Reviewerly/exHarmony huggingface dataset:
Hypnotic suggestion versus sensory modulation of bodily awareness

Bodily awareness arises from somatosensory, vestibular, and visual inputs but cannot be reduced to these incoming sensory signals. Cognitive factors are known to also impact bodily awareness, though their specific influence is poorly understood. Here we systematically compared the effects of sensory (bottom-up) and cognitive (top-down) manipulations on the estimated size of body parts. Toward this end, in a repeated-measures design, we sought to induce the illusion that the right index finger was elongating by vibrating the biceps tendon of the left arm whilst participants grasped the tip of their right index finger (Lackner illusion; bottom-up) and separately by hypnotic suggestion (top-down), with a sham version of the Lackner illusion as an active control condition. The effects of these manipulations were assessed with perceptual and motor tasks to capture different components of the representation of body size. We found that hypnotic suggestion significantly induced the illusion in both tasks relative to the sham condition. The magnitudes of these effects were stronger than those in the Lackner illusion condition, which only produced a significantly stronger illusion than the sham condition in the perceptual task. We further observed that illusion magnitude significantly correlated across tasks and conditions, suggesting partly shared mechanisms. These results are in line with theories of separate but interacting representational processes for perception and action and highlight the influence of cognitive factors on low-level body representations.
Didáctica de la gramática: una experiencia con tutores pares en modalidad virtual

This paper aims to investigate the pedagogical potential of a didactic sequence for teaching grammar in virtual mode with the support of peer tutors in a course for future language teachers. The research, designed as a case study with pre- and post-test measurement, analyzes the academic performance of two parallel sections of the course Morphosyntax I, one of which had the implementation of a didactic module designed and implemented with the support of peer tutors in virtual modality. The main results show that, although the academic results between one section and the other do not show significant differences, the analysis shows that the course that was supported by tutors showed less dispersion in performance, a lower failure rate and a greater mastery of previous content, while the section taught exclusively by the teacher showed a better performance in the acquisition of new content
LITERACY SOCIALIZATION ON CYBER BULLYING PREVENTION AMONG STUDENTS OF SMP NEGERI 3 BILAH HULU

Cyberbullying is an action taken by a person or group of people against another individual through text messages, pictures/photos, or videos that tend to humiliate and harass. The purpose of this service is to provide an understanding of the impact caused by students' negligence in using social media, increase students' knowledge of intelligence in responding to the world of social media, and increase self-awareness of wisdom in using social media. The location of the service is at SMP Negeri 3 Bilah Hulu, the subject of the service related to the socialization of the impact of cyberbullying on teenagers is teenagers who use social media services or platforms. Most of the teenage respondents said that cyberbullying was inappropriate behavior among teenagers, was an act of crime, harmed others, and endangered others. They also understand behavioral indicators that lead to cyberbullying behavior.
New Marketing Model of Fashion Luxury Industry --- Metaverse Marketing

Metaverse, a concept that brings together highly sophisticated technologies from several major fields, is essentially a virtual, digitized process of the real world. It has received attention from people from all walks of life in the past years. Many fashion luxury brands have also seized this opportunity to innovate a new marketing model - metaverse marketing which has created many benefits for brands, including increased media exposure and public attention, as well as rejuvenation and deepening of the brand's premium image in ways that traditional marketing models could never achieve. Simultaneously, due to the scientific and technological limitations and legal restrictions related to metaverse, brands face many risks in metaverse marketing. Therefore, in this process, the luxury industry needs to always keep the marketing concept with consumers as the core, cooperate with technically mature enterprises for the development of technological products, and also develop diversified marketing plans to optimize the use of metaverse marketing to serve brand building on the basis of not damaging consumers' interests and destroying their own brand positioning.
SOCIALIZATION OF THE USE OF GOOGLE DRIVE AT PUSKESMAS AMBACANG KOTA PADANG

Computer technology has developed significantly, from Windows application programs to increasingly sophisticated data storage media. In the past, we usually stored data using diskettes with small storage sizes, then Flashdisk and Hardisk appeared, until the entry of a new era, namely Cloud storage technology. Cloud technology itself has broad functions, one of which is as an online data storage medium. Like the familiar cloud-based data storage service, Google Drive can store up to 15GB of data for free. In addition to data storage like Google Drive, there is also cloud data storage, such as DropBox, OneDrive, and others. By using Google Drive, users experience many benefits, including being able to share data with those who need data. There is no need to store files on a flash disk or hard disk, where our files are directly stored on Google servers, which can be used at any time, modified. In using Google Drive, many Ambacang Health Center staff do not understand Google Drive. The purpose of holding this Community Service is so that all staff can understand Google Drive how to use it and its features, the results achieved are that all participants understand and understand the use of Google Drive. This socialization has been carried out 2 times, on May 27 and June 17, 2023, with lecture and discussion methods.&#x0D;
Study of the paleochannel in the southeastern part of Pyongyang by using topographic and satellite image analysis: A possibility for successful survey of paleolithic site

Abstract There are Quaternary paleochannels in the left bank of the lower reaches of the Taedong River in the southeastern side of Pyongyang. We aimed to determine the possibility to find Paleolithic sites by locating terraces and paleochannels using digital elevation models (DEM) and Landsat ETM+. The study on paleochannels focused on survey of terrace of the 80–100 m high, associated with the Paleolithic site, performing topography (elevation, slope and aspect) analysis with DEM data and FCC (False Color Component), BR (Band Ratio), PCA (Principal Component Analysis), ISODATA, and SAM with Landsat ETM+ image. The results show that the analysis method using DEM and ETM+ is effective to find Paleolithic sites through surveys of terrace and paleochannel and analysis of facies.
Applications of Cryptocurrency in the Metaverse

The Metaverse and cryptocurrency have become a heated topics of discussion in society due to the rapid development of blockchain technology. However, there is a lack of research and prediction on the future application of cryptocurrencies on the Metaverse. Therefore, this paper reviews the historical development of the Metaverse through literature research and cause-effect analysis and combines the current development trend of new technologies (IoT, AI, NFT, etc.) related to the Metaverse and cryptocurrency with the current successful commercial applications or related academic research (Vtuber, virtual health care ophthalmology) to predict the future application scenarios of cryptocurrency on the Metaverse. This paper's main contribution is to provide an overview of the various cryptocurrency application scenarios currently being used in the Metaverse and predictions of the future development direction in light of the most recent technological trends, thus filling in any existing gaps in the cryptocurrency and related financial fields in the Metaverse. It serves as a resource for academics working on the creation of Metaverse technologies and crypto-currency application case development.
Innovative Active Methodologies That Promote Learning in Postgraduate Students in the 21st Century

The objective of the chapter is to propose the incorporation of active methodologies for the development of the competencies of postgraduate students in order to promote quality professional training. This comparative study comes from research whose results emanate from the use of active and innovative teaching strategies, put into practice in the classroom, with the aim of defeating the problems that frequently arise such as academic lapsing, lack of interest and communication, work team up. Within the solution alternatives, strategies and materials were used to promote learning related to the needs and in the context of the students, to develop skills and knowledge for solving administrative situations. Therefore, a proposal for successful training practices in project-based learning and the flipped classroom is presented to promote quality academic training in postgraduate students.
Empirical Raman calibration of trioctahedral ferromagnesium chlorite minerals

Abstract Chlorite is a common hydrated‐aluminous phyllosilicate mineral group that forms in most geological environments (e.g., hydrothermal, igneous, sedimentary, and metamorphic). The chemical composition of chlorite depends on several factors including temperature, pressure, fluid, and bulk rock composition. Raman spectroscopy is proposed as a quick and cost‐effective alternative to scanning electron microscopy and electron probe micro‐analysis, which involve complex sample preparation. In this paper, we demonstrate that Raman spectroscopy is a viable technique to determine the chemical composition of chlorite. Our results show that chlorite's Raman spectra changes quantitatively as a function of its chemical composition. Iron (Fe) and magnesium (Mg) content (APFU) is linearly correlated with the peak positions of three bands: Band 1 (99–104 cm −1 ), Band 8 (546–553 cm −1 ), and Band D (3,570–3,580 cm −1 ). In contrast, silicon (Si) and tetrahedral aluminum (Al IV ) are correlated with a single band's position, Band 9b (663–679 cm −1 ). We derived 18 empirical rules from these correlations, aiding geoscientists in accurately identifying and determining chlorite composition using Raman spectroscopy. Moreover, this technique holds potential for determining chlorite's chemical composition during planetary exploration, leveraging existing Raman spectrometers deployed on Mars and for future space missions.
Multi-order spatial interaction network for human pose estimation

Recent vision Transformer has been applied to human pose estimation and has achieved excellent performance by two-order spatial interaction with self-attention. However, it is still unclear whether higher-order spatial interaction can facilitate pose estimation. In this paper, we propose a novel approach based on multi-order spatial interactions and confirm that the combination of different orders is beneficial for human pose estimation task. We first build a Triple Interaction Module (TIM) by pure convolutions to make spatial information interactions three times. In contrast to Transformer, the TIM is compatible with several pure convolutions and extends two-order interaction in Transformer to triple-order without extensive additional computation, which makes it easier to explore inter-related features between keypoints in the human body. In addition, we combine TIM with traditional CNN and Transformer to form Multi-order Spatial Interaction Network (MSIN). This paper takes advantage of MSIN to extract keypoint heatmaps and certifies that the order-by-order structure can enhance the overall performance of locating human keypoints. Experimental results demonstrate that MSIN performs favorably against the most state-of-the-art CNN-based and Transformer-based counterparts on the COCO and MPII datasets, while being more lightweight.
Reimagining AI Governance: a Response by AGENCY to the UK Government's White Paper AI Regulation

In March 29, 2023, the UK Government released a white paper outlining its plans to implement a pro-innovation approach to Artificial Intelligence (AI) regulation and strengthen the UK's position as a global leader in AI.As part of the white paper, the government has developed five key principles to guide regulators. These principles encompass safety, security and robustness, appropriate transparency and explainability, fairness, accountability and governance, and contestability and redress. To ensure an effective framework, a flexible sector-specific approach is combined with a central function that coordinates, monitors, and adapts the overall framework. This approach aims “to drive growth and prosperity by boosting innovation, investment, and public trust in AI”, allowing for the opportunities posed by AI to be realised.This response by members of the multi-disciplinary AGENCY team provides comments on the white paper and details our recommendations on how the framework can be improved to ensure that AI is developed in an ethical and socially responsible way that protects citizens against complex online harms.
[Pollution Characteristics and Sources of Heavy Metals in Soil of a Typical Pyrite Concentrated Mining Area in Anhui Province].

To identify the characteristics and sources of heavy metal pollution in the surrounding soil of a typical pyrite concentrated mining area in Anhui Province, the pH value and the concentrations of Zn, Cu, Cd, Pb, Cr, Ni, Hg, and As in 42 surface soil samples and 16 soil samples from two vertical sections in the study area were collected and measured. The distribution characteristics, pollution assessment, and source analysis of heavy metal elements were conducted using the ArcGis inverse distance weight interpolation method, Nemero comprehensive index method, principal component analysis method, and absolute factor score-multiple linear regression (APCS-MLR) receptor model. The results showed that the average concentration of the eight heavy metals was 1.03-13.14 times the background value in the Tongling area. The local enrichment of Zn, Cu, Cd, Pb, Hg, and As was obvious, and the spatial distribution was basically consistent with the location of man-made mining activities. The single-factor pollution index evaluation showed that Zn, Cu, Cd, Pb, and As had different degrees of pollution risk, and the pollution degree of Cd and Cu was the most serious, accounting for 47.62% and 42.86% of moderate pollution, respectively. The Nemerow comprehensive pollution index evaluation showed that 61.90% of the soil samples in the study area were moderately polluted. The ground accumulation index evaluation showed that the pollution degree of Zn, Cu, Cd, Pb, Hg, and As in the study area was mainly from light pollution to strong pollution. In the vertical soil profile variation, heavy metals were easily enriched in the surface layer of the soil but migrated slowly to the deep layer, with concentrations mainly above 1 m. The results of source analysis showed that the high geological background and mining contribution rates of Zn, Pb, and As were 37.82%, 43.49%, and 46.63%, respectively. The natural contribution rates of weathering of parent material were 34.02%, 40.88%, and 38.52%, respectively. The sources of Cr and Ni were mainly natural sources of weathering of the parent material, with contribution rates of 91.95% and 73.68%, respectively. Geological high background and mining activities contributed 41.91% of the Cu sources, and atmospheric sedimentation and agricultural comprehensive sources contributed 41.30%. There were many sources of Hg. The natural source of weathering of soil parent material contributed 35.60%, geological high background and mining activities contributed 29.87%, and unknown sources contributed 34.05%. The main source of Cd was atmospheric sedimentation and agricultural comprehensive sources, contributing 81.81%.
Normal Values

The theoretical and practical problems of constructing normal databases within and between clinics are discussed. Pooling of data is probably a more attractive proposition in theory than in practice. The importance of standardisation of techniques is stressed, whilst caution in the over-interpretation of borderline results is counselled.
Using Big Data &amp; Analytics to Predict Hospital Re-Admissions

&lt;p&gt;“Big data” is a term often used to describe very large data sets, ranging from terabytes to exabytes, which are often complex (Chen, Chiang, &amp; Storey, 2012). SAS, an American developer of advanced analytical software, defines big data as a term to describe “large volumes of data, both structured and unstructured, that inundates business on a day-to-day basis”. Industry analyst Doug Laney suggested that a big data system should carry the attributes of volume, velocity, and variety (SAS, n.d.). In addition to those three attributes of big data, SAS also considers variability and complexity. &lt;/p&gt;
LEVEL OF UNDERSTANDING IN ASSOCIATIVE SEMANTICS AMONG AB-ENGLISH STUDENTS: BASIS FOR INTERVENTION PROGRAM

The presented study aims to check the level of understanding in associative semantics among AB-English students as basis for an intervention program to further improve comprehension as English major student. The framework of this study is supported by the mind of Noam Chomsky with his work in innateness theory. Moreover, this study used a descriptive-evaluative method designed to determine the level of understanding in associative semantics of fifty (50) students under the AB-English program of Ramon Magsaysay Memorial Colleges-Marbel, Inc. (RMMC-MI) who were selected purposively. A test questionnaire of fourty (40) items was used to determine the levels of understanding of the respondents in denotative and connotative, with twenty items for each level for the creation of an intervention program suited to enhance their ability to understand context words, and multiple lexicalities. Finally, the findings stated that out of twenty (20) item each test, students averaged a score of ranging to “Good” in denotative part of test, while still a “Good” range in connotative part. The results revealed that among the fifty (50) students who partake the test, their combine score average is interpreted as “Good”. Thus, a recommended supplemental intervention program is needed to enforce understanding in associative semantics through refresher and engaging activities for the AB-English students of RMMC-MI.
An integrated functionality framework for robust video streaming heterogeneous networks

Video streaming is one of the drastically growing applications and more researchers are focused on their researchers in same. All over the world, the cost of video streaming process is increased up to 37$ billion. Even though video streaming process meets various problems like time, Bit Rate Error (BER) and buffers usage with cost. To provide solution to the above issues, this paper proposed an integrated framework to provide a video streaming method by increased Quality of Service (QoS). The proposed framework integrates (Integrated Framework IF) a popular standard named H.264/AVC video coding and efficient QoE prediction on similar frames in the video. Using the framework, a QoS based video streaming method is proposed, whereas the packet loss is reduced significantly including extra BER value for the channel coding. From the simulation results it is illustrated that high flexibility and efficacy of the proposed framework is more effective in terms of preventing from frequent loss of frames.
A comparison of multiple word embeddings and performance analysis

Based on IMDB data sets for sentiment analysis, this research evaluates the performance of two types of neural networks, namely FNN and BERT. According to the experimental findings, both varieties of neural networks performed well (over 80%) on IMDB data sets. BERT performs the best of them all. The version of FNN improves when the number of layers is increased. The causes behind BERT's outstanding performance are then further examined in this research. In this article, it is hypothesized that a few factors, such as feature extraction capability and classification capability, account for BERT's exceptional performance. The results show that for the two coupling variables of BERT assumed in this paper, including feature extraction and classification ability, BERT has obvious advantages in feature extracting, and its classification ability has certain advantages over SVM and MLP. The deep learning model has achieved excellent performance in the sentiment classification task. The next step of this paper will focus on the robustness of the BERT model in sentiment analysis.
Security analysis in federated learning based on adversarial attacks

Federated learning can fully use more data to improve the model's performance, but there will be a significant risk once the communication data (such as gradient information) is exposed. The risk of communication data leakage is unacceptable to users. When an attacker gets a little communication data from somewhere, the leaked communication data is a deadly poison. Attackers only need this communication data to launch destructive attacks and quickly break through the defensive line. This paper studies how to defend this risk to improve the security of federated learning through simulated attack experiments. For example, a random pruning strategy compresses the attack model (deep neural network). The purpose is to change the model's structure without affecting the model's performance as much as possible to make the structure of the proxy model (attacker) and the attacked model different to verify whether the strategy can improve the defense capability of the model. The experimental results show that the gradient-based attack method has good generalization. Even if the structure of the neural network model is modified in this paper, it still cannot resist the specific attacks brought by gradient exposure.
Research of feature matching algorithm on panoramic mosaic

Focusing on the application problem according to feature matching and panoramic image stitching, comparing direct stitching and smoothing after feature matching algorithms. Through time performance, synthesis accuracy, and synthesis efficiency, comprehensively compared their effects of synthesizing panoramic images to find a better solution for panoramic splicing. In the study, there are three groups of image pairs with parallax and brightness contrast, then use SIFT algorithm to conduct feature point and matching feature point. The RANSAC algorithm obtains the homograph matrix and completes the panoramic image direct splicing and smoothing test through the matrix transformation. Because of the luminance difference, the panoramic picture after direct splicing will show more obvious light and dark. Though the smoothing treatment could be performed rigidly in the light and dark difference, the deformation, and heavy shadow are easier produced when the disparity and brightness difference are large.