Miracle-dz/UniFAR-FTUs huggingface dataset:
A Piecewise Parabolic Method for Estimating Key Parameters in a Three-dimensional Internal Tidal Adjoint Model

A higher-order and conservative Piecewise Parabolic Method was proposed to estimate the open boundary conditions (OBCs) in a 3D internal tidal adjoint model. The interpolation quality was verified by twin experiments. The results showed that the PPM can obtain smoother OBCs than the results obtained by Cressman interpolation. In real experiments, compared with the CI results, the PPM results can reduce the magnitude of misfit vector (m) between the simulated results and the observations of the tidal stations by 5 percent. Meanwhile, the PPM results can simulate the M2 tidal constituent in the northern South China Sea (SCS) more accurate than the Cressman results.
Performance Analysis of FISSER Model in Rural-Urban Cognitive Radio Networks

In the past few decades, Cognitive Radio network (CRN) has been regarded in the literature as the most promising technology for performing dynamic spectrum management. One of the major aspects of spectrum management is referred to as the spectrum-reconfiguration decision-making ability of CR users. Dynamic spectrum reconfiguration has previously been reported to improve the spectrum utilisation in CRN. In exploiting spectrum reconfiguration to improve spectrum utilisation, various approaches have been adopted to develop models. However, none of these research works has been evaluated in the urban and rural settlement context. In a CRN environment, the frequency availability is not static like that of traditional networks. There are resource-rich regions such as in rural areas, where many frequencies are available for the Secondary Users (SUs) and resource-poor regions such as urban areas, where there are only a few frequencies available for SUs. Hence, this paper proposed a novel Foraging Inspired Spectrum Selection and Reconfiguration (FISSER) model. The performance of the FISSER model has been analysed through computer simulations both in the rural and urban CRN, using high and low perceptual radii. A high perceptual radius has been shown in the literature to improve energy efficiency and data communication performance in ad hoc networks. However, the simulation results reported in this paper show that even though the high perceptual radius improves the nodes’ energy efficiency it does not achieve optimal data communication performance compared to when the nodes use a low perceptual radius. Also, the efficacy of FISSER model was tested by comparing it against the reinforcement learning model. Based on the obtained results, it was shown that the FISSER model achieved better results in both the network throughput and the channel switching time.
Numerical modelling of point thermal bridge’s impact on the thermal performance of facade systems

Starting with 31 December 2020 all new buildings, as well as existing ones, must comply with the nearly Zero Energy Buildings levels, as defined by each member state. A very important design criteria is the one regarding an accurate assessment of both linear and point thermal bridges of the building envelope. Usually, point thermal bridges are either not considered in calculations or are assessed by using simplified methodology as described by the standard EN ISO 6946/2017. This is due to the modelling and calculation complexity required in assessing them. Therefore, in several situations the impact is underestimated, and the thermal performance results do not offer a clear image of the building’s thermal performance. Thus, the paper focuses on the modelling and simulation of several constructive solutions for façade systems, aiming to identify a correlation between the geometrical and thermal characteristics of fixing components and the thermal performance of the facade. The studied case scenarios include two types of masonry walls, of 240 and 365 mm, that are thermally insulated in various thicknesses using an ETICS system. A sensitivity analysis is also performed to define a correlation between all the components that define the system and the point thermal bridge impact magnitude. The results of the study indicate an increased impact with a direct consequence on the energy performance of the building.
Study the IL6 (C174G) Promoter SNP and Correlation with Physiological Growth Hormone and TNFA levels in Iraqi Subjects with Psoriasis

Background: The chronic inflammatory skin disease with a strong genetic predisposition and autoimmune pathogenic traits is called Psoriasis. Aim: Study the IL6 (C174G) promoter polymorphisms and correlation with growth factor and TNFA activity in patients with psoriasis in Iraqi population. Subjects and Methods: This study is included 40 subjects (24 males and 16 females) with psoriasis at range of age (11-40) years with mean±SD was (29±11) years and divided into two groups. The control group included 20 subjects matched with age and gender of psoriasis group. GH and TNFA levels were estimated by use of ELISA technique. DNA was extracted from whole blood of both groups and PCR-RFLP was used to perform the genotyping analysis. Results: The results suggesting highly significant differences in GH and TNFA levels between psoriasis and control group (p-value< 0.05). The results showing statistical differences (odd ratio) in CC, CG, and GG between psoriasis and control groups. Conclusion: C174G polymorphism in promoter of IL6 gene with increasing in GH and TNFA levels consider a risk factor for incidence of psoriasis in different ages and genders.
The Impact of CALL Software on the Performance of EFL Students in the Saudi University Context

This paper investigates the extent to which Computer-Assisted Language Learning (CALL) contributes academically and pedagogically to the performance of students majoring English as a Foreign Language (EFL). The paper’s main objective is to explore the extent to which CALL is effective in developing the linguistic and communicative competence of EFL students in the skill of reading. This paper uses both quantitative and qualitative approaches in the process of data collection. As an empirical study, the sample in this study was 47 students studying English at Prince Sattam bin Abdulaziz University. The participants were classified into two groups: experimental and control; each of which has been assigned specific reading activities. The experimental group has been allocated technological learning, by means of using the computer programs of Snagit TM , Screencast; whereas the control group has been assigned traditional learning, i.e. without using computer. Results revealed that the use of CALL has more positive effects on the learning outcomes of the experimental group than those pertaining to the control group. This, in turn, accentuates the fact that the use and application of CALL into EFL contexts improves the students’ learning outcomes concerning the skill of reading. The study recommends further integration of computer software into the designation of the different EFL courses. Keywords—CALL; EFL students; Saudi university context; language skills; reading; Snagit TM ; screencast; performance;
An Empirical Study on the Factors Affecting Organic Food Purchasing Behavior in Bangladesh: Analyzing A Few Factors

Organic foods are more attractive to consumers than conventional foods due to technological advancements, health and environmental protection, and nutritional value. Purpose of this research is to uncover some hidden facts about consumers' organic food purchasing habits. This study employs a purposive sampling method to collect 110 records from people who buy organic food in Dhaka, Bangladesh, from various online shops, superstores, and department stores. The use of multivariate analysis, such as factor analysis, is used to understand why people purchase organic food. When it comes to purchasing organic food, the first consideration is health and lifestyle, followed by environmental benefits, product characteristics, perceived quality and price, marketing strategy, and customer confidence. The result of the factor analysis reveals that, three factors are accounted for explaining more than 75 percent variation explanation and scree plot, Horn’s parallel analysis, and Kaiser Criterion assures it. As a result, availability and trust are needed, which can be achieved through appropriate certification and advertising. The findings of this study suggest that, health-related concerns and lifestyle, environmental benefit, perceived price, trust, perceived quality, and marketing strategy all influence consumer behavior. These factors are crucial for triggering their movement in organic food selling shop. As a result, the government, as well as people of all ages, should speak out about the nutritional value, health problems, and product qualities of organic food in order to raise awareness of buying organic food.
Factors Influencing Student Satisfaction towards Distance Learning Apps During the Coronavirus (Covid-19) Pandemic in Malaysia

The latest coronavirus epidemic has witnessed a catastrophic fall in traditional education system and a significant change to app-based learning to maintain learning continuity. The conventional face-to-face teaching approach has been drastically altered with the addition of a new dimension in which student satisfaction is paramount. This current research paradigm is based on the TAM model. Students residing in Klang Valley, Malaysia, obtained a total of 483 data. By deploying SPSS and AMOS version 24.0, the study found self-efficacy as one of the deciding factors of student satisfaction; there is a strong correlation between self-efficacy and satisfaction. Furthermore, perceived usefulness and perceived ease of use are also influenced by self-efficacy. In contrast, perceived ease of use does not affect perceived usefulness, and perceived usefulness does not affect satisfaction. Finally, to increase the level of distance learning during COVID-19 outbreak, recommendations are made to enhance the virtual learning environment.
Analyzing Teacher Competency: Knowledge, Skills, and Aptitude of Secondary School Teachers of Islamabad, Pakistan

Teacher competency is the key to effective and quality teaching. According to the Oxford English Dictionary, competency denotes the ability, skill, and strength of an individual used to perform a given task. In order to ascertain the efficacy of the learning outcomes of any education system, teacher competency is measured using knowledge, skills, and attitude (KSA) model. The current study used the same model to assess teacher competency of the secondary school teachers of Islamabad. Stratified random sampling technique was used to choose the desired sample comprising 100 male and 100 female secondary school teachers teaching in Islamabad. Data were collected through personal visits of the selected schools. A self-developed questionnaire consisting of 20 items was used to collect the data. Data were analyzed using various statistical techniques such as ANOVA and the mean, standard deviation, and Pearson correlation coefficient were also calculated. The findings revealed that there is a strong and positive association among all the determinants of teacher competency, that is, knowledge, skills and attitude. The study also found that female teachers have better teaching competency as compared to male teachers. Moreover, private school teachers showed better teaching competency than public school teachers. The study also revealed that teachers with less than 5 years of experience performed better than their seniors.
Statistical phylogeography: Admixture graphs and sparg

When I introduced the coalescent several weeks ago, I mentioned the “Out of Africa” hypothesis — the hypothesis that anatomically modern humans evolved in Africa and spread from there throughout the rest of the world. Three decades of research have strengthened support for that hypothesis, and it is now widely accepted that anatomically modern human populations left Africa and moved into other parts of the world about 50,000 years ago [3]. As they expanded, they interacted with archaic human populations, e.g., Neanderthals and Denisovans. And when human populations interact, interbreeding often occurs. The result is that 1-3 percent of human genomes from outside of sub-Saharan Africa show evidence of Neanderthal ancestry [10] and that as much as 5 or 6 percent of the human genomes from Oceania show evidence of ancestry from Denisovans [5]. When we visualize these relationships (Figure 1), the result no longer looks like a simple tree. There are lines connecting different branches representing times when there was some degree of interbreeding among populations that had previously diverged. You may have encountered methods for inferring phylogenies in previous courses. In this course we saw how STRUCTURE can be used to estimate patterns of admixture. How do we go about estimating trees that are admixed? Funny you should ask.
LANCET: Labeling Complex Data at Scale

Cutting-edge machine learning techniques often require millions of labeled data objects to train a robust model. Because relying on humans to supply such a huge number of labels is rarely practical, automated methods for label generation are needed. Unfortunately, critical challenges in auto-labeling remain unsolved, including the following research questions: (1) which objects to ask humans to label, (2) how to automatically propagate labels to other objects, and (3) when to stop labeling. These three questions are not only each challenging in their own right, but they also correspond to tightly interdependent problems. Yet existing techniques provide at best isolated solutions to a subset of these challenges. In this work, we propose the first approach, called LANCET, that successfully addresses all three challenges in an integrated framework. LANCET is based on a theoretical foundation characterizing the properties that the labeled dataset must satisfy to train an effective prediction model, namely the Covariate-shift and the Continuity conditions. First, guided by the Covariate-shift condition, LANCET maps raw input data into a semantic feature space, where an unlabeled object is expected to share the same label with its near-by labeled neighbor. Next, guided by the Continuity condition, LANCET selects objects for labeling, aiming to ensure that unlabeled objects always have some sufficiently close labeled neighbors. These two strategies jointly maximize the accuracy of the automatically produced labels and the prediction accuracy of the machine learning models trained on these labels. Lastly, LANCET uses a distribution matching network to verify whether both the Covariate-shift and Continuity conditions hold, in which case it would be safe to terminate the labeling process. Our experiments on diverse public data sets demonstrate that LANCET consistently outperforms the state-of-the-art methods from Snuba to GOGGLES and other baselines by a large margin - up to 30 percentage points increase in accuracy.
COVID-19 infection in health care workers-our experience at the Regional Institute of Medical Sciences, Imphal

Background: COVID-19 is fast spreading not only across country borders but is seen to involve all ages and walks of life. The risk of acquiring the infection is considered to be high especially among the health care givers. The study is to look into the characteristic profile and clinical outcome in the infected Health care workers (HCWs). Method: An observational study was conducted in a cohort of HCWs actively involved in patient care at a tertiary hospital in Northeast India. Results: There were 115 cases of health care workers infected with COVID-19 in our institute over a span of 9 months from March 2020 to November 2020. Among them 59 were doctors, 32 were nurses, 9 were technicians and 15 were orderlies. The median age of our HCWs was 35 years. Most of the infection was from the work environment from the patients or through colleagues. The emergency wing was the most common place of known infection acquirement. The most frequent symptom was fever followed by body ache. The infection was mild to moderate in most cases with only 1 case requiring oxygen therapy and ICU care. There was no mortality. Conclusion: Health care workers are vulnerable group who have an unavoidable high risk to infection. To curb the infection in the absence of an effective treatment is prevention at its best.
Proper asymptotic unitary equivalence in KK-theory and it , s application

A. E. Zakaria. A. A. A. Elmagi Department of Mathematics, Peace University, Sudan, Faculty of Petroleum and Hydrology Engineering Department of Mathematics, University of Holly Quran Wad Medani, Sudan, College of Education Abstract In this paper we generalize the notation constitutive codimension of Brown, Douglas, Hyun Lee, and Fillmore using KK-theory and prove the result which origins that there is a unitary of the form ‘identity+compact’ which gives the unitary equivalence of m projections if the ‘constitutive codimension’ of m projections vanishes for certain C*algebras employing the proper asymptotic unitary equivalence of KK-theory found by M. Dadarlat and S.Eilers. We also apply our result to the projections in the Corona algebra of
Role and Importance of Cardiac Biomarkers in Diagnosis and Prognosis of Feline Arterial Thromboembolism

Feline arterial thromboembolism (FATE) is a common complication of myocardial disease, often having poor prognosis. The purpose of this study is to evaluate the diagnostic and prognostic value of serum levels of cardiac biomarkers (N-terminal prohormone of brain natriuretic peptide [NTproBNP], creatine kinase isoenzyme-MB [CK-MB], and cardiac troponins [cTnI and cTnT] in cats with hypertrophic cardiomyopathy (HCM) that was complicated by FATE. Two groups were constituted in the study. Cats with a diagnosis of HCM were included in group I (n=10) and cats with HCM having acute episodes of FATE were included in group II (n=10). Results of cardiac biomarkers and echocardiographic measurements of left ventricle related parameters were compared between groups. The ratio of left atrium to aorta (P<0.05), fractional shortening (P<0.05), left ventricular dimensions (P<0.05), and stroke volume (P<0.01) were found statistically significant between groups. Serum CK-MB and cTnI levels in group II were higher (P<0.001 and P<0.05 respectively)) than those in group I. Serum levels of cTnI and cTnT were found respectively under 3.0 ng/mL and 0.1 ng/mL in the cats (n=3) which have survived. Our data demonstrate that remarkably elevated serum levels of cardiac biomarkers could be associated with the diagnosis of HCM with acute onset of FATE in cats, however cTnI and CK_MB might have a role in the risk assessment.
A UNIFIED MODEL FOR THE GOVERNING DYNAMICS OF AGRICULTURAL FRONTIER ZONES

1 University at Buffalo Department of Anthropology, 380 Fillmore Academic Center Ellicott Complex, North Campus, Buffalo, NY 14261-0026 716-645-2414, e-mail: cbtrosko@Buffalo.edu, jmwhite2@Buffalo.edu 2 University at Buffalo Anthropology GIS Social Systems Laboratory, 380 Fillmore Academic Center Ellicott Complex, North Campus, Buffalo, NY 14261-0026 716-645-2414. 3 Laboratory of Bedrock Geology, Nature Research Centre, Akademijos 2, Vilnius, 08412, Lithuania, e-mail: lukas.gaizauskas0@gmail.com
THE PREVALENCE OF MASTITIS AND ITS ASSOCIATED RISK FACTORS IN LACTATING DROMEDARY CAMELS IN AND AROUND HARGESA, SOMALI-LAND

In spite of it living in harsh env ronments of semiarid and arid zones, the dromedary camel is able to produce milk in valuable quantity. Camel milk is one of the main components of diet of the nomads in semiarid and arid zones and is an essential food for livelihood of people and it may be the only milk available in the Hargeisa district where other milking animals cannot be maintained. However, like other dairy animals, dromedary camels could be affected by udder infections such as mastitis. A cross sectional study of camel mastitis was conducted on 170 lactating camels from Hargiesa District Somaliland between August to December 2016 to estimate the prevalence and causes of mastitis, as well the risk factors involved on disease. Prevalence of mastitis was assessed by using California mastitis test (CMT). An overall prevalence of camel mastitis was found to be 30.5% (52/170) out of which, 4.7% (8/170), 25.8% (44/170) were clinical and sub-clinical mastitis, respectively. The overall quarter level prevalence was 30.2% (206/680). There was significant (P<0.05) in prevalence between camels with tick infestation, lactation stage, parity and age to mastitis than those without these factors. Microbiological examination of 206 randomly selected CMT positive milk samples from clinical and sub clinical quarters, revealed that the majority of the isolates were coagulase negative Staphylococci (33.6%), followed by Escherichia coli (25.9%) , Streptococcus agalactiae and Streptococcus epidermidis(11%), Micrococcus (6%) and finally Pseudomanas (4.8%). The prevalence of camel mastitis in the study area was found to be significantly high. Therefore, implementation of integrated approaches has great importance in the study sites for the prevention and control of mastitis hence minimizing economic loss and prevents significant public health risks. There was high sensitivity to Gentamicin, and Cloxacillin, and moderate sensitively to Ampicillin/Sulbactam and Trimoxazole and the greatest resistance was found with Tetracycline and Chloramphenicol.
Impact of Referral Bonus on (RHP) referral Hiring Process with Moderating Effect of Organizational Justice: A Case Study of Telecom Companies of Pakistan

The stimulus to carry out this research to find out referral bonus can impact the referral hiring process in the telecom sector of Pakistan. Referral hiring is the phenomenon of hiring practices where the current employee of the organization has referred to the new employee for the recruitment process. According to the current estimation it is observed that more than 50% to 30% employees are recruited with help of the reference of the current employees. This study has taken the organizational justice in the moderation role, to see if an organization is not being fair in paying employees substantial referral bonus amounts, referral bonus types and on timely manner then how it will affect the referral hiring process within an organization. Data was collected from four major telecom companies which are Warid, Zong, Telenor and Ufone. Data was collected from the employees of the company who has been referred by someone or have refer someone in the company. Survey method has been utilized to collect data. After collection of data it was recorded in SPSS 24. In order to analyze data statistical analysis techniques of regression and correlation has been used. Findings indicate the referral bonus timings; referral bonus size and referral bonus types have significant positive impact on referral hiring process. Moreover, results also indicates that if an organization will not do justice in paying employee referral bonuses then it will affect referral hiring process negatively. Findings of this study will be beneficial for the human resource departments of the telecom companies so they can follow these practices and enhance the effectiveness of their referral hiring programs respectively.