Unrelated Concepts Research Articles

Solving Mean-Payoff Games Via Quasi Dominions

We propose a novel algorithm for the solution of mean-payoff games that merges together two seemingly unrelated concepts introduced in the context of parity games, small progress measures and quasi dominions. We show that the integration of the two notions can be highly beneficial and significantly speeds up convergence to the problem solution. Experiments show that the resulting algorithm performs orders of magnitude better than the asymptotically-best solution algorithm currently known, without sacrificing on the worst-case complexity.

Pre-service Mathematics Teachers' Professional Self-Esteem and Beliefs about the Nature of Mathematics

This study aims to examine the professional self-esteem of pre-service primary school mathematics teachers in the context of their beliefs about the nature of mathematics. The study has a quantitative design and 220 pre-service mathematics teachers voluntarily participated in the study. In the data analysis of this study based on a quantitative research design, independent samples t-test, one-way ANOVA and multiple regression analyzes were performed and the Pearson correlation coefficient was determined. According to the findings of the study, professional self-esteem and belief about the mathematics' nature are not affected by gender and grade level. In addition, professional self-esteem of the pre-service teachers who believe that mathematics is a branch of science open to exploration, knowledge generation, and related to other sciences and daily life, may be said to be higher-positive than the professional self-esteem of the pre-service mathematics teachers who perceive mathematics as a set of unrelated concepts and formulas or believe that mathematics is a deductive and precise body of knowledge.

«NORTHERN LIGHTS»: VISUALIZATION OF THE NEW RUSSIAN HISTORICAL NARRATIVE

The article is devoted to the analysis of one of modern Russia’s local or group historical narratives, which articulates the mystical connection of the north-Russian population with Finno-Ugric shamanic practices based on runes «Kalevala». The TV series «Northern Lights» (the original script of Victoria Platova) in the genre of a mystical detective discusses one of the ways to deploy a «folk» or popular historical narrative, which is some controversial attitude of the state policy of memory and a conservative turn in historical policy. The relationship of the representations about Finnish roots of Russian ethnos with such unrelated concepts as «escapism» and «Aryan myth» was analyzed. The gradual drift of popular history in mass media is considered from the purely Slavic narrative of origin and ancient mystical practices of the people of north-western Russia to the recognition of Finno-Ugric roots or even the unity of Russian and Finnish peoples of the Russian north. The deconstruction of the series by visual anthropology techniques revealed a constant appeal to the everyday magical practices of the Karelian heroes of the series, who identify themselves as Russians. The inhabitants of the Island, where the action takes place, all the structure of their daily lives and holidays are built around the gods and heroes of Kalevala. The narratives «Finnish roots» in media are considered in connection with the interpretation of dubious results «Russian Nobility DNA Project», the origin of Princess Olha and Old Ladoga, as the source of Russia. The conclusion is reached on the participation of many actors and polyphonicity of modern Russian historical narrative, search for new lines of interface of Russian history and Europe.

Leveraging non-lattice subgraphs for suggestion of new concepts for SNOMED CT.

Missing hierarchical is-a relations and missing concepts are common quality issues in biomedical ontologies. Non-lattice subgraphs have been extensively studied for automatically identifying missing is-a relations in biomedical ontologies like SNOMED CT. However, little is known about non-lattice subgraphs' capability to uncover new or missing concepts in biomedical ontologies. In this work, we investigate a lexical-based intersection approach based on non-lattice subgraphs to identify potential missing concepts in SNOMED CT. We first construct lexical features of concepts using their fully specified names. Then we generate hierarchically unrelated concept pairs in non-lattice subgraphs as the candidates to derive new concepts. For each candidate pair of concepts, we conduct an order-preserving intersection based on the two concepts' lexical features, with the intersection result serving as the potential new concept name suggested. We further perform automatic validation through terminologies in the Unified Medical Language System (UMLS) and literature in PubMed. Applying this approach to the March 2021 release of SNOMED CT US Edition, we obtained 7,702 potential missing concepts, among which 1,288 were validated through UMLS and 1,309 were validated through PubMed. The results showed that non-lattice subgraphs have the potential to facilitate suggestion of new concepts for SNOMED CT.

Bioinspired translation of classical music into de novo protein structures using deep learning and molecular modeling

Architected biomaterials, as well as sound and music, are constructed from small building blocks that are assembled across time- and length-scales. Here we present a novel deep learning-enabled integrated algorithmic workflow to merge the two concepts for radical discovery of de novo protein materials, exploiting musical creativity as the foundation, and extrapolating through a recursive method to increase protein complexity by successively injecting protein chemistry into the process. Indeed, music is one of the few universal expressions that can create bridges between cultures, find associations between seemingly unrelated concepts, and can be used as a novel way to generate bio-inspired designs that derive functions from the imaginations of the creative mind. Earlier work has offered a pathway to convert proteins into sound, and sound into proteins. Here we build on this paradigm and translate a piece of classical music into matter. Based on Bach’s Goldberg variations, we offer a series of case studies to convert the musical data imagined by the composer into protein design, and folded into a 3D structure using deep learning. The quest we seek to address is to identify semblances, or memories, or information content in such musical creation, that offers new insights into pattern relationships between distinct manifestations of information. Using basic local alignment search tool analysis, we find that several fragments of the new proteins display similarities to existing protein sequences found in proteobacteria among other organisms, especially in regions of low complexity and repetitive motifs. The resulting protein forms the basis for iterative musical composition, and an evolutionary paradigm that defines a variational pathway for melodic development, complementing conventional creative or mathematical methods. This paper broadens the concept of what is understood as bio-inspiration to include a broad array of systems created by humans, animals, or other natural mechanisms.

Centrality of Religiosity and Dyadic Coping in Close Romantic Relationships: Actor Partner Interdependence Model

Some studies suggest that religious people cope better with stress. For married couples, if partners perceive their relationship as sacred, supportive dyadic coping mediates the association of sanctification with marital satisfaction and well-being. In the current study, applying the actor–partner interdependence model to 116 Polish couples (n = 232), aged between 21 and 64 (males: M = 37.8, SD = 11.8; females M = 37.1, SD = 12.0), we examined the link between centrality of religiosity and dyadic coping. Although general dyadic analyses indicate that centrality of religiosity and dyadic coping are unrelated concepts, at the subscales level, we could observe few significant relationships. The results show that Polish religious men rate their common dyadic coping low. Actor effects in women are moderated by the type of relationship (cohabitation and civil marriage vs. catholic marriage).

Diversity, dependence and independence

We propose a very general, unifying framework for the concepts of dependence and independence. For this purpose, we introduce the notion of diversity rank. By means of this diversity rank we identify total determination with the inability to create more diversity, and independence with the presence of maximum diversity. We show that our theory of dependence and independence covers a variety of dependence concepts, for example the seemingly unrelated concepts of linear dependence in algebra and dependence of variables in logic.

Activating the Right Hemisphere Through Left-Hand Muscle Contraction Improves Novel Metaphor Comprehension.

The neurotypical brain is characterized by left hemisphere lateralization for most language processing. However, the right hemisphere plays a crucial part when it is required to bring together seemingly unrelated concepts into meaningful expressions, such as in the case of novel metaphors (unfamiliar figurative expressions). The aim of the current study was to test whether it is possible to enhance novel metaphor comprehension through an easy, efficient, and non-invasive method – intentional contraction of the left hand’s muscles, to activate the motor and sensory areas in the contralateral hemisphere. One hundred eighteen neurotypical participants were asked to perform a semantic judgment task involving two-word expressions of four types: literal, conventional metaphors, novel metaphors, or unrelated, while squeezing a rubber ball with their right hand, left hand, or not at all. Results demonstrated that left-hand contraction improved novel metaphor comprehension, as participants were more accurate and quicker in judging them to be meaningful. The findings of the present work provide a simple and efficient method for boosting right hemisphere activation, which can be used to improve metaphoric language comprehension. This method can aid several populations in which right hemisphere function is not fully established, and who struggle with processing figurative language, such as adolescents and individuals on the autistic spectrum.

An Implicit Measure of Sexual Double Standard Endorsement in Emerging Adults: Reliability and Validity Aspects

Psychometric characteristics were investigated of an Implicit Association Test to assess implicit endorsement of the sexual double standard (SDS-IAT) in emerging adults. The reliability of the SDS-IAT was investigated focusing on internal consistency across different phases of the test. Convergent validity of the SDS-IAT was evaluated against the Scale for the Assessment of Sexual Standards in Youth, an explicit measure of SDS, and against gender investment. Divergent validity was evaluated against the personality characteristics of extraversion, neuroticism, and social desirability proneness. Gendered patterns were examined. Attenuation-corrected alphas demonstrated acceptable internal consistency, with alphas ranging for .65–.70. A modest level of explicit SDS endorsement was found in both female and male participants. In line with their explicit SDS level, a modest level of implicit SDS endorsement was found in male participants, whereas a reverse implicit SDS was found among young women. In agreement with our theoretical expectations, we found low convergent validity in multitrait-multimethod analysis of the SDS-IAT with a measure of explicit SDS endorsement, and with general level of investment in gender ideals. Similarly, divergent validity analysis revealed absence of significant correlations with the conceptually unrelated concepts of extraversion, neuroticism, and social desirability proneness, except for extraversion in female participants. The present findings suggest that implicit SDS endorsement can be assessed using the SDS-IAT. The finding that explicit and implicit SDS approvals differ in young female participants, while they align in young male participants, warrants further research.

A common computational principle for vibrotactile pitch perception in mouse and human

We live surrounded by vibrations generated by moving objects. These oscillatory stimuli propagate through solid substrates, are sensed by mechanoreceptors in our body and give rise to perceptual attributes such as vibrotactile pitch (i.e. the perception of how high or low a vibration’s frequency is). Here, we establish a mechanistic relationship between vibrotactile pitch perception and the physical properties of vibrations using behavioral tasks, in which vibratory stimuli were delivered to the human fingertip or the mouse forelimb. The resulting perceptual reports were analyzed with a model demonstrating that physically different combinations of vibration frequencies and amplitudes can produce equal pitch perception. We found that the perceptually indistinguishable but physically different stimuli follow a common computational principle in mouse and human. It dictates that vibrotactile pitch perception is shifted with increases in amplitude toward the frequency of highest vibrotactile sensitivity. These findings suggest the existence of a fundamental relationship between the seemingly unrelated concepts of spectral sensitivity and pitch perception.

Identifying Concepts Created for Geometric Objects: Mind Map

The purpose of this research is to determine the knowledge, perceptions and misconceptions of preservice primary school teachers about geometric objects through mind maps. For this purpose, the research was designed with a case study, one of the qualitative research methods. The study group of the research consists of 52 pre-service primary school teachers studying at a state university in the Aegean Region of Turkey. After giving information about mind maps to pre-service primary school teachers, they were asked to create mind maps about the concept of “Geometric Objects”. The created mind maps were subjected to content analysis and codes and categories were created. The mind maps of pre-service primary school teachers were analysed one by one, starting from the centre towards the outer branches and separated as related and unrelated concepts. As a result of the research, it was revealed that most of the pre-service primary school teachers who participated in the study used the concepts of geometric objects and geometric shapes interchangeably. In addition, as a result of the analysis of the first branches of mind maps, it was determined that unrelated concepts were more than related concepts. Very few of them have reached the fourth branch in the mind maps created by pre-service primary school teachers, and they had difficulty explaining the concept. In line with the results obtained from the research, the concepts related to geometric objects should be taught in the undergraduate education of pre-service primary school teachers to provide meaningful learning about geometric concepts in pre-service primary school teachers.

Reframing Architecture through Design

Reframing Architecture through Design

Distant Transfer Learning via Deep Random Walk

Transfer learning, which is to improve the learning performance in the target domain by leveraging useful knowledge from the source domain, often requires that those two domains are very close, which limits its application scope. Recently, distant transfer learning has been studied to transfer knowledge between two distant or even totally unrelated domains via unlabeled auxiliary domains that act as a bridge in the spirit of human transitive inference that two completely unrelated concepts can be connected through gradual knowledge transfer. In this paper, we study distant transfer learning by proposing a DeEp Random Walk basEd distaNt Transfer (DERWENT) method. Different from existing distant transfer learning models that implicitly identify the path of knowledge transfer between the source and target instances through auxiliary instances, the proposed DERWENT model can explicitly learn such paths via the deep random walk technique. Specifically, based on sequences identified by the random walk technique on a data graph where source and target data have no direct connection, the proposed DERWENT model enforces adjacent data points in a sequence to be similar, makes the ending data point be represented by other data points in the same sequence, and considers weighted classification losses of source data. Empirical studies on several benchmark datasets demonstrate that the proposed DERWENT algorithm yields the state-of-the-art performance.

Does the interleaving effect extend to unrelated concepts? Learners’ beliefs versus empirical evidence.

When learning new information, should students focus on studying 1 concept at a time or should they alternate studying between different concepts? Recent research shows that students should mix up or interleave the study of different concepts, particularly when the concepts are related or hard to discriminate (Carvalho & Goldstone, 2015). But students rarely study only 1 course, so how should the study of unrelated courses be sequenced? Should the study sessions be blocked by course to avoid unproductive juxtapositions or be interleaved across different courses because it inherently involves spaced practice, which is also effective for learning? In Experiments 1 and 2, we explored how students construct their study sessions by using hypothetical scenarios. Finally, in Experiment 3, we experimentally manipulated the study sequence of related concepts within 2 unrelated domains (i.e., physics and statistics). Given only 1 level to schedule (related modules or unrelated courses; Experiment 1), students chose to block related modules but to interleave unrelated topics—even though the literature suggests the related concepts are more likely to benefit from interleaving. Given 2 levels to schedule (concepts and domains; Experiment 2), students chose to interleave everything—even though empirical data from Experiment 3 suggests that the optimal schedule involves interleaving at either the concept or the domain level, but not both or neither. (PsycInfo Database Record (c) 2021 APA, all rights reserved)

Processes of knowledge recombination in two-person teams: resource pool and resource integration

ABSTRACT Knowledge recombination is a process through which distant fields of knowledge are brought together to solve complex problems and has important outcomes, such as scientific, technical, or social innovation. However, although recombination is both a cognitive and social process, there is little theoretical and empirical evidence on what happens between people while they are creating bridges between their different and complex fields of knowledge. In this study, we draw on problem-solving research and social cognition models to provide and test a model of recombination. We predict that (1) two-person teams map larger areas of the problem domain if they explore that domain using dissimilar problem models and (2) an implicit cognitive intervention can help team members integrate their diverse problem definitions. We tested these predictions in an experiment with N= 31 dyads. Our results show that dissimilar problem models lead to more comprehensive problem definitions which in turn increase solution creativity when members are primed to combine unrelated concepts. This work advances understanding of knowledge recombination processes and sets the stage for more comprehensive models.

Physico-theoretical basis of the mesoscopic approach to the study of soil and climatic regulations

Aim of the study. The aim of the work was to review critically the practice of applying system approach in soil research and identify existing problems; to consider the cognitive potential of micro- and macroscopic approaches in computational simulation of soil-bioclimatic regularities. Methodology. Mathematical simulation. Results of the study. A new mesoscopic approach to the study of the structure of soil-bioclimatic areas is proposed. It is based on two principles referred to as the principle of invariance and the principle of optimality. Application of these principles makes it possible to express the regularities in soil-climate relationship in the form of a single universal quantitative dependence. The study showed that a mathematical model built on the basis of these principles resulted in the emergence of new generalized concepts, logically combining the previously considered to be unrelated concepts of hydro- and thermal series introduced by V.R. Volobuev, the Vysotsky - Ivanov moisture coefficient and the radiation dryness index by M. Budyko. In addition, the simulation showed that the concepts elucidating the indicator of the radiation energy utilization by biogeocenosis were represented by the interrelated coefficients of the heat and precipitation utilization in soils. The coefficients were also shown to have specific values ​​for different soil-bioclimatic areas. On the basis of the new indicators, soils were grouped in such a way as to produce patterns essentially different in many details from the conventional grouping. Conclusions. The new concepts represent a unified integral system, and the approach as a whole can be considered as an alternative physico-theoretical way to describe natural laws and regularities by using extreme (variational) methodology.

Pre-service elementary teachers’ conceptual understanding of average speed: the systematicity and persistence of related and unrelated concepts

ABSTRACT Background Recent literature indicates that the trend towards investigating pre-service elementary teachers’ conceptual understanding of science concepts they are expected to teach and their command of that content-specific conceptual understanding is gaining momentum in science education. Purpose The purpose of this study was to investigate pre-service elementary teachers’ conceptual understanding of average speed. The research question that framed the study was ‘What are pre-service elementary teachers’ conceptual understanding of average speed?’ Design and Methods: Three perspectives, the scientifically accepted explanation of the concept of average speed the research on conceptual resources, and pedagogical content knowledge served as the conceptual framework. Written responses to questions that required pre-service teachers’ to define, identify associated concepts, and describe how they plan to teach and explain average speed served as data. The data were analysed using both content analysis and thematic analysis guided by constructs from the conceptual framework. Results Analysis revealed that pre-service elementary teachers held related science concepts, unrelated science concepts and other concepts within their conceptual understanding of average speed. This was despite the fact that they were able to provide accurate and/or inaccurate definitions of average speed. Conclusion Implications include the need for a developmental model to seek pre-service elementary teachers’ conceptual understanding of average speed from the standpoint of average speed as a complex property concept with its associated conceptual structures, and as a concept transformed for instruction. Additionally, there is a need to provide knowledge-based theory and practice to enable teachers to identify their own and their students’ conceptual understandings of average speed.

Managing operational risks through knowledge sharing infoodsupply chains

Despite the unprecedented growth in research on knowledge management and supply chain risk management, most prior studies discuss these two topics in isolation. Also, there is a scarcity of empirical research on both topics. By pulling together seemingly unrelated concepts of knowledge sharing and supply chain risk management, this study devises an integrated model investigating the extent to which operational risks affect supply chain performance and the moderating role of knowledge sharing. The dataset contains 225 responses collected from the firm managers of the Australian food supply chains (FSCs) and analyzed through structural equation modeling. The findings uncover that operational risks significantly undermine FSCs performance. However, knowledge sharing inversely moderates the adverse effect of operational risks, such that the higher the knowledge sharing, the lower the adverse performance effect of operational risks and vice versa. The findings enhance managerial discernment about the criticality of frequently occurring operational risks and the role of knowledge sharing in risk mitigation. The novelty of this study lies in the unified model that simultaneously delves into the performance effect of operational risks and moderating influence of knowledge sharing on risk‐performance nexus.

Adaptive security awareness training using linked open data datasets

Cybersecurity is no longer an issue discussed only between the professionals or technologists, but it is also closely related to ordinary people whose daily life is exposed to kinds of cyberattacks. And Womabat Security Technologies conducted a survey revealed that ransomware is an unknown concept to nearly two-thirds of employees. In practical, almost 95% of cybersecurity attacks are due to human error. At fact, expensive and sophisticated systems cannot work effectively without considering the human factor, while human factor is the major vulnerability in cybersecurity. Thus, it has great significance to give people cybersecurity awareness training. In this paper, we present a system, named ASURA, providing adaptive training aimed at improving cybersecurity awareness of people. Three issues can’t be neglected in adaptive cybersecurity awareness training, as follows. Firstly, we need to decide the proper training contents from the huge training materials. Secondly, the training contents should be timely updated, as cyber attacks constantly changing. At last, we should conduct training through effective and acceptable approach. We solved above three issues in this paper, and the innovative idea of this paper is constructing hierarchical concept map from the LOD database DBpedia. Then, we employ a series of processing on hierarchical concept map, including PageRank algorithm used to calculate the importance of each concept node, and filtering used to filtered out undefined and unrelated concepts. In particular, we get training contents from DBpedia dynamically and timely updated, so that training contents is keeping up to date. ASURA delivered training contents completely online, thus significant trimmed budget and allowed learners accessing training outside of a traditional classroom. Moreover, ASURA provide adaptive training targeted to individual learner, as it generate training contents based on the keyword from the learner.

The Interplay Between Language Form and Concept During Language Switching: A Behavioral Investigation.

Language switching involves multiple processing stages. Previous studies have not dissociated the cognitive process underlying language form switches and concept switches. Here, we examined the two factors using a novel language-switching paradigm. Chinese-English bilinguals named individually presented pictures in either Chinese or English according to a language cue. Pictures in two consecutive trials represented either identical, semantically related, or unrelated concepts. Results showed both language (form) switch costs and concept switch costs. The interaction between these two factors suggested that the effects were additive, with the longest naming response times observed when two pictures were semantically unrelated and involved a switch between languages. These findings suggest that the functional loci of the language control mechanism occur at multiple processing stages. Implications of the findings are discussed within current models of language processing in bilinguals.