Reviewerly/exHarmony huggingface dataset:
Level of Stress, Coping Strategies and Academic Achievement of College Students during HyFlex Learning

Effective stress management strategies correlate with improved academic performance in college students, yet inconsistent findings in existing research warrant further investigation. This study explored the intricate interplay between stress levels, coping mechanisms, and academic achievement in HyFlex learning. A stratified random sample of 111 students from five specializations within the Bachelor of Secondary Education program participated. Utilizing a descriptive-correlational design, data were collected through validated self-report questionnaires and a weighted general average. Subsequent descriptive statistics and bivariate correlation analysis revealed moderate stress levels among participants who preferred task-oriented coping strategies. Interestingly, a significant positive association was observed between stress levels and academic achievement and emotion-oriented coping, while a negative correlation emerged between stress and task-oriented coping. Avoidance-oriented coping, conversely, displayed a significant negative association with academic success. These findings underscore the crucial role of educational institutions in providing robust support mechanisms for stress management and cultivating a task-focused learning environment to optimize student well-being and academic performance within the HyFlex model.
How Does the “Default Mode” Network Contribute to Semantic Cognition?

This review examines whether and how the “default mode” network (DMN) contributes to semantic processing. We review evidence implicating the DMN in the processing of individual word meanings and in sentence- and discourse-level semantics. Next, we argue that the areas that make up the DMN contribute to semantic processing by coordinating and integrating the simultaneous activity of local neuronal ensembles across multiple multimodal and unimodal cortical regions, creating a transient, global neuronal ensemble. The resulting ensemble implements an integrated simulation of phenomenological experience—that is, an embodied situation model—constructed from various modalities of experiential memory traces. We argue that these situation models are necessary not only for semantic processing but also for aspects of cognition that are not traditionally considered semantic. Although many aspects of this proposal remain provisional, we believe that it provides new insights into the relationships between semantic and nonsemantic cognition and into the functions of the DMN.
HP-FLDet: A High Performance Joint Face and Landmark Detector

Abstract Face detection and landmark localization are usually the fundamental and important steps of facial analysis. The accuracy degradation of any task has impacts on the accuracy and robustness of the downstream analysis. In most facial analysis systems, face detection and landmark detection, as two independent tasks, are predicted sequentially with single-task detectors respectively, which suffer from the higher complexity and poorer consistency. In contrast, multi-task joint face and landmark detectors are more efficient and have more shared features. However, when two tasks are predicted in one model, it is difficult to improve the accuracy of all tasks simultaneously, due to the different requirements of the different targets to be detected. In our opinion, the multi-task detection model, integrating the perception ability of both scale variation and detailed texture information for face and landmark detection, is arduous but important in unconstrained settings. In this paper, a High-Performance joint Face and Landmark detector(HP-FLDet) is proposed, which can predict facial bounding boxes and landmarks in single stage and improve the accuracy of both face detection and landmark localization simultaneously. In this detector, the context inception block and scale-aware multi-task strategies are designed to resolve extreme scale variance and improve the perception ability of detailed texture information. It demonstrates superior performance on both face and landmark detection datasets including AFW, PASCAL Face, FDDB, Wider Face and AFLW. Especially, it achieves SOTA results on the most challenging WIDER FACE dataset with 0.970(Easy), 0.963(Medium), 0.921(Hard) mAP on the test subset, which outperforms all state-of-the-art rivals.
Discovering the Underlying Motivations for Empowering Education Through Innovation

Educational innovation has evolved as a revolutionary response to traditional teaching methods' limitations in educating pupils for the complexities of today's society. This method integrates technology, global viewpoints, and inclusive practices, motivated by the need to stimulate creativity, critical thinking, and collaboration. Education can build dynamic learning environments that encourage students to become active participants in their education by embracing innovation. This article investigates the incentives that drive educational innovation, emphasizing the importance of technological integration, leadership, global viewpoints, and inclusivity. This study provides valuable insights for educational practitioners, policymakers, and researchers through discussions, observations, and a comprehensive literature review, emphasizing the importance of embracing innovation to meet the evolving needs of students and prepare them for a rapidly changing future.
Perspektif Belajar dengan Seni Tari Tradisional di Sekolah Menengah Pertama

This research aims to determine the perspective of learning with South Sulawesi Traditional Dance in Junior High Schools. This type of research uses qualitative research with an ethnographic approach. The subjects in this research were teachers and students at SMP Negeri 22 Bantimurung. The results of this research show that students who are already at the junior high school level have been equipped with sufficient knowledge to develop so that the learning process will be more challenging for teachers in order to increase students' interest and motivation to learn art in the classroom, one of which is by highlighting traditions and culture. Locally in the South Sulawesi area, namely the basic movements of South Sulawesi traditional dance. So, the role of arts education in junior high schools is an effort to improve students' abilities, especially in developing interests, increasing creative work, as well as knowing regional arts and the values ??contained therein. Through arts education, students are facilitated in the process of growth and development in three domains as learning outcomes, namely, cognitive, affective and psychomotor.
TRANS-CNN Based Gesture Recognition for mmWave Radar

In order to improve real-time performance of gesture recognition by micro-Doppler map of mmWave Radar, the point cloud based gesture recognition for mmWave Radar is proposed in this paper.Two steps are carried out for mmWave Radar based gesture recognition. The first step is to estimate the point cloud of the gestures by 3D-FFT and the peak grouping. The second step is to train the TRANS-CNN model by combining the multi-head self-attention and the 1D-convolutional network, so as to extract the features in the point cloud data at a deeper level to categorize the gestures. In the experiments, TI mmWave Radar sensor IWR1642 is used as benchmark to evaluate the feasibility of the proposed approach. The results show that the accuracy of the gesture recognition reaches 98.5%. In order to prove the effectiveness of our approach, a simply 2Tx2Rx Radar sensor is developed in our lab and the accuracy of recognition reaches 97.1%. The results show that our proposed gesture recognition approach achieves the best performance in real-time with limited training data, in comparison with the existing methods.
Fast Fake – easy to train Face Swap model

&amp;quot;Deep fake&amp;quot; technologies are often associated with face-swapping algorithms based on images or videos. Although much research is focused on developing these techniques, there is still room for improvement, especially in human and visual assessment. In this study, we present an innovative approach to the problem of face replacement based on one model while preserving background features. Our model uses the Adaptive Attentional Denormalization method from FaceShifter while integrating identity features from the ArcFace and BiSeNet models to support the attribute extraction process. We used Fast GAN as a generative model to optimize and accelerate the training process on smaller data sets. Our research proves the effectiveness of the proposed approach by combining innovative methods and architectures in one coherent solution.
PRODIGY: Probing Resilience Of Domain-wall Interactions at Gauge Theory

Examining the axion-dilaton model within supergravity, we focus on elucidating the construction and stability of domain walls. Emphasizing holographic vitrification action, we unveil insights into domain wall formation in gauge theories with periodic vacuum structures. Featuring a QCD-like axion term and a stabilizing dilaton, our model is scrutinized for conductivity changes under weak disorder. Notably, the system maintains perfect conductivity with a leading-order conductivity correction. Strong disorder emerges as the catalyst for transitioning to an insulator state. This study offers a comprehensive understanding of the axion-dilaton model's resilience and behavior under varying conditions.
The Revised Schrödinger Equation as a Solution of Measurement Paradox: A Unified Model of the U-procedure and R-procedure

The present paper reports an alternative solution of the measurement problem in quantum theory. The measurement problem can be characterized as that the U-procedure verses the R-procedure. The R-procedure is tested by the Yes/No measurement originally proposed by von Neuman and discussed in details by Penrose. We propose a novel stochastic sampling method to tackle the measurement paradox. Each testing sample produces a pair of Yes-number c and No-number d, which in turn generates a sample phase with respect to the exponential form of (c+id). All the sample phases forms a group GR. Taking GR as the sampling potential, combined with the dynamic phase group GU，we establish a unified model of U-procedure and R-procedure for the evolution of wavefunction. Based on the Born rule, the probability of a sample is given by the squared magnitude of （c+id）. Some metaproperties of the new U-R model, such as natural transformation, consistency, and completeness, are presented. The present work provides a new picture of quantum mechanics and alike. The measurement problem widely exists in dynamic analysis, higher cognition, and large data modeling. Thus, the work reported here has a wide range of applications. Keywords: The measurement problem; U-R procedures; the Yes/No type measurement; stochastic sampling; sample phase; Born probability.
A New 2D Cross Hyperchaotic Sine-Modulation-Logistic Map and Its Application in Bit-Level Image Encryption

Chaotic theory is commonly being researched for application in image encryption scheme (IES). In this paper, a novel two-dimensional cross hyperchaotic Sine-modulation-Logistic map (2D-CHSLM) based on the famous Sine and Logistic maps. The hyperchaotic behaviors of 2D-CHSLM is testified with the help of their bifurcation diagrams, trajectory plots, Lyapunov exponents, sample entropy, C0 complexity, permutation entropy and 0-1 test. A new bit-level IES with traditional encryption structure is proposed utilizing 2D-CHSLM. The 2D-CHSLM-IES performs a 2D-CHSLM-based bit-level confusion using zig-zag transform and a 2D-CHSLM-based cross coupled diffusion operations for generating a highly secure cipher-image. Then the simulations and security analyses are further carried out with the help of key space, key sensitivity, histogram, correlation, information entropy, differential attack, noise and data loss attacks, prove that the security of the proposed 2D-CHSLM-IES
Sedentary Behavior, Physical Activity and Functionality of Older Care Home Residents

Background: Nursing home residents (NHRs) have special needs and may experience reduced functionality, higher sedentary behavior time (SBT) and decreased physical activity (PA). This study aimed to characterize NHRs based on SBT, PA, and functional performance (FP), and to identify associations between these factors. Methods: Cross-sectional study with 65 NHRs aged ≥60, evaluated by accelerometer (SBT, PA) and the following tests: Timed Up and Go (TUG), Short Physical Performance Battery (SPPB), Barthel Index (BI), and Mini-Mental State Examina-tion (MMSE). Health-related variables and anthropometry were assessed. The FP (TUG, SPPB, BI), SBT, PA intensities were used for K-means clustering analysis. Results: The cluster analysis identified: C1 – better FP, shorter SBT, and longer time in PA intensities; C2 - lower FP, longer SBT, and shorter time in PA. In addition, C2 were older, with lower MMSE, lower body mass index, and walking aids use. The SBT showed a negative weak correlation with BI. The moderate PA (MPA) was moderately correlated with the SPPB and strongly correlated with the TUG and BI. Conclusions: MPA is strongly associated with better FP and independence. NHRs have dif-ferent physical and cognitive profiles, which indicates the need for personalized strategies to prevent disability and increase PA.
Musical scales optimize pitch spacing: A global analysis of traditional vocal music

Abstract The standard model of musical scales is derived from instrument tunings. However, the study of vocal scales – most especially in indigenous cultures – has been all but ignored. The voice is almost certainly the original musical instrument, and so an analysis of vocal scales provides a more naturalistic means of understanding the evolution of music. In particular, we explore the idea that the structure of musical scales is a reflection of the vocal imprecision inherent in the way that people sing, regardless of culture. To investigate this issue globally, we carried out a large-scale computational analysis of 418 ethnographic field recordings of vocal songs from indigenous/traditional cultures, spanning the 10 principal musical-style regions of the world. The results revealed that vocal scales have reliably larger intervallic spacings between pitch-classes than do instrumental scales in Western culture. In addition, the mean interval-size of the scales was significantly correlated with people’s imprecision in singing pitches across the world regions. These results lend support to a physiological model in which musical scales optimize pitch spacing in order to accommodate the imprecision inherent in vocal production and thereby maintain distinguishability between pitch-classes.
Devising Breast Cancer Diagnosis Protocol through Machine Learning

Breast cancer is a multifaceted disease that has many subcategories characterized by unique genetic features. This research focuses on two important subgroups, including ER+ and HER2-. We conducted an analysis of gene expression data obtained from reliable sources (Array Express: E-GEOD-52194, E-GEOD-75367, and E-GEOD-58135) in order to reveal the complex molecular details of these subtypes. The computational pipeline we used identified 396 genes that exhibited distinct patterns of gene expression in ER+ and HER2- breast cancers. The diagnostic and prognostic significance of these genes was evaluated using machine learning methods, namely SVM and decision tree models. Metrics like as accuracy, sensitivity, and specificity provide insights into their usefulness. Furthermore, the use of the STRING database for network analysis revealed significant signaling pathways and biological processes associated with the development of ER+ and HER2- breast cancer. The results of our research enhance our comprehension of these subcategories, which might possibly facilitate more accurate diagnoses and focused treatment interventions. To summarize, this work provides valuable information on the genetic foundations of ER+ and HER2- breast cancer, which has potential implications for enhancing patient treatment and outcomes.
Peningkatkan Hasil Belajar Bahasa Indonesia Melalui Metode Role Playing

The problem in this classroom action research is that the low value of Indonesian through the role playing method can improve the speaking skills of Class V students at SDN 219 Ara, Bonto Bahari District, Bulukumba Regency. Bulukumba. The approach used is a qualitative approach. The type of research used is classroom action research which consists of two cycles, where each cycle consists of two meetings, with activity procedures including planning, implementation, observation and reflection. The subjects in this study were teachers and fifth grade students at SDN 219 Ara, Bonto Bahari District, Bulukumba Regency. Those who are actively registered in the odd semester of the 2012/2013 academic year have 10 students, consisting of 9 boys and 1 girl. Data collection techniques used are observation, tests and documentation. The data analysis technique used is descriptive quantitative analysis. The indicators of the success of this research are the indicators of the process and results of speaking skills. The results show that with the optimal application of the Role Playing method, student learning activities increase, this can be seen in the first cycle being in the medium category because it is seen from the results of the speaking skills test at the end of the first cycle where the average score The average student has not reached the predetermined KKM and in the second cycle is in the very high category. Thus there is an increase in students' speaking skills in Indonesian subjects after the implementation of the Role Playing method can increase.
Kontribusi Latihan Passing Bawah Berpasangan dan Passing Bawah Ke Dinding Terhadap Ketepatan Passing Bawah

This research was motivated by the inability of the volleyball players at SDN 1 Pasirjati to make down passes so that when they were about to make a pass the ball was often not directed which resulted in the ball going out of court. This research aims to determine the effect of pair bottom passing practice and bottom passing practice against a wall on volleyball bottom passing accuracy. This type of research uses quantitative research and uses pre-experimental methods. The instrument used in this research was accuracy of passing down (Brumbach) using a sample of 12 volleyball players from SDN 1 Pasirjati. The sampling technique in this research uses a total sampling technique. The research was conducted in the field at SDN 1 Pasirjati. The results of the study showed that the results of the paired down passing exercise had an average increase of 2 times, while the results of the down to the wall passing exercise had an average increase of 3 times, so the results of the down to the wall passing exercise were greater and had a significant influence on increasing the ability to accurately pass volleyball.
The Importance of Digital Technology and Clustering for Innovation in MSEs. Evidence from Secondary Data in Indonesia

This paper explores the relationship between innovation and these two determinants in micro and small enterprises (MSEs) in the manufacturing industry in Indonesia, using secondary data. The key question in this research: is there evidence of the importance of DT and clustering for innovation capability in MSEs in Indonesia? The paper analyzes secondary data from Indonesia’s National Agency of Statistics and reviews key literature on innovation and digitalization in MSEs, and industrial cluster development in Indonesia. It is found that the number of industrial clusters of micro-, small-, and medium-sized enterprises (MSMEs) is concentrated on the island of Java, where more than 50% of the population is located, and is the most advanced region in economic development and industrialization in Indonesia. The majority of MSME clusters are in the food industry and woodworking industries. Only a very few of MSEs in the manufacturing industry use the Internet and do innovation. The type of innovation mostly is product innovation. Both relationships between MSEs doing innovation and MSEs using the internet and the total number of clusters are positive. But, statistically, only the relationship between the number of MSEs doing innovation and use of the internet is significant.
An analysis of digital literacy skills of high school students in biology

&lt;p&gt;Digital literacy is a crucial skill for understanding information from various sources, such as the use of the internet and other digital media as a learning resource. Navigating the internet is an important skill to master to keep updated with the development of information and communication technology in the era of Industrial Revolution 4.0 and to master one of the 21st-century skills. Skills that someone should have in digital literacy include internet searching, hypertextual navigation, evaluating information, and synthesizing information. This study aims to determine the digital literacy skills of tenth-grade high school students in biology class. The research method follows the quantitative descriptive method. The population and sample were 62 tenth-grade high school students. The data collection technique is in the form of questionnaires focusing on four aspects of digital literacy. The results indicate that the digital literacy of tenth-grade high school students with an average score of 44% is in the fair category. Meanwhile, the results for each aspect of the digital literacy indicator obtained different scores, namely internet searching at 47% (fair), hypertext navigation at 27% (fair), evaluating information at 40.32% (fair), and synthesizing information at 60.48% (good). This research suggests how stakeholders can issue policies as a basis for improving students' digital literacy to support the learning process focusing more on 21st-century skills.&lt;/p&gt;
Design of Computerized Patient Registration Application System at Tanjung Pati Health Center

One of the shortcomings of manual patient registration systems is the procedures that affect the efficiency of service care to patients. Therefore, researchers are interested in designing a computerized patient registration application using Microsoft Access software. The type of research used is Research and Development (R&amp;D). This research was conducted at Tanjung Pati Community Health Center, with in-depth interviews with two registration officers. The research results show that the data elements needed to design the patient registration application system, sourced from the Patient Registration Book, will be developed by creating an application system using UML modeling. The application system undergoes Black Box Testing with the result that all components run well. The application system is efficient, with an average comparison of manual patient registration time to system patient registration of 420:180 seconds for new patients and 360:33 seconds for existing patients. The application system is efficient according to the results of interviews with informants. Therefore, the design of the computerized patient registration application system using Microsoft Access meets the needs of the community health center and is efficient in terms of patient registration time. It is recommended that the patient registration application be used continuously in the medical records unit at Tanjung Pati Community Health Center.