nils-herrmann/clean_scirepeval huggingface dataset:
Climate Change and Air Pollution: Effects on Respiratory Allergy
Venue: Allergy, asthma immunology research

A body of evidence suggests that major changes involving the atmosphere and the climate, including global warming induced by anthropogenic factors, have impact on the biosphere and human environment. Studies on the effects of climate change on respiratory allergy are still lacking and current knowledge is provided by epidemiological and experimental studies on the relationship between allergic respiratory diseases, asthma and environmental factors, such as meteorological variables, airborne allergens, and air pollution. Urbanization with its high levels of vehicle emissions, and a westernized lifestyle are linked to the rising frequency of respiratory allergic diseases and bronchial asthma observed over recent decades in most industrialized countries. However, it is not easy to evaluate the impact of climate changes and air pollution on the prevalence of asthma in the general population and on the timing of asthma exacerbations, although the global rise in asthma prevalence and severity could also be an effect of air pollution and climate change. Since airborne allergens and air pollutants are frequently increased contemporaneously in the atmosphere, an enhanced IgE mediated response to aeroallergens and enhanced airway inflammation could account for the increasing frequency of respiratory allergy and asthma in atopic subjects in the last 5 decades. Pollen allergy is frequently used to study the relationship between air pollution and respiratory allergic diseases, such as rhinitis and bronchial asthma. Epidemiologic studies have demonstrated that urbanization, high levels of vehicle emissions, and westernized lifestyle are correlated with an increased frequency of respiratory allergy prevalently in people who live in urban areas in comparison with people living in rural areas. Climatic factors (temperature, wind speed, humidity, thunderstorms, etc. can affect both components (biological and chemical) of this interaction.
The Effects of a Medical Plant Mixture and a Probiotic on Performance, Antioxidant Activity and Weaning Age of Newborn Holstein Calves

The aim of this study was to investigate the effects of a medical plant mixture and a probiotic on performance, antioxidant activity and weaning age of suckling Holstein calves. For this experiment, 30 newborn calves (0 10 days of age) with an average birth weight of 42 8 kg were used in a factorial design (3x2) with 6 treatments and 5 replicates. Treatments were: 1) basal diet including a calves starter feed and whole m ilk, 2) control diet 2 g probiotic 3) control diet 1.5% of medical plant, 4) control diet 1.5% medical plant 2 g probiotic, 5) control diet 3% medical plant and 6) control diet 3% medical plant 2 g probiotic. The calves were offered experimental pelleted feeds ad libitum and after one month were supplied with imported hay. Results showed that the treatments had no significant effect on dry matter intake during the experiment. However, addition of the 1.5% medical plant increased dry matter intake (P<0.05) However, the 1.5% level of medical plant reduced calves weaning age (P<0.05) Calves receiving control diet 1.5% of medical plant mixed and 1.5% medical plant mixed 2 g probiotic showed a higher plasma antioxidant activity (P<0.05) This study suggested that 1.5% of medical plant in calves starter feed will improve performance and the immune system and will also reduce the weaning age of calves.
RESEARCH IN SOME MEDICAL PLANT DRYING PROCESS

The drying process by free convection of six different medical plants (flowers of garden marigold (Calendula officinalis) leaves of lemon balm (Melissa officinalis) origanum (Origanum vulgare) common agrimony (Agrimonia eupatoria) common lavender (Lavandula angustifolia) and common sage (Salvia officinalis) is compared. The constant and changing drying coefficients are determined using the gravimetric methods of measurement and a special mathematical evaluation methodology. Theoretical and experimental results are compared. The experimental results show that the drying coefficient of a plant at the first 10 hours of drying is changing linearly until it becomes constant. The corresponding linearity is strong, characterized by high coefficients of determination. The changes of speeds of sample drying rate are approximately equal, except lemon balm, which is more than twice greater than the others.
A Single Phase Voltage Sag Generator for Testing Electrical Equipments

This paper describes a transformer based voltage sag generator (VSG) suitable to evaluate the susceptibility of electrical equipment to voltage sag. The built VSG utilized one auto transformer and two solid state relays (SSRs) to provide nominal voltage and sag voltage to the load. The switch statuses of two SSRs are controlled by nominal voltage and sag voltage duration signal produced by electronic circuits. The VSG operating result shows that it enables effective control of sag magnitude, duration, beginning and ending points on output voltage wave. If needed, it can work as a voltage swell generator and a voltage interruption generator. By supplying high voltage (HV) transformer from the primary side, the VSG also can provide HV sag, swell, and interruption. The presented VSG is easier to set up in the lab, and the construction cost is much lower than buying VSG products at the current market.
Textual emotion recognition for enhancing enterprise computing
Venue: Enterp. Inf. Syst.

The growing interest in affective computing (AC) brings a lot of valuable research topics that can meet different application demands in enterprise systems. The present study explores a sub area of AC techniques textual emotion recognition for enhancing enterprise computing. Multi label emotion recognition in text is able to provide a more comprehensive understanding of emotions than single label emotion recognition. A representation of 'emotion state in text' is proposed to encompass the multidimensional emotions in text. It ensures the description in a formal way of the configurations of basic emotions as well as of the relations between them. Our method allows recognition of the emotions for the words bear indirect emotions, emotion ambiguity and multiple emotions. We further investigate the effect of word order for emotional expression by comparing the performances of bag of words model and sequence model for multi label sentence emotion recognition. The experiments show that the classification results under sequence model are better than under bag of words model. And homogeneous Markov model showed promising results of multi label sentence emotion recognition. This emotion recognition system is able to provide a convenient way to acquire valuable emotion information and to improve enterprise competitive ability in many aspects.
Do Preferences for Pop Music Converge Across Countries? Empirical Evidence from the Eurovision Song Contest

The combination of the digitalization of cultural goods and facilitated cross border availability through the internet fuels a globalization process that is often said to cause a homogenization of demand across countries, in particular, for entertainment goods as music and movies. In the markets for music, this implies that the same hits and the same artists should be popular across countries and cultures. In order to test this hypothesis, we analyze historical voting data of the Eurovision Song Contest, the worldwide biggest live broadcasted international music competition between all countries of the European Broadcasting Union. It covers the period from 1975 2016 where digitalization and internet availability were invented and evolved into mass phenomena. Consequently, according to the outlined theory of homogenization of preferences, voting should have become more concentrated on the leading artists and less focused on regional differences in taste. For the purpose of detecting concentration trends in the points allocation, we employ different indicators for measuring concentration. First, we calculate a concentration ratio, representing the accumulated total number of points of the top three, five and ten placed countries in each year of the contest. Second, we calculate the Herfindahl Hirschman Index (HHI) and, third, the Gini Coefficient for each year. Furthermore, we test trendlines for statistical significance. The results show, that our analysis cannot support the thesis of preference homogenization. We find no significant trend towards preference convergence. In contrast, some of the employed indicators and methods point towards significant, albeit weak, deconcentration trends in voting behavior for the contest.
In vitro Comparative Evaluation of Various Restorative Materials used for restoring Class III Cavities in Deciduous Anterior Teeth: A Clinical Study.
Venue: The journal of contemporary dental practice

Beauty standards in today's modernized world scenario are formed by well aligned and well designed bright white teeth. One of the major reasons behind patients reporting to dental clinics is pain. Caries in the anterior primary teeth forms one of the major concerns from a restorative point of view. Very few studies are quoted in literature which stresses on the follow up of anterior restorations in primary teeth. Hence, we evaluated and compared the efficacy of composite resin and resin modified glass ionomer cement (RGIC) for class III restorations in primary anterior teeth.  The present study was conducted in the pediatric dental wing and included a total of 80 patients aged 3 to 5 1/2 years who reported with the chief complaint of carious lesions in the primary anterior teeth. Patients having minimal of a pair of similar appearing small carious lesions on the same proximal surfaces of the deciduous maxillary incisors were included for the study. All the patients were randomly divided into two groups: One in which RGIC restoration was done and other in which composite restoration was done. Cavity preparation was done and filling of the cavity with the restorative materials was carried out. Assessment of the restorations was done at 4, 8, and 12 months time following criteria given by Ryge et al. All the results were analyzed by Statistical Package for the Social Sciences (SPSS) software. Mann Whitney test and one way analysis of variance (ANOVA) were used to evaluate the level of significance; p value less than 0.05 was considered as significant.  For composite and RGIC restorations, the mean score for anatomic shape was 1.21 and 1.10 respectively. While comparing the clinical parameters, nonsignificant results were obtained between composite and RGIC restorative materials at 4 8 and 12 month interval. On comparing the clinical parameters for individual restorative materials at different time intervals, statistically significant results were obtained only for anatomical shape and form.  Both RGIC and composite resin restorative materials showed acceptable clinical outcomes after 12 months of follow up in deciduous anterior teeth. In restoring class III restorations in primary anterior teeth, both the restorative materials showed similar outcome.  Composite, Marginal, Resin modified glass ionomer cement.
Application Analysis on Internal Rate of Return Rule for Investment Decision

The net present value (NPV) rule is not the only criterion available to evaluate a capital investment proposal. You may be familiar with the payback period, the internal rate of return, or another criterion. This paper examines and explains how to apply to the NPV rule: the internal rate of return (IRR) rule, the criteria used by a large sample of companies when making capital budgeting decisions, with the IRR rules being the most popular and the average accounting return and PI rules being the least popular. We analyze whether the internal rate of return (IRR) rule satisfy the conditions of a good investment decision rule. Recall that a good investment decision rule must take into account the timing of a project's expected cash flows and the project's risk. In addition, it should select projects that increase the market value of the firm's equity. In our analysis of the alternative rules, we identify a number of cases in which the methods lead to a decision that contradicts the NPV rule. We explain why these conflicts occur and why some firms still use some of these techniques to screen investment proposals. We use the projects to illustrate how the alternatives to the NPV rule are usually applied in making investment decisions and compare their performance with that of the NPV rule.
The Recent Development of a7 Nicotinic Acetylcholine Receptor (nAChR) Ligands as Therapeutic Candidates for the Treatment of Central Nervous System (CNS) Diseases.
Venue: Current pharmaceutical design

Homomeric a7 nicotinic acetylcholine receptors (nAChRs) are implicated in the regulation of cognitive processes such as memory and attention and have potential as therapeutic targets for the treatment of the cognitive deficits associated with schizophrenia. Though numerous a7 nAChR agonists have been developed, and several have progressed to clinical trials, these are derived from few common chemotypes. Consequently, many of these a7 nAChR clinical candidates share unfavorable side effect profile. SEN12333 represents a novel chemotype for the development of a7 nAChR agonists, and exploration of this scaffold has produced structurally diverse ligands with promising pharmacological properties. This review will summarize structure affinity and activity relationships surrounding analogs of SEN12333.
Degradation of 4 chloro 2 aminophenol using combined strategies based on ultrasound, photolysis and ozone.
Venue: Ultrasonics sonochemistry

The present work investigates the degradation of 4 chloro 2 aminophenol (4C2AP) a highly toxic organic compound, using ultrasonic reactors and combination of ultrasound with photolysis and ozonation for the first time. Two types of ultrasonic reactors viz. ultrasonic horn and ultrasonic bath operating at frequency of 20 kHz and 36 kHz respectively have been used in the work. The effect of initial pH, temperature and power dissipation of the ultrasonic horn on the degradation rate has been investigated. The established optimum parameters of initial pH as 6 (natural pH of the aqueous solution) and temperature as 30 2degC were then used in the degradation studies using the combined approaches. Kinetic study revealed that degradation of 4C2AP followed first order kinetics for all the treatment approaches investigated in the present work. It has been established that US+UV+O3 combined process was the most promising method giving maximum degradation of 4C2AP in both ultrasonic horn (complete removal) and bath (89.9% with synergistic index as 1.98 and 1.29 respectively. The cavitational yield of ultrasonic bath was found to be eighteen times higher as compared to ultrasonic horn implying that configurations with higher overall areas of transducers would be better selection for large scale treatment. Overall, the work has clearly demonstrated that combined approaches could synergistically remove the toxic pollutant (4C2AP)
Insights into the removal of terbuthylazine from aqueous solution by several treatment methods.
Venue: Water research

This paper reports the removal of the s triazine herbicide terbuthylazine (TBA) from aqueous solution by various treatment methods including adsorption onto activated carbon (AC) and multiwalled carbon nanotubes (MWCNT) UV254 photolysis, UV254/H2O2, single ozonation, O3/H2O2, catalytic ozonation (AC, MWCNT and TiO2 as catalysts) and some solar driven processes such as TiO2 photocatalytic oxidation and photo ozonation. TBA was adsorbed onto AC and MWCNT following a pseudo second order kinetics and Freundlich isotherm. Rapid small scale column tests showed that TBA could be removed from solution by adsorption onto AC better than atrazine. The UV254/H2O2 treatment resulted in excellent removal of TBA primarily due to the oxidation capability of hydroxyl radicals (kHO 3.310(9) M( 1) s( 1) generated from H2O2 photolysis. As the H2O2 initial concentration was increased from 5 to 50 mg L( 1) the HO exposure per UV fluence (RHO,UV) increased, making the process more efficient. Single ozonation also allowed complete removal of the herbicide though the process was slow (kO3=15.4 M( 1) s( 1) at pH 4) The ozonation process could be greatly accelerated by the enhanced generation of HO through O3/H2O2 and O3/AC processes, which also led to more efficient processes in terms of ozone utilization. Commercial TiO2 (TiO2 P25) and lab prepared anatase TiO2 (TiO2 cat) nanoparticles catalyzed the removal of TBA by solar photocatalysis. In contrast, a lab prepared MWCNT TiO2 composite was not useful as catalyst in solar photo oxidation processes because of the HO scavenging nature of the MWCNT used as support. A mechanism for TBA degradation by O3 and HO has been suggested after TBA degradation intermediates identification.
Full Intelligent Cancer Classification of Thermal Breast Images to Assist Physician in Clinical Diagnostic Applications
Venue: Journal of medical signals and sensors

Breast cancer is the most common type of cancer among women. The important key to treat the breast cancer is early detection of it because according to many pathological studies more than 75% 80% of all abnormalities are still benign at primary stages; so in recent years, many studies and extensive research done to early detection of breast cancer with higher precision and accuracy. Infra red breast thermography is an imaging technique based on recording temperature distribution patterns of breast tissue. Compared with breast mammography technique, thermography is more suitable technique because it is noninvasive, non contact, passive and free ionizing radiation. In this paper, a full automatic high accuracy technique for classification of suspicious areas in thermogram images with the aim of assisting physicians in early detection of breast cancer has been presented. Proposed algorithm consists of four main steps: pre processing segmentation, feature extraction, feature selection and classification. At the first step, using full automatic operation, region of interest (ROI) determined and the quality of image improved. Using thresholding and edge detection techniques, both right and left breasts separated from each other. Then relative suspected areas become segmented and image matrix normalized due to the uniqueness of each person's body temperature. At feature extraction stage, 23 features, including statistical, morphological, frequency domain, histogram and Gray Level Co occurrence Matrix (GLCM) based features are extracted from segmented right and left breast obtained from step 1. To achieve the best features, feature selection methods such as minimum Redundancy and Maximum Relevance (mRMR) Sequential Forward Selection (SFS) Sequential Backward Selection (SBS) Sequential Floating Forward Selection (SFFS) Sequential Floating Backward Selection (SFBS) and Genetic Algorithm (GA) have been used at step 3. Finally to classify and TH labeling procedures, different classifiers such as AdaBoost, Support Vector Machine (SVM) k Nearest Neighbors (kNN) Naive Bayes (NB) and probability Neural Network (PNN) are assessed to find the best suitable one. These steps are applied on different thermogram images degrees. The results obtained on native database showed the best and significant performance of the proposed algorithm in comprise to the similar studies. According to experimental results, GA combined with AdaBoost with the mean accuracy of 85.33% and 87.42% on the left and right breast images with 0 degree, GA combined with AdaBoost with mean accuracy of 85.17% on the left breast images with 45 degree and mRMR combined with AdaBoost with mean accuracy of 85.15% on the right breast images with 45 degree, and also GA combined with AdaBoost with a mean accuracy of 84.67% and 86.21% on the left and right breast images with 90 degree, are the best combinations of feature selection and classifier for evaluation of breast images.
Developments in the diagnosis and treatment of allergic bronchopulmonary aspergillosis
Venue: Expert review of respiratory medicine

Allergic bronchopulmonary aspergillosis (ABPA) is a complex pulmonary disorder characterized by recurrent episodes of wheezing, fleeting pulmonary opacities and bronchiectasis. It is the most prevalent of the Aspergillus disorders with an estimated five million cases worldwide. Despite six decades of research, the pathogenesis, diagnosis and treatment of this condition remains controversial. The International Society for Human and Animal Mycology has formed a working group to resolve the controversies around this entity. In the year 2013, this group had proposed new criteria for diagnosis and staging, and suggested a treatment protocol for the management of this disorder. Since then, several pieces of new evidence have been published in the investigation and therapeutics of this condition.  A non systematic review of the available literature was performed. We summarize the current evidence in the evaluation and treatment of this enigmatic disorder. We suggest modifications to the existing criteria and propose a new scoring system for the diagnosis of ABPA.  All patients with asthma and cystic fibrosis should routinely be screened for ABPA using A. fumigatus specific IgE levels. Glucocorticoids should be used as the first line of therapy in ABPA, and itraconazole reserved in those with recurrent exacerbations and glucocorticoid dependent disease.
New Advances in the Diagnosis and Treatment of Allergic Bronchopulmonary Aspergillosis.
Venue: Zhongguo yi xue ke xue yuan xue bao. Acta Academiae Medicinae Sinicae

Allergic bronchopulmonary aspergillosis is one of major pulmonary fungal diseases. Although it is not a rare in clinical settings,the misdiagnosis rate is high and the treatment effectiveness remains unstable. This article reviews the recent advances in the diagnosis and treatment of this disease.
Hybrid Approach for Prediction of Cardiovascular Disease Using Class Association Rules and MLP

Revised Feb 26, 2016 Accepted Mar 10, 2016 In data mining classification techniques are used to predict group membership for data instances. These techniques are capable of processing a wider variety of data and the output can be easily interpreted. The aim of any classification algorithm is the design and conception of a standard model with reference to the given input. The model thus generated may be deployed to classify new examples or enable a better comprehension of available data. Medical data classification is the process of transforming descriptions of medical diagnoses and procedures used to find hidden information. Two experiments are performed to identify the prediction accuracy of Cardiovascular Disease (CVD).A hybrid approach for classification is proposed in this paper by combining the results of the associate classifier and artificial neural networks (MLP) The first experiment is performed using associative classifier to identify the key attributes which contribute more towards the decision by taking the 13 independent attributes as input. Subsequently classification using Multi Layer Perceptrons (MLP) also performed to generate the accuracy of prediction using all attributes. In the second experiment, identified key attributes using associative classifier are used as inputs for the feed forward neural networks for predicting the presence or absence of CVD.