Reviewerly/exHarmony huggingface dataset:
Observation of the non-Hermitian skin effect and Fermi skin on a digital quantum computer

Abstract Non-Hermitian physics has attracted considerable attention in the recent years, in particular the non-Hermitian skin effect (NHSE) for its extreme sensitivity and non-locality. While the NHSE has been physically observed in various classical metamaterials and even ultracold atomic arrays, its highly-nontrivial implications in many-body dynamics have never been experimentally investigated. In this work, we report the first observation of the NHSE on a universal quantum processor, as well as its characteristic but elusive Fermi skin from many-fermion statistics. To implement NHSE dynamics on a quantum computer, the effective time-evolution circuit not only needs to be non-reciprocal and non-unitary, but must also be scaled up to a sufficient number of lattice qubits to achieve spatial non-locality. We show how such a non-unitary operation can be systematically realized by post-selecting multiple ancilla qubits, as demonstrated through two paradigmatic non-reciprocal models on a noisy IBM quantum processor, with clear signatures of asymmetric spatial propagation and many-body Fermi skin accumulation. To minimize errors from inevitable device noise, time evolution is performed using a trainable optimized quantum circuit produced with variational quantum algorithms. Our study represents a critical milestone in the quantum simulation of non-Hermitian lattice phenomena on present-day quantum computers, and can be readily generalized to more sophisticated many-body models with the remarkable programmability of quantum computers.
Prediction of turbulent flows behind cylinder arrays via Echo State Networks

Abstract This study aims at the prediction of the turbulent flow behind cylinder arrays by the application of Echo State Networks (ESN). Three different arrangements of arrays of seven cylinders are chosen for the current study. Three different wake flow regimes are represented by these arrays: single bluff body flow, transient flow, and co-shedding flow, which allows inherently similar, yet very different, turbulent flows to be studied. The data is reduced by Proper Orthogonal Decomposition (POD), and then the Time Coefficients of the POD Modes (TCPM) are predicted by the ESN. The ESN is optimized with respect to its three main hyperparameters, Input Scaling (INS), Spectral Radius (SR), and Leaking Rate (LR), in order to produce the best predictions in terms of Weighted Prediction Score (WPS). In general, the ESN is capable of imitating the complex dynamics of turbulent flows even for long periods. Furthermore, the mutual interdependencies of the TCPM are well preserved. However, the ESN’s performance in different hyperparameters depends on the flow characteristics. Generally, as flow dynamics become faster and more intermittent, larger LR and INS values make better predictions, whereas less clear trends in SR values tend to emerge.
SMART EDUCATION TECHNOLOGIES IN HIGHER EDUCATION: POSSIBILITIES AND PROSPECTS OF APPLICATION IN UKRAINE

The Ukrainian education system is actively engaged in the processes of Eurointegration, prompting leaders, researchers, and educators from many domestic educational institutions to explore the possibilities and prospects of implementing SMART education technologies in the learning process. This issue is relevant as it aligns with the contemporary trends in the development of higher education in Ukraine and globally. SMART education allows for the high-level resolution of a wide range of issues related to the quality management of educational services.
ENHANCING ICT CURRICULUM FOR A MASTER'S DEGREE PROGRAMME IN PROFESSIONAL EDUCATION AND COMPUTER TECHNOLOGIES IN UKRAINE

The Russian war against Ukraine and the restrictions of the COVID-19 pandemic have forced the Ukrainian education system to make an urgent transition to distance learning [1]. This has highlighted the urgent need for teachers and students to use information and communication technologies (ICTs) effectively for teaching, communication, and collaboration. Professional education programmes must equip graduates not only to use ICT, but also to integrate it seamlessly into their work [2]. This study focusses on improving the ICT curriculum for a Master's Degree Programme in Professional Education and Computer Technologies in Ukraine to meet the pressing needs of distance education.
METHODS OF IMPLEMENTATION OF FLIPPED LEARNING TECHNOLOGY IN THE PROCESS OF TRAINING STUDENTS IN INSTITUTIONS OF HIGHER AND PROFESSIONAL PRE-HIGHER EDUCATION

The article examines the problem of substantiating the expediency of using the "flipped learning" technology in the process of training future specialists and introducing innovative methods into teaching activities. The main models of the flipped classroom are considered, as well as the main approaches to solving the problem of organizing the educational process with the involvement of the "flipped learning" technology to ensure the quality of providing educational services in the process of training future specialists. The article also analyzes the main advantages of this technology in the conditions of mixed and distance learning.
Analisis Tone Warna Dalam Sinematografi Dalam Menciptakan Efek Bahagia Pada Film Dokumenter “ Permata Di Tengah Danau Toba” Sutradara Andi Hutagalung

This research investigates the role and impact of the use of color tones in documentary films. Through analysis of a number of leading documentary films, this study aims to understand how choosing color tones can influence the audience's experience and convey messages more effectively. The research results show that color tones can create atmosphere, highlight themes, and influence audience emotions. These findings provide additional insight for ocumentary filmmakers to enhance the power of their visual narratives through intelligent use of color palettes
Giulia Pepe, New migrations, new multilingual practices, new identities: The case of post-2008 Italian migrants in London. Cham: Springer, 2022. Pp. 219. Hb. £89.99.

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Nuria Lorenzo-Dus, Digital grooming: Discourses of manipulation and cyber-crime. Oxford: Oxford University Press, 2022. Pp. 240. Hb. £64.

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Greedy‐based user selection for federated graph neural networks with limited communication resources

Abstract Recently, graph neural networks (GNNs) have attracted much attention in the field of machine learning due to their remarkable success in learning from graph‐structured data. However, implementing GNNs in practice faces a critical bottleneck from the high complexity of communication and computation, which arises from the frequent exchange of graphic data during model training, especially in limited communication scenarios. To address this issue, we propose a novel framework of federated graph neural networks, where multiple mobile users collaboratively train the global model of graph neural networks in a federated way. The utilization of federated learning into the training of graph neural networks can help reduce the communication overhead of the system and protect the data privacy of local users. In addition, the federated training can help reduce the system computational complexity significantly. We further introduce a greedy‐based user selection for the federated graph neural networks, where the wireless bandwidth is dynamically allocated among users to encourage more users to attend the federated training of neural networks. We perform the convergence analysis on the federated training of neural networks, in order to obtain some more insights on the impact of critical parameters on the system design. Finally, we perform the simulations on the coriolis ocean for reAnalysis (CORA) dataset and show the advantages of the proposed method in this paper.
Persepsi Kesiapan, Sikap dan Motivasi Belajar Mandiri terhadap Pembelajaran Matematika secara Kolaboratif Berbasis Online

The research aims to describe the readiness, attitude and motivation of self-learning towards collaborative online based mathematics learning during the covid-19 pandemic. The researcher applies a quantitative descriptive methods in this study. Data collection has been done by giving three kinds of questionnaires including readiness, attitude and self learning motivation during covid-19 pandemic, and has distributed to 80 students in 3 Senior High School and 1 Vacational High School at Nuha district. The result of this research shows that the students are ready for Mathematics learning collaborative online based during covid-19 pandemic. That is supported by their ability to operate the computer and the usage of internet as well as their online learning experience they have been through for 2 years in online learning situation. Students' motivation towards learning mathematics through the implementation of online based collaborative learning is inconsistent even though it is in moderate level of motivation. Some students prefer the face to face learning process to online learning process and think that the previous learning will provide better learning outcomes. This is a challenge for teachers to prepare for the new normal phase with more interesting teaching material, strategies and learning methods by the development of digitalization of learning
ARVMex: A web application for obtaining acoustic reference values for forensic studies in Spanish

Abstract Forensic speech experts using the auditory-acoustic-phonetic approach face different challenges when dealing with recordings collected under different technical conditions. We developed ARVMex tool to provide acoustic reference values to describe variation due to technical conditions in recordings. The tool employs a corpus of Spanish speakers, generating descriptive statistics based on different attributes, including speaker characteristics, different sounds, and on two technical conditions: face-to-face interviews and telephone conditions. The results indicate that, for the fundamental frequency, the mean values of the interview attribute accurately depict the behavior of each vowel by gender, whereas the mean values of the telephone attribute exhibit deviation from the general average. In relation to vowel formants, reference values per vowel, gender, and technical conditions must be established considering variations among vowels and the overall mean. The tool presented here aims to assist experts by providing insights into the variations in the measurements of acoustic properties due to technical conditions.
Pembuatan Peta Resiko Bencana di Desa Kubang Tangah Kota Sawahlunto dengan Metode Arc Toolbox

Landslide movement is the activity of a balance disturbance process that causes the movement of masses of soil and/or rock from higher to lower areas. The cause of landslides is that the driving force on the slope is greater than the resisting force. Several factors cause landslides such as rainfall, steep slopes, soil density, rock type, land use and vibration. Sawahlunto City is one of 19 cities/regencies in West Sumatra Province that has a high level of vulnerability to landslides. Areas prone to landslides can be identified by utilizing remote sensing data and geographic information systems. This service is carried out by making maps of areas prone to landslides using parameters that cause landslides, including rainfall, soil type, height, slope and land use. These parameters will be processed and analyzed with the help of the ArcToolbox method, where ArcToolbox can be used to detect landslide areas in Kubang Tangah Village. The analysis process is carried out by using the spatial analysis tools feature found in ArcGIS software. Community service produces a slope map that can illustrate the vulnerability of landslides. Obtain results in the form of a landslide vulnerability level map which has 4 vulnerability classes, including non-prone vulnerability class, low vulnerability class, medium vulnerability class, and high vulnerability class.
ANALYSIS OF STUDENTS’ DIFFICULTIES IN TRANSLATING DESCRIPTIVE TEXT FROM INDONESIAN INTO ENGLISH

The aims of this research was to find out the students’ difficulties into English and to know how the students were cope with the difficulties in translating descriptive text from Indonesian into English at the eighth grade students of junior high school Tri Dharma Palembang. The descriptive qualitative research was used in this sample of this research. The sample of this research was the eighth grade students at Junior High School Tri Dharma Palembang. There were fifteen participants of students and there was one participant of their English teacher. The data was taken by using test and interview as the instrument. The research finding showed that the highest percentage of students’ difficulties in translating was grammar (27%). the highest number of the students’ grammar difficulties was phrase (45%). The second difficulty faced by students was clarity and cohesion &amp; naturalness (24%). The third difficulty face by students was spelling &amp; style (14%) and the last difficulty was realizing &amp; understanding (11%). Based on the result of students and their English teacher interview matrix, it showed that students asked their friends and teacher to help solving their problem. It could be concluded that students had difficulties in translating Indonesian descriptive text into English was Grammar and the students asked their friends or teacher to give them a help.
Pengelompokan Provinsi di Indonesia Menggunakan Time Series Clustering pada Sektor Ekspor Nonmigas

Indonesia's export activities are dominated by non-oil and gas exports consisting of four sectors, namely the processing industry, agriculture, mining, and others. The government must pay attention to non-oil and gas exports for each province because exports can play an essential role in a country's economic growth. This study was conducted to cluster provinces in Indonesia using time series clustering in the non-oil and gas export sector based on data patterns concerning Dynamic Time Warping (DTW) distance. The sectors used in this study are the manufacturing industry sector and the agricultural sector in 34 Indonesian provinces in the period 2017 - 2021. Time series clustering analysis uses the average linkage method with DTW distance and the selection of the optimum number of clusters using the silhouette coefficient method. The results of the analysis in the processing industry sector resulted in 3 optimum clusters, namely cluster 1 consisting of 1 province that has high processing industry exports, cluster 2 consisting of 8 provinces that have medium processing industry exports, and cluster 3 consisting of 25 provinces that have low processing industry exports. As for the agricultural sector, it produces 2 optimum clusters, namely cluster 1 consisting of 5 provinces that have high agricultural industry exports, and cluster 2 consisting of 29 provinces that have low agricultural industry exports. The clustering results in the processing industry sector and the agricultural sectors have a silhouette coefficient value of 0.778 and 0.798, so it is said to have a strong cluster structure.
A Conversation Analytic Study on Clicks in Mandarin Chinese

From the perspective of Conversation Analysis, this paper analyzes clicks in daily Chinese communication. Data analysis shows that clicks generally appear in negative contexts and play an important role in conveying the speaker’s negative attitudes or feelings. This article first discusses the main ways that the linguistic resource of clicks helps the speaker convey his/her negative attitudes: presupposing the click-producer’s disdain, presupposing the speaker’s dissatisfaction, presupposing the speaker’s impatience, and strengthening the speaker’s negative attitude. On this basis, the author explores the main two functions of clicks in Chinese conversation, that is serving as a signal of topic transition and maintaining harmonious social relations.
The Impact of Nutritional School Based Feeding Program on Academic Achievement of Selected Elementary Learners in West Philippines

This study investigates the impact of nutritional school-based feeding programs on the academic performance of 45 elementary learners. This research method uses a quasi-experimental design with a pretest and posttest structure; a two-part questionnaire was the primary research tool. The first part gathered demographic information, while the second assessed participating students’ nutritional status and academic performance. Researchers administered the questionnaire to parents or caregivers, selected students systematically, traced household addresses, and conducted home interviews. The study results showed that the general weighted average increased noticeably and statistically significantly after implementing school-based feeding programs. Subsequent investigation, however, revealed a fascinating finding: the gains in academic achievement did not correspond consistently with the varied profiles of respondents, including age, gender, socioeconomic status, and educational attainment. The research highlights the necessity for additional investigation into the impact of nutrition on academic achievement.
End-to-end VVC encoding for energy-aware HDR rendering

The production, transmission and display of video content requires significant amounts of energy. Whether broadcasting or streaming a video, its display on modern televisions is responsible for a significant proportion of the energy consumption. This paper proposes a framework for analyzing and processing High Dynamic Range (HDR) video frames that allows a modern screen to use less energy when displaying these frames. The content is analyzed prior to encoding and transmission, generating metadata that are attached to the content. After reception by a compatible display, the metadata is then used along with display parameters and user settings to adapt the peak brightness of the content. Picture quality is assessed objectively and subjectively, while in the meantime, we analyze the influence of the peak brightness over the power consumption of the screen. All these analysis provide us new insights to propose an energy-aware HDR rendering.
3D rooms map concept based augmented reality for green library

Abstract Green libraries are an exciting topic for creating environmentally friendly buildings. Libraries are synonymous with book lending services and comfortable reading rooms. The green library concept will be in line with increasing the comfort of library visitors. Libraries with large buildings need room maps for visitors to find room information. This research aims to create a room map with the concept of Augmented Reality (AR). Room maps generally use 2D images that provide information or instructions for all rooms in a building. The Augmented Reality approach as a 3D-based room map will undoubtedly provide a different experience to library visitors. Creating an AR room map will apply the Multimedia Development Life Cycle (MDLC) method. This method is suitable for application in multimedia product development. However, the resulting product is not only used as room map information but can also be used as a library promotional tool.
An Analysis of the Arts Curriculum Framework in India According to the ‘National Curriculum Framework for School Education 2023’ Document

The purpose of this study is to explore and analyze the arts curriculum framework, including music subjects, in India's newly announced 'National Curriculum Framework for School Education 2023', in order to examine various implications for Korea's music curriculum. For this purpose, this paper utilizes a literature research method to examine India’s curriculum documents, focusing on items such as 'document structure', 'competency', 'rationale and aims', 'content system and achievement standards' and ‘teaching &amp; learning and assessment’ according to the components of Korea's 2022 revised music curriculum. As a result of the analysis, the characteristics of each item and the differences with Korea's 2022 revised music curriculum were presented, and based on this, implications related to the design method and content of Korea's music curriculum were derived.
The Analysis of Word Formation Process in Song Album “Traumazine” by Megan Thee Stallion

Songs can be used to express ideas or emotions, or even as a way for people to communicate with one another. One area of linguistics, morphology, deals with how language structure might be used to analyze meanings or feelings in song lyrics. In this study, the word formation process for the song Megan Thee Stallion from the album “Traumazine” will be analyze. Descriptive research is the qualitative method employed in this study. The word formation hypothesis of George Yule (2019) is used by the researcher. The 18 songs on Megan Thee Stallion’s album “Traumazine” provided the source of the data used in this research. The “traumazine” album by Megan Thee Stallion contains 8 of the 14 different kinds of word formation process that were examined in this study. This study discovered 34 data on word formation process. There are three data from borrowing, seven from ccompounding, three from blending, ten from clipping, one each from hypocorisms and backformation, eight from acronyms, and one from multiple processes. Based on the findings, Megan Thee Stallion’s song albu ‘Traumazine” most dominantly uses the clipping process to create words
Determination of Radiation Value by Month Using Artificial Neural Network Model; Ankara, Sivas, Erzurum example

This research examines the estimation of solar radiation using artificial neural network (ANN) models in Turkish cities with similar latitude values such as Ankara, Sivas and Erzurum. The aim of this study is to investigate whether cities at similar latitudes exhibit similar trends in solar radiation values, despite their geographical differences. In this study, solar radiation prediction was made for 3 cities with a single-layer neural network. Monthly solar radiation intensity was estimated for the 10-year period between 2012 and 2022 with a total of 4764 samples taken from the General Directorate of State Meteorology. An artificial neural network model was developed with 8 units in the first hidden layer and 4 units in the second hidden layer. The optimizer used in compiling the model was determined as Adam, the loss function as 'mean_squared_error' and the metric as 'mse'. ReLU activation function was used in the input layer and hidden layers. A 10-year solar radiation intensity value was used in the output layer. 70% of the data set is reserved for training and 30% for testing data set. As a result, similar solar radiation trends were obtained in the same latitude regions, the results were confirmed by meteorological data.