Reviewerly/exHarmony huggingface dataset:
PENGARUH MODEL PEMBELAJARAN GAME BASED LEARNING DENGAN BANTUAN MEDIA UNO STACKO FOR QUESTION CARD TERHADAP HASIL BELAJAR BAHASA INDONESIA TOPIK BAHASAN PUISI RAKYAT

The use of still traditional learning models is one of the causes of the underdevelopment of students in terms of both values and interest in learning. Indonesian subjects that are supposed to be fun get boring if the learning model used is not appropriate. The game based learning model with UNO Stacko for question card media is one of the innovative learning models that teachers can use when learning Indonesian. This study aims to determine the differences in learning outcomes and to describe the effects of game-based learning models with the UN Stacko for question card media on Indonesian language learning outcomes for seventh grade students at MTS Darul Ulum Lamongan. This research is an experimental type of research with a quantitative approach. The sample of this research includes 2 groups of 7th grade students for the 2020-2021 academic year. Data collection techniques in the form of observations and tests. Based on the results of the analysis, it was concluded that there were differences in the learning outcomes of the Indonesian language in the group of students with the application of game-based learning models and in the groups of students with the application of conventional learning models and the application of this learning model influenced Learning outcomes of grade VII Indonesian students at MTS Darul Ulum Lamongan strong.
Особливості хімічного експерименту в умовах вимушеного дистанційного навчання

The article focuses on the study of online learning at school, the problems that arose during the school experiment and its impact on the quality of the acquired knowledge. The issue of the quality of knowledge obtained by means of distance learning, the organization of online practical and laboratory work, and the search for methods of diagnosing the quality of knowledge are quite relevant and in demand. The purpose of the study was to establish the level of quality of studying chemistry in the conditions of distance learning and to determine the factors affecting the success of students. The main tasks: to conduct a qualitative observation of the methods of conducting laboratory and practical work (experiments) during online classes and the attitude of students to distance learning and to study the influence of practical and laboratory work (experiments) in chemistry on the quality of knowledge and the identification of students' misconceptions in chemistry that arose during distance learning. It was established that the main common problems for chemistry teachers were finding ways to conduct laboratory and practical work, identifying false (false) ideas and diagnostic tools. According to the results of the student survey, the main disadvantages of distance learning in general and conducting laboratory-practical classes in particular were determined: loss of direct contact, problems with the Internet, lack of light, understanding of the material, lack of skills in working with laboratory equipment, inability to manage time, unfair assessment, as well as the fact that that teachers conduct classes too quickly, leaving no time for questions and discussion. This, obviously, reduces interest in disciplines, understanding of certain concepts and quality of knowledge and level of success. Increasing the share of school and home experiments in chemistry contributed to interest in the subject, understanding of the topic and had a positive effect on the quality of knowledge. According to the results of four knowledge controls, positive dynamics were observed: the average increase was 0.66 points: from 0.2 (for 7th grade students) to 1.1 points (for 11th grade students). The use of conversations and various multi-level tests allows not only to discover which ideas and knowledge students have, but also to understand what actions need to be taken to eliminate them.
Educational Equity in China's Education System under Different Perspectives

As a result of the spread of the new coronavirus, Chinas education system has been forced to change, with the introduction of a series of education policies such as the suspension of classes and unschooling, but in the process of implementation many difficulties and challenges have been encountered, so this paper uses Chinese education in the context of the epidemic as a breakthrough to discuss and reflect on the aims of education and the difficulties encountered in reforming the education system in China from ancient times to the present. The research draws further conclusions by looking at previous literature and data for comparison, ultimately concluding that overall the development of the Chinese education system has been influenced by many sources, political, economic, cultural or international, but it is clear that the quality of education available to Chinese citizens is becoming higher and higher, and that the Chinese government is working hard to promote the development of education in the country.
Jiah and Rosa, tell me when you are in trouble. I love you! (The daughters are similar to their mother Hyeonhi!) (Tcheonzamun 609th-624th)

French missionary Dallet (1874) wrote in his book that ‘the thousand character essay’ has been utilized as a textbook for the children of ancient China. ‘The thousand character essay’ is called as ‘Tcheonzamun’ in Korea. And this book of Tcheonzamun was used for the education of Chinese characters for their children. Korean people firmly believed that this Tcheonzamun book was created by Chinese people (Han, 1583). And the translation until now is carried out on the viewpoint of Chinese historical heroes and on the viewpoint of Chinese local names (Han, 1583). However, recent studies showed that Tcheonzamun poem was well translated on Korean grammar (Park et al., 2021a) and through Korean pronunciation (Park et al., 2021b). In the present study, the poem of 16 Chinese characters (Tcheonzamun 609th-624th) will be translated through the meaning of Chinese characters. It is known that a Tcheonzamun poem is composed of 16 letters (Park et al., 2021a). There are two methods for the Tcheonzamun translation. The first one is through the meaning of Chinese character (Park et al., 2021a), and the second is through Korean pronunciation of Chinese characters in the Tcheonzamun poem (Park et al., 2021b). In the present study, the method through the meaning of Chinese characters was used. In the present poem (Tcheonzamun 609th-624th), the pronunciation of Chinese character was introduced from the somewhat old book of Tcheonzamun (Han, 1583). A poem of Tcheonzamun is composed of 16 letters. And the next is the translation of Tcheonzamun poem (Tcheonzamun 609th-624th). The title of this study is ‘Jiah and Rosa, tell me when you are in trouble. I love you! (The daughters are similar to their mother Hyeonhi!) (Tcheonzamun 609th-624th)’. As a theme of this study, the next part will be appropriate. 613-616 百(Baeg) 郡(Kun) 秦(Zin) 幷(Byeong). My husband! No, it is not such a thing. Travelling many places is not so important! The important thing is to cultivate the land here and there (郡). To cultivate the land, what does it mean? ‘To cultivate the land’ is ‘to make the land enough fertile for us to live together’. My husband! In order to accomplish (百) such a thing, what will you do? ‘Please live your life earnestly (秦)’, and then ‘you can concentrate your mind (幷)’. "Love me (your wife) only!"
A Family of Discrete Distributions with Infinite Moments

In probability theory, distribution laws of random variables are distinguished, in which the moments diverge to infinity. Such distributions are important for understanding the features of probability distributions; in addition, they find practical application in the study of estimation procedures. Continuous distributions with infinite moments are known and well studied. The paper proposes a family of distributions of discrete random variables that does not have moments starting from a certain order. The distributions are supplemented with a parameter that linearly affects the mathematical expectation. A method for calculating distribution moments is proposed. The probability generating function is determined.
Cooled ferromagnetic shield as a part hybrid system for isolation of a flux qubit from electromagnetic environment

Currently, circuits for quantum informatics, communications and measuring equipment containing superconducting flux qubits in a planar design are being created by quantum engineering techniques. To function, such structures must be cooled in a refrigerator down to about 10 mK. The flux qubits have linear size of superconducting circuit of some tens of micrometers and are very sensitive to external magnetic fields and their variations. The qubit built in the gradiometer-like design has reduced sensitivity to external uniform magnetic fields, but remains quite sensitive to their variations. To protect the qubit from unwanted external magnetic fields, which include the Earth's field, man-made fields, and residual magnetic fields of the cryostat parts, it is necessary to create efficient magnetic shields. Earlier, we proposed a scheme for a single-photon microwave counter, in which a planar flux qubit in a gradiometer version serves as the receiving element. To let it function properly, a 3-layer hybrid magnetic shield composed of two superconducting and one ferromagnetic cylinders, has been designed for installation in a dilution refrigerator at 10 mK temperature. The effectiveness of such a shield depends on the correct design of all three shells. This paper presents the results of calculation and magnetic measurements of a cylindrical ferromagnetic screen made of low-temperature permalloy Cryoperm 10 in dc and low-frequency alternating magnetic fields. Cryoperm 10 keeps high magnetic permeability at liquid helium temperatures and below. It is shown that this shield is able of reducing the absolute value of the magnetic field and its variations by 55-70 dB. Together with superconducting lead magnetic shields, this design will reduce the absolute value of the field by 70 dB, and the field variation by 200 dB, which will provide the necessary conditions for the operation of a single-photon counter based on a flux qubit.
Tactile Network Resource Allocation Enabled by Quantum Annealing Based on ILP Modeling

Agile networks with fast adaptation and reconfiguration capabilities are required for on-demand provisioning of various network services. We propose a new methodical framework for short-time network optimization based on quantum computing (QC) and integer linear program (ILP) models, which has the potential of realizing a real-time network automation. We define methods to map a nearly real-world ILP model for resource provisioning to a quadratic unconstrained binary optimization (QUBO) problem, which is solvable on quantum annealer (QA). We concentrate on the three-node network to evaluate our approach and its obtainable quality of solution using the state-of-the-art quantum annealer D-Wave Advantage™ 5.2/5.3. By studying the annealing process, we find annealing configuration parameters that obtain feasible solutions close to the reference solution generated by the classical ILP-solver CPLEX. Further, we studied the scaling of the network problem and provide estimations on quantum annealer's hardware requirements to enable a proper QUBO problem embedding of larger networks. We achieved the QUBO embedding of networks with up to 6 nodes on the D-Wave Advantage™. According to our estimates a real-sized network with 12 to 16 nodes require a QA hardware with at least 50000 qubits or more.
History of Physics

Physics is an exact science and studies the quantitative regularities of natural phenomena at both the macroscopic and microscopic levels. The term "physics" first appears in the works of Aristotle in antiquity. In the early days, the terms "physics" and "philosophy" (natural) were used as synonyms, as both were intended to explain the laws of the universe. However, as a result of the scientific revolution, physics began to take shape as a separate field of science in the 16th century. A [1-50] reference was used in writing the review article.
Code Structure and Logical Statements

In the previous chapter, we discussed some of the fundamentals around JavaScript and where to write it. In this chapter, we’ll start writing JavaScript and learn about its basic concepts. We’ll cover the fundamentals, including code structure, logical statements, and variables, all of which are requirements to write JavaScript code. We’ll also be discussing how each of these actually works so that you have a deeper understanding of the code you are writing.
INQUA in India: Some Reminiscences and Some Anticipations

A brief narrative on early development of Quaternary Sciences in India and its association with International Quaternary Union is presented. A discussion on expectations that accrue from increasing demands on the use of geoscience as services is presented along with some thoughts on recalibration of scientific objectives, resource augmentation through enhanced inclusivity of other disciplines and capacity building in Global South, are outlined, both for the Indian and the international context.
Compact 3D Scene Representation via Self-Organizing Gaussian Grids

3D Gaussian Splatting has recently emerged as a highly promising technique for modeling of static 3D scenes. In contrast to Neural Radiance Fields, it utilizes efficient rasterization allowing for very fast rendering at high-quality. However, the storage size is significantly higher, which hinders practical deployment, e.g.~on resource constrained devices. In this paper, we introduce a compact scene representation organizing the parameters of 3D Gaussian Splatting (3DGS) into a 2D grid with local homogeneity, ensuring a drastic reduction in storage requirements without compromising visual quality during rendering. Central to our idea is the explicit exploitation of perceptual redundancies present in natural scenes. In essence, the inherent nature of a scene allows for numerous permutations of Gaussian parameters to equivalently represent it. To this end, we propose a novel highly parallel algorithm that regularly arranges the high-dimensional Gaussian parameters into a 2D grid while preserving their neighborhood structure. During training, we further enforce local smoothness between the sorted parameters in the grid. The uncompressed Gaussians use the same structure as 3DGS, ensuring a seamless integration with established renderers. Our method achieves a reduction factor of 8x to 26x in size for complex scenes with no increase in training time, marking a substantial leap forward in the domain of 3D scene distribution and consumption. Additional information can be found on our project page: https://fraunhoferhhi.github.io/Self-Organizing-Gaussians/
Theoretical analysis of git bisect

In this paper, we consider the problem of finding a regression in a version control system (VCS), such as \texttt{git}. The set of versions is modelled by a Directed Acyclic Graph (DAG) where vertices represent versions of the software, and arcs are the changes between different versions. We assume that somewhere in the DAG, a bug was introduced, which persists in all of its subsequent versions. It is possible to query a vertex to check whether the corresponding version carries the bug. Given a DAG and a bugged vertex, the Regression Search Problem consists in finding the first vertex containing the bug in a minimum number of queries in the worst-case scenario. This problem is known to be NP-complete. We study the algorithm used in \texttt{git} to address this problem, known as \texttt{git bisect}. We prove that in a general setting, \texttt{git bisect} can use an exponentially larger number of queries than an optimal algorithm. We also consider the restriction where all vertices have indegree at most 2 (i.e. where merges are made between at most two branches at a time in the VCS), and prove that in this case, \texttt{git bisect} is a $\frac{1}{\log_2(3/2)}$-approximation algorithm, and that this bound is tight. We also provide a better approximation algorithm for this case. Finally, we give an alternative proof of the NP-completeness of the Regression Search Problem, via a variation with bounded indegree.
Understanding the Significance of Kinship

The individuals, belonging to all occupations, communities and socio-economic backgrounds are required to understand the meaning and significance of relationships in their lives. From the stage of early childhood, throughout their lives, they are required to be well-informed in terms of ways of management of relationships. Some of these are, implementing effective communication processes, inculcating the traits of morality and ethics, being well-informed in terms of job duties and methodologies, and depicting the traits of helpfulness and co-operation. All these factors are required to be acknowledged and reinforced, when the individuals are forming terms and relationships with all types of kin. The individuals are required to be well-informed in terms of the factor that their tasks and activities are required to promote well-being and goodwill of others. The individuals acquire support and assistance from others in carrying out their tasks and activities efficiently. Furthermore, they will be able to cope with various types of dilemmas and challenging situations in an efficient manner. As a consequence, individuals will contribute efficiently in doing well in one’s job duties and achievement of desired goals and objectives in personal and professional lives. Therefore, it is well-understood, kinship is facilitating in bringing about improvements in overall standards of living of individuals. The main concepts that are taken into account in this research paper are, types of kin, degrees of kinship and factors highlighting roles and importance of kinship in family structures.
Improving the Performance of Echo State Networks Through Feedback

Reservoir computing, using nonlinear dynamical systems, offers a cost-effective alternative to neural networks for complex tasks involving processing of sequential data, time series modeling, and system identification. Echo state networks (ESNs), a type of reservoir computer, mirror neural networks but simplify training. They apply fixed, random linear transformations to the internal state, followed by nonlinear changes. This process, guided by input signals and linear regression, adapts the system to match target characteristics, reducing computational demands. A potential drawback of ESNs is that the fixed reservoir may not offer the complexity needed for specific problems. While directly altering (training) the internal ESN would reintroduce the computational burden, an indirect modification can be achieved by redirecting some output as input. This feedback can influence the internal reservoir state, yielding ESNs with enhanced complexity suitable for broader challenges. In this paper, we demonstrate that by feeding some component of the reservoir state back into the network through the input, we can drastically improve upon the performance of a given ESN. We rigorously prove that, for any given ESN, feedback will almost always improve the accuracy of the output. For a set of three tasks, each representing different problem classes, we find that with feedback the average error measures are reduced by $30\%-60\%$. Remarkably, feedback provides at least an equivalent performance boost to doubling the initial number of computational nodes, a computationally expensive and technologically challenging alternative. These results demonstrate the broad applicability and substantial usefulness of this feedback scheme.
Cycle-Consistency Learning for Captioning and Grounding

We present that visual grounding and image captioning, which perform as two mutually inverse processes, can be bridged together for collaborative training by careful designs. By consolidating this idea, we introduce CyCo, a cyclic-consistent learning framework to ameliorate the independent training pipelines of visual grounding and image captioning. The proposed framework (1) allows the semi-weakly supervised training of visual grounding; (2) improves the performance of fully supervised visual grounding; (3) yields a general captioning model that can describe arbitrary image regions. Extensive experiments show that our fully supervised grounding model achieves state-of-the-art performance, and the semi-weakly supervised one also exhibits competitive performance compared to the fully supervised counterparts. Our image captioning model has the capability to freely describe image regions and meanwhile shows impressive performance on prevalent captioning benchmarks.
SAIC: Integration of Speech Anonymization and Identity Classification

Speech anonymization and de-identification have garnered significant attention recently, especially in the healthcare area including telehealth consultations, patient voiceprint matching, and patient real-time monitoring. Speaker identity classification tasks, which involve recognizing specific speakers from audio to learn identity features, are crucial for de-identification. Since rare studies have effectively combined speech anonymization with identity classification, we propose SAIC - an innovative pipeline for integrating Speech Anonymization and Identity Classification. SAIC demonstrates remarkable performance and reaches state-of-the-art in the speaker identity classification task on the Voxceleb1 dataset, with a top-1 accuracy of 96.1%. Although SAIC is not trained or evaluated specifically on clinical data, the result strongly proves the model's effectiveness and the possibility to generalize into the healthcare area, providing insightful guidance for future work.
BSRAW: Improving Blind RAW Image Super-Resolution

In smartphones and compact cameras, the Image Signal Processor (ISP) transforms the RAW sensor image into a human-readable sRGB image. Most popular super-resolution methods depart from a sRGB image and upscale it further, improving its quality. However, modeling the degradations in the sRGB domain is complicated because of the non-linear ISP transformations. Despite this known issue, only a few methods work directly with RAW images and tackle real-world sensor degradations. We tackle blind image super-resolution in the RAW domain. We design a realistic degradation pipeline tailored specifically for training models with raw sensor data. Our approach considers sensor noise, defocus, exposure, and other common issues. Our BSRAW models trained with our pipeline can upscale real-scene RAW images and improve their quality. As part of this effort, we also present a new DSLM dataset and benchmark for this task.