for stroke. The pharmacoeconomic data were computed from the patient data collection forms.Result: The incremental cost-effectiveness ratio of aspirin and clopidogrel were calculated to be Rs. 8046.2/year.Conclusion: The study concludes that aspirin has the increased socioeconomic impact when compared to Clopidogrel and we can see that the earlier therapy has supported discharge, home-based rehabilitation along with reduced hospital stay and hence preferable.
Bentazone adsorption and desorption on agricultural soils

Herbicide fate and transport in soils greatly depend upon adsorption-desorption processes. Batch adsorption and desorption experiments were performed with the herbicide bentazone using 13 contrasted agricultural soil samples. Bentazone was found to be weakly sorbed by the different soils, showing average Freundlich adsorption coefficients (K f ) value of 1.4 ± 2.3 mg 1-nf L n f kg -1 Soil organic matter content did not have a significant effect on bentazone sorption (r 2 = 0.12), whereas natural soil pH appeared to be a key factor (r = 0.68). A large part (average of 96.9 ± 4.1%) of the sorbed bentazone was released into aqueous solution after successive desorption steps, although some hysteresis was observed for each soil. Whereas soil pH was found to also influence bentazone desorption, other soil properties did not show well-defined relationships with sorption.
INTRODUCTION TO HYPERLIPIDEMIA AND ITS TREATMENT: A REVIEW

Hyperlipidemia is a family of disorders that are characterised by abnormally high levels of lipida (fats) in the blood. While fats play a vital role in the body’s metabolic processes, high blood levels of fats increase the risk of coronary heart disease (CHD). Cardiovascular diseases, especially coronary heart disease (CHD), are epidemic in India. According to American Heart Association, the Centres for Disease Control and Prevention, the National Institutes of Health and other government sources, cardiovascular disease is the leading global cause of death, accounting for more than 17.3 million deaths per year, a number that is expected to grow to more than 23.6 million by 2030. India has seen a rapid transition in its heart disease burden over the past couple of decades. Of the 30 million heart patients in India, 14 million reside in urban areas and 16 million in rural areas. If the current trend continues, by the year 2020, the burden of atherothrombotic cardiovascular diseases in India will surpass that of any other country in the world. The Registrar General of India reported that CHD led to 17% of total deaths and 26% of adult deaths in 2001-2003, which increased to 23% of total and 32% of adult deaths in 2010-2013. The global increase in the prevalence of hyperlipidemia is due to unhealthy eating habits, obesity and physical inactivity. The emergencies, risk factors and remedies are described in the literature. Hyperlipidemia, Coronary heart disease, lipoproteins
Dietary fructans and their potential beneficial influence on health and performance parametrs in broiler chickens.

Fructans, which include inulin and fructooligosaccharides, are non-digestible carbohydrates that are fermented in the large intestine. This review focuses on the effect of these prebiotics on gut microflora, fermentation characteristics, gut morphology, enzymes activity, nutrients digestibility and absorption, lipids metabolism and performance parameters in broiler chickens. Inulin-type fructans can improve performance of birds and health by affecting microbial community in the gastrointestinal tract, gut morphology and nutrient digestion. It is documented that dietary fructans influence the intestinal gut microflora of broiler chickens by increasing the population of Bifidobacterium spp. , Lactobacillus spp. and Eubacterium spp. while decreasing the concentration of Clostridium spp. and Escherichia coli in the large intestine and caeca. The supplementation of poultry diets with inulin or oligofructose can lead to an increase of the length of small and large intestines in broilers, elongation of the villus in the chickens jejunal mucosa and increase in the ratio of villus height to crypt depth. The beneficial effect of inulin-type fructans on performance parameters in broilers may be partially explained by the elevated intestinal enzymatic activity under the influence of the fructooligosaccharides and increase of digestibility and absorption of nutrients, mainly protein and fat. The prebiotic effectiveness of inulin-type fructans in broilers depends on a number of factors, like the type of supplement (inulin vs. oligofructose), inclusion level, composition of the basal diet, animal characteristics (age, sex, stage of production) and hygienic conditions (i.e. stress factors).
An Introduction to Software Usability

Interactive computer applications have become ubiquitous and therefore large sections of our societies have become users of computer software. In this context the issue of Software Usability has gained prime importance. So computer professionals and the software industry need to put special attention in this issue. In this paper an introduction to the field of Software Usability is attempted. This is a prominent area of the discipline of Human-Computer Interaction (HCI) that studies interaction of humans and computer machinery and focuses on the design of interactive computer systems. The paper introduces a workshop on Software Usability, organised by the network of Excellence on Software Usability, which has been active for the last two years in Greece.
Comparative Study of Feature Selection Approaches for Urdu Text Categorization

This paper presentsacomparative study of feature selection methods for Urdu text categorization. Fivewellknownfeature selection methods were analyzedby means ofsixrecognized classification algorithms: support vector machines (with linear, polynomial and radial basis kernels), naive Bayes, k-nearest neighbour (KNN), and decision tree (i.e. J48). Experimentations are performed on two test collections includinga standard EMILLE collection and a naive collection. We have found that information gain, Chi statistics, and symmetrical uncertainfeature selection methods have uniformly performed in mostly cases. We also found that no solo feature selection technique is best for every classifier.That is,naive Bayes and J48 have advantage with gain ratio than other feature selection methods. Similarly, support vector machines (SVM) and KNN classifiers have shown top performance with information gain.Generally,linear SVM with any of feature selection methods outperformed other classifiers on moderate-size naive collection.Conversely, naive Bayes with any of feature selection technique has an advantage over other classifiers for a small-size EMILLE corpus.
The influence of sport on the development of postural disorders in athletes

The high incidence of postural disorders in certain branches of sport, especially among adolescents has questioned the influence of sports activities on the postural status of athletes. Although there is still no definite opinion about the connection between sports and postural disorders, researchers have established the existence of certain factors such as amenorrhea, weakness of the joints, highly repetitive activity of sports, muscle imbalance and others that could affect the occurrence or development of some postural disorders. These factors, along with the influence of the heritage of athletes, justify the thesis of certain authors, that scoliosis, kyphosis and lordosis are multifactorial disorders.
Towards Automatic Compiler-assisted Performance and Energy Modeling for Message Passing Parallel Programs

Optimizing programs for modern distributed memory parallel architectures is a notoriously difficult task that generated the need for modeling tools that can estimate the execution time and energy consumption for message passing programs. Many prediction tools require substantial manual effort, excessive training for every given architecture or limit the class of input programs that can be handled. We present a compiler-based approach that automatically generates parametrized analytical models. While requiring only a minimum training overhead on target architectures it still provides reasonably accurate models for execution time and energy consumption of message passing programs. Our method uses compiler analyses to identify the structure of code regions of input programs, and extracts important parameters such as loop iteration counts or message buffer sizes. We can then predict the performance of these code regions for new problem sizes and target machines. We show that compiler knowledge can be effectively used to minimize training overhead and evaluate our approach on multiple target applications with varying problem and machine sizes. Initial results obtained with our prototype implementation show a mean coefficient of determination (R(exp)2) of 0:93 over 7 input programs.
Building a Classifier Employing Prism Algorithm with Fuzzy Logic

Classification in data mining is receiving immense interest in recent times. As the knowledge is based on historical data, classifications of data are essential for discovering the knowledge. To decrease the classification complexity, the quantitative attributes of data need splitting. But the splitting using the classical logic is less accurate. This can be overcome by the use of fuzzy logic. This paper illustrates how to build up the classification rules using the fuzzy logic. The fuzzy classifier is built on by using the prism decision tree algorithm. This classifier produces more realistic results than the classical one. The effectiveness of this method is justified over a sample dataset.
Oil Price Shocks and Their Short- and Long-Term Effects on the Chinese Economy

A considerable body of economic literature shows the adverse economic impacts of oil-price shocks for the developed economies. However, there has been a lack of empirical study of this kind on China and other developing countries. This paper attempts to fill this gap by answering how and to what extent oil-price shocks impact China’s economy, emphasizing on the price transmission mechanisms. To that end, we develop a structural vector auto-regressive model. Our results show that an oil-price increase negatively affects output and investment, but positively affects inflation rate and interest rate. However, with the differentiated price control policies for materials and intermediates on the one hand and final products on the other hand in China, the impact on real economy, represented by real output and real investment, lasts much longer than that to price/monetary variables. Our decomposition results also show that the short-term impact, namely output decrease induced by the cut of capacity-utilization rate, is greater in the first one to two years, but the portion of the long-term impact, defined as the impact realized through an investment change, increases steadily and exceeds that of short-term impact at the end of the second year. Afterwards, the long-term impact dominates, and maintains for quite some time.
SIFT Accordion: A Space-Time Descriptor Applied to Human Action Recognition

Recognizing human action from videos is an active field of research in computer vision and pattern recognition. Human activity recognition has many potential applications such as video surveillance, human machine interaction, sport videos retrieval and robot navigation. Actually, local descriptors and bag of visuals words models achieve state-of-the-art performance for human action recognition. The main challenge in features description is how to represent efficiently the local motion information. Most of the previous works focus on the extension of 2D local descriptors on 3D ones to describe local information around every interest point. In this paper, we propose a new spatio-temporal descriptor based on a spacetime description of moving points. Our description is focused on an Accordion representation of video which is well-suited to recognize human action from 2D local descriptors without the need to 3D extensions. We use the bag of words approach to represent videos. We quantify 2D local descriptor describing both temporal and spatial features with a good compromise between computational complexity and action recognition rates. We have reached impressive results on publicly available action data set Keywords—Accordion, Bag of Features, Human action, Motion, Moving point, Space-Time Descriptor, SIFT, Video.
Toward Secured Social Tagging Systems

Social tagging systems provide an open platform for users to share and annotate their resources such as photos and URLs. Due to their open nature, however, these systems present a security problem. Malicious users may try to distort the systems behavior by inserting false user profiles. This paper addresses the problem of security and robustness of social tagging systems. We outline a framework to model the navigation of a tagging system. Using our framework we classify attack models and identify different kinds of potential attacks to a social tagging system. We implement two of our attack models and study the impact of attacks on existing algorithms used by tagging
Human Vaccines: News

Reversing a downward trend, immunization rates are now at their highest ever and vaccine development worldwide is booming, according to a new assessment released in october 2009 by the WHo, UNicEF and the World Bank. The reversal of the downward trend was due in great part to the efforts of developing countries, who made good use of support from the GAVi Alliance, a vaccine-financing partnership that includes WHo, UNicEF, the World Bank and the Bill & Melinda Gates Foundation. The third edition of the State of the World’s Vaccines and Immunization report is a call to action to governments and donors to sustain and increase funding for immunization in order to build upon the progress made so far in meeting the global goals. it focuses on the major developments in vaccines and immunization since 2000. The report states that more infants are being immunized today than ever before—a record 106 million in 2008—according to new data. Nevertheless, life-saving vaccines, now common in developed countries, still do not reach an estimated 24 million high-risk children. Experts report that at least 120 vaccines— a record number—are now available against deadly diseases. over the last few years new life-saving vaccines for meningococcal meningitis, rotavirus diarrhea, pneumococcal diseases and human papillomavirus disease (HPV) have been developed. in addition, over 80 new products are in late-stage clinical testing, including more than 30 that target diseases for which no commercial vaccine exists. At the same time, a significant number of vaccine candidates, including ones targeting diseases such as HiV/AiDS, malaria, tuberculosis and dengue, are moving through the research pipeline. The cost of delivering vaccines to those who need them most is increasingly an issue that is only partially solved by financing partnerships such as GAVi. Even at greatly reduced prices, the cost of new vaccines for pneumococcal disease, rotavirus diarrhea and HPV are individually greater than the cost of all other traditional vaccines combined. According to Helen Evans, GAVi’s Deputy chief Executive officer, GAVi partners plan to introduce the pediatric pneumococcal vaccine in 42 countries and the rotavirus vaccine in 44 countries by 2015. “The use of both vaccines could make a significant impact on the Millennium Development Goals and prevent more than 11 million child deaths by 2030” says Dr. Evans. The complete State of the World’s Vaccines and Immunization report can be downloaded on the WHo Web site http://www.who. int/ immunization/sowvi/en/
The Effect of Irradiation on Rheological and Electrical Properties of Collagen

Abstract This paper describes the effects of irradiation on the rheological and electrical properties of a 7.7% mass fraction of native bovine collagen in water. The radiation dose was in the range of 0 - 500 Gy. Rheological oscillation measurements were done at temperatures of 10, 20, and 30 °C. There was a statistically significant dependency of storage and loss moduli on irradiation dose and oscillation frequency. There was no significant change in the electrical conductivity of collagen during oscillation movements or any dependence on irradiation dose.
Information Structure in PA/SN or Descriptive/ Metalinguistic Negation: With Reference to Scalar Implicatures1

This paper attempts to show how the information structure categories of Contrastive Topic (CT) and Contrastive Focus (CF) are correlated with PA (pero/aber) vs. SN (sino/sondern) respectively and also with DN (descriptive negation) vs. MN (metalinguistic negation) respectively when negative utterances are involved. Far Eastern and other languages including English will be investigated. It further claims that the CT–PA pattern underlies the phenomenon of scalar implicatures, whereas the CF–SN pattern, which is MN, typically ‘blocks’ them or is irrelevant to them. Scalar implicatures, conventionalized by CT, are viewed as basically semantic but linked to Gricean, dynamic, argumentation-theoretic, game-theoretic reasoning. 1 I thank those who asked questions and made comments at the Shanghai conference and its organizers. I am particularly grateful to Ken Turner for his comments on the draft and to Larry Horn for his comments on one aspect of predicate scales such as <like, love>, which may be different from other scales. The research reported here was partially supported by the grant from the Japan Society for the Promotion of Science, Grant-in-Aid for Scientific Research (A) (1), No. 15202009 (2003–7) to Takao Gunji.
High-performance organic integrated circuits based on solution processable polymer-small molecule blends

The prospect of realizing high-performance organic circuits via large-area fabrication is attractive for many applications of organic microelectronics. Here we report solution processed organic field-effect transistors and circuits based on polymer-small molecule blends comprising of polytriarylamine and 5,11-bis(triethylsilylethynyl) anthradithiophene. By optimizing blend composition and deposition conditions we are able to demonstrate short channel, bottom-gate, bottom-contact transistors with high mobility and excellent reproducibility. Using these transistors we have built unipolar voltage inverters and ring oscillators with a single stage delay of 712 ns. These are among the fastest organic circuits reported to date and could satisfy the performance requirements of low-end electronic applications.