Reviewerly/exHarmony huggingface dataset:
A Multi-Scale Recursive Attention Feature Fusion Network for Image Super-Resolution Reconstruction Algorithm

In recent years, deep convolutional neural networks (CNNs) have made significant progress in single-image super-resolution (SISR) tasks. Despite their good performance, the single-image super-resolution task remains a challenging one due to problems with underutilization of feature information and loss of feature details. In this paper, a multi-scale recursive attention feature fusion network (MSRAFFN) is proposed for this purpose. The network consists of three parts: a shallow feature extraction module, a multi-scale recursive attention feature fusion module, and a reconstruction module. The shallow features of the image are first extracted by the shallow feature extraction module. Then, the feature information at different scales is extracted by the multi-scale recursive attention feature fusion network block (MSRAFFB) to enhance the channel features of the network through the attention mechanism and fully fuse the feature information at different scales in order to improve the network’s performance. In addition, the image features at different levels are integrated through cross-layer connections using residual connections. Finally, in the reconstruction module, the upsampling capability of the deconvolution module is used to enlarge the image while extracting its high-frequency information in order to obtain a sharper high-resolution image and achieve a better visual effect. Through extensive experiments on a benchmark dataset, the proposed network model is shown to have better performance than other models in terms of both subjective visual effects and objective evaluation metrics.
Dynamic Ocean Explorer: XR Experience

The Dynamic Ocean Explorer XR experience allows users to explore oceanographic volumes in mixed reality; combining standard 2D ocean science visualisation approaches such as flow fields with approaches only possible in dynamic 3D such as arbitrary 6-axis clipping, as well as the embodied interaction techniques of natural gestural interaction and direct manipulation. The system is instantiated as mixed reality with pass-through video in a VR headset, and also using Web3D in a standard browser.
“Embark the Journey · Embrace the Universe”: An Interactive System of Astronomy Education Based on Spherical TUI in MR

The widespread adoption and application of MR technology have opened up new possibilities in the field of education. Integrating physical objects and virtual contents in the physical interactive interface provides a larger practical platform for astronomy science education. However, very few attempts are currently at this form of science education. Therefore, we have summarized the design principles for the spherical TUI regarding both interactive interfaces and behaviors. Based on this, we have developed a spherical TUI-based astronomical knowledge system. It delivers users with a more diverse knowledge presentation by a fusion of virtual and reality and mapping interaction of spherical TUI in MR.
“Dongba Script Character Construction Space”: VR science-based interactive experience of pictographs in intangible cultural heritage

The "Dongba Script Character Construction Space" is an interactive science VR experience based on the Dongba script of the Naxi people in Yunnan Province, China, which provides an immersive virtual reality experience based on the traditional Yiyin script theory. [Selmanović et al., 2020] Specifically, this work combines the character construction characteristics of "pictogram", "simple ideographs" and "compound ideographs" to explore the meaning and visual symbolic characteristics of Naxi pictograms through three interesting forms of interaction, and provides more possibilities for the inheritance and development of Dongba in the future by using various forms of interaction.
Peer Review Statement

All papers published in this volume have been reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing. Type of peer review: Double anonymous Conference submission management system: Morressier Number of submissions received: 47 Number of submissions sent for review: 47 Number of submissions accepted: 46 Acceptance Rate (Submissions Accepted / Submissions Received × 100): 97.9 % Average number of reviews per paper: 2.09 Total number of reviewers involved: 25 Contact person for queries: Name: Ts. Dr. Masturah Tunnur Mohamad Talib Affiliation: Faculty of Electrical Engineering &amp; Technology, Universiti Malaysia Perlis, Arau, Perlis, Malaysia. Email: masturah@unimap.edu.my * means value has been edited
Impact of Pre-reading Strategies on Secondary School Students’ English Reading Comprehension Skill: An Experimental Study in Pakistani Context

This study experimented impact of pre-reding strategies on English reading comprehension of secondary level students at public sector schools. It was a quasi-experimental study, which was conducted in two secondary schools of Karachi, Pakistan. It followed pretest posttest approach based on experimental and controlled group. Each of the group had 48 individuals. The tested strategies were related to i) activating prior knowledge, ii) previewing text, iii) predicting and, iv) self-questioning. The data was analyzed using SPSS and independent sample -t test. Results of the study showed that the experimental group that employed pre-reading strategies outperformed in English reading comprehension test than the control group, which employed traditional reading comprehension approach.
Why bundengan musicians always drench their instruments prior to playing

Bundengan is an indigenous musical instrument from Indonesia. It evolved from a bamboo-woven dome originally used by duck herders as a portable shelter during rain and sun. By embedding strings and bars into the dome, the herders turned this shelter into a unique instrument, under which they sit and play music. Bundengan musicians have learned from experience that the instrument sounds better when played under the rain. Nowadays, they use various ways to drench their instruments prior to playing, such as soaking it in fish ponds or putting it under the shower. We explore the physics of why wetter bundengan sounds better. First, we analyze the construction steps of the bamboo dome: the weaving of the bamboo splits, the bending of the woven splits, the layering of bamboo culm sheaths on the woven splits, and the deformation of the sheaths during wetting. Second, we analyze the coupling between the mechanical vibrations in the dome and the acoustical waves from the instrument. Certain conditions of the coupling may lead to an evanescent acoustical field dominating over the radiating acoustical field, which may explain why the best bundengan sound is confined only to under the dome, where the musicians sit.
Research and design of software components for an intelligent chatbot of the company’s service department

International scientific conference “MININGMETALTECH 2023 – The mining and metals sector: integration of business, technology and education” : conference proceedings (November 29–30, 2023. Riga, the Republic of Latvia). Riga, Latvia : “Baltija Publishing”, 2023. Vol. 1. 272 pages.
Multilevel thresholding image segmentation algorithm based on Mumford–Shah model

Abstract Image segmentation is one of the important tasks of computer vision and computer image processing, and the purpose of image segmentation is to achieve the extraction and recognition of the target image region. The classical Mumford–Shah (MSh) image segmentation model is used to achieve the segmentation of images. With the goal to get the best segmentation effect on images by minimizing the MSh energy generalization function, a level set strategy is developed, and a model with global information infinite curve evolution is utilized. However, considering the low efficiency of this model for processing level set curves and the general quality of image segmentation. A multi-layer threshold search scheme is proposed to achieve rapid convergence of the target image level set curve. The experimental results showed that the multi-level thresholding image segmentation algorithm based on the MSh model can significantly improve the segmentation effect of images and reduce the segmentation time. The suggested MSK method outperforms the MPO algorithm, SSA algorithm, and EMO algorithm in the picture segmentation convergence time test, respectively, in terms of runtime efficiency by 356, 289, and 71%. Additionally, it performs superbly in both threshold searches and picture quality tests. The research topic has significant reference value for the study of contemporary computer vision imaging technologies.
Embodied Conversational Agents for Chronic Diseases: A Scoping Review (Preprint)

Background: Embodied conversational agents (ECAs) are computer-generated animated humanlike characters that interact with users through verbal and nonverbal behavioral cues. They are increasingly used in a range of fields, including health care. Objective: This scoping review aims to identify the current practice in the development and evaluation of ECAs for chronic diseases. Methods: We applied a methodological framework in this review. A total of 6 databases (ie, PubMed, Embase, CINAHL, ACM Digital Library, IEEE Xplore Digital Library, and Web of Science) were searched using a combination of terms related to ECAs and health in October 2023. Two independent reviewers selected the studies and extracted the data. This review followed the PRISMA-ScR (Preferred Reporting Items of Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) statement. Results: The literature search found 6332 papers, of which 36 (0.57%) met the inclusion criteria. Among the 36 studies, 27 (75%) originated from the United States, and 28 (78%) were published from 2020 onward. The reported ECAs covered a wide range of chronic diseases, with a focus on cancers, atrial fibrillation, and type 2 diabetes, primarily to promote screening and self-management. Most ECAs were depicted as middle-aged women based on screenshots and communicated with users through voice and nonverbal behavior. The most frequently reported evaluation outcomes were acceptability and effectiveness. Conclusions: This scoping review provides valuable insights for technology developers and health care professionals regarding the development and implementation of ECAs. It emphasizes the importance of technological advances in the embodiment, personalized strategy, and communication modality and requires in-depth knowledge of user preferences regarding appearance, animation, and intervention content. Future studies should incorporate measures of cost, efficiency, and productivity to provide a comprehensive evaluation of the benefits of using ECAs in health care.
CytogeneticsPathBrowser: an educational tool to convert textbook images and captions into flashcards

Abstract Background Competence in reaching the correct diagnosis from analysis of clinical pathology specimens requires exposure to a large volume and breadth of cases. Images from textbooks are critical resources that supplement actual cases with well curated information. However, learning from textbooks has several setbacks. Images from individual textbooks are limited in number and often do not adequately capture variation of the disease entity. Textbooks also do not usually provide a platform for learners to assess their diagnostic abilities. This burdens the learner with creating flashcards for self-assessment, which is manually intensive. Methods To address these limitations, we developed PathBrowser, a web browser-accessible program that leverages the PyMuPDF Python package (Artifex) to extract images and captions from textbooks in PDF format. Captions are written to the image files using ExifTool (Phil Harvey), making the images searchable by keywords. The program then displays the image while hiding the caption, challenging the user to enter the appropriate diagnosis. To minimize work by the user to prepare flashcard questions and answers, the program can automatically generate quiz questions by using natural language processing tools and a Naïve Bayes (NB) classifier (NLTK and SpaCy packages) to identify important terms from the caption as either diagnoses or cytologic features. Results As a proof of principle, we used PathBrowser to build an image repository of myeloblasts and common mimickers, including reactive lymphocytes and chronic lymphoid leukemias, towards training junior pathology residents to identify blasts in peripheral blood and body fluids. In total, PathBrowser extracted 173 images (63 myeloblasts and 110 non-blasts) from 2 textbook sources (Atlas of Diagnostic Hematology by Salama et al., and Hematopathology by Jaffe et al.). We trained a NB classifier to label images as “myeloblast” or “non-myeloblast,” based on keywords in the caption. We manually ascertained that PathBrowser extracted the appropriate caption from 30/30 (100%) images of myeloblasts. Of these, the NB classifier correctly extracted the term “myeloblast” in 28 (93%) images. A survey of pathology residents showed that 89% of respondents agreed the program is a useful pathology learning tool. Conclusions We developed a program that makes reading from textbooks an interactive learning experience. By automating the manual-intensive steps of extracting images and captions and preparing flashcards with quiz questions using caption terms classified by machine learning tools, learners can focus on recognizing the diagnostic features represented by the images. Finally, our program enables the rapid generation of a repository of images from diverse sources, so that learners can browse a wide spectrum of disease entities and their variants.
Title Pending 754

Committee work is a requisite job function for many in academia, yet designing a productive collaborative experience often remains a challenge. In this article, we reflect on our experiences as part of a successful cross-institutional working group and describe strategies to improve leadership structure, group dynamics, accountability, and incentives for collaborative projects.As of January 2023, the National Institutes of Health (NIH) Data Management &amp;amp; Sharing (DMS) Policy requires investigators applying for funding to submit a Data Management and Sharing Plan (DMS Plan) that describes how scientific data will be managed, preserved, and shared. In response to this new policy, a community of more than 30 librarians and other research data professionals convened the Working Group on NIH DMSP Guidance, collaboratively producing comprehensive guidance about the policy for researchers and research support staff. In less than a year, the working group produced glossaries of NIH and data management jargon, an example data management and sharing plan, a directory of existing example plans, checklists for researchers and librarians, and an interactive repository finder.This group was a successful grassroots effort by contributors with diverse expertise and backgrounds. We discuss practical strategies for each stage of activity throughout the lifecycle of the working group; from recruiting members, designing pathways to encourage participation from busy professionals, structuring the meetings to facilitate progress and productivity, and disseminating final products broadly. We invite fellow librarians, data professionals, and academics to apply and build upon these strategies to tackle cross-institutional challenges.
Speckle suppression in holographic phase fringe patterns with different level noises based on FFDNet

In this paper, an ANLVENet speckle suppression method in holographic phase fringe patterns with different level noises is proposed based on FFDNet, combined with asymmetric pyramid non-local block with a verge extraction module. The experimental results are compared to three network models and several representative algorithms. It is shown that the ANLVENet method not only has better superiority in the speckle suppression with different noise levels, but also preserves more details of the image edge. In addition, another speckle noise model is applied in the phase fringe patterns to prove the stronger generalization of the ANLVENet algorithm. The proposed method is suitable for suppressing the speckle with different levels in a large noise range under complex environmental conditions.
Thematic Progression Used on Introduction of Journal of Teaching of English

This study examined the thematic progression in the introduction of the Journal of Teaching of English. This study aimed to determine the types of thematic progressions used and the most common types of thematic progressions used in the introduction of the journal. This study used qualitative descriptive as a research design. The data of this study were from six introduction journals written by students divided into three research areas: teaching, linguistics, and literature. After collecting the data, the data were analyzed based on the Bloor and Bloor (2004) framework. The findings showed that three of the six journals did not apply the four types of thematic progression. The first journal of teaching did not apply the derived theme pattern, whereas the second journal of teaching and the first journal of linguistics did not apply the split rheme pattern. However, overall, this study found four types of thematic progression: constant theme pattern, linear theme pattern, split rheme pattern, and derived theme pattern. Out of four types, the findings also showed that constant theme pattern was the most commonly used type (134 times), followed by linear theme pattern (63 times), split rheme pattern (22 times), and derived theme pattern (14 times). This study concluded that students applied various types of thematic progression in making the introduction of the journal in order to become coherent.
Accurate and Fast VR Eye-Tracking using Deflectometric Information

We present two methods for fast and precise eye-tracking in VR headsets. Both methods exploit deflectometric information, i.e., the specular reflection of an extended screen over the eye surface.
Novel circular fringe projection method using conical mirror

We present a novel 3D circular reconstruction method that uses a conical mirror to project the fringe patterns. The proposed approach is based on the principle of uni-axial projection method which defines the relationship between the phase information in the DFP system and the 3D geometry of the 360-degree view of the environment. Furthermore, the proposed method is capable of producing accurate 3D geometry of the environment without using the conventional method projector calibration method, which is suitable in scanning unstructured environments such as inside tunnels and bridges.
R2-PBFT: An Improved PBFT Consensus Algorithm Based on Hash Ring and Reputation Model

To address the issue of poor stability in consensus networks caused by arbitrary selection of main nodes in the PBFT consensus algorithm, this paper proposes a improved algorithm named R2-PBFT, which means Random and Reliable PBFT and is improved from PBFT algorithm based on hash ring and reputation
Integrated cyber resilience strategy for safeguarding the national infrastructure of Somalia: Addressing threats

In today’s digital world, cyber resilience is key element for the security and steadiness of nations. It refers to the capacity to get ready for, adjust to, endure, and swiftly bounce back from cyber threats, playing a crucial role in protecting a nation's critical infrastructure. This research outlines a comprehensive cyber resilience strategy to protect Somalia's critical infrastructure from evolving cyber threats. The study analyzes the current threat landscape, identifies vulnerabilities in key sectors, and proposes a comprehensive approach. The findings of the study present a multifaceted strategy that combines inculcation, international collaboration, and recognized frameworks, forming a structured approach to identify vulnerabilities, protect critical assets, and respond effectively to cyber incidents. The proposed strategy intents to enhance Somalia's cyber resilience, offering a practical strategy for proactive defense against evolving threats and securing a digital future.
The Features of Contemporary Communication in Student Online Communities on the Example of Kostroma State University

The article deals with the problem of modern communication of universities with the student audience in the online space. In order to identify the features of user involvement in the work of university groups in social networks, the interests of the target audience and the specifics of user actions, a comprehensive study was conducted, based on the methods of expert survey, event analysis, content analysis, case study and index analysis. The respondents of the expert survey were 18 representatives — administrators of university groups in social networks from Yaroslavl, Kostroma, and Cherepovets. The study also included a review of the posted content in the main Kostroma State University communities on the VK social network and Telegram messenger, the VK student union group in two spring academic months (March — April) and summer (July — August). As a result, classifications of posts posted in online groups by form and content were developed, user involvement in a particular type of content was calculated, the most frequently used publications in different groups were identified, the dynamics of posting posts depending on the type of site and time period were revealed.
Assessing the Efficacy of Improved Learning in Hourly Global Irradiance Prediction

Increasing global energy consumption has become an urgent problem as natural energy sources such as oil, gas, and uranium are rapidly running out. Research into renewable energy sources such as solar energy is being pursued to counter this. Solar energy is one of the most promising renewable energy sources, as it has the potential to meet the world’s energy needs indefinitely. This study aims to develop and evaluate artificial intelligence (AI) models for predicting hourly global irradiation. The hyperparameters were optimized using the Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton training algorithm and STATISTICA software. Data from two stations in Algeria with different climatic zones were used to develop the model. Various error measurements were used to determine the accuracy of the prediction models, including the correlation coefficient, the mean absolute error, and the root mean square error (RMSE). The optimal support vector machine (SVM) model showed exceptional efficiency during the training phase, with a high correlation coefficient (R = 0.99) and a low mean absolute error (MAE = 26.5741 Wh/m<sup>2</sup>), as well as an RMSE of 38.7045 Wh/m² across all phases. Overall, this study highlights the importance of accurate prediction models in the renewable energy, which can contribute to better energy management and planning.