Miracle-dz/UniFAR-FTUs huggingface dataset:
Question Analysis and Classification for Question Answering System

Question answering(Q/A) are part of information retrieval (IR) research in which users instead of providing a few keywords to retrieve a set of documents, actually provide complete questions and expect from the QA system to get the most relevant answers(s). This way an efficient Q/A system will be more helpful in providing an accurate answer to a question instead of a query based information retrieval system. No one could have predicted that question answering system would become an indispensable technology for Information Retrieval that would enable the creation of new technologies for information retrieval. The Q/A systems have now been recognized as one of the challenging problem in IR. The task of question classification is one of the most important steps for the efficiency and relevancy of any QA system design. After going through the available literature on the QA systems, we found that there could be different classification of questions. This paper first discusses the general architecture of a QA system and then proposes a more elaborative classification of questions along with some major approaches used for classification in order to design a suitable question answering (QA) system.
Effect of Educational Program on Vulvitis Prevention Among Nursing Students

The aim of this study was to evaluate the effect of educational program on vulvitis prevention among nursing students Research design: A quasi-experimental design was utilized. Setting: This study was conducted at Faculty of Nursing, Benha University. Sample: convenient sample included two hundred and fifty nursing students female all enrolled in first academic years. Tools of data collection1) a structured interviewing sheet to collect data about socio-demographic characteristics, menstrual and gynecological history and knowledge of nursing students regarding vulvitis 2) reported practices assessment 3) modified likert scale for students' attitude regarding vulvitis. Results: there were general improvements regarding students' knowledge, attitude and practice regarding prevention of vulvitis with highly significant (P ≤ 0.001) difference after educational Program. The mother was the main sources of knowledge to students (60%). There was insignificant relation between students' total knowledge, total attitude and total practice scores with their age. Conclusion: The implementation of educational Program significantly improved students’ knowledge, practices and attitude towards prevention of vulvitis. There were positive high statistically significant correlations between students' total knowledge, total practices and total attitude scores after educational Program. Recommendation: Provide students booklets and pamphlet about healthy habits and measures to prevent infection in reproductive system. Replication of the study on a larger sample and in different geographical areas in Egypt is recommended for generalization of findings.
Multi-View Point based Similarity Measure Using Fuzzy-C Means Clustering

Theoretical analysis and scientific illustrations display that Multi-Viewpoint based Similarity, or MVS is possibly more suitable for written text records than the well-known cosine similarity. Depending on MVS, two requirements features, IR and IV, and their specific clustering techniques, MVSC-IR and MVSC-IV, have been presented. In contrast to other state-of-the-art clustering techniques that use different types of likeness evaluate, on a huge variety of papers, data sets and under different assessment analytics, the proposed algorithms display that they could offer significantly improved clustering efficiency. In this paper we propose to develop efficient and effective clustering algorithm for processing similar type of data items in application framework based on related topics present in processed data sets. Our experimental results show efficient and communication related to application development in real time processes.
Evaluation of filtering techniques to increase the reliability of weather forecasts for ground-based telescopes

In this contribution we evaluate the impact of filtering techniques in enhancing the accuracy of forecasts of optical turbulence and atmospheric parameters critical for ground-based telescopes. These techniques make use of the data continuously provided by the telescope sensors and instruments to improve the performances of real-time forecasts which have an impact on the telescope operation. In previous works we have already shown how a mesoscale high-frequency forecast (Meso-NH and Astro-Meso-Nh models can produce reliable predictions of different atmospheric parameters and the optical turbulence. The mesoscale forecast has an advantage on the global model in having a better implementation of the physical atmospheric processes, including turbulence, and produces an output with greater spatial resolution (up to 100m or beyond). Filtering techniques that make use of the real-time sensor data at the telescope may help in removing potential biases and trends which have an impact on short term mesoscale forecast and, as a consequence, may increase the accuracy of the final output. Given the complexity and cost of present and future top-class telescope installations, each improvement of forecasts of future observing conditions will definitely help in better allocating observing time, especially in queue-mode operation, and will definitely benefit the scientific community in medium-long term.
Usability Evaluation of Mobile Weather Hazard Alert Applications

Cell phones enable us to receive and respond to critical incidents, such as: severe storms, tornadoes, and flash floods. However, due to the small display size of cell phones, and regardless of simplified symbols or alert messages, it is possible to overlook users’ ability to interact with the available features and understand the messages in a timely manner. Untrained and trained users of the Weather Radio application participated in an experiment to perform three search tasks; (task 1: location search, task 2: alert settings, and task 3: map settings). In task 4, they evaluated two types of weather alert messages: original National Weather Service (NWS) messages vs. filtered (proposed) messages. By recording users’ completion time on the search tasks, the results showed that the time of the typing in text bar method for task 1 was significantly less than the pin on map method, while much more time was required to complete tasks 2 and 3 by the untrained users compared to the trained users. It was also revealed that the proposed messages were more effective than the original messages by both user groups. This research of user-centered designs provides a foundation to support the designs of time-critical mobile alert systems.
Optimized Kernel Extreme Learning Machine for Myoelectric Pattern Recognition

Myoelectric pattern recognition (MPR) is used to detect user’s intention to achieve a smooth interaction between human and machine. The performance of MPR is influenced by the features extracted and the classifier employed. A kernel extreme learning machine especially radial basis function extreme learning machine (RBF-ELM) has emerged as one of the potential classifiers for MPR. However, RBF-ELM should be optimized to work efficiently. This paper proposed an optimization of RBF-ELM parameters using hybridization of particle swarm optimization (PSO) and a wavelet function. These proposed systems are employed to classify finger movements on the amputees and able-bodied subjects using electromyography signals. The experimental results show that the accuracy of the optimized RBF-ELM is 95.71% and 94.27% in the healthy subjects and the amputees, respectively. Meanwhile, the optimization using PSO only attained the average accuracy of 95.53 %, and 92.55 %, on the healthy subjects and the amputees, respectively. The experimental results also show that SW-RBF-ELM achieved the accuracy that is better than other well-known classifiers such as support vector machine (SVM), linear discriminant analysis (LDA) and k-nearest neighbor (kNN).
Prognostic Value of CD133 and SOX2 in Advanced Cancer

Background The prognostic value of CD133 and SOX2 expression in advanced cancer remains unclear. This study was first conducted to investigate the association between CD133 or SOX2 positivity and clinical outcomes for advanced cancer patients. Methods Hazard ratios (HRs) with 95% confidence intervals (95% CIs) were calculated to evaluate the correlation between CD133 or SOX2 positivity and overall survival (OS), disease-free survival (DFS), progression-free survival (PFS), cancer-specific survival (CSS), or recurrence-free survival (RFS) from multivariable analysis. Trial sequential analysis (TSA) was also performed. Results 13 studies with 1358 cases (CD133) and five studies with 433 cases (SOX2) were identified. CD133 positivity was correlated with worse CSS and OS, but there was no correlation between CD133 positivity and DFS. SOX2 positivity was associated with poor DFS and RFS but was not linked to PFS. Stratified analysis by study source showed that only CD133 positivity can decrease OS for Chinese patients. Stratified analysis by treatment regimens indicated that CD133 positivity was linked to poor OS in patients treated with adjuvant therapy. TSA showed that additional studies were necessary. Conclusions CD133 and SOX2 might be associated with worse prognosis in advanced cancer. More prospective studies are strongly needed. Impact CD133 and SOX2 may be promising targeted molecular therapy for advanced cancer patients.
Semi Supervised Graph Based Keyword Extraction Using Lexical Chains and Centrality Measures

This paper presents keyword extraction using lexical chains and graph centrality measures, derived from the semantic similarity of the words by analysis of the graphical network created using WordNet. The hypothesis is presented using a small-world approach where every paragraph in a document is constrained to a local point, while the document in all is centered on a global concept. Creating lexical chains for each paragraph and combining the best via scoring methods and graph based algorithms, we present parallels to baseline system to extract the keywords from the document.
Design and programming of a coprocessor for a RISC-V architecture

class RoCC(implicit p: Parameters) extends CoreModule()(p) { val io = new RoCCIO } // define a black-box module class Coprocessor(implicit p: Parameters) extends BlackBox { val io = new Bundle{ val clock = Clock(INPUT) val reset = Bool(INPUT) val io = new RoCCIO()(p) } def connect(clk : Clock, rst : Bool, rocc : RoCCIO) = { io.clock := clk io.reset := rst rocc <> io.io } } // define a wrapper module that uses the black-box coprocessor class CoprocessorExample(implicit p: Parameters) extends RoCC()(p){ val box = Module(new Coprocessor()(p)). connect(clock, reset, io) } Figure C.5. Definition of the black-box coprocessor. In order to use the black-box coprocessor, a new configuration is needed instantiating the “CoporcessorExample” class module. To do so two different configuration classes are added, one in /src/main/scala/coreplex/Configs.Scala, used to define the coprocessor map, the other in /src/main/scala/rocketchip/Configs.Scala to specify a global configuration of the SoC for the use of the black-box coprocessor. The first configuration is shown in figure C.6, while the global configuration
Contact-Less Real-Time Monitoring of Cardiovascular Risk Using Video Imaging and Fuzzy Inference Rules

Conventional methods for measuring cardiovascular parameters use skin contact techniques requiring a measuring device to be worn by the user. To avoid discomfort of contact devices, camera-based techniques using photoplethysmography have been recently introduced. Nevertheless, these solutions are typically expensive and difficult to be used daily at home. In this work, we propose an innovative solution for monitoring cardiovascular parameters that is low cost and can be easily integrated within any common home environment. The proposed system is a contact-less device composed of a see-through mirror equipped with a camera that detects the person’s face and processes video frames using photoplethysmography in order to estimate the heart rate, the breath rate and the blood oxygen saturation. In addition, the color of lips is automatically detected via clustering-based color quantization. The estimated parameters are used to predict a risk of cardiovascular disease by means of fuzzy inference rules integrated in the mirror-based monitoring system. Comparing our system to a contact device in measuring vital parameters on still or slightly moving subjects, we achieve measurement errors that are within acceptable margins according to the literature. Moreover, in most cases, the response of the fuzzy rule-based system is comparable with that of the clinician in assessing a risk level of cardiovascular disease.
Social and demographic characteristics of e-learning distance students at university

This paper presents the results of a survey of the social and demographic characteristics of university students involved in distance education. Data were collected in 2012–2014 using a specific questionnaire from 4848 distance students of Modern University for the Humanities (Russia). The analysis of data reveals that the average age of distance students (26–35) tends to increase, which is obviously related to the demographic trends of the population of Russia. The proportion of married students and those having children also grows (more than 50%). The proportions of students by sex is approximately equal. The most students (over 70%) have a full time job. About a quarter of employed students have jobs in the army, police, fire or emergency services. The number of state and municipal employees is also increased. The living location for first-year students in 2012 was roughly equal between big sities, medium-sized towns and small settlements. But in recent years there has been decline of the number of students from smaller communities (village, etc.). Parents of enrolled students are most often workers, military or police personnel, engineers, trade staff, state or municipal employees, staff in education or medicine. Only a fifth of the mothers and one-third of fathers have a college or university degree. So, the parents of distance education students have lower educational status than parents of full-time students. This study provides evidence that distance education is important for social mobility. The proportion of students whose families have incomes higher than the average increase, perhaps because distance education (which is paid) has become less accessible for lowincome families. The study showed the educational intentions of students: about 48% wish to have a bachelor’s degree, about 29% want to achieve master’s degree (also mentioned are other levels of qualification). About 80% of students after graduation intend to work according to the acquired education. The results are discussed in comparison to previous studies. The findings are considered within the context of the current situation in Russian economy.
Survey of Analytical Methods for Big Data of Quality Inspection

Big data of quality inspection is consist of structured data, semi-structured data and unstructured data. It brings great challenge for data analysis as the features of huge volume, various types, high timeliness and low value density. This paper introduced the research status of semantic analysis technology based on depth learning, migration learning algorithm based on depth neural network, reinforcement learning algorithm based on depth neural network and visualization analysis from the characteristics of quality inspection data. The existence problems are analyzed and the research direction is looking forward of the on data analysis in this paper.
The CONSORT extension for Stepped-Wedge Cluster Randomised Trials: baseline assessment of reporting quality -and assessment of inter-rater reliability using a crowd-sourcing systematic review

The Consolidated Standards Of Reporting Trials (CONSORT) extension for the randomised (SW-CRT) is a recently published reporting guideline for SW-CRTs. We assess the quality of reporting of a recent sample of SW-CRTs according to the 26 items in the new guideline using a novel crowd sourcing methodology conducted independently and in duplicate, with random assignment, by 50 reviewers. We assessed reliability of the quality assessments, proposing this as a novel way to assess robustness of items in reporting guidelines. Several items were well reported. Some items were very poorly reported, including several items that have unique requirements for the SW-CRT, such as the rationale for use of the design, description of the design, identification and recruitment of participants within clusters, and concealment of cluster allocation (not reported in more than 50% of the reports). Agreement across items was moderate (median percentage agreement was 76% [IQR 64 to 86]). Agreement was low for several items including the of trial why trial ended stopped for
Seasonal changes of commercial traits, proximate and fatty acid compositions of the scallop Flexopecten glaber from the Mediterranean Sea (Southern Italy)

This study provides information on biological (gonadosomatic index), commercial quality (condition index and meat yield) and biochemical aspects (proximate composition, fatty acids) of the soft tissues of Flexopecten glaber reared in suspended cages in the Ionian Sea. The results showed that condition index (CI) and meat yield (MY) peaked in December (60 and 30%, respectively) and in April, May and June (from 53 to 60% for CI and from 34 to 36% for MY). Gonadosomatic index showed three main peaks in winter, spring and summer months. Contents of protein 8.18–11.9 g/100 g), lipid (0,.78–1.18 g/100 g) and carbohydrate (1.19–3.30 g/100 g) varied significantly during the study period. Saturated fatty acids was the dominant group, except in December when polyunsaturated fatty acids showed the highest proportion (43% of total FAs). Fatty acids of the n3 group were dominant with docosahexaenoic and eicosapentaenoic acids. Highest n3/n6 ratios were recorded in spring-summer specimens, with values > of 5. The results showed a better nutritional quality of scallops in May, July and December.
Development, feasibility and acceptability of a gamified cognitive DEvelopmental assessment on an E-Platform (DEEP) in rural Indian pre-schoolers – a pilot study

ABSTRACT Background: Assessment of cognitive development is essential to identify children with faltering developmental attainment and monitor the impact of interventions. A key barrier to achieving these goals is the lack of standardized, scalable tools to assess cognitive abilities. Objective: This study aimed to develop a tablet-based gamified assessment of cognitive abilities of 3-year-old children which can be administered by non-specialist field workers. Methods: Workshops among domain experts, literature search for established and gamified paradigms of cognitive assessments and rapid review of mobile games for 3-year-old children was done to conceptualize games for this study. Formative household visits (N = 20) informed the design and content of the games. A cross-sectional pilot study (N = 100) was done to assess feasibility of the tool and check if increasing levels of difficulty and the expected variability between children were evident in game metrics. In-depth interviews (N = 9) were conducted with mothers of participating children to assess its acceptability. Results: Six cognitive domains were identified as being integral to learning – divided attention, response inhibition, reasoning, visual form perception and integration and memory. A narrative, musical soundtrack and positive reinforcement were incorporated into the tool to enhance participant engagement. Child performance determined level timers and difficulty levels in each game. Pilot data indicate that children differ in their performance profile on the tool as measured by the number of game levels played and their accuracy and completion time indicating that it might be possible to differentiate children based on these metrics. Qualitative data suggest high levels of acceptability of the tool amongst participants. Conclusions: A DEvelopmental assessment on an E-Platform (DEEP) has been created comprising distinct games woven into a narrative, which assess six cognitive domains, and shows high levels of acceptability and generates metrics which may be used for validation against gold standard cognitive assessments.
Treatment with new organic nitrites in pulmonary hypertension of acute experimental pulmonary embolism

Acute pulmonary embolism may cause right heart failure due to increased pulmonary vascular resistance and arterial hypoxemia. Effective vasodilator therapy of the pulmonary hypertension is highly needed. Therefore, we investigated the effects of a newly developed effective pulmonary vasodilator, the organic mononitrites of 1,2‐propanediol (PDNO), in a rabbit model of acute pulmonary embolism. In anesthetized and ventilated rabbits, systemic and pulmonary hemodynamics, exhaled nitric oxide (NO), plasma nitrite concentration, and blood gases were monitored. First, dose–response experiments with intravenous and left heart ventricle infusions of PDNO and inorganic nitrite were done in naive animals and in pulmonary hypertension induced by a thromboxane A2 analogue. Second, acute pulmonary embolism was induced and either PDNO or placebo were administered intravenously within 20 minutes and evaluated within 1 hour after pulmonary embolization. PDNO intravenously, in contrast to inorganic nitrite intravenously, increased exhaled NO and counteracted pulmonary hypertension and vasodilated the systemic circulation, dose‐dependently, thereby showing efficient NO donation. Pulmonary embolization induced pulmonary hypertension and gas exchange disturbances. PDNO significantly decreased and normalized pulmonary vascular resistance and the right ventricle rate‐pressure product, without causing tolerance, with no significant side effects on the systemic circulation, nor on blood‐gas values or on methemoglobin formation. In conclusion, PDNO is a NO donor and an efficient vasodilator in the pulmonary circulation. Treatment with this or similar organic nitrites intravenously may be a future option to avoid right heart failure in life‐threatening acute pulmonary embolism.