Reviewerly/exHarmony huggingface dataset:
Investigation of the Input-Output Relationship of Engineered Neural Networks Using High-Density Microelectrode Arrays

Bottom-up neuroscience utilizes small, engineered biological neural networks to study neuronal activity in systems of reduced complexity. We present a platform that establishes up to six independent networks formed by primary rat neurons on planar complementary metal–oxide–semiconductor (CMOS) microelectrode arrays (MEAs). We introduce an approach that allows repetitive stimulation and recording of network activity at any of the over 700 electrodes underlying a network. We demonstrate that the continuous application of a repetitive super-threshold stimulus yields a reproducible network answer within a 15 ms post-stimulus window. This response can be tracked with high spatiotemporal resolution across the whole extent of the network. Moreover, we show that the location of the stimulation plays a significant role in the networks’ early response to the stimulus. By applying a stimulation pattern to all network-underlying electrodes in sequence, the sensitivity of the whole network to the stimulus can be visualized. We demonstrate that microchannels reduce the voltage stimulation threshold and induce the strongest network response. By varying the stimulation amplitude and frequency we reveal discrete network transition points. Finally, we introduce vector fields to follow stimulation-induced spike propagation pathways within the network. Overall we show that our defined neural networks on CMOS MEAs enable us to elicit highly reproducible activity patterns that can be precisely modulated by stimulation amplitude, stimulation frequency and the site of stimulation.
Crypto is Not Property

A short paper explaining why "cryptoassets" cannot constitute legal property, despite the academic consensus to the contrary.
The Effect of Climbing Grammar Mountain Game on Students' Writing Achievement

The objective of this research is to find out whether or not there is a significant effect of using climbing grammar mountain game on students writing achievement of the eighth-grade students at MTsN 2 Batanghari. This was quantitative research that was conducted with a quasi-experimental design. The subjects in this research were 39 students. The study result showed that the mean of the post-test score (56.62) was higher than the mean of the pre-test score (51.69) in the experimental class. The p-value in the paired sample t-test was less than 0,05 (0,002&lt;0,05). It shows that the result was significantly different. As a result, was accepted. It shows that students' writing ability improved significantly before and after being taught through the climbing grammar mountain game. The p-value for the independent sample t-test in the equal variances assumed and not assumed cases was (0,007&lt;.0,05). It shows that has been accepted and has been rejected. It shows that there was a significant difference between the students who were taught using the climbing grammar mountain game and those who were not.
The Effect of Repeated Reading Method (RRM) in Teaching Reading Comprehension of Narrative Text to the Eighth Grade Students of SMP Negeri 1 Tanah Abang Pali

Abstract. The study aims to investigate the problems: “Whether or not there is any significant effect of using Repeated Reading Method to the eighth-grade students of SMP Negeri 1 Tanah Abang.” Therefore, the objective of the research was to find out whether or not there is any significant effect of using repeated reading method on the students’ reading narrative text to the eighth-grade students’ of SMP Negeri 1 Tanah Abang Pali. The sample of this research was 62 students, divided in to two classes: experimental class and control class. The sample of this research was purposive sampling. The data obtained were analyzed by using independents sample t-test in SPSS (Statistical Package for the Social Science) The result of t-obtained 4.752 was at the significant level p&lt;0.05 for two tailed and degree of freedom (df) was 60, t-table was 2,000.&#x0D; Keywords: Repeated Reading Method , Teaching , Narrative , Reading Comprehension.&#x0D;
Vision-based Autonomous UAS Landing on a Stochastically Moving Platform

This paper describes the development of avionics and control systems, followed by flight demonstration for vision-based landing of a multirotor UAS on a moving platform replicating a ship-deck. The UAS is a quadrotor designed and fabricated in-house with an integrated avionics package developed for autonomous vision-based navigation. A monocular camera is used for detection and pose estimation of a moving platform. The platform replicates ship-deck motion using six degrees of freedom capable of oscillatory motions upto 10 cm in linear and 30 degrees in angular amplitude with speeds upto 50 cm/s. Ship-deck motions of progressively increasing intensity were obtained from ONR and simulated using the moving platform to understand the problems involved in estimation and tracking of large stochastic motions. Results were verified with an independent Vicon system. The key conclusion is that it is possible to track a moving ship-deck with vision alone. Indeed vision based ship-deck position estimation was found to be near perfect with errors of 1-2 cm. Ship-deck tracking shows a phase lag error that increases with increasing frequency of ship-deck motion. It was found that this error can be decreased by estimating ship-deck's velocity and using it as a feedback in tracking controller.
Analysis of Educational Aspects in the Novel "Bukan Pinang Dibelah Dua" and its Relationship with Literary Learning in Senior High School

The purpose of this research is to understand and discover the aspects of education existing in the novel.The method used in this research is descriptive by describing the object or target of research through a pragmatic approach to study the value of education, the documenter method is a literature study, the observation method is to record the assessment and consideration of the object studied, the intuitive method is to carefully analyze every data found and empirically can be lived the meaning of the data.The research result concluded that: (1) the teaching of literature should be emphasize on students' appreciation development, (2) the teaching of literature is one of the educational media of the student, and (3) the novel "Bukan Pinang dibelah dua" by Ratna Indraswari: can be used as one of the teaching materials in senior high school, due to the form and content are appropriate with educational goal and the purpose of literary appreciation that students can get pleasure and benefit (dulce et utyle) from the novel, such as; it can develop the students' feelings, students' mind power and students' moral.
The Mediating Effect of Tutorial Videos in Mathematics on the Relationship between Teaching Strategies and Academic Motivation of Students

The study determined the mediating effect of tutorial videos in mathematics on the relationship between teaching strategies and academic motivation of students.The study utilized descriptive correlational design and employed a survey method to attain the objective.Five hundred seventy-eight ( 578) students from Private and Public Senior High School in Davao City were the selected respondents of the study through random sampling technique.The researcher made use of pilot-tested and enhanced adapted questionnaires to describe the tutorial videos in mathematics, teaching strategies and academic motivation of students, utilizing mean, standard deviation, Pearson's Moment-Product Correlation, and path analysis to analyze the data.Results indicated that tutorial videos in mathematics, teaching strategies obtained different mean scores but both belong to a high descriptive level, while academic motivation belongs to a moderately high descriptive level.Furthermore, it was found that there is a significant relationship between and among teaching strategies, academic motivation, and tutorial videos in mathematics.A significant partial mediation of tutorial videos in mathematics on the relationship between teaching strategies and academic motivation.
REFLEXOS DA PANDEMIA DA COVID-19 EM PACIENTES DIABÉTICOS: UMA REVISÃO NARRATIVA

OBJECTIVE: To analyze the impact of the COVID-19 pandemic on diabetic patients. MATERIALS AND METHODS: This is a narrative, descriptive and qualitative review, based on electronic databases, applying the descriptors: “COVID-19”, “Diabetes mellitus” and “Pandemic”, inserted in combination with the controlled Boolean operator “AND” . Only studies published in English and Portuguese between 2020 and 2022 were considered. RESULTS AND DISCUSSION: According to the findings, it was observed that diabetic patients, in the pandemic context, were an impacted group, especially with regard to the mental health and lifestyle of the population, especially in terms of diet and physical activity. Thus, the pandemic strongly demonstrated the need for multidisciplinary care for patients with diabetes. FINAL CONSIDERATIONS: Individuals with diabetes, during the COVID-19 pandemic, showed increased levels of stress, anxiety, depression, changes in sleep and eating disorders, associated with social isolation measures. In view of this, the creation of strategies and comprehensive lines of care aimed at promoting health and adequately coping with the current context in which we live and that can minimize the psychosocial impacts caused by the pandemic in this population segment becomes essential.
Deep Convolutional Neural Network with a Stochastic Gradient Descent Optimizer (PDCNN-SGD) model for telugu character recognition

Telugu Character Recognition (TCR) has received significant attention because of the drastic increase in technological advancements such as multimedia, smartphones and iPods, and paper documents. Offline character recognition is the process of identifying Telugu characters from the scanned image or document whereas online character recognition enables to recognition of characters by the machine while the user writes. Several researchers have attempted to design online TCR models by the use of distinct classification models and feature extraction approaches. It is still necessary to construct automated and intelligent online TCR models, even if many studies have focused on offline TCR models. The Telugu character dataset construction and validation using an Inception and ResNet-based model are presented. The collection of 645 letters in the dataset includes 18 Achus, 38 Hallus, 35 Othulu, 34*16 Guninthamulu and 10 Ankelu. The proposed technique aims to efficiently recognize and identify distinctive Telugu characters online. This model's main preprocessing steps to achieve its goals include normalization, smoothing, and interpolation. Improved recognition performance can be attained by using Stochastic Gradient Descent (SGD) to optimize the model's hyperparameters.
Breast cancer disease prediction using ensemble techniques

Breast Cancer is a highly lethal reproductive cancer that disproportionately affects women and is a leading cause of death worldwide. Cancer is characterized by the uncontrolled division and invasion of abnormal cells into the surrounding tissues. Early detection is crucial in the diagnosis of Breast Cancer, as it accounts for a significant percentage of cancer diagnoses and deaths among women. To prevent unnecessary tests, accurate classification of malignant and benign tumors is necessary. Researchers have developed numerous automated classification methods for Breast Cancer, with soft computing techniques being widely used due to their high performance in classification. Machine learning algorithms, known for their ability to identify critical features from medical datasets, are also extensively utilized in Breast Cancer prediction. Therefore, this study seeks to employ Boosting algorithms in machine learning to predict Breast Cancer accurately. Over the years, the mortality rate in Breast Cancer diagnosis has decreased due to research efforts.
Lazy Abstraction for Probabilistic Systems

Reliability analysis of complex safety-critical systems by probabilistic model checking is often hindered by state space explosion.Abstraction is one way to counteract this problem.In this paper, we adapt an existing lazy abstraction algorithm to the analysis of Markov Decision Process reliability models and prove its soundness.
Detection of Fraudulent Credit Card Transactions Using Deep Neural Network

The usage of credit cards for online purchases has increased exponentially and so has fraud. In recent years, detecting fraud in credit card transactions has become significantly more difficult. As a result, having effective and accurate methods for detecting fraud in credit card transactions is vital. Although supervised learning algorithms have been shown to be effective in detecting credit card fraud, they have not generated substantial results. Hence, a Deep Neural Network (DNN)-based technique is proposed. The sequential model is used to construct the proposed DNN. However, the parameters of the model, such as the number of nodes and the activation function in the hidden layers, can also have an impact on its output. The proposed technique was evaluated on a credit card transaction dataset that comprised fraudulent and genuine transactions. This technique obtained the accuracy, area under curve (AUC), and precision of 99.93%, 99.99%, and 99.89%, respectively. This technique was compared with various models such as Optimized LightGBM, Multilayer Perceptron (MLP), K-Nearest Neighbor (KNN) and Support Vector Machine (SVM).
N-Version Programming as a Mitigation for Smart Contract Faults in Execute-Order-Validate Blockchain Systems

In this paper, we propose the application of a wellknown runtime fault-tolerance technique, N-Version Programming (NVP), as a new tool of smart contract software fault mitigation, especially for execute-order-validate blockchain systems, such as Hyperledger Fabric (HLF).Two patterns for aligning the NVP concept with the HLF architecture are proposed.A fully transparent solution where all peers have the same N versions installed and one we termed 'O-Version Programming' (where 'O' stands for 'Organization'), which relies on the majority voting aspects of execute-order-validate consensus mechanisms.
TEXT-CREATING PERFORMANCE IN THE TRAINING SYSTEM OF THE FUTURE TEACHER OF PRIMARY GRADES

The peculiarities of formation of text creating competence of future teachers of primary school are found out in the article. The author believes that knowledge about the text and text making activity will ensure the student’s orientation to the development of professional and personal realization, personal and creative attitude to pedagogical activity, confidence in his (her) readiness for it and the desire for professional self-improvement. The purpose of the article is to highlight modern methodological approaches (text-creating performance) to the formation of the text-creating competence of the future primary school teacher. The theoretical-methodological basis of studying consists of classical and modern properties of world and native lingvonodidactics of pedagogy, psychology, active theory of learning and development of personality. A set of researching methods is used: theoretical – analysis of linguistic, psychological, pedagogical, educational and methodological literature on research problems; synthesis and generalization, comparison; development of work experience of teachers of higher education institutions, defining the conceptual system of research; empirical – observation and analysis of pedagogical phenomena and processes, collective and individual conversations in order to identify the main contradictions and defects in the content, teaching methods in order to identify the problems of the formation of the text-creating competence of the future primary school teacher. The text-creating competence is stressed to be knowledge, abilities, skills and experience of text-creating activity acquired in the learning process-primary (reproduction of ready-made texts, creation of own and editing them) and secondary (perception, interpretation, understanding of texts) and also the experience of emotional and valuable attitude to the process and result of text creation. The formation of text-creating competence is found out to be an integrative process that includes philological, psychological and pedagogical components. A detailed analysis of the content and genesis of the concept made it possible to define a text-creating performer as an effective (necessary impact on the reader), high-quality (normative content, composition, language design) text-creating activity of primary school teacher. The studying of the methodological base about the structure of text-creating competence is proved to distinguish its components: textual, cognitive-interpretive, textological, text-productive. These are the abilities to make and edit texts which are formed on the basis of test-creating performance.
The impact of COVID-19 pandemic on cybersecurity in electronic banking in Poland

Purpose: The purpose of the article is to present both theoretical and practical basis for cybersecurity in electronic banking in Poland during the COVID-19 pandemic. During this period a major reorganisation of IT solutions occurred, which allowed to extend the range of online products and services offered both to bank customers and employees. As our life is more and more dependent on digital technologies, cyber attacks have become more costly and more dangerous. Driven by dynamic technological development regulations have changed, which resulted in cybersecurity becoming a key priority in financial institutions. All the more so because the rapid technological development has been followed by more and more advanced techniques used by criminals searching for easy financial profits. Methodology: The paper uses the method of literature review - mostly electronic sources, descriptive and comparative analyses. Findings: From customers, perspective, the impact of COVID-19 pandemic on cybersecurity in electronic banking in Poland may be recognized as negative. The years 2020-2021 brought a dynamic growth in the number of digital banking customers, especially mobile banking. In those years financial institutions recorded an enormous increase in online payments, which was the result of strong, forced by the pandemic, surge in sales in E-commerce. At the same time, there was a sharp rise in the crime rate targeted at banks, but most of all, at bank customers. While the security of the very financial institutions remained unthreatened, there was an explosion in the number of cybercrimes targeted at E-banking users, with the losses giving dozens of millions PLN in total. That is reflected by the data provided by the National Bank of Poland, numerous complaints to the Financial Ombudsman, the Office of Competition and Consumer Protection, as well as the police investigations. Practical implications: The analysis of relations between theoretical and practical bases of cybersecurity in E-banking in Poland during the COVID-19 pandemic is a key factor for financial institutions. Cybercrime undermines customers' trust in E-channels and therefore negatively influences how banks are perceived, the level of the users' activity in digital channels, and consequently, activity and sales in E-channels. Besides the image and financial risks, banks need to take into consideration the increase in reputation, operation and legal risks. On these grounds, it is possible for state organisations and financial institutions to develop professional education concerning cybersecurity, not only for E-banking customers, but for the whole society.
Differentiated Pedagogy and Efficiency of the Practice of E-Learning in Secondary School

Different definitions are applied to the word pedagogy.We can define it as all the methods and practices of teaching and education as well as all the qualities required to transmit any knowledge, which can be categorized according to several criteria.Clerc (2002) designates it as the set of scientific and practical knowledge, relational and social skills that are mobilized to design and implement teaching strategies.We have, among others: general pedagogy, specific pedagogy and differentiated pedagogy which designates an education in which the pupil is considered as a person with his own representations of the training situation.In other words, it is a varied learning method that offers a range of approaches opposing the identity myth of uniformity according to which everyone must work at the same pace, for the same duration and by the same routes; hence distance education, which for ages has been seen as a way of making education accessible to anyone who cannot enroll in "normal education."Sometimes it can be geographic remoteness, lack of financial resources, crises like the health crisis (COVID 19), or even lack of time (on the part of those who work).Distance education offers have been developed at all levels in secondary education (correspondence courses, support courses in vocational training and higher education), using traditional means, mail, television as well as from the radio.Information and communication technologies have opened up new perspectives and allowed an extraordinary development of this type of education.The use of the Internet has greatly facilitated access to education and to a wide variety of audiences around the world.
Bullying Behavior and Its Effect on Preparatory School Students

Bullying is an ever-present problem occurring within preparatory schools across the world. Bullying creates personal, social, and emotional, as well as academic problems for the victim. Therefore, this study was
Spring MVC: REST Services

In this chapter, you will learn how Spring addresses Representational State Transfer, usually referred to by its acronym REST. REST has had an important impact on web applications since the term was coined by Roy Fielding in the year 2000.
Task Scheduling Strategy in the Cloud Based on Cauchy Chaotic Harris Hawk Optimization

The widespread use of cloud computing in different domains brings many challenges such as resource scheduling, load balancing, power consumption, and security. To achieve high performance of cloud resources, an efficient scheduling algorithm is required to distribute jobs among available resources to maintain system balance and fast response to user tasks. This study presents a four-level cloud scheduling model and a better Harris Hawk Optimization algorithm for scheduling, called the Cauchy Chaotic Harris Hawk Optimization algorithm (CCHHO), to address the multi-objective scheduling problem in the cloud. First, a dynamic spiral function is used to improve the exploration phase of the standard HHO algorithm. Then, a nonlinear exponential energy decreasing strategy is used to balance the exploration to exploitation transition. Finally, we use a Cauchy chaotic mutation strategy to avoid local optimum conditions and maximize resource utilization and execution time. We describe the CCHHO implementation in detail and demonstrate through simulation-based experiments that the proposed CCHHO outperforms various existing meta-heuristics in terms of convergence speed and accuracy when looking for the best task scheduling plan in the cloud.
Mean estimation of multidimensional numerical data with local differential privacy

As the localization of differential privacy (DP), local differential privacy (LDP) can provide a higher level of privacy protection by perturbing data at the user’s side, instead of through a third-party data collector. The majority of existing multidimensional data collection methods typically divided the privacy budget equally into k part and use a one-dimensional perturbation algorithm for a random k attributes. This may lead to a waste of the privacy budgets. In this paper, we propose a privacy budget allocation method with weights, where the privacy budget is allocated according to the attribute weights set by the server and the perturbed attribute values are uploaded to the server. The server can collect data with higher availability.