Reviewerly/exHarmony huggingface dataset:
Experimental Evidence on Negative Impact of Generative AI on Scientific Learning Outcomes

In this study, I explored the impact of Generative AI on learning efficacy in academic reading materials using experimental methods. College-educated participants engaged in three cycles of reading and writing tasks. After each cycle, they responded to comprehension questions related to the material. After adjusting for background knowledge and demographic factors, complete reliance on AI for writing tasks led to a 25.1% reduction in accuracy. In contrast, AI-assisted reading resulted in a 12% decline. Interestingly, using AI for summarization significantly improved both quality and output. Accuracy exhibited notable variance in the AI-assisted section. Further analysis revealed that individuals with a robust background in the reading topic and superior reading/writing skills benefitted the most. I conclude the research by discussing educational policy implications, emphasizing the need for educators to warn students about the dangers of over-dependence on AI and provide guidance on its optimal use in educational settings.
System Performance With K-out-of–N System

This paper deals with system performance with k-out-of –n system.This paper also shows that the investigation related to system performance applies to any branch of engineering by utilizing the mathematical tools. Further studies are in progress.
Lithology classification of igneous rocks using C-band and L-band dual-polarization SAR data

Abstract Distinguishing different kinds of igneous rocks is difficult because of their subtle differences. Synthetic aperture radar (SAR) is sensitive to rock surface morphology, which can help a lot in classification. Dual-pol SAR data have the advantages of low cost, but few articles are using only dual-pol SAR data for igneous rock classification. In this study, we explored the performance of dual-pol SAR data in distinguishing granitoid, tuff, and syenite porphyry. Backscatter coefficients, polarization decomposition parameters, and texture features from gray-level co-occurrence matrix extracted by Sentinel-1 or PALSAR were classified using several machine learning algorithms. The results are as follows. First, the texture information has greater potential for igneous rock classification, but the polarization decomposition parameters contribute less. Second, after comparing machine learning algorithms, AdaBoost algorithm has the highest overall accuracy for either C-band or L-band SAR data. C-band SAR data provide better classification results than L-band. Finally, tuff is the easiest igneous rock to be successfully classified, and L-band dual-pol SAR data have advantages in the discrimination of syenite porphyry. This study outlines the effectiveness of dual-pol SAR data for igneous rock classification, which will help to select SAR data of appropriate wavelengths for specific types of lithology discrimination.
Resource theory of dephasing estimation in multiqubit systems

We present a resource theory to investigate the power of a multqubit system as a probe in the task of dephasing estimation. Our approach employs the quantum Fisher information about the dephasing parameter as the resource measure. Based on the monotonicity of quantum Fisher information, we propose two sets of free operations in our resource theory: the Hamming distance preserving operations and the selectively Hamming distance preserving operations. We derive a necessary condition for the state transformation under these free operations and demonstrate that uniform superposition states are the golden states in our resource theory. We further compare our resource theory with the resource theory of coherence and thoroughly investigate the relation between their free operations in both single-qubit and multiqubit cases. Additionally, for multiqubit systems, we discover the incompatibility between the resource theory of dephasing estimation and that of $\text{U}(1)$ asymmetry, which is responsible for phase estimation. The condition for enhancing the performance of a probe state in phase estimation while preserving its ability in dephasing estimation is also discussed. Our results provide insights into quantum parameter estimation by the resource-theoretic approach.
Friction, Dissonance, and Affordances

Nothing ventured, nothing gained is the adage associated with risk taking and adventure. We live in a time when opportunities abound for the brave and bold. It's not simply ideas but taking the first step into the unknown. Young millionaires are leading the charge into this whole new world of difference. To embrace the opportunities it affords is the way forward epistemologically. Whether we approve of such concepts as universal basic income or the rights of cancel culture is largely irrelevant. In the scheme of things, the education process is one of responding to change. The world of AI is one big new world to embrace ontologically and epistemologically.
The impact of E-learning and ICT on English language learning: COVID-19 context

Background:&nbsp;E-learning and ICT have developed an innovative way of teaching English. To make sure the learning of this foreign language is effective, educational establishments and universities adjusted their infrastructure and technological devices. Aim:&nbsp;This article aims to present the results from a comprehensive examination of the literature regarding the Effects of E-learning and ICT on English language learning in COVID-19. Methods:&nbsp;The investigators made use of the PRISMA MODEL to determine the 65 articles to be included in the sample selection. A systematic search was performed on databases to select articles on E-learning and ICT related to English language learning. The databases employed for this study were Scielo, Redalyc, Dialnet, cademic Publishing (ACPI), Springer, Scopus, ECLAC, and MINTIC. Results:&nbsp;These technologies experienced an increase in usage during the COVID-19 pandemic. Conclusion:&nbsp;Incorporating e-learning and ICT has made language learning more dynamic. In addition, it demanded training of teachers to manage the tools and resources that they offer.
The fundamentals of the book studies (The review of the book “Neurobibliology: The first effort of the cognitive study” by V. P. Leonov)

The book [in Russian] comprises three chapters, i. e. “The book as a human innate program”, “The bibliology in search of the meanings: The book is an outer cognitome?”, “The bibliology and music as an outer cognitome and form of knowledge”, “On the reading neurobiology and “brain book”, “Neurphilosophy and neurobibliology: The problems at the interface of disciplines”, “On the interdisciplinarity of bibliology: From Bibliologos to Neurobibliology”, and “Neurbibliology as the interdisciplinary studies of the book and cognitive processes”. The reviewer dissects and analyzes the key provisions of the book. The assumption that “the book is the human innate program” contradicts to the speech evolutionary descent theory and to the practice. The documentology also answers to the question surprisingly mysterious to the book author (“what are the origins of the writing?”) – the sound is a sign and “represents” the thought. It is impossible to preserve the initial meaning for the long time so the appropriate equivalent had to be found in the form of the letters as the transformed sound signs, or the code. Further, V. Leonov develops the concept of the book as an outer cognitome, i. e. the element of integrated biomedical, technological, and existential – brain cognitive power which makes him to view the bibliology on the conjunction of neurosciences and the humanities. The theory of cognitive systems has to become the methodological foundation of the bibliology and bibliography, and the Russian Academy of Sciences needs an interdisciplinary analytic center for studies of the book phenomenon. The author suggests the term “bibliology of neurosciences” for the new discipline. Besides, he suggests that a new interdisciplinary science of cognitology has to integrate psychology, computer science, linguistics, anthropology, neuroscience, philosophy, pedagogy, bibliology, and bibliography in the aspect of knowledge. The cognitome is the innate cognitome while the book is an outer cognitome. This interpretation coincides with that of K. Popper’s three worlds, one of which is the world of “products of thought”, the objects in their own right. The reference to this concept would significantly strengthen Leonov’s hand.
Alexander M. Mazuritsky – The heights taken

The biography of Alexander Mikhailovich Mazuritskiy, a prominent Russian librarian, teacher, manager of library education, is discussed. In 1973, upon the graduation from the Moscow State Institute of Culture (MSIC), Mazuritsky took a job at Lenin State Library of the USSR, then he worked as an instructor for the State Republican Juvenile Library. In 1977, he started work at Moscow State Institute of Culture Library, and took the post-graduate program at the Institute. In 1982, A. Mazuritsky defended his candidate’s thesis and became a lecturer. In 1984, he became the associate dean, and in 1993 – the dean of the MSIC Library Department. The author discusses the key research works by A. Mazuritsky on the various aspects of the library history in the WWII period, and analyzes in brief the contents and conceptual conclusions. In 2007, A. Mazuritsky defended his doctoral thesis in pedagogy. The author characterizes the contents and importance of his doctoral paper. He gives credits to Mazuritsky’s effort as a manager of MSIC authority departments. The principles of Mazuritsky’s scholar school are discussed; his followers and students who completed dissertation, are named.
Living zealously (On Alexander Mazuritsky’s 70&lt;sup&gt;th&lt;/sup&gt; anniversary)

The author gives credits to Alexander Mikhailovich Mazuritsky’s educational efforts. A. Mazuritsky is a prominent library scholar, expert in the library history, Doctor of Science in Pedagogy, Dean of the Library Information Department of Moscow State Institute of Culture (MSIC), Professor of the Information Analytics Chair of Moscow State Linguistic University (MSLU). The author reviews Mazuritsky’s professional and public efforts as a historian, pedagogue and educator in the sphere of higher professional training. His scientific interest toward the problem of missed cultural valuables has transformed into the need to educate historical memory and civic mindedness in the younger generations. In his public lectures and interviews to mass media, speaking at forums and conferences, he strongly promotes libraries engagement in educating ethical principles and social knowledge as the foundation for patriotism. A. M. Mazuritsky maintains his principled stand on the national library policy and library development vectors. Keeping with the best traditions of the Russian library science, Alexander M. Mazuritsky voices challenging ideas and suggestions that stir up disputes and discussions in the professional community.
BiblioGorizont – the digest by the Russian National Public Library for Science and Technology: The first two years. The selected review of publications of 2021–2022

The quarterly digest BiblioGorizont has been published since 2021. It is a new periodical by the Russian National Public Library for Science and Technology on the spectrum of problems of the library information industry. The digest comprises brief analytical reviews of publications in the English-language professional journals. Both printed serial and electronic versions are registered with the Federal Service for Supervision of Communications, Information Technology and Mass Media of the Russian Federation. Each abstract comprises title translation, author(s) name(s), extended content review, keywords, UDC, GRNTI code, DOI (if any) and link to the original source. If necessary, additional information on the authors, terminology, mentioned editions, etc., is added. The access to the electronic edition is free; the search by text, title, author, keywords is available. The goals of the digest are specified: widening information base of the Russian library science, advancing professional education and international cooperation, etc. The reviewer analyzes 8 first issues of the digest from the viewpoint of professional and research subject scope of the English-language publications and the information needs of Russian librarians and researchers. She emphasizes that BiblioGorizont provides wide coverage of publications in the professional periodicals, both geographical and thematic; and highlights the problems both theoretical and applied practical. The reviewer discusses extensively the subject scope of the articles, from conceptual, philosophical and sociological problems to the technological aspects of library services; from the problems of library digital transformation, open science and open access to copyright, professional education and ethics; from bibliometrics and scientometrics to AI, sustainable development, etc.
<i>LoGenText-Plus</i> : Improving Neural Machine Translation Based Logging Texts Generation with Syntactic Templates

Developers insert logging statements in the source code to collect important runtime information about software systems. The textual descriptions in logging statements (i.e., logging texts) are printed during system executions and exposed to multiple stakeholders including developers, operators, users, and regulatory authorities. Writing proper logging texts is an important but often challenging task for developers. Prior studies find that developers spend significant efforts modifying their logging texts. However, despite extensive research on automated logging suggestions, research on suggesting logging texts rarely exists. To fill this knowledge gap, we first propose LoGenText (initially reported in our conference paper), an automated approach that uses neural machine translation (NMT) models to generate logging texts by translating the related source code into short textual descriptions. LoGenText takes the preceding source code of a logging text as the input and considers other context information, such as the location of the logging statement, to automatically generate the logging text. LoGenText ’s evaluation on 10 open source projects indicates that the approach is promising for automatic logging text generation and significantly outperforms the state-of-the-art approach. Furthermore, we extend LoGenText to LoGenText-Plus by incorporating the syntactic templates of the logging texts. Different from LoGenText , LoGenText-Plus decomposes the logging text generation process into two stages. LoGenText-Plus first adopts an NMT model to generate the syntactic template of the target logging text. Then LoGenText-Plus feeds the source code and the generated template as the input to another NMT model for logging text generation. We also evaluate LoGenText-Plus on the same 10 projects and observe that it outperforms LoGenText on 9 of them. According to a human evaluation from developers’ perspectives, the logging texts generated by LoGenText-Plus have a higher quality than those generated by LoGenText and the prior baseline approach. By manually examining the generated logging texts, we then identify five aspects that can serve as guidance for writing or generating good logging texts. Our work is an important step toward the automated generation of logging statements, which can potentially save developers’ efforts and improve the quality of software logging. Our findings shed light on research opportunities that leverage advances in NMT techniques for automated generation and suggestion of logging statements.
Legal system-oriented telecom fraud detection, identification and prevention

INTRODUCTION: With the development of technology, telecom fraud is appearing more and more frequently and causing more and more harm.OBJECTIVES: This paper focused on the detection, identification, and prevention of telecom fraud.METHODS: Firstly, the telecom fraud crime was analyzed, the existing legal system was explained, and some suggestions on the protection of telecom fraud were proposed at the legal level. Then, the characteristics of telecom fraud users were analyzed to point out the differences between fraud users and normal users in terms of call, message, and traffic behavior. Finally, the Boosting algorithm was used to detect and identify telecom fraud.RESULTS: The experiments found that the boosting algorithm had advantages in the detection and recognition of telecom fraud compared with the algorithms such as support vector machine and random forest algorithms. Among several boosting algorithms, the CatBoost algorithm performed the best, with an accuracy of 0.9465 and an F1 value of 0.9047.CONCLUSION: The results demonstrate the reliability of the CatBoost algorithm in detecting and recognizing telecom fraud, and it can be applied in practice.
A Graph-Based Context-Aware Model to Understand Online Conversations

Online forums that allow for participatory engagement between users have been transformative for the public discussion of many important issues. However, such conversations can sometimes escalate into full-blown exchanges of hate and misinformation. Existing approaches in natural language processing (NLP), such as deep learning models for classification tasks, use as inputs only a single comment or a pair of comments depending upon whether the task concerns the inference of properties of the individual comments or the replies between pairs of comments, respectively. However, in online conversations, comments and replies may be based on external context beyond the immediately relevant information that is input to the model. Therefore, being aware of the conversations’ surrounding contexts should improve the model’s performance for the inference task at hand. We propose GraphNLI , 1 a novel graph-based deep learning architecture that uses graph walks to incorporate the wider context of a conversation in a principled manner. Specifically, a graph walk starts from a given comment and samples “nearby” comments in the same or parallel conversation threads, which results in additional embeddings that are aggregated together with the initial comment’s embedding. We then use these enriched embeddings for downstream NLP prediction tasks that are important for online conversations. We evaluate GraphNLI on two such tasks - polarity prediction and misogynistic hate speech detection - and find that our model consistently outperforms all relevant baselines for both tasks. Specifically, GraphNLI with a biased root-seeking random walk performs with a macro- F 1 score of 3 and 6 percentage points better than the best-performing BERT-based baselines for the polarity prediction and hate speech detection tasks, respectively. We also perform extensive ablative experiments and hyperparameter searches to understand the efficacy of GraphNLI. This demonstrates the potential of context-aware models to capture the global context along with the local context of online conversations for these two tasks.
SpinQ: Compilation Strategies for Scalable Spin-Qubit Architectures

Despite Noisy Intermediate-Scale Quantum devices being severely constrained, hardware- and algorithm-aware quantum circuit mapping techniques have been developed to enable successful algorithm executions. Not so much attention has been paid to mapping and compilation implementations for spin-qubit quantum processors due to the scarce availability of experimental devices and their small sizes. However, based on their high scalability potential and their rapid progress it is timely to start exploring solutions on such devices. In this work, we discuss the unique mapping challenges of a scalable crossbar architecture with shared control and introduce SpinQ , the first native compilation framework for scalable spin-qubit architectures. At the core of SpinQ is the Integrated Strategy that addresses the unique operational constraints of the crossbar while considering compilation scalability and obtaining a O(n) computational complexity. To evaluate the performance of SpinQ on this novel architecture, we compiled a broad set of well-defined quantum circuits and performed an in-depth analysis based on multiple metrics such as gate overhead, depth overhead, and estimated success probability, which in turn allowed us to create unique mapping and architectural insights. Finally, we propose novel mapping techniques that could increase algorithm success rates on this architecture and potentially inspire further research on quantum circuit mapping for other scalable spin-qubit architectures.
A Dynamic Ensemble Selection of Deepfake Detectors Specialized for Individual Face Parts

The development of deepfake technology, based on deep learning, has made it easier to create images of fake human faces that are indistinguishable from the real thing. Many deepfake methods and programs are publicly available and can be used maliciously, for example, by creating fake social media accounts with images of non-existent human faces. To prevent the misuse of such fake images, several deepfake detection methods have been proposed as a countermeasure and have proven capable of detecting deepfakes with high accuracy when the target deepfake model has been identified. However, the existing approaches are not robust to partial editing and/or occlusion caused by masks, glasses, or manual editing, all of which can lead to an unacceptable drop in accuracy. In this paper, we propose a novel deepfake detection approach based on a dynamic configuration of an ensemble model that consists of deepfake detectors. These deepfake detectors are based on convolutional neural networks (CNNs) and are specialized to detect deepfakes by focusing on individual parts of the face. We demonstrate that a dynamic selection of face parts and an ensemble of selected CNN models is effective at realizing highly accurate deepfake detection even from partly edited and occluded images.
The work engagement cycles of federal civil servants

Abstract Civil servants have different levels of work engagement throughout their working lives. These variations are the work engagement cycles, which occur based on available resources and work environment demands. This study describes the work engagement cycles of federal civil servants based on their professional life histories, highlighting the demands and resources of the work environment in their professional trajectory. Using the job demands-resources (JD-R) model and the cognitive maps methodology, it was possible to identify a positive cycle of work engagement, a reinforcing cycle (related to opportunities and appreciation), and two disequilibrium cycles, one related to dysfunctional productivity and the other to administrative discontinuity. The analysis of the engagement cycles allowed the identification of work environment resources that interfere in the engagement of public servants in different ways. Finally, the concept of “coping cycle” was used as a subsidy of policies for disengaged servants.