Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhancement of Employment Satisfaction on Emotional Needs and Work Persistence

The satisfaction factors in this study refer to the factors which influence job satisfaction that meet the emotional needs of teachers towards their tasks. The study identifies how job satisfaction can create work excitement and increase the determination to work hard. The findings of this study are focused on job satisfaction which will have a high impact on emotions in influencing the thinking and action of participants. The discussion covers three main job satisfactions namely: i) job satisfaction from student achievement ii) job satisfaction from administrator action and iii) job satisfaction from colleagues cooperation. This qualitative case study is conducted to ensure that the responsibilities need to be done by teachers should be complemented by job satisfaction and the excellent teaching outcomes can shape the quality students. Data sources were obtained from five excellent teachers as research participants. Two instruments, interview protocols and document analysis were used as tools to collect data. In-depth interviews were conducted to obtain detailed information from the participants. The findings was analyzed descriptive and interpretive based on emerging themes and triangulation techniques were conducted to determine the validity and reliability of the results. The findings show job satisfaction is a requirement that needs to be fulfilled because every individual needs internal satisfaction which can encourage ones to achieve the desired goal. The role of students, administrators and colleagues cooperation are the needs to be given priority as inspiration in improving the commitment of teachers to the task being entrusted. Therefore, this study will provide guidance to teacher education programs to plan and implement teachers' professional development efforts by emphasizing the importance of job satisfaction to produce outstanding teachers.
On conservation laws in teleparallel gravity

Applying directly the Noether theorem in the framework of the Teleparallel Equivalent of General Relativity (TEGR), we construct conserved quantities, currents and superpotentials. They are covariant both under coordinate transformations and under local Lorentz rotations, unlike earlier approaches. This advantage is achieved by a presence in expressions of conservation laws of a displacement vector that can be interpreted as a Killing vector, as a proper vector of an observer, etc. We introduce, as well, a principle for a definition of an inertial spin connection that is an undetermined quantity in TEGR in the original formulation. The new expressions for conserved quantities and the introduced principle are applied to calculate mass for the Schwarzschild black hole and energy density for an observer freely falling in spatially flat Friedmann world.
Pesticide use and impact assessment of SKUAST-K spray schedule on the socio-economic conditions of the people of apple growing region of Jammu & Kashmir

Pesticide use has changed considerably the overall scenario of horticulture over the past few decades throughout the world. It has revolutionised the gamut of horticulture in terms of quality and quantity of produce. Jammu and Kashmir the northern state of the Indian union produces high quality apple that are exported to every nook and corner of the country along with few international borders as well. Pesticide trade has shown a remarkable growth in the valley from past few decades. About 70-80 per cent of populace in the region is involved directly or indirectly with the apple trade be it apple production, transportation, marketing, cold-storage, box-making, packing material, labour and the dealers and sub-dealers of pesticides and fertilizers. The worse part of pesticide business in the region is that from past few years the sub-standard and spurious brands have taken over the market and has reduced production and quality of apple resulting the distress and poverty of apple growers in the region. The only Agricultural University; Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir (SKUAST-K) in the region has framed a spray schedule, but unfortunately, either due to ignorance or lack of extension services, the growers are not fully following the schedule, resulting in losses and huge financial expenses. In this backdrop, the present study was undertaken with an extensive survey of 600 apple growers from the valley comprising of 260 adopters of SKUAST-K spray schedule and 157 non-adopters of spray schedule. Propensity score matching model was employed to get accurate results. In addition, four matching methods were employed to get counterfactual/equally likely match of the adopter and non-adopters in distribution. Results of nearest neighbour method, kernal method, radius method and stratified method, respectively revealed that adopters of spray schedule are at saving side by saving Rs. 1.13/-, Rs. 33717.75/, Rs. 9773.69/and Rs. 11952.90/of money as compared to their controlled group.
EFFECT OF PROFITABILITY, LEVERAGE, AND LIQUIDITY TO THE FIRM VALUE

DOI:10.31933/DIJEFA Abstract: This study aims to determine the effect of profitability (ROA), leverage (DER) and liquidity (CR) on corporate value (PBV) in food and beverage manufacturing companies listed on the Jakarta Stock Exchange. Research Methodology research uses the data panel regression analysis method with the model used is fixed effect. The results of the F test show that profitability (ROA), leverage (DER), and liquidity (CR) adequately explain the influence on firm value (PBV). Result of research show that profitability (ROA) and leverage (DER) have significant effect to company value variable (PBV) while variable of liquidity (CR) has no significant effect to company value variable (PBV). The results of Determination Coefficient Test showed that the proportion influence of profitability, leverage and liquidity to company value was 86%. While the rest of 14% influenced by other variables.
Coral reef benthic assemblages of a Marine Protected Area in eastern Brazil: effect of reef habitats on the spatial pattern of species

ABSTRACT In this study, we recognise the current physiographic characteristics of the Recife de Fora Marine Park (Royal Charlotte Bank, eastern Brazil) and describe the spatial pattern of the benthic community through reef habitats. Benthic assemblages differed from sectors and habitats, showing a marked coastal oceanic gradient. The results indicate that local environmental factors, such as coastal influence, exposure to waves, light radiation, and substrate inclination exert a strong influence on the structure of benthic communities. Seagrass banks predominated in the coastal sector, characterised by calm waters and greater influence of the continent. The reef walls showed high species richness, suggesting the formation of vertical light and temperature gradients. The oceanic sector showed a lower inclination of the substrate and was widely dominated by algae. Patch reefs encompass complementary physical conditions that are equivalent to those presented by other habitats, highlighting their importance with regard to the representation of physical and biological aspects of the local reef system. The main indicating organisms/categories suggest a balance between reef accretion and erosion processes. We emphasise the need for a continuous and standardised monitoring programme in order to understand the drivers of change in the distribution patterns of the communities, as well as to provide subsidies for conservation measures and adaptive management. The Recife de Fora Marine Park provides an interesting case study to explore the biophysical influences on benthic ecology and the dynamics of Brazilian shallow reefs.
A Novel Approach Based on Point Cut Set to Predict Associations of Diseases and LncRNAs

In recent years, more evidence have progressively indicated that Long non-coding RNAs (lncRNAs) play vital roles in wide-ranging human diseases, which can serve as potential biomarkers and drug targets. Comparing with vast lncRNAs being found, the relationships between lncRNAs and diseases remain largely unknown. The prediction of novel and potential associations between lncRNAs and diseases would contribute to dissect the complex mechanisms of disease pathogenesis. associations while known disease-lncRNA associations are required only. In this paper, a new computational method based on Point Cut Set is proposed to predict LncRNA-Disease Associations (PCSLDA) based on known lncRNA-disease associations. Compared with the existing state-of-the-art methods, the major novelty of PCSLDA lies in the incorporation of distance difference matrix and point cut set to set the distance correlation coefficient of nodes in the lncRNA-disease interaction network. Hence, PCSLDA can be applied to forecast potential lncRNAdisease associations while known disease-lncRNA associations are required only. Simulation results show that PCSLDA can significantly outperform previous state-of-the-art methods with reliable AUC of 0.8902 in the leave-one-out cross-validation and AUCs of 0.7634 and 0.8317 in 5-fold cross-validation and 10-fold cross-validation respectively. And additionally, 70% of top 10 predicted cancer-lncRNA associations can be confirmed. It is anticipated that our proposed model can be a great addition to the biomedical research field.
Detecting Accident using Smartphone and detecting vehicle information using RFID Technique

: Now days, road accidents widely happens due to lots of problems like, rush driving, pothole, drunk driving etc. The existing system has lots of issues and problem is that it is totally hardware based application with high cost. So we have proposed a new system that uses smartphone sensing of vehicle dynamics to detect the accident. The given system design can facilitate many traffic safety applications for victims. We have developed an android application that use embedded sensors i.e., accelerometer and gyroscope, to capture differences in centripetal acceleration due to vehicle dynamics. Once any car accident happens then our application will activate and generate alert. If no any respond to the application then it will find nearest hospital and police station using KNN algorithm and then it will automatically send the notification to the nearest police station, nearest hospital and parent. We have also enhanced this project based on IoT Concept using RFID technique to detect the vehicle number plate information for verifying complaint to the police station for further process.
Complete F mitochondrial genomes of the Biwa pearl mussel, Hyriopsis schlegelii: the first report from the species’ native lake in Japan

Abstract We determined two complete mitochondrial sequences of female-transmitted (F) mitogenomes of two Hyriopsis schlegelii specimens from this species’ original habitat, Lake Biwa. The mitogenomes were both 15,951 bp in length, and the gene contents and orders agreed with those of the typical F mitogenome of Hyriopsis. Molecular phylogenetic analysis based on the previously identified 13 partial sequences confirmed that the two mitogenomes both belonged to H. schlegelii and not to a closely related Chinese species, Hyriopsis cumingii. The same analysis revealed that two mitogenomes (HQ641406 and FJ529186) previously published as H. schlegelii and H. cumingii might be misidentified.
Ensemble of online sequential extreme learning machine based on cross-validation

The online sequential extreme learning machine (OS-ELM) was proposed as an evolution of the Extreme learning machine (ELM) in 2006. The learning algorithm can learn data by fixing or changing the size of the chunk (a block of data). Compared with other online algorithms, it has faster training speed, and the generalization performance is better. The proposed ensemble of neural networks further demonstrates that the use of the neural network sets with multiple consensus schemes has a greater improvement over the stability of a single network. The basic idea of cross-validation is to group the original data sets, part of which is to train as the training set and the other part of which is to verify as the test set, so the algorithm can reduce the over-fitting problem of the data to a certain extent, and extract more valid information in the limited data set. In this paper, a new ensemble of online sequential extreme learning machine based on cross-validation (ENOS-ELM) is proposed. Through application of cross-validation and integration to the training stage, the accuracy of the algorithm in classification is further improved.
Phylogenetic relationships of endornaviruses in common bean from the western highlands of Kenya and global sequences

Background: Endornaviruses are non-pathogenic viruses infecting multiple agricultural important crops including legumes, with global distribution. However, there is an absence on the complete genome of endornaviruses from legumes in particular with the subSaharan region. In this study, we report the first complete genomes of PvEV1 and PvEV2, and the evolutionary relationship of these genomes. Methods: Viral symptomatic common beans (Phaseolus vulgaris) showing Bean common mosaic necrosis virus (BCMNV) symptoms from Vihiga county, in the western highlands of Kenya were collected during field survey’s in the region. High throughput sequencing (RNA-Seq) was carried out on total RNA isolated from symptomatic leaf samples. Subsequently, de novo assembly and reference mapping was carried out to obtain the complete genomes of PvEV-1 and PvEV-2. Results: We identified the complete genome of Phaseolus vulgaris endornavirus 1 and 2 (PvEV-1 and PvEV-2) from sub-Saharan Africa (SSA). The average genome size of PvEV-1 was ~13,890 nucleotides (nt) while PvEV-2 was ~14,698 nt, encoding a single open reading frame (ORF). Single ORFs ranged from 4,632 to 4,633 aa in PvEV-1 and from 4,899 – to 4,954 aa in PvEV-2. Both ORFs encoded for the RNA-dependent RNA polymerase (RdRP) gene. The percentage sequence similarity between PvEV-1, PvEV-2 from this study GenBanks sequences was 29 % to 99 %. Bayesian phylogenetic analysis resolved in two well-supported monophyletic clades, with isolates from this study clustering with those from Brazil sequences. Discussion: This study provides the first insights into the evolutionary relationships of PvEV from SSA diverse and contributes towards filling the current knowledge gaps on endornaviruses
Investigation of the Gap Between Patients’ Perceptions and Expectations of Hospital Service Quality

Background: Health care services are costly and complex and provide facilities that significantly affect the economy and quality of life of individuals. In this study, we determined the gap between patients’ expectations and perceptions of hospital service quality to provide reference data for creating strategies to improve health care quality. Methods: In this descriptive cross-sectional study, five private hospitals in Tehran were selected. Using a simple random sampling method, 110 patients were recruited and voluntarily responded to the standard service quality (SERVQUAL) model questionnaire. Data were analyzed by the K-S test, t-test, and paired t-test using SPSS V. 23. Results: The results showed that among the quality of health care components, the highest mean was related to the responsiveness (M=3.89) and the least was related to the tangible dimension (M=3.11). The lowest average quality gap (perceived service and expected service) was seen in the responsiveness dimension (2.96 and 3.28) and followed by reliability (2.66 and 3.90), tangible (2.53 and 3.91), empathy (1.36, 3.19), and assurance dimensions (2.39 and 4.75). Conclusion: The findings revealed a significant difference between the patients’ perceived and expected services, which indicates that the quality of services as perceived by patients was lower than their expectations. According to the findings, the assurance dimension had the greatest gap. To reduce or eliminate the existing gap, it is suggested that hospitals consider strategic and operational planning to improve hospitalization experience‏, quality of medical services, and hospital resources.
The implementation of research based learning and the effect to the student metacognition thinking skills in solving H-irregularity problem

This study aims to develop learning tools based on Learning Based Research and produce learning tools in the form of student worksheets (LKM), learning outcomes tests (THB) and monographs and describe the profile of students’ metacognitive skills. The procedure of this study refers to Thiagarajan’s 4D development model which consists of 4 stages, namely defining, designing, developing, and disseminating. This research is a type of mixed research method which is a multimethod approach. Data collection techniques using test methods, interviews, observation and documentation. Educational research data analysis techniques using quantitative research approaches, data collection techniques are usually carried out with test techniques. While data collection techniques in qualitative research generally use observation techniques, in-depth interviews and documentation. The results showed, after the application of research-based learning, 14% of students were categorized in low-level mathematical metacognition thinking skills, and 34% were categorized as medium-level mathematical metacognition thinking skills and 52% were categorized in high-level mathematical metacognitive thinking skills. The results revealed that the implementation of research-based learning can improve the ability of students’ metacognitive thinking skills in solving H-Irregularity problems.
Pedestrians Detection of Offline Retail Stores Based on Computer Vision

Pedestrian Detection is a sub-task in the object detection due to it plays an important role in video surveillance. This project train model algorithm by using offline retail data and intelligent identification based on the offline retail brand store scene and focuses on the two core personnel of the retail scene-shopping guides and customers. This project detects pedestrian’s localization and their key points by using deep learning and computer vision technologies.
Behavioral Interactions for Food among Two Clones of Parthenogenetic Lepidodactylus lugubris and Sexually Reproducing Hemidactylus frenatus Geckos

Abstract: Lepidodactylus lugubris is an all-female parthenogenetic gecko. This gecko consists of diploid and triploid clones in the tropical and subtropical regions, and Clones A (diploid) and C (triploid) cohabit most islands in Ogasawara, Japan. On some Ogasawara islands, another cosmopolitan, but sexually reproductive, gecko Hemidactylus frenatus coexists with L. lugubris. This situation offers a unique opportunity to examine interactions not only between asexual female clones of L. lugubris but also between L. lugubris and both sexes of H. frenatus. We induced behavioral contests for food in small laboratory enclosures between two individuals of different clone, sex, and species combinations. Clone C interacted with other individuals less frequently and had a lower success in feeding the prey than Clone A and both sexes of H. frenatus. Clone C also showed few aggressive behaviors such as arches, growls, bites, and lunges, and never wrestled with other individuals. This interactive tendency of Clone C helps explain the microdistribution patterns of these sympatric geckos in the field.
An Evolutionary MultiLayer Perceptron Algorithm for Real Time River Flood Prediction

Severe flash flood events give very little opportunity for issuing warnings. In this paper, we approach the automated and real time prediction of river flooding by proposing and evaluating different variations of the conventional Multilayer Perceptron (MLP) machine learning algorithm. Our first approach follows a trial and error attempt to optimize the MLP architecture. The second and third approaches are based on the application of nature inspired evolutionary techniques, namely the Genetic Algorithm (MLP-GA) and the Bat Algorithm (MLP-BA) respectively. The MLP-GA generates an improved MLP configuration and MLP-BA enhances the training method. Our fourth, novel approach (MLP-BA-GA) is based on the application of GA to further optimize both the BA and MLP architecture. When compared with previous work, experiments show improvement in the accuracy of river flood prediction, with significant results for the MLP-BA-GA.
Divergência genética, adaptabilidade e estabilidade produtiva de genótipos de soja sob infecção natural por ferrugem, sem fungicida

The study of genetic diversity assists the breeder in the choice of parents which are more divergent, allowing the exploration of preexisting genetic variability in the parents. The objectives of this chapter were to evaluate the agronomic traits, to determine the genetic diversity between soybean strains and cultivars under natural infection by Phakopsora pachyrhizi and to indicate crosses in soybean for resistance to Asian rust. The experiment was conducted in the 2016/17 crop, at Fazenda Capim Branco, UFU, with 14 soybean genotypes, with 10 lines developed by the UFU Soybean Breeding Program (UFUS 1117-01, UFUS 1117-02, UFUS 1117-03 , UFUS 1117-05, UFUS 1117-06, UFUS 1117-07, UFUS 1117-08, UFUS 1117-09, UFUS 1117-10 and UFUS 1117-11) and 4 cultivars (UFUS 7415, UFUS Riqueza, TMG 801 and BRSGO 7560), in a randomized complete block design with three replicates. It was verified the existence of genetic variability for all traits studied, except for first pod insertion height and plant height at flowering. The genotypes UFUS 1117-01, UFUS 1117-07, UFUS 1117-08, UFUS 1117-09, UFUS 1117-10 showed resistance to Phakopsora pachyrhizi and the traits plant height at maturity, number of empty pods, number of days at maturity and area below the disease progress curve were the major contributors to genetic diversity. The strains UFUS 1117-03 and UFUS 1117-06 were the most divergent, and hybridizations between the following pairs of genotypes are promising for obtaining segregant populations with high genetic variability and resistance to Asian rust UFUS 1117-06 x UFUS 1117-09 ; UFUS 1117-06 x UFUS 1117-08; UFUS 1117-06 x UFUS 1117-01; UFUS 1117-06 x TMG 801; UFUS 111706 x UFUS 1117-10; UFUS 1117-06 x UFUS 1117-07; UFUS 1117-06 x BRSGO 7560.
Understanding Epidemiologic Risks for Infectious Disease Control

As of April 2020, the coronavirus disease 2019 (COVID-19) pandemic has already irreversibly changed our perception of the field of infectious diseases. The first two chapters in this thesis were completed in the pre-2020 era, when we focused on developing tools to inform tuberculosis (TB) control programs in high-burden countries. The last chapter is our quick response to the emerging COVID-19 pandemic, in which we described the disease burden on healthcare resources in cities in China and explored its implication for cities in the United States. One common theme in all three chapters is our focus on epidemiologic risks. In Lima, Peru, can we predict the risk of disease progression among household contacts of TB patients to better their clinical management (Chapter 1)? In India, how can we use information about the distribution of TB risk factors to identify populations who were missed by disease surveillance systems (Chapter 2)? And finally, how to translate experience from one city to another during a pandemic, when the underlying populations have potentially different risk profiles (Chapter 3)? While TB continues to plague our most vulnerable population, knowledge about risk and risk factors for the COVID-19 will start to accumulate. The enclosed three chapters are our exploration of how epidemiologic risks could help with infectious disease control programs.