Miracle-dz/UniFAR-FTUs huggingface dataset:
The IMproving Primary Screening And Colposcopy Triage trial: human papillomavirus, cervical cytology, and histopathologic results from the baseline and 1-year follow-up phase

BACKGROUND: An increase in human papillomavirus test volumes is expected in the near future because human papillomavirus e based screening protocols are expected to become more widely adopted. OBJECTIVE: The IMproving Primary Screening And Colposcopy Triage trial, a prospective, multicenter, US-based cervical cancer screening trial, was conducted to obtain US Food and Drug Administration approvals for the new, high-throughput cobas human papillomavirus (cobas HPV) test for use on the cobas 6800/8800 Systems (cobas HPV) for detecting cervical precancerous and cancerous cells (cervical intraepithelial neoplasia of grade 2 or worse and grade 3 or worse). Here, the baseline demographics, human papillomavirus test results, cervical cytology, and histopathologic results are presented. In addition, the baseline and 1-year risks of cervical intraepithelial neoplasia grade 2 or worse and grade 3 or worse associated with the human papillomavirus results are reported. routine liquid-based cytology and 2 polymerase chain reaction e for high-risk human papillomavirus high-risk human papillomavirus by either of the 2 human papillomavirus tests, and a random subset of women according to the Papanicolaou cytology and the 2 human papillomavirus tests referred for a colposcopy and cervical biopsy. follow-up phase. Veriﬁcation bias-adjusted cervical disease prevalence and risks and 95% conﬁdence intervals were computed. RESULTS: The prevalence of atypical squamous cells of undetermined signiﬁcance and worse than atypical squamous cells of undetermined signiﬁcance cytology were 6.5% and 3.2%, respectively. Prevalence of high-risk human papillomavirus, human papillomavirus 16, and human papillomavirus 18 based on the new cobas HPV test were 15.1%, 3.1%, and 1.4%, respectively. Both cytologic abnormalities and human papillomavirus positivity declined with increasing age. Among women who had a colposcopy and biopsy, the prevalence of cervical intraepithelial neoplasia grade 2 or worse and grade 3 or worse were 8.8% and 3.6%, respectively. The baseline and 1-year cumulative risks for cervical intraepithelial neoplasia grade 3 or worse were 13.6% and 16.9%, respectively, among women who tested positive for human papillomavirus 16. Women who tested negative for human papillomavirus had the lowest 1-year cumulative risk for cervical intraepithelial neoplasia grade 3 or worse (0.06%). CONCLUSION: The contemporary, age-speciﬁc prevalence of human papillomaviruses (including human papillomavirus 16 and 18), cytologic abnormalities, and cervical intraepithelial neoplasia in a large, US-based cervical cancer screening population provides benchmarks for healthcare policies, screening programs, and for laboratories and clinicians.
Environmental effect of the Coronavirus-19 determinants and lockdown on carbon emissions

BACKGROUND AND OBJECTIVES: Coronavirus-19 has affected carbon emissions, which was declared as a pandemic by World Health Organization. Unprecedented environmental effects are being caused by Bangladesh's strict lockdown policies, which were implemented to stop the spread of Coronavirus-19. However, it is still unclear how the temporary halting and restart of industrial and commercial activities will affect the environment. In this study, it has been identified how Coronavirus-19 determinants like lockdown, daily confirmed cases, and daily confirmed deaths affect greenhouse gases. METHODS: From March 18, 2020 to February 4, 2022 the data series is used for Bangladesh. To ensure that the data series were stationary, the Augmented Dickey-Fuller and Phillips-Perron tests were utilized. Johansen co-integration test was utilized to determine co-integration among variables. The Granger causality test was utilized to identify directional causes and effects between Coronavirus-19 determinants and carbon emissions and the Vector Error Correction Model was employed to determine short-run and long run connections. FINDINGS: The study finds a bidirectional relationship between lockdown, carbon emissions and daily confirmed deaths, while a unidirectional association exists among Coronavirus-19 confirmed cases according to the Vector Error Correction Model. The Granger causality test also established the relationship between variables, except for daily confirmed cases. The pandemic's onset and subsequent lockdown resulted in decreased carbon dioxide emissions. The short-run link of carbon dioxide emissions with newly confirmed cases was corroborated by the directional relationship of variables, whereas there was a long-term and short-term association between confirmed deaths and lockdown. CONCLUSION: The reduction in carbon emissions during the pandemic will not be long-lasting because it is anticipated that global economic activity will gradually return to the preCoronavirus-19 state. The directional and relational nature of lockdown offers the potential to connect carbon dioxide emissions to regular lives. During a lockdown, there is a connection between the atmosphere's changes and how natural organisms behave. Importantly, there is a room for investigation into how communities of organisms and the atmosphere would function without humans. The essential point is to stress that during the lockdown, the ecosystem is self-healing. Environmental activists and business people will find this study useful in developing future sustainable improvement strategies.
Implementation of Flipped Learning Classroom in Academic Context of Higher Education

: The article deals with the issues based on implementation of flipped learning classroom in academic context of higher education. The “Flipped” learning approach is becoming increasingly popular not only in schools, but also in universities. It creates opportunities for solving complex pedagogical problems in education. Since, on the one hand, the teacher can work individually with students with different levels of education, who are representatives of different cultures. So, on the other hand, it allows the teacher to organize the joint work of students on projects in the classroom by groups artificially created by him, from students of different cultures and levels of education.
AN INVESTIGATION OF SELF-EFFICACY AND PERCEIVED BENEFIT BELIEFS REGARDING DISTANCE EDUCATION OF PRESERVICE TEACHERS AS FUTURE IMPLEMENTERS GELECEKTEKİ UYGULAMACILAR OLARAK ÖĞRETMEN ADAYLARININ UZAKTAN EĞİTİME YÖNELİK ÖZ YETERLİK VE YARAR ALGILARI ÜZERİNE BİR ARAŞTIRMA

The current study aims to explore self-efficacy and perceived benefit beliefs of preservice teachers regarding distance education according to their experiences as future implementers of distance education from an undergraduate distance education course they received. A case study was employed including both quantitative and qualitative data collection methods. The participants of the current study were 143 preservice teachers who had completed a distance education course during their undergraduate program at a university in Turkey. Quantitative data were collected through two, five-point, Likert-type scales, with one that assessed self-efficacy towards distance education and one that assessed perceived benefit beliefs regarding distance education. Qualitative data were collected through an open-ended questionnaire. Descriptive statistics results from the scale data revealed that the mean scores for the constructs of self-efficacy and perceived benefit of distance education ranged from 3.66 to 4.07. Correlation analysis results indicated that the preservice teachers’ self-efficacy towards distance education was significantly related to their perceived benefit from distance education, r = . 56, p < . 01. The preservice teachers mentioned positive aspects of their distance education course under (1) Contribution of the course to the preservice teachers’ knowledge and skills development for technology integration, (2) Contribution of the course to the preservice teachers’ knowledge and skills development for designing effective distance education, (3) Positive features of the distance education course, and (4) Positive features of distance education in general. The preservice teachers stated negative aspects under (1) Issues related to common course components, and (2) Issues related to technology. The research results and implications are presented and discussed within this study.
Decreasing household food waste: A study of food waste interventions

Households play an important role in the problem of food waste. Unfortunately, there is little evidence as to which possible interventions to reduce the amount of food wasted by households can be successful and which possible interventions do not work. Past efforts to decrease the amount of food wasted by households in the Netherlands have not had significant long-term effects. The objective of this study is to investigate the potential of possible interventions to reduce household food waste. A System Dynamics model has been developed to capture the feedback mechanisms in the system. The model represents different phases in which food waste may be generated: planning, purchasing, storing, preparing, consuming, and re-using leftovers. The results show that influencing food waste in one phase has a limited effect on the total amount of food wasted and that combinations of interventions can strengthen or weaken each other. The model shows that it is important to use combinations of interventions to address both the knowhow of a household about food waste and their willingness to reduce food waste. on food spoilage, 3) an intervention avoiding discounts on food, and 4) an intervention improving the awareness about food waste. Applying interventions to reduce food waste results in adding temporary feedback loops in the model. The model results show that none of the individual interventions has a large impact on the reduction of household food waste.
Open Research Online Academic and social integration of international and local students at ﬁve business schools, a cross-institutional comparison

An increasing number of students choose to study at a university in a foreign country. A common belief among educators is that international students are insufficiently academically adjusted. Recent research has found a mixed picture on whether international students underperform in academic integration and academic performance. Therefore, Morrison et al. (2005) argue that research should extend its focus to understanding the underlying reasons for these performance differences of international versus local students . In a cross-institutional comparison among 871 students of five business schools, we investigated the differences in academic and social integration amongst local and international students. International students value their faculty and educational system more than local students. However, international and local students have limited social contact with each other and spend their private time differently. Finally, students with a non-Western background are less integrated than Western students, have considerable lower academic and social integration scores and have (marginally) lower GPA and ECTS scores. Institutes with small classes and collaborative learning settings seem to provide a more favourable learning environment for international students.
DMSO_A_286334 487..495

Serviço de Endocrinologia, Diabetes e Metabolismo do Centro Hospitalar Universitário de São João, Porto, Portugal; Departamento de Cirurgia e Fisiologia, Faculdade de Medicina da Universidade do Porto, Porto, Portugal; Serviço de Endocrinologia do Instituto Português de Oncologia do Porto, Porto, Portugal; Serviço de Patologia Clínica do Centro Hospitalar Universitário Cova da Beira, Covilhã, Portugal; Faculdade de Ciências da Nutrição e Alimentação da Universidade do Porto, Porto, Portugal; Investigação e Inovação Em Saúde (I3s), Faculdade de Medicina da Universidade do Porto, Porto, Portugal Purpose: We aimed to evaluate the association between vitamin D status and hepatic function parameters and scores: Fatty Liver Index (FLI, predictor of hepatic steatosis) and BARD (BMI, AST/ALT ratio and DM, predictor of hepatic fibrosis) in patients with morbid obesity. Patients and Methods: Cross-sectional study including patients with morbid obesity followed in our centre between January 2010 and July 2018. Patients with missing vitamin D levels or hepatic profile parameters were excluded. We divided the population according to two cut-offs of vitamin D levels (12ng/mL and 20ng/mL). Results: The included population (n=1124) had an average age of 43.3±10.7 years and 84.3% were female. Seventy-point eight percent of the population had vitamin D levels lower than 20ng/mL and 34.8% lower than 12ng/dL. Patients with lower vitamin D levels (<12ng/mL) had higher BMI, hip and waist circumferences and higher prevalence of hypertension. Higher FLI scores [OR= 0.77 (0.07), p<0.01] and ALP levels [β= −0.03 (−0.06, −0.01), p<0.01] associated to lower vitamin D levels. Conclusion: Vitamin D deficiency is associated with a higher risk of hepatic steatosis in individuals with morbid obesity. Correction of vitamin D deficiency may have a beneficial role in the management of NAFLD in patients with morbid obesity.
Sample Augmented Sample Sampling Contextual Embedding Task Output Update Policy to Maximize Rewards “ Difficult ” “ Not too Different ” Augmentations : probability : magnitude Augmentation Policy

The practice of data augmentation has been extensively used to boost the performance of deep neural networks for various NLP tasks. It is more effective when only a limited number of labeled samples is available, e.g., low-data or classimbalanced regimes. Most current augmentation techniques rely on parameter tuning or inherent randomness; hence, their effectiveness largely varies on the tasks. To efficiently find the best augmentation strategy for each task, learning data augmentation policy is a promising solution, but the question of what makes a good augmentation in NLP tasks and how to design the reward function for learning a good policy remains under-explored. To answer this, we hypothesize that good data augmentation should construct more diverse and challenging samples for providing informative training signals, while avoiding the risk of losing the semantics of original samples. Therefore, we design a novel reward function for updating the augmentation policy to construct difficult but not too different samples (DND). Particularly, we jointly optimize a data augmentation policy while training the model, to construct the augmented samples with low confidence but a high semantic similarity with original ones. In addition, we introduce a sample re-weighting scheme to focus on difficult augmented samples after the original ones are learned confidently for more effective learning from the augmented ones. Our learning-based augmentation outperforms the recent state-of-the-art augmentation schemes on various text classification tasks and GLUE benchmark by successfully discovering the effective augmentations for each task. Remarkably, our method is more effective on the challenging low-data and class-imbalanced regimes, and the learned augmentation policy is well-transferable to the different tasks and models.
Design, Simulation and Comparative Analysis of Novel Nine Level Symmetrical Multilevel Inverter with Improved THD and Reduced Number of Switches for Power Quality Improvement

The multilevel inverters have several key applications in the industry, transportation, defence, nuclear and space research, etc. including high voltage DC transmission. A novel topology of the multilevel inverter with improved parameters is proposed in this paper. The parameters considered here for comparison with conventional multilevel inverter are number of switches, total harmonic distortion and power loss. The topology results in a three phase nine level multilevel inverter incorporating twenty-four switches with twelve DC sources which have been less than the conventional inverter circuit arrangements like Diode Clamped Multilevel Inverter, Flying Capacitor Multilevel Inverter including Conventional Cascaded H Bridge MultilevelInverter. A Selective Harmonic Mitigation strategy has been utilized for eliminating low order harmonics along with minimal power loss in the switches thus resulting in total harmonic distortion less than 7%. At any given time only three switches are operating with lower switching frequency such that heat loss in the switches get reduced. The comparative analysis of proposed topology with performing successful simulation is described in the paper. Circuit simulation results of proposed novel topology have also discussed.
An improved event-by-event clustering algorithm for noisy acquisition

Event-based image sensors are a new class of sensors developed thanks to non-uniform sampling and asynchronous technology, which overcomes many image sensor limitations such as a high throughput or a huge power consumption. As their behavior and outputs are really different from traditional image sensors, the produced data stream imposes to completely rethink image processing. Indeed, dedicated algorithms are mandatory to take advantage of this specific data stream, known as Address Event Representation (AER). This paper presents an improved and dedicated event-by-event clustering algorithm allowing the object detection in a noisy environment which is still performant with a SNR of 1/4. We measure high recall and precision for different simulated scenarios with multiple objects and show an improvement compared to the previous algorithm. The approach especially demonstrates a low computational complexity and a reduced memory footprint, which is perfectly suited for low-cost and low-power embedded image sensing applications.
Analysis of Software Bug Prediction and Tracing Models from a Statistical Perspective Using Machine Learning

Software is the heart of over 99% of all modern-day devices which include smartphones, personal computers, internet of things (IoT) networks, etc. This software is built by a team of engineers which divide the final product into multiple smaller components and these components are integrated together to build the final software, due to which inherent interfacing vulnerabilities & bugs are injected into it. Multiple bugs are also injected into the system due to inexperience or mistakes made by software engineers & programmers. To identify these mistakes, a wide variety of bug prediction & tracing models are proposed by researchers, which assist programmers to predict & track these bugs. But these models have large variations in terms of accuracy, precision, recall, delay, computational complexity, cost of deployment and other performance metrics, due to which it is ambiguous for software designers to identify best bug tracing method(s) for their application deployments. To reduce this ambiguity, a discussion about design of different bug tracing & prediction models and their statistical comparison is done in this paper. This comparison includes evaluation of accuracy, precision, recall, computational complexity and scalability under different scenarios. Based on this comparison, in this paper experiments were performed on five publically available datasets from NASA MDP repository using different algorithms i.e. DRF, LSVM, LR, RF, and kNN. From the results it was observed that kNN algorithm outperforms average 98.8% accuracy on these five datasets and hence kNN were considered to be the most significant with its selected features. In the future, this performance can be improved via use of CNN & LSTM based models, which can utilize the base kNN layer, and estimate highly dense features for efficient classification performance.
A Novel Concept of Dynamic Line Rating Systems Based on Soft Computing Models

Due to the transformation of the electricity system, the system operators emphasize the maximum utilization of the existing network elements, such as transmission lines. Full utilization requires accurate tracking of the conductors' thermal behavior, which can also form the basis of the dynamic line rating (DLR) method. Due to these international trends, continuous monitoring of high-voltage transmission lines and developing resilience-increasing systems are becoming more common. The primary purpose of this paper is to demonstrate the operation and applicability limit of international DLR models and their conductor temperature tracking approach based on EU-funded international projects. The paper investigates two independent conductor thermal monitoring sensors and compares their measurements with the model results, highlighting key findings of the projects. A novel, artificial neural network-based DLR concept is introduced based on the results presented, emphasizing its structure and operation steps. The advantages of the new concept in terms of conductor thermal tracking and power line rating are also presented in detail. One general novelty of the proposed concept is that it makes the transfer capacity calculation model operate independently from the line monitoring sensors over time. Thus, these devices can be dismantled or relocated to other spans or power lines based on the system operators' decisions. In this way, the novel concept has not only technological but also significant economic benefits.
Economic Gardening and Leadership Styles: A Case Study of Udon Thani, Thailand

The purpose of this paper is to scrutinize the association between the concepts of Economic Gardening, Leadership Styles, and city growth in a case study of Udon Thani Province, Thailand. Initially, this research applies the mixed methods in the data collection and analysis processes. 72 respondents participated in the survey questionnaire. Based on the performance (The capabilities of each local organisation in contributing and proving related activities to increase level of economic gardening in the area) score of each return survey questionnaire, the extreme case study of the mayor of Udon Thani was purposively selected to explain the phenomenon of the Economic Gardening and Leadership Styles of the mayor or leader in the community. More specifically, in this research article, the data analysis and results are proposed in the view of qualitative research approach since the selected case presented is the distinguished case. Findings indicate that there are substantial effects between the relationship of economic gardening and leadership styles, and then this could bring about the greater level of city growth. Implications are discussed, along with limitations and recommendations for future investigations. Furthermore, the implications on how to increase the levels of the growth of the city through applying the appropriate concepts of Economic Gardening and the styles of leadership under rapid changing and unstable world environment. In term of the originality, this is the first research to establish that there is association between the concept of Economic Gardening and Leadership Styles and how to develop the growth of the city in the Thai contexts.