Understanding Déjà vu: Explanations, Mechanisms and the ‘normal’ kind of déjà vu (Part 2)

Hypnoterapi action research on pain management and anxiety based colon cancer patients in the problems of pain and anxiety often expressed by colon cancer patients who have undergone surgery and is in the process of chemotherapy, anxiety will increase when individuals face the threat of a life change as a result of disease and duration of the treatment process. The root of the problem in this research is how hypnotherapy reduce pain and anxiety in patients with colon cancer in a surgical disease inpatient unit RSU Banyumas. Design a qualitative research approach action research/action research using Elliot›s Action Research Model, which consists of the process of identifying the initial idea, searching and analyzing facts about pain and anxiety, making planning hypnoterapi, action hypnoterapi, evaluate the success or failure of interventions hypnotherapy, revise ideas, the steps are performed in three cycles. Formulation of the problem in this research is «How to decrease pain and anxiety in patients with colon cancermafter hypnotherapy in the inpatient surgical disease RSU Banyumas». Data processing and data interpretation using NVivo software 9.0.204.0. Based on the data obtained during the application of the three cycles of action showed that hypnotherapy is eff ective in reducing pain and anxiety in patients with colon cancer who are undergoing chemotherapy inpatient unit RSU Banyumas. Decrease in pain every cycle between 4 to 6.3, while the average decrease anxiety between 7 to 15.8. Conclusions in hypnotherapy research helpful in reducing pain and anxiety of patients who suff er from colon cancer and is undergoing chemotherapy in RSU Banyumas. Researchers hope hypnoterapi intervention can be arranged with a standard operating procedure nursing care in the health facilities and can be learned by nurses through nursing education curriculum. Keywords: hypnotherapy, colon cancer, pain, anxiety.

Relevance. Global and tectonic shifts in the world economy that occurred in the XXI century in the world inevitably reflected on the state of national economies. The Russian economy, over a decade of economic sanctions against it, which are practically open-ended sabotage by the United States and a number of Western countries against the Russian critical infrastructure - the Nord Stream 2 gas pipeline on September 26, 2022, has found itself in a situation of de facto complete stoppage of export-import operations in the field of foreign trade with European countries.The purpose is to study the institutional foundations of the formation of a resource-innovative model of economic growth in the modern Russian economy. The objectives are interrelated and consist in the following: to analyze an array of economic scientific papers on the problem of research; to analyze the institutional foundations for the formation of a resource-innovative model of the development of the Russian economy; to determine the dynamics of budget financing of scientific research for the period from 2012 to 2022, etc. Methodology is a combination of general scientific research methods – analysis, synthesis of received information, interpretation of data. The information base of the study includes presidential decrees, strategic planning documents, national projects, scientific articles by Russian researchers on the problem under study. Results: the main problems of forming a resource-innovative model of economic growth in Russia at the present stage of economic development are identified; the shortcomings of the state policy in the field of financing R&D, innovative solutions and products that hinder the activities of innovative enterprises in the real sector of the economy are revealed.Conclusions. The Russian economy remains raw in its essential content. However, the introduction of digitalization technologies, artificial intelligence, new ideas and knowledge are gradually forming a resourceinnovative model for the development of the Russian economy.

The article describes the essence of master’s education, actualizes the problems of master’s training of artists and teachers in modern Russia. It is suggested that the lack of qualification of the previous level of specialized education for master’s students violates the specifics of training in higher art education. The purpose of the article is to update the problems of master’s training of specialists who do not have a diploma in art and pedagogical education. Methodology. The study is built on the basis of a contextual approach, which made it possible to identify a problem relevant to the current state of art education related to the master’s training of an artist-teacher. The theoretical method was chosen as the main research method (analysis of regulatory documents and literature on the research problem, analysis and synthesis, comparison, generalization and interpretation of data). Research result. The analysis of the state of implementation of the master’s training of the artist-teacher in Russian education made it possible to identify a problem that must be addressed at the legislative level. Artistic and pedagogical education has its own specifics, which must be taken into account when organizing recruitment for a master’s degree in the field of “Art Education”. The lack of thought of innovations has a negative impact on the quality of training of graduates who do not have a previous level of specialized education. Conclusion. In conclusion, the authors argue that applicants with a non-core education experience difficulties in a master’s program in art education, since they do not have a list of competencies required by the master’s training of an artist-teacher.

ABSTRACTEvaluation of soil transformations and degradation is important not only for agriculture, but also for fundamental research on identification of new features for classification. In 1999, new Lithuanian soil classification (LTDK-99) was developed by adopting the diagnostic principles of WRB 1998. Together with new knowledge, it highlighted some relevant soil research and classification problems. Not only new terms but also diagnostic features of several newly distinguished first-level soils groups are being discussed, especially for the identification of cambisols, planosols, arenosols, and regosols. Additionally, a group of stagnosols is suggested for inclusion into this classification. The presence of glaciogenic secondary clay minerals in Lithuanian cambisols does not imply unambiguous brownification involvement, neither any study shows cambisols having specific to brownification iron minerals. The intensively occurring lesive in these soils questions correctness of identification of cambisols additionally aggravated by strong and deep anthropogenization of the soil profiles within the territorial range. Complex glaciogenesis makes it difficult to identify Lithuanian planosols. WRB 2014 (update 2015) identifies planosols according to the pedogenesis in old, strongly weathered binomial deposits using examples mostly from South American, South and East African plateaus of the subtropical zone. The same classification assigns planosols identified in Lithuania to stagnosols, that is, to the soils characterized by binomial genesis and stagnification. The diagnostic features of arenosols and regosols are similar in both groups and are related to primitive pedogenesis. Difficulties in distinguishing between the two groups in Lithuania are strengthened by the intensive cultivation of the ecosystems in their territorial range. The existing problems in Lithuanian soil diagnostics underline the questions of soil classification in general, especially regarding the evolution tendencies in soil classification. The article draws attention to the soil diagnostic aspects like distribution and genesis of clay particles, genesis of territory, and anthropogenic transformation for the improvement of soil identification.

Introduction The modern conditions of existence of armies are characterized by a high level of requirements for professional knowledge and skills on the one hand and aging of knowledge in the conditions of rapid changes of the world on the other. Therefore, the educational process must be continuous and territorially distributed. These conditions (time requirements) can be fulfilled only with the use of modern information technologies, which should be applied in the educational activities of higher military educational institutions. The article analyzes the current experience of using information systems in military education and outlines the main problematic issues that need to be addressed.Purpose The purpose of the article is to determine the directions of use of modern technologies in information support of the military education system.Methods the system of general scientific and special methods of theoretical and empirical research, namely theoretical and methodological analysis of the problem, analysis of scientific literature on the problem of research, systematization and generalization of scientific information concerning the nature and content of certain tasks, monitoring of existing systems were used to solve the set research problems. training of military specialists in the Russian Armed Forces, scientific generalization, general scientific methods of logical and comparative analysis, systematic approach, expert zinc, analysis and interpretation of theoretical and empirical data. Results the result of the article is a set of directions of use of modern technologies in the information support of the military education system.Originality The article first analyzes the state of the distance learning system in military education and outlines ways to solve the main problems.Conclusion The system of military education in Ukraine in terms of distance learning is in the stage of active development and implementation of best practices in teaching non-secret disciplines and courses. The problem remains the task of creating an infrastructure for handling classified information. Of course, this will be the next stage in the development of the distance learning system.

The article discusses the main key competencies of a future teacher in the field of pedagogical sciences in the direction of training teachers with a subject specialization in the general development of the group of educational programs (EP) "Artistic Labor" on the material of the innovative educational program "Technical Modeling and Cyber Pedagogy". The study is represented by the unity of four stages (theoretical analysis of publications on the research problem; research comparative analysis of existing EPs in the direction of technical education; empirical stage of developing, piloting and distributing a questionnaire in the Google forms format among the participants in this study-stakeholders; analytical and synthetic stage of analysis and interpretation of the survey data obtained, highlighting the key competencies of the EP, formulating conclusions and research prospects). Based on the analysis, 38 EP texts of the studied area of training teachers with subject specialization of the general development of the group of educational programs "Artistic Labor" were analyzed; three criteria for comparing the content of the EP (the fields of technical education, cyberpedagogy and supplementary technical education) were defined. Within the framework of the EP being developed, 6 general pedagogical competencies and 10 professional competencies of the innovative EP "Technical Modeling and Cyber Pedagogy" (A. Baitursynov Kostanay Regional University) were identified, analyzed and ranked by stakeholders.

Dynamic network link prediction is a hot research problem in complex networks. Network representation learning can effectively learn the similarity of nodes and can be used for link prediction. Existing dynamic network representation learning methods mainly discrete window dynamic networks and then model them on static network snapshot graphs, which is difficult to effectively deal with dynamic networks with fine-grained temporal characteristics. In this paper, we propose a link prediction model that can learn complex temporal properties in dynamic networks. The model uses continuous time event sequences to represent dynamic networks, learns continuous temporal information and structural evolution features in the networks, and proposes a temporal attention-based information transfer mechanism to model the diffusion and aggregation of information in the networks. Finally, it transforms link prediction into a classification problem. The experiments are conducted on four real dynamic network datasets and simulated networks, using ap and auc as evaluation metrics. The experimental results of real networks demonstrate that the model can effectively learn the continuity of network evolution and obtain an effective node representation, thus improving the link prediction effect. The experimental results of the simulated network show that the effect of link prediction is related to the network model, but the model in this paper can still obtain better prediction results.

Several activities, comprising animate and inanimate entities, can be examined by means of Social Network Analysis (SNA). Classification tasks within social network structures remain crucial research problems in SNA. Inherent and latent facts about social graphs can be effectively exploited for training Artificial Intelligence (AI) models in a bid to categorize actors/nodes as well as identify clusters with respect to a given social network. Thus, important factors such as the individual attributes of spatial social actors and the underlying patterns of relationship binding these social actors must be taken into consideration. These factors are relevant to understanding the nature and dynamics of a given social graph. In this paper, we have proposed a hybrid model: Representation Learning via Knowledge-Graph Embeddings and Convolution Operations (RLVECO) which has been modelled for studying and extracting meaningful facts from social network structures to aid in node classification and community detection problems. RLVECO utilizes an edge sampling approach for exploiting features of a social graph, via learning the context of each actor with respect to its neighboring actors, with the aim of generating vector-space embeddings per actor which are further exploited for unexpressed representations via a sequence of convolution operations. Successively, these relatively low-dimensional representations are fed as input features to a downstream classifier for solving community detection and node classification problems about a given social network.

Research is a quest, driven by a specific question, that needs an answer. Leedy (1993), in his book, Practical Research: Planning and Design, lists eight characteristics to define research. Research: 1. Originates with a question or a problem 2. Requires a clear articulation of a goal 3. Follows a specific plan of procedure 4. Usually divides the principal problem into more manageable subproblems 5. Is a specific research problem, question, or hypothesis that will guide research 6. Accepts certain critical assumptions. These assumptions are underlying theories or ideas about how the world works 7. Requires the collection and interpretation of data in attempting to resolve the problem that initiated the research 8. Is, by its nature, cyclical; or more exactly, spiral or helical Anderson and Kanuka (2003) loosely define e-research as research that takes advantage of “the excitement, breadth, and diversity offered by an ever-increasing and sometimes bewildering set of new Net-based tools and techniques” (Anderson & Kanuka, 2003, p. 4).

It is our great pleasure to welcome you to Modularity: aosd.12, the premiere international research conference on modularity in software and software-intensive systems. Modularity: aosd.12 is the 11th annual international conference on Aspect Oriented Software Development (AOSD), and the first in which the conference committee will give an award for the most influential paper published in the Proceedings of the conference 10 years ago: in 2002. This year's conference continues to broaden of the scope of the field to address all aspects of modularity, abstraction, and separation of concerns as they pertain to software, including new forms, uses, and analysis of modularity, along with the costs and benefits, and tradeoffs involved in their application. Modularity provides the international computer science research community and its many sub-disciplines (including software engineering, languages, and computer systems) with unique opportunities to come together to share and discuss perspectives, results, and visions with others interested in modularity as well as in the languages, development methods, architectures, algorithms, and other technologies organized around this fundamental concept. The Modularity: aosd.12 conference comprises two main events: Research Results and Modularity Visions. Both events invited full, scholarly papers of the highest quality on results and new ideas in areas that include but are not limited to complex systems, software design and engineering, programming languages, cyber-physical systems, and other areas across the whole system life cycle. Papers submitted to the Research Results track were reviewed in accordance with the highest established standards of scientific rigor applied in peer review of putative research results. Reviewers assessed works in terms of research problem formulations, novelty and sophistication of proposed solutions, clarity and significance of hypotheses, proper design and execution of experimental or analytical assessments, sound interpretation of data, and correct characterization of work in relation to existing knowledge. Papers submitted to the Modularity Visions track were reviewed in accordance with the highest established standards of scientific rigor applied in peer review of scientific research proposals. Reviewers assessed works in terms of research problem formulations, novelty and sophistication of proposed solutions, clarity and significance of hypotheses, compelling preliminary results, proposals for sound future experimental or analytical assessments and interpretation of data, and correct characterization of work in relation to existing knowledge. The Results track attracted 79 submissions from across the world. Of these, 20 papers were accepted for publication, for a 25% acceptance rate. The program committee accepted papers in three rounds. In each round papers each paper was accepted, rejected, or (except in the last round) invited for revision and a second review. Five (5) papers were invited for revision and a second review, all of which were ultimately accepted. The Visions track reviewed 10 papers, one of which was referred from the Results track. Of these, three papers were accepted for publication for a 30% acceptance rate. Our keynote and heart of technology speakers are Lars Bak, James O. Coplien, and Martin C. Rinard. Lars will report on implementing language-based virtual machines; Jim will talk about objects of the people, for the people, and by the people; and Martin will tell us what to do when things go wrong and how to recover in complex systems.

This study aims to investigate the influence of a person's optimistic and pessimistic personality on the saving habits of household financial managers in Kupang City. To achieve the purpose of the research in question, in this study, the author took literature sources from financial management and psychology, then the relevant hypotheses were built. The data was analyzed using Structural Equation Modeling (SEM) techniques using the help of SmartPLS software. This research was conducted in 2 (two) stages, namely the initial stage and the advanced stage. At the initial stage, we determine the topic and theme of the research, and formulate a research problem. In the advanced stage, conduct data collection, analysis, data interpretation and finally compile the final research report. The results of this study show that both optimism and pessimism influence saving habits through prudence in shopping.

This paper aims to conduct a discussion backed up by academic findings on the study of challenges faced by economic HR managers who compete in the digital era; the problems and challenges faced by HR managers are admittedly weighty. Therefore, various breakthroughs and studies are needed to minimize these challenges. For this reason, this study has utilized many academic publications to back up a study of the challenges faced by managing sustainable economic and human resources based on digital applications. We did an online search for data in many published journals, both books, and articles, which we then studied carefully, such as involving data coding, data analysis, comprehensive data evaluation, and data interpretation so that these data become valid and valid findings to answer research problems and hypotheses.

The Kanun Negeri Lingga (KNL) manuscript is an Old Malay Law (UML) text that proves the existence of Islamic legislation in Sarawak. This text represents Malay customary law that aligns with Islamic law. KNL consists of 88 pages detailing Islamic Law (Sharia); Laws of Royal Governance (Hukum Kanun Datu); Lingga Malay Customary Law; Criminal Law; Maritime Law (Ports, ships, navigation, merchant boats); and Commercial Law (trading, business, pawning, buying and selling, and lending). This study aims to prove the existence of Islamic family law practices in Sarawak before James Brooke’s arrival in the state. The specific objectives of this study are to elaborate on the information and content related to the Kanun Negeri Lingga manuscript; and to examine the Islamic family laws contained within the Kanun Negeri Lingga manuscript. This research employs a qualitative descriptive research approach, utilizing library research methods and document analysis. The data analysis method used to examine and explain the interpretations found in KNL is micro in nature and involves five main stages: text preparation and understanding research problems; reading the entire KNL; data coding; data classification based on themes; and data interpretation or explaining the meaning of the obtained data. The study successfully elaborates on the information and content of the KNL manuscript, with a particular focus on aspects of Islamic family law. Detailed analysis has been conducted on various aspects of Islamic family law in KNL, covering marriage, engagement, guardianship, offer and acceptance (ijab and kabul), witnesses, the concept of khiyar, as well as specific provisions related to marriage laws between Muslims and non-Muslims, and between free individuals and slaves. This study concludes that the existence of KNL serves as evidence contributing significantly to the formation of Sarawak’s constitutional framework in general and Islamic legislation in Sarawak in particular.

This research addresses the research problem of sentiment classification and topic analysis in the context of the Aftermovie Piala Presiden Esports 2019 (Onic Esport), employing the CRISP-DM methodology. Leveraging a dataset comprising 1830 posts, sentiment analysis was conducted on 191 posts using Vader and TextBlob algorithms, revealing the distribution of polarity values: 7.41% negative, 58.02% neutral, and 34.57% positive sentiments. Furthermore, the study evaluates the performance of classification algorithms, such as k-nearest Neighbors (k-NN), Support Vector Machine (SVM), and Decision Tree (DT), utilizing SMOTE. Notably, SVM demonstrated an accuracy of 90.34%, AUC of 0.995, precision of 99.91%, recall of 80.77%, and F-measure of 89.29%. Similarly, DT exhibited an accuracy of 94.83%, AUC of 0.950, precision of 92.12%, recall of 98.12%, and F-measure of 95.00%. K-NN displayed an accuracy of 92.83%, AUC of 0.972, precision of 98.01%, recall of 87.46%, and F-measure of 92.42%. The analysis also revealed frequently used words in the dataset, including 'onic' (127 occurrences), 'udil' (95 occurrences), and 'piala' (28 occurrences). This study sheds light on sentiment patterns and prevalent topics among esports enthusiasts, offering insights for content optimization and event management strategies.

This paper works on the idea of integrating the acoustic scene classification technique in active noise control (ANC), whereby the major difficulty lies in the limited dataset available from an ANC system in use. A large-scale acoustic scene dataset recorded by a different acoustic device has to be considered. This leads to the research problem of acoustic scene classification by mismatched devices. Hence, an ensemble of the convolutional neural networks (CNNs) is demonstrated with a novel data augmentation method. Monaural samples are processed by the head-related transfer functions (HRTFs) of 24 azimuths to add in the artificial spatial information. Every two symmetrical azimuths are then paired together to provide a tempo-spectral feature consisting of 4 channels. 12 CNNs are trained with respective features. Finally, different ensemble strategies are carried out and their classification accuracies are compared. When the random forest is used as the meta-learner, the ensemble of CNNs achieves the best classification accuracy of 65.1% over 10 acoustic scenes.