Reviewerly/exHarmony huggingface dataset:
A framework for improving the reproducibility of data extraction for meta-analysis

Extracting data from studies is the norm in meta-analyses, enabling researchers to generate effect sizes when raw data are otherwise not available. While there has been a general push for increased reproducibility throughout the many facets of meta-analysis, the transparency and reproducibility of the data extraction phase are still lagging be-hind. This particular meta-analytic facet is critical because it facilitates error-checking and enables users to update older meta-analyses. Unfortunately, there is little guidance of how to make the process of data extraction more transparent and shareable, in part this is as a result of relatively few data extraction tools currently offering such functionality. Here, we suggest a simple framework that aims to help increase the reproducibility of data extraction for meta-analysis. We also provide suggestions of software that can further help users adopt open data policies. More specifically, we overview two GUI style software in the R environment, shinyDigitise and juicr, that both facilitate reproducible workflows while reducing the need for coding skills in R. Adopting the guiding principles listed here and using appropriate software will provide a more streamlined, transparent, and shareable form of data extraction for meta-analyses.
Big Data Visualization for Cyber Security: BETH Dataset

In this study, the literature on big data visualization for cyber security purposes was scanned and a purposeful data visualization study was carried out on a sample data set. When the visualization study carried out is compared with its counterpart in the literature, it reveals that if the visualization with the criteria suggested in this study is applied, the user (human) can read the graphics much more easily and it will be a facilitating way for attack detection. The criteria in the study are based on the use of current data sets such as BETH and the use of methods such as Principle Component Analysis (PCA).
Application of the Tilawati Method in Improving The Quality of Reading the Qur'an for MDTA Students Nurul Huda Singajaya Indramayu

This research is to find out how the application of the tilawati method improves the quality of students reading the Koran at MDTA Nurul Huda Singajaya Indramayu. The type of this research is in the form of field research, namely research that is carried out systematically by collecting existing data in the field. And the research technique used is data analysis technique, namely the process of searching and systematically compiling data obtained from interviews, observation and documentation. The conclusion from this study is that the application of the tilawati method is carried out in 3 stages, the effectiveness of learning can be adjusted by several existing aspects. Then that in increasing the quality or results of improving the quality of Santri reading the Qur'an consists of several methods, teacher quality and child factors. The tilawati method applied at MDTA Nurul Huda Singajaya Indramayu is very effective in improving the quality of santri's reading of the Qur'an
Mixed reality for minimally invasive Bone Tumor ablation

Minimally invasive intervention requires accuracy and practice as it can be vital in complex and narrow places. In this paper we propose a solution based on augmented reality (AR) for the ablation of bone tumors. Our proposal deals with the preoperative and intraoperative phases of the procedure. The first part consists of the segmentation and 3D reconstruction of the structures of interest. The second part consists of the visualization in AR. This solution is intended to facilitate the tasks of surgeons and radiologists when planning RF needle insertion and trajectory in order to avoid excessive exposure to X-rays, which is a phase that requires more precision and knowledge of the morphology of the mass tumor. The second part offers AR assistance based on the planning of the preoperative phase. The solution we proposed is based on the use of HoloLens 2 headsets to provide better AR visualization and assistance.
ARCH-COMP22 Category Report: Hybrid Systems Theorem Proving

This paper reports on the Hybrid Systems Theorem Proving (HSTP) category in the ARCH-COMP Friendly Competition 2022. The characteristic features of the HSTP cate- gory remain as in the previous editions [MST+18, MST+19, MMJ+20], it focuses on flexi- bility of programming languages as structuring principles for hybrid systems, unambiguity and precision of program semantics, and mathematical rigor of logical reasoning principles. The benchmark set includes nonlinear and parametric continuous and hybrid systems and hybrid games, each in three modes: fully automatic verification, semi-automatic verifica- tion from proof hints, proof checking from scripted tactics. This instance of the competition focuses on presenting the differences between the provers on a subset of the benchmark examples.
Provenance of Upper Devonian Ilanqareh Formation (NW Iran), assessed using petrography and major element geochemistry

In this study, a combination of petrographic and major element geochemical methods was employed on sandstones and shales of Upper Devonian Ilanqareh Formation, northwest of Iran, aimed at investigating the tectonic setting and the weathering degree of rocks in the source area. The index of compositional variability (ICV below 1) indicated that the studied quartzarenite and subarkose sandstones were not in the first cycle. Petrographic studies showed the existence of a craton interior provenance for these sandstones and geochemical studies identified recycling of older formations as an important source of these deposits. The chemical index of alteration (CIA values of 78.18 to 90.42 for sandstones and 91.55 to 91.93 for shale samples) indicated that the samples were affected by the high degree of weathering due to the humid climate in the source areas. Geochemical discrimination diagrams revealed that the samples were deposited in a passive margin. According to the paleogeography, this passive margin was the margin of a rift basin in the northwest of Gondwana, and the Ilanqareh deposits were derived from the Arabian-Nubian shield and the recycling of the Lower Palaeozoic sandstones in the region.
Time inhomogeneous quantum dynamical maps

Abstract We discuss a wide class of time inhomogeneous quantum evolution which is represented by two-parameter family of completely positive trace-preserving maps. These dynamical maps are constructed as infinite series of jump processes. It is shown that such dynamical maps satisfy time inhomogeneous memory kernel master equation which provides a generalization of the master equation involving the standard convolution. Time-local (time convolution-less) approach is discussed as well. Finally, the comparative analysis of traditional time homogeneous versus time inhomogeneous scenario is provided.
Year 2021: COVID-19, Information Extraction and BERTization among the Hottest Topics in Medical Natural Language Processing

Analyze the content of publications within the medical natural language processing (NLP) domain in 2021.Automatic and manual preselection of publications to be reviewed, and selection of the best NLP papers of the year. Analysis of the important issues.Four best papers have been selected in 2021. We also propose an analysis of the content of the NLP publications in 2021, all topics included.The main issues addressed in 2021 are related to the investigation of COVID-related questions and to the further adaptation and use of transformer models. Besides, the trends from the past years continue, such as information extraction and use of information from social networks.
Machine Learning for Clinical Predictive Analytics

In this chapter, we provide a brief overview of applying machine learning techniques for clinical prediction tasks. We begin with a quick introduction to the concepts of machine learning and outline some of the most common machine learning algorithms. Next, we demonstrate how to apply the algorithms with appropriate toolkits to conduct machine learning experiments for clinical prediction tasks. The objectives of this chapter are to (1) understand the basics of machine learning techniques and the reasons behind why they are useful for solving clinical prediction problems, (2) understand the intuition behind some machine learning models, including regression, decision trees, and support vector machines, and (3) understand how to apply these models to clinical prediction problems using publicly available datasets via case studies.
EVALUATING INTERACTIVE VIDEO UTILIZATION IN ENGLISH FOR TOURISM BUSINESS CLASS

Interactive video as one technology product provides an opportunity to enrich students' learning experience. The current study aimed to identify students' perception of interactive video utilization in English for tourism business classes and students' preference in applying interactive video in learning English for tourism business. The interactive videos were embedded in the learning management system, and the students had to utilize them individually. This study employed mixed-method research with an explanatory design. The data were gained through an administering questionnaire survey to 34 students majoring in the Hospitality program and analyzed using descriptive statistics by calculating the frequency of the answer to each question. Then, an interview was also conducted with several students to gain a further explanation of their learning media preferences. The results showed that the students perceived the interactive video positively based on its question layout, quality, and user interface. Furthermore, 94.1% of the students prefer to learn with interactive video than video. The students claimed that the interactive video helps them remember the learning material better, guides them to understand the material, encourages them to focus while watching the video, and makes the learning process more exciting. However, one student argued that the questions needed to be fully understood, and another highlighted the rewind button's unavailability. The result of the study indicated that the utilization of interactive video could be a beneficial learning tool in teaching English to the tourism business. In contrast, the English teacher or lecturer should also consider the students' freedom of learning.
READING COMPREHENSION AND SELF-REGULATED LEARNING: A CROSS SECTIONAL STUDY OF UNIVERSITY STUDENTS

Reading is a critical component of academic life. Undergraduate students' course success depends much on how they process their reading. However, some studies show that students face difficulties in their reading in several terms. These difficulties are twofold for English as a Foreign Language students who have to deal with reading and language content. In this respect, students must be able to self-regulate their reading activities in and outside classrooms. This study was intended to investigate the students' levels of self-regulated learning in reading comprehension. This study used a cross-sectional design with 40 English Language Education Study Program students at Universitas Lambung Mangkurat. The instrument was a questionnaire adapted from Zimmerman's Academic Self-Regulated Learning Scale (2000). The questionnaire was distributed online to the students using Microsoft Forms. The data were analyzed using a t-test. The findings show that the ways both groups of students regulate their cognitive processes, motivation, and behavior within an educational setting are similar. Nevertheless, concerning that the fourth-semester students might be more organized SRL students than the second-semester ones, reading instructions must be structured to develop students' self-regulated learning. In other words, lecturers should condition the instructions to enhance the students' self-regulation
A Descriptive Study of Reporting of breast Fine Needle Aspirationcytology Using International Academy of Cytology Yokohama System

Background: The International Academy of Cytology (IAC) has established standardizedapproach for reporting breast FNAC by categorizing lesions in a five-tier system from C1 to C5. Materials and Methods: From May 2020 to April 2021, a descriptive cross-sectional study was conducted in the cytology section of the Department of Pathology, SMS Medical College, Jaipur. Results: The current study involved 335 cases of breast FNAC, with a maximum of 333 (99.40%) females and 2 (0.60%) males. Maximum cases were in the age range of 21-40 years. There were 79 (23.60%) cases in C1 (Insufficient) category, C2 (Benign) had 177 (52.80%) cases, C3 (Atypical) had 9 (2.70%) cases, C4 (Suspicious) had 16 (4.80%) cases, and C5 (Malignant) had 54 (16.10%) cases respectively. Fibroadenoma was the most prevalent benign lesion in our analysis, accounting for 45 of the 177 benign cases, whereas ductal carcinoma was the most common malignant lesion.In a total of 92 cases where histology was examined, 86 cases were found to be compatible with the cytological diagnosis. In a triple assessment, 103 (78.03%) of the 132 cases were concordant in the benign group, only 1 (12.50%) case showed concordance in the atypia category, and 21 (39.62%) of the 53 cases showed concordance in the suspicious or malignant category. The Risk Of Malignancy (ROM) was calculated as follows: inadequate 0%, benign 0%, atypia 0%, suspicious for malignancy 71.43%, and malignant 97.56% for each group. Conclusion: This system is a valuable tool for breast cancer patient diagnosis and care. It also simplifies clinical audits and aids in improved coordination between pathologists, hospitals, and institutes.
Implementasi Model Pembelajaran Make A Match Dengan Pendekatan Contextual Teaching And Learning Untuk Meningkatkan Kemampuan Menulis Teks Berbentuk Procedure Pada Siswa Kelas XII MIPA 1 Man 1 Bungo

This Classroom Action Research Aims to improve Students' Ability to write Texts in The Form Of Procedure. Based on the results of tests carried out by the author before conducting classroom action research and the results of observations during the teaching and learning process at MAN 1 Bungo, especially class XII IPA 1, most students have not been able to write text in the form of procedures. Procedure text learning is contained in the curriculum standard at the unit level of education (KTSP) in class XII semester 1. By using the Make a Match learning model, it is expected that students' ability to write procedure texts will increase. The results of this classroom action research showed that students' ability to write procedure texts could increase. This lies in the actions that researchers perform in each cycle 1, namely cycle 1 and cycle 2. This PTK was carried out in class XII IPA 1 MAN 1 Bungo with 2 cycles. In each cycle planning, implementing actions, observing, and reflecting on data were carried out. The collected data is processed quantitatively. Thus it can be emphasized that the Make a Match learning model can be used as an alternative to improve students' ability to write procedure texts in class XII IPA 1 MAN 1 Bungo. The results of the actions of each cycle obtained an overview of the results of cycle 1. The success rate of students reached an average of 67.4 with good category abilities. In cycle 2 the success of students reached an average of 73.85 with good category ability.
Extracurricular Activities in the Function of Intellectual Education

Modern life imposes various demands on intellectual education as a designed system of influence on individual development in the field of development of the individual's cognitive abilities. At the same time, authors agree that school activities alone cannot lead to optimal intellectual development, which leads to thinking about extracurricular activities as a function of intellectual education. This article starts from the understanding of intellectual education and the essential characteristics of extracurricular activities, which allows consideration of the importance of extracurricular activities in the process of intellectual education, the realization of the tasks of intellectual education through extracurricular activities, as well as the situation in practice. By highlighting various examples of extracurricular activities in the function of intellectual education, their importance is clearly expressed, as well as the connection and conditioning of intellectual with other areas of education.
Two-Stage Feature Selection Method Created for 20 Neurons Artificial Neural Networks for Automatic Breast Cancer Detection

Breast cancer is a common deadly diseases in women. Initial recognition of breast cancer using mammogram images is a challenging task. Hence, this paper proposed a unique automatic diagnosis model for breast cancer. Initially, the mammogram images are preprocessed with a median filter and contrast limited adaptive histogram equalization (CLAHE). The pre-processed image is automatically segmented using the multilevel threshold method. Subsequently, statistical, texture, shape, and geometric features are extracted from the segmented image. So, the length of the feature vector is high, and it is important to identify optimum features. In this paper, the dimension of the feature vector is reduced by 2-stage feature selection methods. Initially, the feature vector is applied to the best first search method information gain (IG) with rank feature method, and then secondly, apply the Pearson correlation method (PCM). Artificial neural networks (ANNs) are used to increase the classification accuracy of a breast cancer diagnosis. In this model, the selection of appropriate neurons in a single hidden layer is used to avoid overfitting problems in an ANN model. Based on optimum feature selection, the appropriate number of neurons chosen in the hidden layer is 20, which was applied for the proposed IG+PCM+Boosted-ANN model. The proposed model is applied on 2 regular datasets mini-Mammographic Image Analysis Society (mini-MIAS) and Digital Database for Screening Mammography (DDSM). The proposed model was superior to other exiting models and the model in this study achieves the accuracy of 99 and 98.80 % for mini-MIAS and DDSM datasets, respectively.
The Possible Solutions to Three Dimensions of Educational Reform in China

The application-oriented colleges and universities must implement the policy of vocational education reform in order to train practical talents. At the same time, they also face many three dimensions of educational reform (TDER) problems in the implementation of vocational education reform. Therefore, the purpose of this study is to clarify the TDER’s problems through literature review, and put forward countermeasures. Based on this, three dimensions of educational reform were taken as key words for literature retrieval, and a total of 20 literatures within the past three years were obtained. Then, the subsequent analysis and induction are conducted. Findings show that the essence of the TDER is how teachers can impart their professional knowledge to students in a reasonable and orderly way through textbooks and teaching methods, so as to achieve the teaching objectives of the course. Future research can be followed by teaching methods improvement of different types of majors and courses.
Ontologies in educational process management

In the educational processes of universities, the ontological approach is used in the management of curricula, to describe the subject areas of the academic disciplines programs, to assess the knowledge of students. The article discusses the ways of using ontologies in teaching and provides an example of an ontological approach to managing the educational process. The process area "Preparation for the reporting event" was selected as part of the research seminar for graduate students. Based on the results of a three-year experiment, an update was proposed to the original domain model associated with the ―Teacher‖ entity. The resulting changes have a positive effect on the practice of the educational process both for the teacher (improving qualifications and motivation) and for students (increasing academic performance and involvement). Conclusions are formulated about the usefulness of the proposed method and its prospects, about the possibility of expanding the scope of the study by performing a further analysis of educational processes and using the results presented in the article.
Building an ontology of fundamental concepts based on a transdisciplinary approach

The procedures for applying a transdisciplinary approach to the development of formulations of fundamental concepts and to the construction of the ontology of these concepts are described. The analysis of the terminological and content components necessary for such an application is carried out. The role of the state of harmony is established as a criteri- on for the presence of positive and negative trends in assessing the situation under consideration. The application of technology for formulating and building an ontology is shown on the example of the concept of "Love". It is noted that love is based on positive trends in a state of harmony, as well as a number of other essential features. The formulations of a number of concepts related to love are proposed. Based on the results obtained, the place of artificial intelligence systems in the formed integral construction was determined, the restrictions on the potential capabilities of such systems were indicated. The transdisciplinary technology is universal and applicable to all areas in which research is carried out, including in the field of ontologies. The article is intended for specialists interested in a holistic ontological picture at the level of fundamental concepts..
Small pedestrian target detection based on YOLOv5

YOLOv5s is the network with the smallest depth and feature map width and the fastest image inference, but when applied to small pedestrian target detection in complex scenes, the detection still suffers from wrong and missed detections. To address this problem, an improved model based on YOLOv5s is proposed with the addition of a new convolutional neural module, SPD-Conv, which improves the accuracy of the network in detection tasks of low-resolution images or smaller objects. The improved YOLOv5s-SPD model obtained better detection results compared with the original network model, with an average accuracy improvement of 3.9% and an increase in mAP value of about 9.9%.
Research on the Fast Construction Method of Basic Geographic Framework of 3D Smart Community

In order to promote the reform and innovation of social governance system, create "community brain" and build digital twin community in digital space, the hierarchical and household-level three-dimensional basic geographic framework plays the role of data base. Based on the key technologies such as deep learning change monitoring, batch building and rendering of hierarchical household 3D models on the Web side, and multi-source address matching, this paper explores and realizes the technical route of quickly building hierarchical household-level 3D basic geographic framework of 3D smart communities. Through the technique of dynamic rendering monomer, a three-dimensional model visualization platform of oblique photography is built, which effectively integrates various government resources of people, houses, things and things, and realizes socialization, intelligence and specialization of social governance and convenience services.
Detection of Domestic Waste Based on YOLO

Deep learning has increasingly permeated every aspect of our lives. Currently, the economy develops rapidly and the population living in cities grows quickly. In the meanwhile, the amount of domestic waste is constantly rising, and the serious shortage of waste treatment competence has become increasingly prominent. Many cities can only use landfill or incineration to generate electricity for most of the waste, but this is not a long-term solution. In this paper, the YOLO-based domestic waste classification and treatment method are proposed to improve the efficiency of waste treatment.