Reviewerly/exHarmony huggingface dataset:
Native Iron in Siberian Traps

The results of study of intrusive traps with a large-scale occurrence of native iron allowed us to identify general patterns of their composition and origin. Intrusive bodies are weakly differentiated; they feature a similar structure and mineralogical, petrochemical and geochemical composition. Two associations of rock-forming minerals were found in all the studied bodies, i.e. early deep (pre-chamber) and intra-chamber. Native iron forms nodular segregation, with a subordinate amount of cohenite, troilite and magnetite-wustite. Natural reduced iron can concentrate many elements, such as Ni, Co, Au and PGE. Their content in metal increases by hundreds or even thousands of times compared to the hosting silicate part. The formation of native iron is based on the fluid-magmatic interaction between magma substance and reducing components of the fluid, primarily of methane-hydrogen composition. As a result, dispersion of a primarily homogeneous basalt liquid into silicate and metallic components occurs. In the process of transfer, finely dispersed phases of iron form droplet-liquid segregations with a monomolecular layer of gas on their surface that prevents enlargement of metallic droplets. In the hypabyssal chamber, magma degassing occurs, including degassing from metallic spherules. The processes of droplet fusion and formation of native phase segregations begin.
The Monticellite-Bearing Rocks of the Krestovskaya Intrusion: the Genesis According to Melt Inclusion Study

The investigation of monticellitolites and olivine-monticellite rocks from the Krestovskaya Intrusion shows that the principal minerals (olivine and monticellite) contain higher amount of MgO than same minerals in olivinites and kugdites of the Intrusion. In the studied rocks olivine contains 90–93 mol. % Fo and monticellite has 41.6–42.3 mol. % Fo whereas in olivinites and kugdites olivine and monticellite contains 86–87 mol. % Fo, and 37.2–41.2 mol. % Fo, respectively. Melt inclusion study in minerals of monticellite rocks evidenced that the monticellite rocks of the Krestovskaya Intrusion were formed due to mixing melts different in composition and volatiles: K-rich high-iron low-alumina kamafugitic melt and Na-rich high-magnesia high-alumina picritic one. Minerals crystallized at high temperatures in the following sequence: perovskite I (1250–1230°C) → perovskite II (≥1200°C) ↔ olivine (1200°C) → monticellite (1150°C). Perovskite I in monticellite rocks, as well as olivine in olivinites, crystallized from K-rich high-iron (Mg # = MgO/(MgO + FeO) – 0.37), low-alumina kamafugitic melt. During crystallization of late perovskite II in monticellite rocks, the melt became more magnesian (Mg# = 0.41) and richer in Na2O and Al2O3, which is intermediate in composition between kamafugite and alkali picritoid. Olivine in monticellite rocks crystallized from melts similar in composition to melilitite, having a K-rich composition with Mg # = 0.39, whereas monticellite formed from a heterogeneous high-magnesian Si-undersaturated melt, which is highly enriched with volatile components (including H2O) and salts. The crystallization of minerals was accompanied by accumulation of volatile components in the mixing melts and as a result by the further processes of silicate-carbonate liquid immiscibility under 1250–1190°C and by multiphase carbonate-salt immiscibility under below 1190°C. In the latter event, the separated carbonate melt began to decompose into simpler immiscible fractions: alkali-sulfate-carbonate, alkali-phosphate-carbonate and calcio-carbonate.
Automatic Generation of Lexico-Grammatical Tests for Russian as a Foreign Language Using Predictive Language Models

The authors argue that in teaching a foreign language, one of the basic needs of participants of the educational process is a sufficient number of educational data. Among the tasks that contribute to the acquisition of lexical and grammatical units, gap-filling exercises with multiple-choice have become particularly popular. Nowadays, creating unique tasks manually turns out to be laborintensive. Unlike English, the development of algorithms for exercise generation for Russian is not so active, despite the existing need. In this regard, the authors propose a method for automatic generation of tasks of this type for Russian as a foreign language (RFL). The proposed method is based on distributive semantic models like word2vec and allows to create tasks based on authentic texts, it does not depend on the genre and style of the text or the corresponding language level, and can be easily adapted for other languages. To train the word2vec model, a corpus of children’s and educational literature was developed to emulate the language experience of students. In the course of the work, a web application for teachers was also launched. To assess the consistency and relevance of generated tasks, two experiments were conducted. In the first experiment, naive native speakers of the Russian language were interviewed, while in the second, a survey of experts in RFL was carried out. The high degree of correctness of the tasks and the selected distractors is proved by high scores of precision (0.8) and recall (0.91). The experts have also noted the convenience of the web application.
PENGGUNAAN WEBSITE WKWK JAPAN DALAM PEMBELAJARAN MANDIRI PADA MATA KULIAH NIHONGO SHOKYUU PADA MASA PANDEMI COVID-19

Independent learning is a person's readiness or willingness to learn independently which consists of an attitude component that takes the initiative to learn with or without the help of others. This study aims to find out how the use of the WKWK Japan website in independent learning based on the generative theory by Huda (2014) in the Nihongo Shokyuu course by Japanese Language Education students FKIP UNRI batch 2020. This study uses a qualitative descriptive method. The research was conducted by conducting interviews with data sources. The data sources in this study were 7 students of the 2020 Japanese Language Education FKIP Riau University who took the Nihongo Shokyuu class and used the WKWK Japan website in independent learning. The results of this study indicate that the class of 2020 students use independent learning strategies according to Huda (2014) in various ways in each strategy.
Hate Speech Legislation and Freedom of Expression: Finding the Balance

This study aims to explore the balance between hate speech legislation and the principle of freedom of expression. It seeks to understand the perspectives of various stakeholders on the effectiveness of current legal frameworks, the societal impact of hate speech, the challenges faced by digital platforms in moderating content, and the responses of legislative and policy measures to address these issues. Employing a qualitative research design, this study collected data through semi-structured interviews with 24 participants, including legal experts, activists, victims of hate speech, and representatives from social media platforms. Theoretical saturation guided the data collection process, ensuring a comprehensive exploration of the subject matter. Thematic analysis was utilized to identify patterns and themes within the data, with a focus on understanding the nuanced perspectives on hate speech legislation and freedom of expression. Four main themes were identified: Legal Frameworks, Societal Impact, Digital Platforms, and Legislative and Policy Responses. Under Legal Frameworks, categories such as Constitutionality, Hate Speech Legislation, Regulatory Bodies, and Legal Challenges were discussed. Societal Impact was analyzed through Public Perception, Victim Impact, and Community Relations. Digital Platforms encompassed Moderation Policies, Enforcement Challenges, Platform Accountability, User Behavior, and Impact on Public Discourse. Legislative and Policy Responses included Policy Development, Education and Awareness, Support Systems for Victims, Monitoring and Evaluation, and International Cooperation. The findings highlight the complexity of regulating hate speech while preserving freedom of expression and the need for nuanced, multi-faceted approaches. The study concludes that navigating the balance between hate speech legislation and freedom of expression requires a nuanced approach that considers legal, societal, technological, and educational perspectives. Effective hate speech regulation must protect individuals and communities from harm while respecting the fundamental right to free speech. Collaborative efforts across stakeholders and continuous refinement of policies are essential in addressing the evolving challenges posed by hate speech in digital and physical spaces.
Use of Information and Communication Technologies (ICT) for Inclusive Education

Every Indian citizen has the fundamental right to education, regardless of whether they live in a posh neighbourhood or a remote, underdeveloped village. Article 45 of the Indian Constitution mandates that all children must receive a basic elementary education up until the age of fourteen. The education sector can benefit from the application of information and communication technology (ICT). Education encompasses in-person, virtual, remote, and part-time learning. Applications for ICT in the real world are practically endless. ICT can be used to educate those who are unable to attend school because of a variety of obstacles.. Both formal and informal educational settings can benefit greatly from ICT use. The concept of inclusive education suggests that all students should have equal access to education, not in a segregated environment but rather within the framework of a mainstream educational system. Accessible Information and Communication Technologies (ICTs) are essential for parents, students, teachers, and educational authorities, and their availability greatly facilitates the advancement of an inclusive educational system. ICT’s function as a tool for education, a communication aid, and a way to access learning resources that were previously unavailable. ICT is distinct in that it is a transformative catalyst that is changing educational frameworks. The focus lies in efficiently applying ICT tools to create inclusive learning environments that are customised to meet the necessarily of a broad reach of assimilator, guaranteeing impartial access participation for all.
Colloborative Learning in Professional Education: Role of National Education Policy-2020

As outlined in the National Education Policy 2020, the cultivation of professionals should include three fundamental elements: a grounding in the ethical and societal significance of public service, specialized instruction in their chosen disciplines, and an education for practical application. These three elements are essential for fostering holistic development in professionals. Furthermore, professional education ought not to be constrained within the narrow boundaries of one’s field of expertise. Rather, it should actively promote critical thinking, interdisciplinary cooperation, and cultivate an atmosphere conducive to discourse, deliberation, exploration, and creativity. These institutions should provide holistic and comprehensive education that goes beyond disciplinary boundaries. By the year 2030, all educational institutions, regardless of their focus on professional or general education, should aim to seamlessly integrate both aspects. Collaborative Learning serves the purpose of the country by ensuring the students contribute equally and share the workload. It also allows students to embrace new challenges and collaborate with their peers on different aspects of their subject while learning.
«Method is an intellectual machine for the production of knowledge»

The article examines the role of Academician I.D. Kovalchenko in the process of formation and development in the USSR/Russia of an interdisciplinary field of historical studies called “Quantitative history”. Materials from the prominent historian’s personal archive are used as the main source.
Distribution of the cyrillic printed book of the 16th-17th centuries in the regions of Russia

The paper, for the first time, raises and resolves the question of how in XVI-XVII centuries’ copies of books printed in Cyrillic by Moscow Printing House and other printing houses were distributed to regions of Russia. The books analyzed in this paper were identified, studied and received scientific descriptions, as a part of the long-term efforts by the Moscow State University archaeographers and local specialists trained by them. The paper analyzes 2,932 copies of 520 publication titles that were delivered to regions in XVI-XVII century and preserved there until the end of the twentieth century. The ratio of Moscow and foreign publications in the regions, included in the study, allows to assume coordination of publishing plans between foreign Slavic printing houses and Moscow Printing House.
Reducing Time Steps Needed of Multi-Agent Reinforcement Methods in a Dynamic Navigation Environment

In a simpler version of the delivery variation of the multi-agent pathfinding problem, we use a reinforcement learning approach instead of other common traditional algorithmic heuristics to tackle this NP-hard problem. The paper proposes using either fully decentralized or decentralized data and a centralized model to alleviate the problem of requiring large training time steps in multi-agent reinforcement learning by reducing the number of time steps needed, especially in an environment with cumulative rewards. These approaches don’t require the concatenation of local data among agents, and, as such, are relieved of the computational burden of increased data complexity. The proposed approaches were tested in an environment where multiple agents try to work together and clean the maximum number of total nonregenerative unclean tiles in a grid filled with obstacles in a set amount of time. In a final test on a randomized dynamic environment with varying grid sizes, one of our approaches proved very promising in application and scalability. This paper's most commonly used algorithm was proximal policy optimization, with brief mentions of deep q-network. Different implementations of these algorithms had their training tracked and recorded, including Stablebaseline3 and self-implementation using TensorFlow.
Environmental Digitalization as a Task of Engineering Environment (Review of the Problem)

Digitalization (development of the information society) affects all aspects of our life, having an increasingly noticeable (both positive and negative) impact on the environment. Some information technologies in the field of ecology, directions, goals and objectives of digitalization of environmental knowledge and nature management in Russia are discussed.
On the Statistical Significance Test for the Procedure of Polarity Classification by Types of Acoustic Emission Sources

Using a mathematical statistics approach, we review the procedure for type classification of acoustic emission (AE) events into shear, tension, and collapse, proposed by Zang et al. (1998). The procedure is based on counting the signs of first pulses of waves arriving at acoustic sensors and is widely used in rock physics experiments. Under the assumption that the determination errors of first-pulse signs at sensors have uniform and independent distribution, the statistical significance and power of the type separation test are evaluated for a given number of sensors used. We consider and compare three methods of the construction of a statistical test based on the P-value approach and symmetric and asymmetric statistical hypothesis tests. Considering the results of the statistical study, we propose some practical recommendations for selecting a threshold to classify AE event types in experimental studies.
Cognitive Architecture of Cognitive Activity: Modeling and Psychophysiological Assessment

Abstract—The main approaches to modeling human cognitive activity and the underlying neural mechanisms are described. The systematization of cognitive architectures is given, and such popular models as ACT-R, SOAR, CLARION and CHREST is overviewed with examples of their practical application in psychology and neurophysiology. The use of the developed models of cognitive functions makes it possible to predict the effectiveness of perception and selection of information, which knowledge and procedures are required for the optimal solution of the problem, the expected error rate while task performing, and what functional brain system is used to organize behavior. Improvement and addition of existing models of cognitive architecture is considered as a prospect for the development of cognitive neuroscience, understanding the patterns of intelligence formation and the development of artificial intelligence.
Pelatihan Integrasi Kecerdasan Buatan Digital dalam Pembelajaran Bahasa Inggris di Madrasah

This research highlights the importance of digital literacy training and the integration of artificial intelligence in learning to improve teachers' abilities and the quality of English language learning in the digital era. The research evaluates teachers' digital literacy and knowledge of artificial intelligence (AI) and its integration into English language learning. Design quantitative descriptive with survey methods used. Online questionnaires and interviews were applied to English teachers at SMP-MA Diniyah Al-Falahiyah Lamongan to measure digital literacy, knowledge, training experience, and IT and AI media integration in learning. Most teachers have adequate digital skills, but training is still needed to increase digital literacy. Survey results show that most teachers have limited knowledge about AI, with most having never integrated AI into learning.
Research Data Management Services in the Indian Institute of Technology Libraries

Research Data Management (RDM) Service in university libraries is growing and is the most demanded service, especially for researchers. Still, many researchers need help understanding the particular research process, the life cycle of their produced data, and its management for upcoming research. Nowadays, research data is used to train upcoming professionals and teach them about specific fields of knowledge. These data will be stored, organized, and preserved on the institutional repository or the researcher's departmental external disk to be easily reused and promoted for other research works. The study's main objective is to determine the awareness of RDM services among Library and Information Science professionals working at seven IITs in North India.
Penyebab Melemahnya Bitcoin Pasca Ditemukan Varian Covid-19 Omicron

Bitcoin is one of the most valuable crypto currencies among other crypto currencies. However, the legality of Bitcoin itself has not been recognized by Indonesia and many other countries as a legal tender, but it is allowed to be used as an investment asset. In the midst of the price of Bitcoin and its very high popularity, a sudden decline occurred after the discovery of a new variant of the Covid-19 virus. This study aims to find out about the cause of the fall in the value of Bitcoin after the establishment of the new Omicron Covid-19 variant as a variant that all countries in the world must be wary of. This research is a Library Research type with data sources in the form of news published by CNBC Indonesia on December 5, 2021, using the content analysis method. The conclusion of this study is that the fall in the price of Bitcoin was caused by the fear of shareholders and other high-risk assets due to news about the possibility of a lockdown in various countries, so these investors released their risky assets, including Bitcoin as a new asset which is still experiencing very high volatility so it is considered risky.
Legislation in the Knowledge Base Paradigm: Interactive Decision Enactment for Registration Duties

Recently, a prototype for an interactive decision enactment system for notaries was developed. This prototype follows the Knowledge Base Paradigm (KBP): it consists of purely declarative domain knowledge, to which various logical inference methods can be applied. This paper extends that work in two ways. First, we experimentally validate the claim that the KBP leads to highly maintainable software. Second, we extend the number of additional logical inferences, which allows us to address a number of usability concerns. This provides further evidence for the claim that the KBP is indeed a viable method of developing interactive software systems. The resulting interactive decision enactment prototype is a fully generic system, that can be applied to other domains with minimal effort.
Simplifying the creation and management of utility models in continuous domains for cognitive robotics

Establishing goal/sub-goal hierarchies in robotic motivational systems for open-ended learning situations and modelling this utility in a manner that is useful for robots is an open research problem, especially when the robots’ state-spaces are continuous and may present ambiguities. In these cases, directly obtaining value functions, and in particular, precise Artificial Neural Network based value functions, becomes very difficult. In this paper, this issue is addressed through a new type of coarse utility functions for the representation of motivation. The proposed approach can be used as an intermediate step in order to be able to produce more consistent data for the subsequent training of precise value functions when and where it becomes necessary. This type of coarse utility functions, called Separable Utility Regions (SUR), are based on the use of the variation of sensor values as clues to the position of goals in state space. Moreover, areas in the state-space must be established where there are correlations between the desired direction the system should follow in its state-space towards a goal, and the direction of variation of the values of a particular sensor. The main focus of this paper is on the process of creating sub-goal hierarchies that permit leading the system in a consistent manner towards goals, so that it can autonomously learn to achieve them whatever its starting state. To this end, an approach to sub-goal determination and chaining based on a recursive establishment of consolidated goal domains as new goals for new utility functions is described. The approach is tested on a real robotic system and the results are extensively analysed and discussed.
Automatic MRI prostate segmentation using 3D deeply supervised FCN with concatenated atrous convolution

Prostate segmentation of MR volumes is a very important task for treatment planning and image-guided brachytherapy and radiotherapy. Manual delineation of prostate in MR image is very time-consuming and depends on the subjective experience of the physicians. On the other hand, automatic prostate segmentation becomes a reasonable and attractive choice for its speed, even though the task is very challenging because of inhomogeneous intensity and variability of prostate appearance and shape. In this paper, we propose a method to automatically segment MR prostate image based on 3D deeply supervised FCN with concatenated atrous convolution (3D DSA-FCN). More discriminative features provide explicit convergence acceleration in training stage using straightforward dense predictions as deep supervision and the concatenated atrous convolution extract more global contextual information for accurate predictions. The presented method was evaluated on the internal dataset comprising 15 T2-weighted prostate MR volumes from Winship Cancer Institute and obtained a mean Dice similarity coefficient (DSC) of 0.852&plusmn;0.031, 95% Hausdorff distance (95%HD) 7.189&plusmn;1.953 mm and mean surface distance (MSD) of 1.597&plusmn;0.360 mm. The experimental results show that our 3D DSA-FCN could yield satisfied MR prostate segmentation, which can be used for image-guided radiotherapy.