Reviewerly/exHarmony huggingface dataset:
step-by-step formation of students' skill in applying the algorithm for converting numbers between number systems with bases p and q, where q is the degree of p

The formation of the skill of applying the algorithm for converting numbers between number systems, where the base of one number system is the degree of the base of another, assumes to use a set of tasks to convert mental action from a conscious, open, external state into an unconscious, surrogated, mental one. When developing such a set of tasks, it is necessary to rely on the basic provisions of the theory of phased formation of mental actions. At the first stage of learning the algorithm, it is reasonable to offer students a set of tasks and questions that will allow them to independently single out the orienting basis of an action in short form. Work with an open form of recording a number will correspond to the stage of materialized action, while a materialized form of mental action can be combined with speech; the result of students' work at this stage will be the formulation of the algorithm. At the stage of forming an action in external speech, you can offer students tasks to work with the wording of the algorithm; to do this, you can use tasks "with omissions" and errors in the description of the algorithm. The translation of the action into external speech "silently" will be facilitated by tasks for finding out an error in solving a problem, for applying one step of the algorithm. To automate the described mental action, it is necessary that students should perform a sufficient number of standard exercises to convert numbers between number systems, including tasks where the use of the studied algorithm is impossible. For further development of the skill of applying the algorithm, it is necessary to use tasks that may require recreating the original, open form of action. The authors' experience shows that six lessons are enough to form the skills of using this algorithm, three of the lessons are devoted to students' independent work.
Experience in developing and holding the All-Russian distance team quest on informatics

Every year since 2017, Yaroslavl State Pedagogical University named after K. D. Ushinsky (YSPU) holds the All-Russian distance team quest "Around informatics" for 7–11-grade students, college and university students of all training areas. The geography of the quest is constantly expanding; 1065 teams took part in the quest in March-April 2022. The quest includes 100 tasks on all topics of the informatics school course, including tasks in the Basic State Examination and Unified State Examination format and Olympiad nature tasks. Quest tasks are united by a single plot. Each quest consists of four stages; 7-grade students can cope with the tasks of the first stage, 9-grade students can cope with the tasks of the second stage, 10–11-grade students can cope with the tasks of the 3rd and 4th stages. Information support for the quest is carried out in the group "Quest "Around Informatics" (the Physics and Mathematics Faculty, YSPU)" on the social network "VKontakte" and on the website of the Physics and Mathematics Faculty, YSPU. A demo version of the quest is published at the end of November, the main quest takes place in March-April. The article in general describes tasks related to various content lines of the school course in Informatics; examples of tasks at each stage of the quest are presented. The materials of the quest will be useful in teaching Informatics in 7–11 grades at school, including when preparing students for the Basic State Examination and the Unified State Exam in informatics.
Student Mental Health Cloud Assessment Algorithm Based on Blink Frequency Image Detection Algorithm in Heterogeneous Network Environment

With the development of society, the environment that contemporary college students live in becomes more and more complex, and the mental health of college students has become a very concerned issue at the social level.This paper firstly introduces the relationship between blink frequency and college students' mental health, and uses the blink frequency image detection algorithm to evaluate college students' mental health based on complex heterogeneous networks.Then use C++ to design a cloud evaluation platform for students' mental health in a heterogeneous network environment, upload the evaluated mental health data to the cloud platform based on big data, and use cloud evaluation algorithms to comprehensively review the mental health of college students.Finally, a joint ranking model is used."MutuRank" tests the mental health intelligence evaluation index of college students.The results show that the method can comprehensively and objectively describe the change characteristics of college students' mental health, and the results of the intelligent assessment of college students' mental health are stable.
Kuprin and Moscow Publishing House: History of Cooperation

Based on unpublished archival materials and pieces from printed memoir, epistolary sources, the article restores a comprehensive picture of A. I. Kuprin’s cooperation in a popular publishing enterprise at the beginning of the 20th century – Moscow Publishing House. The article analyses business and personal relationships between Kuprin and Moscow Publishing House staff members: G. G. Blumenberg, the owner and the editor of the literary digests Zemlya (20 books, issued by Moscow Publishing House from 1908 to 1917); brothers N. S. and V. S. Klyostovs, representatives of Moscow Publishing House; I. A. Bunin, the editor of the first two Zemlya’s books. The article follows the history of Kuprin’s art works publications (Sulamith, Yama: The Pit, The Garnet Bracelet) in the literary digest Zemlya. The article determines the leading role of Kuprin in literary digests Zemlya: the Publishing House’s owners and staff inevitably made compromises while arguing with the writer, tolerated manuscripts delays, sought the cooperation of certain authors to please Kuprin. The article gives an overview of relationships (sometimes tough) between Kuprin and the authors of Zemlya’s almanac: rivalry with L. N. Andreyev, patronizing tone towards M. P. Artsybashev, support and protection of F. K. Sologub, friendly terms with S. S. Yushkevich.&#x0D;
Liberation of the signified from a rigid connection with the signifier as one of the conditions of the arbitrary nature of the sign

How do arbitrary signs occur? The article suggests that the basis of arbitrariness is the liberation of the signified from a rigid connection with the signifier. An important role is played by the psychological present. The psychological present is not one-dimensional but is represented by dimensions of sequence, simultaneity, and duration. Non-arbitrary signs are as if one-dimensional: the signifier and the signified are in undifferentiated unity – in one dimension of the present time. When forming arbitrary signs, the signified and the signifier are separated from each other and are embodied in different dimensions – the levels of the psychological present tense, invariant and variable. At the same time, the signified occupies an invariant level, and the signifier is variable so that the signified remains constant with any change in the signifier. Therefore, different signifiers can be applied to the same object at will, and the content of the designated object does not change. The signified thus becomes relatively independent and free from the signifier.
A Secure Storage and Deletion Verification Scheme of Microgrid Data Based on Integrating Blockchain into Edge Computing

A microgrid generates a large amount of power data during daily operation, which needs to be safely transferred, stored, and deleted. In this paper, we propose a secure storage and deletion verification scheme that combines blockchain and edge computing for the problems of limited storage capacity of blockchain and unverifiable data deletion. Firstly, edge computing is used to preprocess power data to reduce the amount of data and to improve the quality of data. Secondly, a hybrid encryption method that combines the improved ElGamal algorithm and the AES-256 algorithm is used to encrypt outsourcing data, and a secure storage chain is built based on the K-Raft consensus protocol to ensure the security of data in the transmission process. Finally, after initiating a data deletion request and successfully deleting the data, a deletion proof is generated and stored in the chain built, based on the Streamlet consensus protocol. The experimental results illustrate that the basic computing cost, block generation time, and communication delay of this scheme are the most efficient; the efficiency of the improved ElGamal algorithm is three times that of the traditional algorithm; the transaction throughput of the the double-layer blockchain can reach 13,000 tps at most. This scheme can realize the safe storage of microgrid data, and can also realize the efficient deletion and verification of outsourcing data.
Impacts of Technology in Learning: Mobile Typing Applications for Writing and Accomplishing Academic Tasks among Arabic-Speaking Undergraduate Students

In recent years, especially during and after the COVID-19 pandemic, the use of mobile applications (apps) has become common in all areas of life for carrying out tasks, facilitating communication, and completing work. Education has been one of the most prominent areas that has presented a strong trend for using mobile apps. For instance, a huge number of Arabic-speaking undergraduate students in Saudi Arabia have been using mobile typing apps to accomplish their academic tasks and for other educational purposes. This phenomenon has influenced the academic writing skills of undergraduate students. In this study, we identify the relationship between academic tasks, academic writing skills, and the use of mobile typing apps among Arabic-speaking undergraduate students by analyzing which skills were affected by typing via mobile apps. A total of 276 Arabic-speaking undergraduate students in Saudi Arabia participated in this study. By applying structural equation modeling to analyze the quantitative data, results revealed that use of mobile typing apps had the strongest effect on the academic writing skills of clarity and cohesiveness. Meanwhile, using mobile typing apps to accomplish academic tasks had less impact on accuracy and vocabulary. Several pedagogical and technical implications are presented at the end of the study.
Quantum Spatial Search with Electric Potential: Long-Time Dynamics and Robustness to Noise

We present various results on the scheme introduced in a previous work, which is a quantum spatial-search algorithm on a two-dimensional (2D) square spatial grid, realized with a 2D Dirac discrete-time quantum walk (DQW) coupled to a Coulomb electric field centered on the the node to be found. In such a walk, the electric term acts as the oracle of the algorithm, and the free walk (i.e., without electric term) acts as the "diffusion" part, as it is called in Grover's algorithm. The results are the following. First, we run long time simulations of this electric Dirac DQW, and observe that there is a second localization peak around the node marked by the oracle, reached in a time O(N), where N is the number of nodes of the 2D grid, with a localization probability scaling as O(1/lnN). This matches the state-of-the-art 2D-DQW search algorithms before amplitude amplification We then study the effect of adding noise on the Coulomb potential, and observe that the walk, especially the second localization peak, is highly robust to spatial noise, more modestly robust to spatiotemporal noise, and that the first localization peak is even highly robust to spatiotemporal noise.
Information and Communication Technologies in Peruvian University Students: A Confirmatory Analysis of Their Frequency and Extent of Use

Pedagogical strategies with technology have an impact on university academic teaching. Hence, there is a need to develop competencies that allow the efficient use of various digital resources. The present study validated through a confirmatory factor analysis the constructs proposed in the CUTIC-28 in a sample of 318 Peruvian university students. It was a quantitative approach research at a descriptive level and based on a non-experimental design. The results demonstrated, as reflected in each metric of the confirmatory factor analysis (CFA), the theoretical and empirical sustainability of the original questionnaire to assess the frequency and extent of ICT use in Peruvian university students; the set of data reported offers the certainty that it is a defensible and sustainable factorial model. The covariances and correlations between the dimensions and subdimensions are highly significant and positive, and, therefore, the factorial structure is confirmed by the sample data. The confirmed scale has adequate properties that allow it to be considered a valid and reliable measure in future research, even after adding other variables, such as gender, age, and type of university, among the variables of interest that show significant differences. The results also show that there is still a knowledge gap to be covered.
Resonant Actualization of Cultural Codes as a Determinant of Mental and Social Transformations (Part 2)

The cumulation of cultural codes forms and structures the integral matrix of information capacity - the cognitive thesaurus (CT) of the psyche. The dissociation of the parameters of the current balance of somatic/mental homeostasis initiates a compensatory need. The "need" extracts from the CT (actualizes) the "image" of the cultural code - a representable informational equivalent of the "need" ("dominant"). Being the content of consciousness at the time of relevance, "dominant" acquires the properties of a resonant operator, a dominant focus, forming control mental constructs. Actualization of the "dominant" initiates the activity of the "action result acceptor." For the actual dominant, the "action result acceptor" is an indicator/corrector, a frequency matching censor (resonance): perceptual dynamics of operational images of external presentation ("code key") to the parameters of the "dominant" (code). Decoding the physical parameters of the "code" provides the potential to regulate the resonant impact on the arsenal of "cultural codes" of CT through moderation of the "code key." The CT, through the "action result acceptor" (the extra-conscious regulator of the actual autonoetic forms of mental activity), programs and formats the somatic/psychic continuum of the individual. The integral matrix of the CT, having a location outside the conscious sector of the psyche, including the imperative corrector of the perceived sector of the psyche associated with the emotional register, determining/correcting the main vectors of the regulation of the life continuum, is meaningfully close to the philosophical/psychological criteria of the main cognitive regulator of the person activity, defined as the soul.
SCR: Smooth Contour Regression with Geometric Priors

While object detection methods traditionally make use of pixel-level masks or bounding boxes, alternative representations such as polygons or active contours have recently emerged. Among them, methods based on the regression of Fourier or Chebyshev coefficients have shown high potential on freeform objects. By defining object shapes as polar functions, they are however limited to star-shaped domains. We address this issue with SCR: a method that captures resolution-free object contours as complex periodic functions. The method offers a good compromise between accuracy and compactness thanks to the design of efficient geometric shape priors. We benchmark SCR on the popular COCO 2017 instance segmentation dataset, and show its competitiveness against existing algorithms in the field. In addition, we design a compact version of our network, which we benchmark on embedded hardware with a wide range of power targets, achieving up to real-time performance.
Intrusion Detection System using Regulated Patrolling Robots for Apartments

Nowadays robots are incorporated in the job which are often difficult for humans and these robots can be used as an effective alternative for humans. Mobile robots have become a significant topic in the security field Several techniques have been introduced to work with mobile robots and security. Most of these methods are not capable of working in low visibility environments and need to be manually controlled by a person all the time. In this smart security system, a mobile robot acts as an e-patrol in both light and dark environments. The design and implementation of mobile robots consist of three subsystems: The obstacle avoidance, image capturing and alarm indication for theft prevention. By means of which bot can be deployed for surveillance in a defined path with specific intervals.
The effect of additional lessons on elementary school students’ knowledge level in Pucakwangi, Lamongan

Background:The progress of a region is greatly influenced by the quality of its human resources (HR).This is inseparable from the level of knowledge of the community as human resources in an area that must be fostered from an early age.Methods: Additional lessons are given to elementary school students of MIM 03 and MI Al-Huda.Data collection used a knowledge questionnaire to evaluate the knowledge before and after the implementation of all additional learning sessions which were carried out 8 times within 4 weeks.The subject of this study were 19 elementary school children in Pucakwangi Village, Lamongan.The marks are then analyzed by using Statistical Package for Social Science (SPSS) Statistic 23. Results:The results showed an increase in the results of the knowledge questionnaire on the post test (p<0.05). Conclusion:This study concludes that additional lessons have a positive impact on subject knowledge, and a sustainable program is needed to maintain or even increase knowledge levels and quality of human resources.
The Impact of Online Learning on Statistics Courses for Students of the Department of Development Economics, State University of Malang

This study aims to determine the impact of online learning on student learning activities and understanding in online statistics courses.This study uses a qualitative approach.The informants of this study were students of the Economic Development Department, Class of 2020, at the Faculty of Economics and Business, Malang State University, which was determined using purposive sampling.Data collection techniques used structured interviews and documentation.Data analysis was carried out through three stages of activity, including data reduction, data presentation, and data verification.The results show that online learning in statistics courses harmed student learning activities and understanding.Learning activities are limited and hampered because of several obstacles, so students find them challenging to understand.The common understanding of students can be seen from the CPMK Statistics that has yet to be achieved.
f-divergence regression models for compositional data

The paper considers the class of $f$-divergence regression models as alternatives to parametric regression models for compositional data. The special cases examined in this paper include the Jensen-Shannon, Kullback-Leibler, Hellinger, chi^2 and total variation divergence. Strong advantages of the proposed regression models are a) the absence of parametric assumptions and b) the ability to treat zero values (which commonly occur in practice) naturally. Extensive Monte Carlo simulation studies comparatively assess the performance of the models in terms of bias and an empirical evaluation using real data examining further aspects, such as predictive performance and computational cost. The results reveal that Kullback-Leibler and Jensen-Shannon divergence regression models exhibited high quality performance in multiple directions. Ultimately, penalised versions of the Kullback-Leibler divergence regression are introduced and illustrated using real data rendering this model the optimal model to utilise in practice.
Gradient-tracking Based Differentially Private Distributed Optimization with Enhanced Optimization Accuracy

Privacy protection has become an increasingly pressing requirement in distributed optimization. However, equipping distributed optimization with differential privacy, the state-of-the-art privacy protection mechanism, will unavoidably compromise optimization accuracy. In this paper, we propose an algorithm to achieve rigorous $\epsilon$-differential privacy in gradient-tracking based distributed optimization with enhanced optimization accuracy. More specifically, to suppress the influence of differential-privacy noise, we propose a new robust gradient-tracking based distributed optimization algorithm that allows both stepsize and the variance of injected noise to vary with time. Then, we establish a new analyzing approach that can characterize the convergence of the gradient-tracking based algorithm under both constant and time-varying stespsizes. To our knowledge, this is the first analyzing framework that can treat gradient-tracking based distributed optimization under both constant and time-varying stepsizes in a unified manner. More importantly, the new analyzing approach gives a much less conservative analytical bound on the stepsize compared with existing proof techniques for gradient-tracking based distributed optimization. We also theoretically characterize the influence of differential-privacy design on the accuracy of distributed optimization, which reveals that inter-agent interaction has a significant impact on the final optimization accuracy. Numerical simulation results confirm the theoretical predictions.
Bi-Noising Diffusion: Towards Conditional Diffusion Models with Generative Restoration Priors

Conditional diffusion probabilistic models can model the distribution of natural images and can generate diverse and realistic samples based on given conditions. However, oftentimes their results can be unrealistic with observable color shifts and textures. We believe that this issue results from the divergence between the probabilistic distribution learned by the model and the distribution of natural images. The delicate conditions gradually enlarge the divergence during each sampling timestep. To address this issue, we introduce a new method that brings the predicted samples to the training data manifold using a pretrained unconditional diffusion model. The unconditional model acts as a regularizer and reduces the divergence introduced by the conditional model at each sampling step. We perform comprehensive experiments to demonstrate the effectiveness of our approach on super-resolution, colorization, turbulence removal, and image-deraining tasks. The improvements obtained by our method suggest that the priors can be incorporated as a general plugin for improving conditional diffusion models.
3DHumanGAN: 3D-Aware Human Image Generation with 3D Pose Mapping

We present 3DHumanGAN, a 3D-aware generative adversarial network that synthesizes photorealistic images of full-body humans with consistent appearances under different view-angles and body-poses. To tackle the representational and computational challenges in synthesizing the articulated structure of human bodies, we propose a novel generator architecture in which a 2D convolutional backbone is modulated by a 3D pose mapping network. The 3D pose mapping network is formulated as a renderable implicit function conditioned on a posed 3D human mesh. This design has several merits: i) it leverages the strength of 2D GANs to produce high-quality images; ii) it generates consistent images under varying view-angles and poses; iii) the model can incorporate the 3D human prior and enable pose conditioning. Project page: https://3dhumangan.github.io/.