Miracle-dz/UniFAR-FTUs huggingface dataset:
UTILIZING QUESTIONING TECHNIQUE TO IMPROVE THE STUDENTS’ COMPREHENSION SKILLS ON EXPOSITORY TEXTS

This collaborative classroom action research (CAR) which was assembled in two cycles aimed at describing the implementation of questioning technique in improving the students’ comprehension skills on expository text. The procedures of instruction involve four steps namely (1) explaining and brainstorming; (2) grouping and discussing; (3) leading; and (4) concluding and presenting. The finding which supported by data on the teaching-learning process shows that the percentage of the students who get greater than or equal to 20 point at the first test is 59.5 % and 80 % in the second test. Accordingly, with 70 % of the participants get 20 point in the set-up criteria of success, it concluded that such technique is still outstanding in improving the students’ comprehension skills on expository texts type.
Where Do I Go to Treat Me? Factors That Influence Users’ Behavioral Intention

Medical tourism is a historical phenomenon refers to the travel of persons to a foreign country with the purpose of receiving health-care services, medical treatment, preventive/wellness or clinical surgical (Richard, Melisa & Rupa, 2011; Abubakar & Ilkan, 2016; Misung, Heesup, & Tim, 2012; Moghavvemmi et al., 2017; Skountridaki, 2017; Bookman & Bookman, 2007). Many scholars, in the last years, have explored a new phenomenon has developed, namely, the medical tourism market (Lee & Kim, 2015), consisting in travellers going from developed to developing countries to access medical services at a lower cost (Johnson et al., 2015; Misung et al., 2012; Aydin & Karamehmet, 2017; Connell, 2013; Esiyok, et al., 2017; Moghavvemi et al., 2017; The aim of this paper is to analyze how some specific factors can impact on attitudes towards usage (ATU), and effect on behavioral intention (BI), when the potential medical tourist carries out the medical tourist destination information sourcing process. Specifically, we considered electronic word of mouth communication (eWOM), trust (TRT), perceived usefulness (PU), and perceived ease of use (PEOU). The data were collected from 698 experienced users participating in a tourism thematic Facebook group. The results state that being social media an effective channel to share contents among users, the more expert users are more influenced in the behavioural intention of choosing medical tourism destinations and trust is the variables with the strongest influence on attitude, which affects users’ behavioural intention towards the use of Facebook to find information on medical tourism destination. These results contribute to the scientific debate on users’ behavior in utilizing social media to find information for a medical tourism destination and provide support to the marketing and communication strategies of medical tourism practitioners.
A DFT Study for Eliminating a Water Pollutant by Using an Adsorbent

A pollutant on the water is an azoic dye molecule (adsorbate) within its corresponding ˉO3S active site, and it can be relieved from water using chitosan copolymer molecule (adsorbent) within its active site, which is an ion 3 NH + of ammonia from amino group protonated. After DFT geometry optimization, the reactivity between these two active sites in acidic aqueous solutions can become either neutral acid form or two products (sulfur dioxide SO2 and H2NOH). We infer the kind of adsorption established on the neutral acid form molecule. 345 Introduction Our primary goal in here is to apply DFT to the interaction between chitosan (adsorbent) and azoic dye (adsorbate), through their reaction sites 3 NH + (ion of ammonia from amino group protonated) and ˉO3S (sulfur trioxide ion of sulfonate group) respectively, just to infer possible existing adsorption. This is done first calculating its geometry optimization between 3 NH + and ˉO3S. The reaction among these molecular ions produces sulfamic acid which in zwitterion form 3 3 H NSO + − is more stable than the neutral acid form H2NSO2OH in solid state [1-5]. Physical properties (structural and spectroscopic) and chemical reactions of sulfamic acid have been extensively reviewed [6-8]. The structure of both the zwitterion and neutral form has theoretically been studied previously [9-13]. We study here the neutral acid case as an isomer HSO3NH2. Azo dyes are a class of synthetic dyes which when degraded in the bodies of water can cause the rupture of azo bond of amines, causing many harmful effects in some human organs such as the brain, liver, kidneys, central nervous system and reproductive system. Synthetic dyes also affect the photosynthetic activity of some aquifer’s plants due to the presence of aromatics, metals, chlorides, etc. [14]. The discovery of synthetic dyes has limited the role of natural dyes due to its characteristics such as low production cost, brighter colors, better resistance to environmental factors and easy application. However synthetic dyes can be often highly toxic and carcinogenic [15]. The dyes have become a major source of severe water pollution as a result of the rapid development of many industries that use them in order to colorize their products [16]. Effects described by the pollution of azoic dyes mean a problem that requires attention and treatment. Chitosan is a product of chitin, which is the second most abundant natural polysaccharide in nature. Chitosan can be obtained from partial deacetylation of chitin [17]. Among the many uses of chitosan products are nutraceuticals, food protectors, medical uses, agricultural uses, and many others. Application to water purification is in research. Chitosan is a polymer, its chemical structure as copolymer is drawn in (s 1a), which is the input for applying geometry optimization, and its output can be seen in (Figure 1b). This copolymer chitosan is made up two units: a. β-(1-4)-2-acetamide-2-deoxy-D-glucopyranose b. β-(1-4)-2-amino-2-deoxy-D-glucopyranose.
Aspects of applying theory of human ecology to design safe heat-protective clothing for the disabled people

The article discusses current theoretical and practical issues of scientific research based on the interaction of environmental and technogenic factors in the development of safe heat-protective clothing models for people with restricted motor abilities. In particular, the main results of studying the interaction of elements and objects belonging to the dynamic system «human – habitat – heat-protective clothes» are presented. The purpose of the work was to justify the choice of structural clothing materials with the help of using obtained analytical information on thermal field formation of under clothing space area. The relevance of the described studies is due to the permanently increased demand for special heat-protective products for the disabled and insufficient knowledge of multi factorial environmental processes in spatio-temporal coordinates. The scientific novelty of the presented work consists in solving the problem based on the analysis of the interaction of human lower limbs and heat protective clothing by means of using the author’s mathematical model. To carry out the research, modern mathematical methods were used, including system analysis, synthesis of alternatives, modeling, generalization and results verification. The obtained materials develop the theory of applied areas of human ecology. The implementation of the above stated recommendations in the practice of heat protective clothing design contributes to a process of people’s socialization with restricted motorabilities.
Comparison of the Smith-Waterman and Needleman-Wunsch algorithms for online similarity analysis of industrial alarm floods

Alarm floods are considered to be the major obstacles that prevent the smooth process operations of large-scale industrial facilities. During an alarm flood situation, industrial operators often get confused by too many alarms and thus have difficulties in observing and handling critical alarms. In recent years, sequence alignment based similarity analysis has emerged as an effective way to handle alarm floods. Alarm floods caused by the same fault are very likely to consist of the same group of alarms in a certain sequential order. Conducting realtime sequence alignment of industrial alarm floods can help operators to quickly recall the root cause and make prompt corrective actions. This paper proposes the online similarity analysis of alarm floods based on the Smith-Waterman and Needleman-Wunsch algorithms, and compares their differences and application conditions. Case studies are provided to illustrate the proposed online similarity analysis methods and the differences of the two sequence alignment algorithms.
Coevolutionary history of ERVs and Perissodactyls inferred from the retroviral fossil record

The horse (Equus caballus) is an economically and scientifically important species of mammal. The horse genome (and that of other mammals) contains thousands of sequences derived from retroviruses, called endogenous retroviruses (ERVs). These sequences are highly informative about the long-term interactions of retroviruses and hosts. They are also interesting because they have influenced the evolution of mammalian genomes in various ways. Horses belong to the family Equidae in the order Perissodactyla - comprising 16 extant species of strict herbivores adapted for running and dietary specialisation. This PhD thesis describes my work developing and applying a novel bioinformatics approach for characterising ERVs. I used this approach to characterise ERVs in genomes of Hippomorpha species in relation to those found in a representative of the Ceratomorpha - the white rhinoceros (Ceratotherium simum). Through comparative analysis of these three genomes, I derive a calibrated timeline describing the process through which ERV diversity has been generated in the equine germline. My project has provided an overview of retrotranspositional activity in perissodactyl ERV lineages and identified individual ERV loci that show evidence of involvement in physiological processes and/or pathological conditions. The dataset generated in this project will be of great utility for future studies aiming to investigate the potential functional roles of equine ERVs and their impact on equine evolution.
Data analysis for a set of university student lists using the k-Nearest Neighbors machine learning method

A tool using machine learning which organizes, clean and analyzes data in massive quantities was developed. So that the user can make predictions about different aspects of a list of more than 2000 students, using the k-nearest neighbor machine learning method. Data were obtained from a Colombian university, which has previously it has been cleaned and organized to accommodate the input parameters into a script. The computational tool was written in python from Jupyter notebook. The script is able to perform analysis predictive of the different filters previously chosen for decision raking by the example of marketing, the tool will keep track of financial actions and of the different categories chosen for students at the university, allowing a global analysis and thus choose the best options from all data granted. Among these categories we can classify method of payment, the value paid, what is the method of most commonly used payout by students, individual averages per semester and academic programs, addresses, and academic careers among others.
DETERMINANTS OF ENTREPRENEURIAL PRACTICE AMONG STUDENTS IN NIGERIAN HIGHER INSTITUTIONS OF LEARNING: A STRUCTURAL EQUATION MODEL (SEM) APPROACH

Entrepreneurial practice has been observed to be the bedrock of economic growth and development of any nation. Of course, there are a number of factors that contribute to students inclination towards entrepreneurial practice. As such, the study seeks to examine the effects of entrepreneurship education and family business background on Kaduna State Polytechnics students inclination towards entrepreneurial practice. Cross sectional research designs and simple random sampling technique were utilized. 497 copies of questionnaires were administered to the National Diploma (ND) students of the Kaduna State polytechnics, Kaduna, Nigeria but only 457 were returned representing 91% return rate. Data collected were analysed using Partial Least Square –Structural Equation Model (PLS-SEM). The findings of the study revealed that both entrepreneurship education and family business background have positive significant effect on students inclination towards entrepreneurial practice. It was concluded by the study that entrepreneurship education and family business background contribute majorly to students inclination towards entrepreneurial practice in Kaduna State polytechnics. It was thus recommended that the level of entrepreneurship education in higher institution of learning should be increased as well as involvement of young ones/students by parents/ guardians so as to enhance students’ entrepreneurial practice.
The design and optimisation of a bubble pump for an aqua–ammonia diffusion absorption heat pump

The design and optimisation of a bubble pump for an aqua-ammonia diffusion absorption heat pump i Abstract Energy shortages around the world necessitated research into alternative energy sources especially for domestic applications to reduce the load on conventional energy sources. This resulted in research done on the possibility of integrating solar energy with an aqua-ammonia diffusion absorption cycle specifically for domestic applications. The bubble pump can be seen as the heart of the diffusion absorption cycle, since it is responsible, in the absence of a mechanical pump, to circulate the fluid and to desorb the refrigerant (ammonia) from the mixture. It is thus of paramount importance to ensure that the bubble pump is designed efficiently. Various bubble pump simulation models have been developed over the years, but it was found that none of the existing models served as a good basis for application-specific design. Most of the models constrained too many parameters from the outset which made the investigation of the effects of certain parameters on the bubble pump‟s performance impossible. According to the research, no bubble pump model investigated the effect of such a wide variety of factors including tube diameter, heat flux, mass flux, generator heat input and system pressure on the bubble pump‟s lift height. A simulation model for a bubble pump for integration with a solar-driven aqua-ammonia diffusion absorption cycle was developed. It serves as a versatile design model to optimise the bubble pump for a large variety of conditions as well as changes in parameters. It was achieved by constraining the bubble pump dimensions and parameters as little as possible. A unique feature of this model was the fact that the bubble pump tube was divided into segments of known quality which made the length of the pipe completely dependent on the flow inside the pipe. It also made the demarcation of the flow development inside the tube easier. The model attempted to incorporate the most appropriate correlations for pressurised twophase aqua-ammonia flow. The most appropriate void fraction correlation was found to be
Comparative Genomic Analysis of Recommended Primer Sets for COVID-19 (SARS-CoV-2) Coronavirus Infection Diagnosis Revealed the Best One

Coronaviruses are RNA viruses that can infect humans and animals. The most famous representatives of the genus Betacoronavirus are SARS-CoV, MERS-CoV and the new 2019-nCoV. Today, the task of detecting a new coronavirus is urgent. We carried out a bioinformatics analysis of the available in the literature and recommended by the WHO and the governments of some country’s primer sets for real-time RT-PCR detection. Based on mutational variability of the genome of the closely related SARS-CoV virus, a map of conservative and variable regions was constructed. Two sets of primers were selected that will show themselves in the most efficient way, since they anneal not only to the conservative areas of 2019-nCoV, but also to conservative areas of SARS-CoV genome, therefore, possible mutational variation in the genome of the new coronavirus will not affect the results of the diagnosis of the disease.
Real time mobile based license plate recognition system with neural networks

In this paper, the implementation of localizing and recognizing license plate in real time environment with a neural network using a mobile device is described. The neural networks used in this research are Convolutional Neural Network (CNN) and Backpropagation Feed Forward Neural Network (BPFFNN). Image processing algorithm for pre-processing, localization and segmentation is chosen based on its ability to cope with limited computational resource in mobile device. The proposed license plate localization steps include combination of Sobel edge detection method and morphological based method. Detected license plate image is segmented using connected component analysis (CCA) and bounding box method. Each cropped character is fed into CNN or BPFFNN model for character recognition process. The neural network model was pretrained using desktop computer and then later exported and implemented in Android mobile device. The experiment was conducted in a moving vehicle on selected driving routes. The results obtained showed that CNN performed better compared to BPFFNN in a real time environment.
Thermal and Physicochemical Properties of Some Starchy Foods: Yam (Dioscorea rotundata), Cocoyam (Xanthosoma sagittifolium) and Plantain (Musa paradisiaca)

The thermal and physicochemical characteristics of yam species (Dioscorea rotundata), plantain species (Musa paradisiaca) and cocoyam species (Xanthosoma sagittifolium) were studied. Yam, cocoyam tubers and fingers of plantains were processed into flour for the determination of quality characteristics. The moisture content of the samples ranged from 5.6 - 8.4% with the plantain flour having the lowest value. The protein content of yam was the highest (3.2%) while the plantain flour was the lowest (2.07%) although with the highest carbohydrate content of about 88.34%. Values for ash content ranged between 1.93% and 2.82% with the lowest value obtained for plantain and the highest for cocoyam. The wettability values ranged from 40.67- 106.67secs being highest in the plantain flour. Angle of repose was highest for plantain (35.67 o ). The amylose content was highest in yam (35.92%) while plantain gave the least (25.53%). Cocoyam has the highest solubility at 45 o C and the highest also at 90 o C, the same thing was observed in its swelling power. Yam gave the least value for solubility. Pasting temperature ranged from 48.01 - 49.51 o C with highest in cocoyam flour. Peak time ranged from 4.97 min to 5.15 min while plantain had the highest value. Peak viscosity ranged between 272.47 and 373.87 RVU being lowest for cocoyam and highest for yam flour. The relatively higher pasting temperatures required, and the lower pasting viscosities make cocoyam suitable for producing weaning foods and other products that require low viscosity. Pasting properties of cocoyam revealed relatively higher thermal and mechanical stability which will make it a good ingredient for processed foods, especially those that require thermal sterilization.
Hierarchical foraging movement of humpback whales relative to the structure of their prey

Movement within and between prey patches can influence the fitness of a predator, and understanding such foraging decisions is an important topic in ecology. Most research has found sustained foraging in dense prey patches but has focused on the movement of raptorial predators that feed on single prey items, or suspension-feeders foraging on comparatively immobile zooplankton. The goal of this study was to investigate the fine-scale movement of a suspension-feeding marine vertebrate species while foraging for mobile prey. Using animal-borne tags and surface observations, we analyzed the movement of foraging humpback whales Megaptera novaeangliae within and among acoustically detected patches of sand lance Ammodytes spp. in the water column in the southern Gulf of Maine, USA. Analyzing data from 9 whales tagged between 2008 and 2012, we found hierarchical whale foraging movements that paralleled a complex, hierarchically structured prey landscape. For 7 out of 9 whales, feeding bout scales corresponded to prey patch scales. For 6 out of 9 whales, movement between sequential feeding events was not significantly different from distances between neighboring prey schools. Targeting neighboring schools during sequential feeding events, as opposed to sustained foraging in profitable patches, may increase foraging success in marine suspension-feeders targeting mobile prey, which confirms findings from many other marine predator taxa feeding on mobile prey species. Our study presents novel evidence for the high behavioral plasticity of an intermittent suspensionfeeder targeting mobile prey, adapting its movement to the behavior of its prey and the structure of its prey field.
Effect of Commercial Arbuscular Mycorrhizal Fungi on Growth, Survivability, and Subsequent Landscape Performance of Selected Container Grown Nursery Crops

Abstract This research evaluated the effects of commercially available arbuscular mycorrhizal fungi (AMF) on growth of selected ornamental plant species grown under a nursery-container production system. Subsequent plant survivability and growth in the landscape was also evaluated for two seasons. Acacia greggii, Chilopsis linearis, Diospyros virginiana, Platanus occidentalis, Ipomoea carnea and Plumbago auriculata were inoculated with commercial AMF: EndoNet®, MycorisePro®, or non-inoculated (NonAMF). Platanus occidentalis had a fourth mycorrhizal treatment, which included BioterraPLUS®. EndoNet® and MycorisePro® enhanced growth of C. linearis, I. carnea and P. auriculata during nursery-container production. Growth enhancement of P. occidentalis was significant with BioterraPLUS®, EndoNet® and MycorisePro® compared to NonAMF. During the container phase, greatest colonization (total arbuscules, vesicles/endospores, and intraradical hyphae) occurred with I. carnea and P. auriculata inoculated with EndoNet®.
A Multi-generation Product Diffusion Model with Social Media Effects -Accerelating Effect of Social Media on Leapfrogs and Switches by the iPhone 6 Battery Problem 2016–2017-

This paper proposes a multi-generational model that captures the direct and indirect effects of social media on product diffusion. Direct effects appear in the adoption rate function as covariates, and indirect effects are imbedded in hierarchical models connecting diffusion parameters to successive generations. Unlike previous multi-generational diffusion models, ours forecasts sales of new-generation products before launch using social media as the leading indicator and a hierarchical model connecting successive diffusion parameters. Empirical results show our model forecasts more precisely and reveals how social media influenced sales of smartphones, particularly leapfrogging and switching to other generations and competing products, as Apple contended with defective batteries in the iPhone 6 during 2016–2017.