Miracle-dz/UniFAR-FTUs huggingface dataset:
Novel assessment of numerical forecasting model relative humidity with satellite probabilistic estimates

Abstract. A novel method of comparison between an atmospheric model and satellite probabilistic estimates of relative humidity (RH) in the tropical atmosphere is presented. The method is developed to assess the Météo-France numerical weather forecasting model ARPEGE using probability density functions (PDF) of RH estimated from the SAPHIR microwave sounder. The satellite RH reference is derived by aggregating footprint-scale probabilistic RH to match the spatial and temporal resolution of ARPEGE over the April-May-June 2018 period. The probabilistic comparison is discussed with respect to a classical deterministic comparison confronting each model RH value to the reference average and using a set confidence interval. The study first documents the significant spatial and temporal variability of the reference distribution spread and shape. It warrants the need for a finer assessment at the individual case level to characterise specific situations beyond the classical bulk comparison using determinist “best” reference estimates. The probabilistic comparison allows for a more contrasted assessment than the deterministic one. Specifically, it reveals cases where the ARPEGE simulated values falling within the deterministic confidence range actually correspond to extreme departures in the reference distribution.
High Resolution, Annual Maps of Field Boundaries for Smallholder-Dominated Croplands at National Scales

Mapping the characteristics of Africa’s smallholder-dominated croplands, including the sizes and numbers of fields, can provide critical insights into food security and a range of other socioeconomic and environmental concerns. However, accurately mapping these systems is difficult because there is 1) a spatial and temporal mismatch between satellite sensors and smallholder fields, and 2) a lack of high-quality labels needed to train and assess machine learning classifiers. We developed an approach designed to address these two problems, and used it to map Ghana’s croplands. To overcome the spatio-temporal mismatch, we converted daily, high resolution imagery into two cloud-free composites (the primary growing season and subsequent dry season) covering the 2018 agricultural year, providing a seasonal contrast that helps to improve classification accuracy. To address the problem of label availability, we created a platform that rigorously assesses and minimizes label error, and used it to iteratively train a Random Forests classifier with active learning, which identifies the most informative training sample based on prediction uncertainty. Minimizing label errors improved model F1 scores by up to 25%. Active learning increased F1 scores by an average of 9.1% between first and last training iterations, and 2.3% more than models trained with randomly selected labels. We used the resulting 3.7 m map of cropland probabilities within a segmentation algorithm to delineate crop field boundaries. Using an independent map reference sample (n = 1,207), we found that the cropland probability and field boundary maps had respective overall accuracies of 88 and 86.7%, user’s accuracies for the cropland class of 61.2 and 78.9%, and producer’s accuracies of 67.3 and 58.2%. An unbiased area estimate calculated from the map reference sample indicates that cropland covers 17.1% (15.4–18.9%) of Ghana. Using the most accurate validation labels to correct for biases in the segmented field boundaries map, we estimated that the average size and total number of field in Ghana are 1.73 ha and 1,662,281, respectively. Our results demonstrate an adaptable and transferable approach for developing annual, country-scale maps of crop field boundaries, with several features that effectively mitigate the errors inherent in remote sensing of smallholder-dominated agriculture.
INVESTIGATING THE CHALLENGES AND PROBLEMS OF MEDICAL LEGAL TRANSLATION: TRANSLATION PRACTITIONERS' VIEWS IN FOCUS

Department of English Language, Kermna Branch, Islamic Azad University, Kerman, Iran. This research investigated the views of translation practitioners towards translating legal texts. Moreover, it aimed at finding out the main challenges and problems of translating legal texts, and providing some strategies which can help translation practitioners to overcome the possible challenges and difficulties. Accordingly, sixty translation practitioners of both genders were selected from Kerman and some cities around it based on cluster sampling. The instruments of this project were questionnaire and structured interview. The questionnaires were distributed to the participants (practitioners) and they completed it by following the instructions. Then, twenty of the translation practitioners were selected randomly to participate in structured interview. Eventually, all the data were analyzed using SPSS software. The results revealed that the majority of the respondents agreed that the translation challenges in legal texts are not only related to the culture-specific challenges, but also they involve linguistic ones. Moreover, most of them referred to legal dictionaries and Babylon translator' strategies to overcome the challenges of translating legal text.
A prospective investigation to evaluate the efficacy and role of Xpert Mycobacterium tuberculosis/rifampicin assay in urinary tuberculosis

Aim: The aim of the present study was to evaluate the efficacy and role of Xpert Mycobacterium tuberculosis/rifampicin assay in urinary tuberculosis. Methods: This was a prospective study conducted in the Department of department of urology, IGIMS Patna, Bihar, India, for 12 months. Three urine samples were collected from each patient and were subjected to Xpert MTB/RIF assay, acid-fast bacillus (AFB) smear microscopy, and liquid media (BACTEC Mycobacteria Growth Indicator Tube [MGIT] 960) culture. Imaging and tissue biopsies were performed as clinically indicated. Sensitivity, specificity, positive predictive value, and negative predictive value were calculated using the bootstrap method for 95% confidence intervals for the Xpert assay. Results: A total of 120 patients were included for analysis. Of these, 70 fulfilled the study's diagnostic criteria (composite reference) and were labelled as positive for urinary tuberculosis while 50 patients had a negative evaluation and were considered as negative for urinary tuberculosis. When compared to the composite reference standard, a single Xpert assay had a sensitivity of 70.11% (54.21%-81.02% and a specificity of 100% (95% CI 91.11–100%). The PPV was 100% (CI 95% 87.96–100%), and NPV was 73.98% (95% CI 60.37–83.02%). In contrast, the sensitivity of a single smear examination was only 22.5%. Three serial AFB smear examinations improved the sensitivity to 33.23% (20.88–47.21). When MGIT 960 liquid AFB culture was compared to the composite standard using the other variables, the sensitivity was 57.87% (95% CI 45.12–65.77%). McNemar's test showed that Xpert MTB/RIF assay was significantly superior to three auramine-O-fluorescent smear microscopy examinations (70.11% vs. 33.23%, P =−0.0001) while its better performance over the MGIT 960 AFB culture was not statistically significant (70.11% vs. 57.87%, P = 0.06). Xpert MTB/RIF assay identified 60% of smear-negative and 35% of culture-negative cases. However, it missed 3 of the 40 (7.5%) culture-positive patients. None of the patients had rifampicin resistance either on Xpert MTB/RIF assay or on AFB cultures. Conclusion: Xpert MTB/RIF assay on an early morning first void urine specimen can replace smear microscopy as the initial diagnostic test for urinary tuberculosis.
Title: COVID-19 and the Brain: A Psychological and Resting-state fMRI Study of the Whole-brain Functional Connectivity Running Title: Psychological & Neuroimaging in COVID-19

1 Ph.D. Candidate, Student Research Committee, School of Medicine, Shahroud University of Medical Sciences, Shahroud, Iran. 2 MSc, Center for Health Related Social and Behavioral Sciences Research, Shahroud University of Medical Sciences, Shahroud, Iran. 3 Assistant professor, Department of Neuroscience, School of Advanced Technologies in Medicine, Mazandaran University of Medical Sciences, Sari, Iran. 4 Assistant professor, Department of Neurology, School of Medicine, Shahroud University of Medical Sciences, Shahroud, Iran. 5 Assistant professor, Psychiatry and Behavioral Sciences Research Center, Addiction Institute, Mazandaran University of Medical Sciences, Sari. 6 Assistant professor, Department of Neuroscience, School of Advanced Technologies in Medicine, Mazandaran University of Medical Sciences, Sari, Iran. 7 Assistant professor, Clinical Research Development Unit, Imam Hossein Hospital, Shahroud University of Medical Sciences, Shahroud, Iran.
PERFORMANCE ANALYSIS OF SUPERVISED LEARNING ALGORITHMS FOR IDENTIFICATION OF AUTISM SPECTRUM DISORDER USING EEG SIGNALS

-Autism Spectrum Disorder (ASD) is a sort of developmental issue of the nervous system, with center impedances in social connections, creative mind, communications, adaptability of thought,intrigue andrestricted range of activities. Examination of electroencephalographic (EEG) signals based on autism is explored in this work. Even so, it is critical to identify autism by the analysis of the EEG signal. Hence feature extraction based on the EEG signals takes part a prominent role in autism recognition.
Evaluating the Evolution of ECMWF Precipitation Products Using Observational Data for Iran: From ERA40 to ERA5

European Center for Medium‐Range Weather Forecasts Reanalysis (ERA), one of the most widely used precipitation products, has evolved from ERA‐40 to ERA‐20CM, ERA‐20C, ERA‐Interim, and ERA5. Studies evaluating the performance of individual ERA products cannot adequately assess the evolution of the products. We compared the performance of all ERA precipitation products at daily, monthly, and annual data (1980–2018) using more than 2100 Iran precipitation gauges. Results indicated that ERA‐40 performed worst, followed by ERA‐20CM, which showed only minor improvements over ERA‐40. ERA‐20C considerably outperformed its predecessors, benefiting from the assimilation of observational data. Although several previous studies have reported full superiority of ERA5 over ERA‐Interim, our results revealed several shortcomings in ERA5 compared with the ERA‐Interim estimates. Both ERA‐Interim and ERA5 performed best overall, with ERA‐Interim showing better statistical and categorical skill scores, and ERA5 performing better in estimating extreme precipitations. These results suggest that the accuracy of ERA precipitation products has improved from ERA‐40 to ERA‐Interim, but not consistently from ERA‐Interim to ERA5. This study employed a grid‐grid comparison approach by first creating a gridded reference data set through the spatial aggregation of point source observations, however, the results from a point‐grid approach showed no change in the overall ranking of products (despite the slight changes in the error index values). These findings are useful for model development at a global scale and for hydrological applications in Iran.
Detecting Cross-Language Plagiarism using Open Knowledge Graphs

Identifying cross-language plagiarism is challenging, especially for distant language pairs and sense-for-sense translations. We introduce the new multilingual retrieval model Cross-Language Ontology-Based Similarity Analysis (CL\nobreakdash-OSA) for this task. CL-OSA represents documents as entity vectors obtained from the open knowledge graph Wikidata. Opposed to other methods, CL\nobreakdash-OSA does not require computationally expensive machine translation, nor pre-training using comparable or parallel corpora. It reliably disambiguates homonyms and scales to allow its application to Web-scale document collections. We show that CL-OSA outperforms state-of-the-art methods for retrieving candidate documents from five large, topically diverse test corpora that include distant language pairs like Japanese-English. For identifying cross-language plagiarism at the character level, CL-OSA primarily improves the detection of sense-for-sense translations. For these challenging cases, CL-OSA's performance in terms of the well-established PlagDet score exceeds that of the best competitor by more than factor two. The code and data of our study are openly available.
Meaningful XAI Based on User-Centric Design Methodology

This report first takes stock of XAI-related requirements appearing in various EU directives, regulations, guidelines, and CJEU case law. This analysis of existing requirements will permit us to have a clearer vision of the purposes, the ``why'', of XAI, which we separate into five categories: contestability, empowerment/redressing information asymmetries, control over system performance, evaluation of algorithmic decisions, and public administration transparency. The analysis of legal requirements also permits us to create four categories of recipients for explainability: data science teams; human operators of the system; persons affected by algorithmic decisions, and regulators/judges/auditors. Lastly, we identify four main operational contexts for explainability: XAI for the upstream design and testing phase; XAI for human-on-the-loop control; XAI for human-in-the-loop control; and XAI for ex-post challenges and investigations.Second, we will present user-centered design methodology, which takes the purposes, the recipients and the operational context into account in order to develop optimal XAI solutions.Third, we will suggest a methodology to permit suppliers and users of high-risk AI applications to propose local XAI solutions that are effective in the sense of being ``meaningful'', for example, useful in light of the operational, safety and fundamental rights contexts. The process used to develop these ``meaningful'' XAI solutions will be based on user-centric design principles examined in the second part.Fourth, we will suggest that the European Commission issue guidelines to provide a harmonised approach to defining ``meaningful'' explanations based on the purposes, audiences and operational contexts of AI systems. These guidelines would apply to the AI Act, but also to the other EU texts requiring explanations for algorithmic systems and results.
Evaluation of Strategic Factors in the Implementation of the Online Tax System in DKI Jakarta Province

In the current New Normal era, service activities are conducted online to reduce the risk of a wider spread of the COVID-19 virus. The DKI Jakarta Provincial Government has provided online-based services for regional taxpayers through a website and a mobile application. However, there are still several challenges in implementing these services. This study analyzes the strategic factors that influence the DKI Jakarta online tax system's implementation using the Human Organization Technology (HOT) Fit Model approach (2008). This research uses a quantitative approach by distributing questionnaires to 100 respondents who have used the DKI Jakarta Online Tax System in 2020. The result indicates that four strategic factors, namely influence the implementation of online tax policies in DKI Jakarta: 1) Support and response from the online system to taxpayers in using the online system (Service Quality); 2) Taxpayer’s perception of the benefits and convenience in using the online tax system (User Satisfaction); 3) Service provider organization (Environment); 4) Support from the system in fulfilling taxpayers’ rights and obligations (Net Benefit). Based on these findings, the DKI Jakarta Provincial Government can formulate a strategy to improve online-based services to address the New Normal era's challenges. Keywords—strategic factors, HOTFit models, online Tax System, DKI Jakarta Province
REVIEW OF HIBRID TOOL TESTING AND MEASURMENT FOR FRICTION

The foremost goal of the review of literature is to Collect, Study and highlight the previous research works conducted by numerous authors(researchers) in an area of the FSW of an alloy of 13Al. Formulating the problem is a central stage in research work with the objectives. In this literature review, the selected main topics are FSW Process analysis, Mechanical properties, Microstructural properties, Experimental designs, bending strength of the welds, Corrosion of the joints, Analysis of wear and Fatigue strength analysis were reviewed.
The Development of Communication Across Timescales

How do young children learn to organize the statistics of communicative input across milliseconds and months? Developmental science has made progress in elucidating how infants learn patterns in language and how infant-directed speech is engineered to ease short-timescale processing, but less is known about how children link perceptual experiences across multiple levels of processing within an interaction (from syllables to stories) and across development. In this article, we propose that three domains of research—statistical summary, neural processing hierarchies, and neural coupling—will be fruitful in uncovering the dynamic exchange of information between children and adults, both in the moment and in aggregate. In particular, we discuss how the study of brain-to-brain and brain-to-behavior coupling between children and adults will advance the field’s understanding of how children’s neural representations become aligned with the increasingly complex statistics of communication across timescales.
Evaluation of oxidative stress in response to examination stress in dental students

Oxidative stress gained the attention recently in behavioral medicine and been contributes to various psychological disturbances and mental stress in Medical and Dental students. This study is to evaluate the level of oxidative stress markers in undergraduate students caused by examination stress. This cross sectional study was conducted at Priyadharshini Dental College. Fifty healthy final year dental students were participated and the level of oxidative stress (Lipid peroxidation and Antioxidant status) were assessed on the day of examination “stress condition” and compared with the same parameters obtained from the same students after the exam “non-stress condition”. The results shows that oxidative damage and sensitivity to lipid oxidation were significantly increased in “stress condition” (P<0.05) when compared with the same parameters in “nonstress” conditions. A significant decrease in plasma antioxidant level was observed (P<0.05) under stress. There is significant higher in oxidative stress its adversely affects the student performance and mental health during the examination.
AP-MOTJ210023 334..344

People oriented toward promotion are concerned with changing (improving) their current state, while those oriented toward prevention are concerned with maintaining (not worsening) their current state (Higgins, 1997). Because a promotion orientation is directed at moving from the reality to a better future, whereas a prevention orientation is directed at keeping the reality, we predicted and found in 4 studies that when thinking about important personal wishes or concerns, promotion-oriented participants focused more on the future (vs. the reality) than prevention-oriented participants. Promotion-oriented participants also viewed the future more positively compared to their reality than prevention-oriented participants. We assessed focus toward the future and reality by asking participants to name and write about an important personal wish or concern and analyzing the content of their written texts. We observed the effects when we manipulated participants’ regulatory focus by asking them to generate promotion (vs. prevention) oriented concerns (Studies 1 and 2) and when we measured their chronic regulatory focus (Study 3).
DETECTION OF MICROCALCIFICATION CLUSTERS USING STATISTICAL PARAMETERS AND DYADIC CONTOURLET TRANSFORM BASED PRECISION ENHANCEMENT

— Recent scenario, breast cancer found to be a threat and dangerous carcinoma among women in the world. In contemplation of reducing the breast, cancer-related death needs an efficient computer-aided diagnosis (CAD) system. The discrimination of microcalcification clusters (MCCs) is an important manifestation for the early diagnosis of breast cancer. This paper focuses on the detection of breast cancers cells size below 2mm. To achieve précised enhanced cancer cell region an efficient technique dyadic Counterlet transform (DCTs) in two dimension is proposed. The enhancement of cancer cell region obtained through preserving the boundaries and borders with curvature for a small region.
UC Merced Proceedings of the Annual Meeting of the Cognitive Science Society

Digitally-enabled means for judgment aggregation have re-newed interest in “wisdom of the crowd” effects and kick-started collective intelligence design as an emerging ﬁeld in the cognitive and computational sciences. A keenly debated question here is whether social inﬂuence helps or hinders collective accuracy on estimation tasks, with recently introduced network theories offering a reconciliation of seemingly contra-dictory past results. Yet, despite a growing body of literature linking social network structure and the accuracy of collective beliefs, strategies for exploiting network structure to harness crowd wisdom are under-explored. In this paper, we introduce a potential new tool for collective intelligence design informed by such network theories: rewiring algorithms. We provide a proof of concept through agent-based modelling and simulation, showing that rewiring algorithms that dynamically manipulate the structure of communicating social networks can increase the accuracy of collective estimations in the absence of knowledge of the ground truth.
DETECTION of SOME VIRULENCE FACTORS and ANTIBIOTIC SENSITIVITY TEST of ENTEROCOCCUS FAECALIS ISOLATED FROM SHEEP by MULTIPLEX PCR

Enterococcus faecalis form an important population of commensal bacteria and have been reported to possess numerous virulence factors considered significantly important in exacerbating diseases caused by them. Objectives: The present study was conducted to evaluates the presence of virulence factors and antibiotic susceptibility among Enterococcus faecalis isolated from sheep. Methods: The study included the collection of 50 samples (25 Milk samples collected from the udder was washed and the teats were disinfected and dried using alcohol, the first milk drop removed. 5ml of milk collected on aseptic tube and 25 Feces samples collected from sheep diarrhea from rectal by aseptic gloves. (from October 2018 to March 2019 ) and transported to laboratory as soon as possible in sterile Brain heart infusion broth that incubated at 37 C for at least 24-28 hours to increasing chances of isolation. Enterococcus faecalis that were recognized by cultural characteristics, Gram stain, and biochemical reactions. Results: The results of the laboratory cultural of 50 cotton swabs used s show that the isolation rate of Enterococcus spp. were 32% and 56% from milk and feaces respectively. the result of PCR test for detection of Enterococcus faecalis: show that the Enterococcus faecalis detected in rate of 66.6% from total Enterococcus spp. While the result of Enterococcus faecalis virulence factors showed that the Surface proteins, Gelatinase and Hemolysin were 75%, 33.3%, 25.5% respectively. Results of antibiotic sensitivity test showed the most bacterial isolated sensitive Nitrofurantoin , Imipenem and Nalidixic acid were 91.6%,83.3% and 58.3%% respectively Conclusion: We report that our simple modification of the existing multiplex PCR had increased the detection of the enterococcal virulence genes. Predominance of virulence genes was in order of Surface proteins, Gelatinase and Hemolysin were 75%, 33.3%, 25.5%. This modified PCR protocol could be useful to resolve the problem of decreased detection of virulence determinants in enterococci.