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The conventional agricultural system heavily depends on chemicals and inorganic fertilizers, which cause environmental issues. Organic agriculture impacts 6 of the 17 Sustainable Developmental Goals (SDGs) of the United Nations. Strategies to develop organic agriculture have used SWOT and MCDM techniques for analysis. However, the examination of the influence of one strategy over the other strategies has yet to be investigated. This paper proposes a model that combines the existing SWOT analysis with neutrosophic cognitive maps (NCM) models to analyze interconnections among the various strategies obtained from SWOT. This research deploys the proposed SWOT–NCM model to analyze the case study of developing organic farming in Tamil Nadu, India. It offers insights into the strategy's influence over other strategies so that the best is given maximum importance while implementing organic farming. The framework captures the interconnections and ranks the strategies by order of influence, providing fresh insights by taking the farmers' perspective while working with the strategies from the SWOT analysis to model an NCM. A comparative analysis of this SWOT–NCM model with other MCDM models that use SWOT to analyze the agriculture problem, and a sensitivity analysis of the proposed model, is performed. According to our study, the best possible strategy to encourage organic farming is minimum support price (MSP) and centralized procurement. This proposed model can analyze other MCDM problems that use SWOT analysis. [ABSTRACT FROM AUTHOR]

Moving from a behavioral definition of intelligence, which describes it as the ability to adapt to the surrounding environment and deal effectively with new situations (Anastasi, 1986), this paper explains to what extent the performance obtained by ChatGPT in the linguistic domain can be considered as intelligent behavior and to what extent they cannot. It also explains in what sense the hypothesis of decoupling between cognitive and problem-solving abilities, proposed by Floridi (2017) and Floridi and Chiriatti (2020) should be interpreted. The problem of symbolic grounding (Harnad, 1990) is then addressed to show the problematic relationship between ChatGPT and the natural environment, and thus the impossibility for it to understand the symbols it manipulates. To explain the reasons why ChatGPT does not succeed in this task, an investigation is carried out and a possible solution to the problem in the artificial domain is proposed by making a comparison with the natural ability of living beings to ground their own meanings from some basic cognitive-sensory aspects, which, it is explained, are directly related to the emergence of self-awareness in humans. Thus, the question is raised whether a possible and concrete solution to the Symbol Grounding Problem would involve in the artificial domain the development of cognitive abilities fully comparable to those of humans. Finally, I explain the difficulties that would have to be overcome before such a level could be reached, since human cognitive capacities are intimately linked to intersubjectivity and intercorporeality. [ABSTRACT FROM AUTHOR]

Purpose: Virtual arthroscopic training has become increasingly popular. However, there is a lack of efficiency-based tracking of the trainee, which may be critical for determining the specifics of training programs and adapting them for the needs of each trainee. This study aims to evaluate and compare the measures obtained with a non-invasive neurophysiological method with The Diagnostic Arthroscopy Skill Score (DASS), a commonly used assessment tool for evaluating arthroscopic skills. Methods: The study collected simulator performance scores, consisting of "Triangulation Right Hand", "Triangulation Left Hand", "Catch the Stars" and "Three Rings" and DASS scores from 22 participants (11 novices, 11 experts). These scores were obtained while participants underwent a structured program of exercises for the fundamentals of arthroscopic surgery training (FAST) and knee module using a simulator-based arthroscopy device. During the evaluation, data on oxy-hemoglobin and deoxy-hemoglobin levels in the prefrontal cortex were collected using the Functional Near-Infrared Spectroscopy (fNIRS) imaging system. Performance scores, DASS scores, and fNIRS data were subsequently analyzed to determine any correlation between performance and cortex activity. Results: The simulator performance scores and the DASSPart2 scores were significantly higher in the expert group compared to the novice group (200.1 ± 28.5 vs 172.5 ± 48.9, p = 0.04 and 9.4 ± 5.6 vs. 5.4 ± 5.6 p = 0.02). In the expert group, fNIRS data showed a significantly lower prefrontal cortex activation during fundamental tasks in the FAST module, indicating significantly more efficient mental resource use. Conclusion: The analysis of cognitive workload changes during simulation-based arthroscopy training revealed a significant correlation between the trainees' DASS scores and fNIRS data. This correlation suggests the potential use of fNIRS data and DASS scores as additional metrics to create adaptive training protocols for each participant. By incorporating these metrics, the training process can be optimized, leading to more efficient arthroscopic training and better preparedness for clinical operations. Level of evidence: III. [ABSTRACT FROM AUTHOR]

Efficient bandwidth utilisation is significant in new communication systems where secondary users can be used besides primary users considering interference issues and idle state of primary users. Using secondary users as relays to transmit their own signals in addition to the primary signals can be applied for more reliability of the system where opportunistic relay selection can significantly enhance the performance of the system. The best-condition secondary user is selected as the optimum relay for retransmission of primary/secondary signal. Outage probability is analysed in this paper based on decode and forward technique in secondary users while the closed-form statement for outage probability is provided and verified by numerical evaluations. [ABSTRACT FROM AUTHOR]

Icebreakers are a critical shared resource between Finland and Sweden required to keep the Baltic Sea clear for differing waterborne activities throughout the winter season. The safety and efficiency (both ecological and in terms of time) of the winter transport system is highly dependent on the decision-making process followed by the icebreakers. The captains in charge of the icebreakers must decide the priority of assistance among all the merchant vessels that may be in need within a given time window. While captains successfully do this every year, with experience, this decision-making becomes second nature and a transparent picture of how the decisions are made is often missing. It is not always clear what salient features captains pay attention to, and how they use those features in their reasoning process to reach a decision during operations. This paper presents a pilot study that uses cognitive task analysis (CTA) to outline captains' decision-making process for ice breaker assistance allocation. In-depth interviews of three subject matter experts were conducted using a naturalistic icebreaker scenario. Results include identified critical decision points, identified, and prioritized salient features, and characterized icebreaker assistance strategies. [ABSTRACT FROM AUTHOR]

The aim of this article is to carry out a work of networking theories which combines two perspectives on the mathematical activity involved in a modelling process, in order to answer the following question: To what extent does the application of the onto-semiotic tools complement the analysis from a cognitive perspective of a mathematical modelling process? To this end, we considered two theoretical frameworks: on the one hand, the onto-semiotic approach, which provides tools for the analysis of any mathematical activity and which here we applied to the activity of modelling; on the other hand, the modelling cycle from a cognitive perspective, which is a reflection on the specific mathematical activity of modelling. Then, we took a modelling problem that we applied to prospective mathematics teachers (at undergraduate and postgraduate level), and we analysed it from the perspective of both frameworks, in order to identify concordances and complementarities between these two ways of analysing the mathematical activity involved in the modelling process. The main conclusion is that both frameworks complement each other for a more detailed analysis of the mathematical activity that underlies the modelling process. Specifically, the analysis with the tools provided by the onto-semiotic approach reveals the phases or transitions of the modelling cycle as a conglomerate of mathematical practices, processes, and the primary objects activated in these practices. [ABSTRACT FROM AUTHOR]

Agrarian growth is becoming increasingly important to many countries as the global demand for food rises, natural resources become scarcer, and environmental problems deepen. Herein, I propose a mechanism for designing agricultural growth management strategies that is based on fuzzy cognitive logic. The research presented is built on three main findings. First, it integrates established theories of economic growth, economic cyclicality, and sectoral market theories into a model of agricultural growth management. This enables the identification of main growth factors and the determination of the nature of their effects on agricultural dynamics. Second, I develop an algorithm for cognitive analysis of agricultural growth management and justify both this mathematical apparatus and the tools it uses. And third, I conduct a computational experiment that applies cognitive technologies to generate what I believe is the best agricultural economic growth strategy for Russia. [ABSTRACT FROM AUTHOR]

Tissue engineering is a relatively recent research area aimed at developing artificial tissues that can restore, maintain, or even improve the anatomical and/or functional integrity of injured tissues. Otolaryngology, as a leading surgical specialty in head and neck surgery, is a candidate for the use of these advanced therapies and medicinal products developed. Nevertheless, a knowledge-based analysis of both areas together is still needed. The dataset was retrieved from the Web of Science database from 1900 to 2020. SciMAT software was used to perform the science mapping analysis and the data for the biomedical translation identification was obtained from the iCite platform. Regarding the analysis of the cognitive structure, we find consolidated research lines, such as the generation of cartilage for use as a graft in reconstructive surgery, reconstruction of microtia, or the closure of perforations of the tympanic membrane. This last research area occupies the most relevant clinical translation with the rest of the areas presenting a lower translational level. In conclusion, Tissue engineering is still in an early translational stage in otolaryngology, otology being the field where most advances have been achieved. Therefore, although otolaryngologists should play an active role in translational research in tissue engineering, greater multidisciplinary efforts are required to promote and encourage the translation of potential clinical applications of tissue engineering for routine clinical use. [ABSTRACT FROM AUTHOR]

Introduction With the Army's emerging doctrine of prolonged field care, and with burns being a common injury among soldiers, non-expert providers must be trained to perform escharotomy when indicated. However, the existing physical simulators and training protocols are not sufficient for training non-experts for performing effective escharotomy. Hence, to provide guidance in developing realistic escharotomy simulators and effective training protocols suitable for prolonged field care, a cognitive task analysis (CTA) is needed. This work aims to obtain educative information from expert burn surgeons regarding escharotomy procedures via the CTA. Materials and methods The CTA was done by interviewing five subject matter experts with experience in performing escharotomy ranging from 20 to over 100 procedures and analyzing their responses. Interview questions were developed to obtain educative information from expert burn surgeons regarding the escharotomy procedure. A "gold standard protocol" was developed based on the CTA of each of the subject matter experts. Results The CTA helped identify general themes, including objectives, conditions that mandate escharotomy, signs of successful escharotomy, precautions, challenges, decisions, and performance standards, and specific learning goals such as the use of equipment, vital signs, performing the procedure, and preoperative and postoperative care. A unique aspect of this CTA is that it identifies the background information and preparations that could be useful to the practitioners at various levels of expertise. Conclusions The CTA enabled us to compile a "gold standard protocol" for escharotomy that may serve as a guide for practitioners at various levels of expertise. This information will provide a framework for escharotomy training systems and simulators. [ABSTRACT FROM AUTHOR]

In recent years, the importance of cognitive intervention promoting physical health and well-being among college students has gained significant attention. The cognitive dimension is pivotal in determining individuals' behaviors and decisions, especially in domains where personal choices significantly impact well-being. However, with increasing awareness concerning the advantages of exercise and healthy behaviors, many college students require assistance prioritizing their physical health because of various problems, including current academic schedules and the stress of postgraduate college admissions. To address these issues, this study presented data mining algorithms to assess the efficacy of cognitive treatments in improving college students' health and fitness through sports activity. It smoothly integrates sports education into a larger social development framework, emphasizing the vital significance of holistic well-being and the numerous benefits of rigorous fitness and physical training regimens. It analyzes the efficacy of college students' sports learning using data mining to clarify the Apriori and decision tree algorithms. It addresses students' sports perceptions, cognitive interventions for sports health and health standards in college physical education. This paper evaluates the intervention's success based on sports value cognition, sports need cognition and sports attitude recognition to improve student performance. The analysis of undergraduate students' post-intervention scores revealed a considerable rise in these areas, with the experimental group scoring 14.2 and the control group scoring 11.53. The specific scores for sports value cognition were 17.86 and 15.7, while those for sports attitudes and cognition were 11.28 and 9.56, respectively. The impact of the cognitive intervention is further analyzed concerning body shape and physical fitness. The results reveal that a higher proportion of students in the intervention group engaged in physical exercise than the control group, especially with more than three weekly exercise sessions. The intervention and control groups' participation rates were 20.2% and 6.75%, respectively. Notably, the intervention group demonstrated a higher proportion (5.78%) of students engaging in five or more physical exercises per week than the control group (1.95%). [ABSTRACT FROM AUTHOR]

• Cognitive defusion is an outcome, not a procedure or a process. • Cognitive defusion can be achieved through different behavioral processes. • Possible processes include selective attention and spatial distancing. • Other relevant processes involve relational coherence, reinforcement and extinction. Cognitive defusion is among the main components of Acceptance and Commitment Therapy (ACT), a contextual behavioral approach to psychotherapy. Defusion serves as a middle-level term, and, as such, may be useful for applying and disseminating behavior science, despite its lower precision. However, some authors argue that for middle-level terms in psychotherapy to be useful to clinicians, they need to be clearly linked to basic behavioral concepts, with higher precision; and that this is not currently the case with defusion. Our objective is to increase the pragmatic utility of the concept of "cognitive defusion" by providing a more nuanced, multifaceted and process-based definition of the term. In order to do this, we surveyed the ACT literature regarding defusion and critically examined it through the lens of conceptual analysis. This culminated in a revised and updated conceptualization of defusion in terms of its relationship to basic behavioral concepts, in which defusion is an outcome that may be achieved through different processes. [ABSTRACT FROM AUTHOR]

This paper studies overlay-based cognitive radio networks (ObCRNs) where transmission from a licensed transmitter (LT) to a licensed receiver (LR) is supported by an unlicensed transmitter (UT) who has its own communication to an unlicensed receiver (UR). To improve power efficiency of UT and diversity gain at UR and LR, UT operates in direct transmission (DT) or amplify-and-forward (AF) mode or decode-and-forward (DF) mode, and UR and LR combine signals with selection combining (SC) and maximum ratio combining (MRC) from LT and UT. Explicit outage probability expressions for ObCRNs with MRC/SC and DT/AF/DF are proposed to promptly rate its performance. Numerous results reveal the efficacy of the proposed solution and its flexibly-controlled performance. [ABSTRACT FROM AUTHOR]

According to the current challenges of spectrum scarcity, poor wireless communication quality, insufficient energy supply and physical layer security, this paper proposes a secure transmission scheme for multi-hop cognitive relay radio networks based on the underlay mode. When a passive eavesdropper E exists in the transmission environment, secondary source S needs to transmit secrecy information to the legitimate destination D. For the underlay spectrum sharing strategy, S and cognitive relays access the licensed spectrum concurrently with primary transmission by controlling the interference to the primary networks under the interference threshold. In order to achieve better communication between S and D, this paper adds some secondary relays to assist cognitive communication, and these secondary relays are equipped with energy harvesting (EH) devices that will collect energy from the surrounding radio frequency (RF) environment based on the time switching strategy. Then, this energy will supply consumption of decoding and forwarding (DF) the received signal. In the process of forwarding the signal through the secondary relays to D, artificial noise is added to the last relay so that D can successfully receive the message while preventing E from eavesdropping on the secret message. This paper analyzes the influence of target data rates, energy harvesting times, interference thresholds, and other factors on secrecy outage probability (SOP), secrecy capacity (SC), and energy efficiency (EE). [ABSTRACT FROM AUTHOR]

The present study investigated the impact of a defendant explicitly countering the claim of a jailhouse informant that the defendant confessed to a murder. Jury-eligible community members (N = 127) recruited from Amazon's Mechanical Turk read (via Qualtrics) a fictional trial summary in which a defendant was accused of murder. The trial was presented in one of four conditions: jailhouse informant only, defendant explicitly countered the jailhouse informant's testimony (said he did not talk to the jailhouse informant or they talked but not about the case), defendant testified but did not explicitly counter the jailhouse informant's testimony (simply said he was innocent), and no jailhouse informant testimony. As predicted, when the defendant explicitly countered the jailhouse informant's testimony the number of guilty verdicts was lower than that when the jailhouse informant only testified. In addition, there was significant mediation, such that explicitly countering the jailhouse informant led to lower jailhouse informant credibility and fewer guilty verdicts. Finally, cognitive network analyses showed that countering the jailhouse informant's testimony was critical to participants representing the jailhouse informant's testimony in a negative light. We discuss these results in terms of the importance of countering what is often unreliable jailhouse informant testimony. [ABSTRACT FROM AUTHOR]

Purpose: Upcycling is conceptualised as a digital historical research practice aimed at increasing the scientific value of historical data collections produced in print or in electronic form between the eighteenth and the late twentieth centuries. The concept of upcycling facilitates data rescue and reuse as well as the study of information creation processes deployed by previous generations of researchers. Design/methodology/approach: Based on a selection of two historical reference works and two legacy collections, an upcycling workflow consisting of three parts (input, processing and documentation and output) is developed. The workflow facilitates the study of historical information creation processes based on paradata analysis and targets the cognitive processes that precede and accompany the creation of historical data collections. Findings: The proposed upcycling workflow furthers the understanding of computational methods and their role in historical research. Through its focus on the information creation processes that precede and accompany historical research, the upcycling workflow contributes to historical data criticism and digital hermeneutics. Originality/value: Many historical data collections produced between the eighteenth and the late twentieth century do not comply with the principles of FAIR data. The paper argues that ignoring the work of previous generations of researchers is not an option, because it would make current research practices more vulnerable and would result in losing access to the experiences and knowledge accumulated by previous generations of scientists. The proposed upcycling workflow takes historical data collections seriously and makes them available for future generations of researchers. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) is a field of computer science that involves the development of programs designed to replicate human cognitive processes and the analysis of complex data. In dermatology, which is predominantly a visual‐based diagnostic field, AI has become increasingly important in improving professional processes, particularly in the diagnosis of psoriasis. In this review, we summarized current AI applications in psoriasis: (i) diagnosis, including identification, classification, lesion segmentation, lesion severity and area scoring; (ii) treatment, including prediction treatment efficiency and prediction candidate drugs; (iii) management, including e‐health and preventive medicine. Key challenges and future aspects of AI in psoriasis were also discussed, in hope of providing potential directions for future studies. [ABSTRACT FROM AUTHOR]

Understanding how mild cognitive impairment affects global neural networks may explain changes in brain electrophysiology. Using graph theory and the visual oddball paradigm, we evaluated the functional connectivity of neuronal networks in brain lobes. The study involved 30 participants: 14 with mild cognitive impairment (MCI) and 16 healthy control (HC) participants. We conducted an examination using the visual oddball paradigm, focusing on electroencephalography signals with targeted stimuli. Our analysis employed functional connectivity utilizing the change point detection method. Additionally, we implemented training for linear discriminant analysis, K-nearest neighbor, and decision tree techniques to classify brain activity, distinguishing between subjects with mild cognitive impairment and those in the healthy control group. Our results demonstrate the efficacy of combining functional connectivity measurements derived from electroencephalography with machine learning for cognitive impairment classification. This research opens avenues for further exploration, including the potential for real-time detection of cognitive decline in complex real-world scenarios. [ABSTRACT FROM AUTHOR]

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The work is devoted to the study of the linguo-cognitive analysis of the literary text in the aspect of linguistic means of expressing concepts and images. The relevance of this article is due to the growing attention to the analysis of the literary text using the methods and techniques of cognitive linguistics. The main aspects of cognitive linguistics, lingua-cognitive analysis, and text as an object of cognitive linguistics research are widely covered in the work. The main features of the literary text, its components, and lingua-cognitive analysis of linguistic means of expressing concepts and images are defined. The purpose of the research is to reveal the lingo-cognitive analysis of the literary text in the aspect of linguistic means of expressing concepts and images. The object of research is a literary text as material for lingua-cognitive research. Research methods. Such research methods such as description, analysis and synthesis, comparison, generalization, cognitive analysis, linguistic analysis, and modelling were used in the work. The article reveals the lingua-cognitive analysis of the literary text in terms of linguistic means of expressing concepts and images. The essence of the concept of "cognitive linguistics" and the main aspects of this phenomenon are characterized. The interpretation of the term "lingua-cognitive analysis" is defined. The essence of the "text" concept and the classification features of the text are described. The scientific work describes the features of the literary text. The components of the literary text influencing the lingua-cognitive analysis are characterized. Such elements of the literary text as image, concept, character, and evaluation are summarized. [ABSTRACT FROM AUTHOR]

Background: Recent advances in Computational Intelligence Tools and the escalating need for decision-making in the face of complex and uncertain phenomena like pandemics, climate change, and geopolitics necessitate understanding the interaction between these tools and human behavior. It is crucial to efficiently utilize the decision-makers cognitive resources in addressing specific problems. Methods: The main goal of this present protocol is to describe the effect that CITs (Computational Intelligence Tools) have on decisions made during complex and uncertain situations. It is an exploratory study with a mixed methodology. Solomon's group experiment design includes a narrative analysis of cognitive features such as integrative complexity (IC), cognitive flexibility (CF), and fluid intelligence (FI). Additionally, measures of neural activity (NA), physiological measures (PM), and eye-tracking data (ET) will be collected during the experimental session to examine the marginal impact of these processes on decision outcomes (DO) and their relation to CIT capabilities. To achieve this objective, 120 undergraduate and graduate students involved in decision-making will participate as subjects. The approximate duration of the study will be 2 years. Strict adherence to the relevant ethical considerations will be maintained during the performance of the experimental tasks. Discussion: The study will provide valuable information on CITs' effect on decision-making under complex and uncertain contexts. This will help to better understand the link between technology and human behavior, which has important implications. CIT designers can use future results and at the same time, it will be possible to understand cognitive, behavioral, physiological processes, and even the subjective assessment of individuals when they use technological tools to solve a problem. [ABSTRACT FROM AUTHOR]

Introduction: This article presents a systematic literature review that follows the PRISMA and PICOS guidelines to analyze current research trends on cognition, integrative complexity (IC) (a cognitive feature focusing on information processing in a person's response rather than its quantity or quality), and decisionmaking from the perspectives of activity theory and neuroscience. Methods: The study examines 31 papers published between 2012 and 2022 and 19 articles specifically related to neuroscience. We performed a content analysis using six categories within activity theory: subjects, objects, rules, community, division of labor, and outcomes. Results: The study investigates the relationship between decision-making outcomes and IC as a cognitive feature in various contexts. Additionally, content analysis on neuroscience and IC revealed significant research gaps, including understanding the nature of IC, challenges related to its measurement, and differentiation from other cognitive features. We also identify opportunities for investigating the brain's activity during decision-making in relation to IC. Discussion:We address the need for a more precise categorization of IC in studies of cognition, IC, and decision-making. We discuss the implications of our analysis for understanding the cognitive nature of IC and the potential of neuroscience methods for studying this attribute. [ABSTRACT FROM AUTHOR]

One's working memory process is a fundamental cognitive activity which often serves as an indicator of brain disease and cognitive impairment. In this research, the approach to evaluate working memory ability by means of electroencephalography (EEG) analysis was proposed. The result shows that the EEG signals of subjects share some characteristics when performing working memory tasks. Through correlation analysis, a working memory model describes the changes in EEG signals within alpha, beta and gamma waves, which shows an inverse tendency compared to Zen meditation. The working memory ability of subjects can be predicted using multi-linear support vector regression (SVR) with fuzzy C-mean (FCM) clustering and knowledge-based fuzzy support vector regression (FSVR), which reaches the mean square error of 0.6 in our collected data. The latter, designed based on the working memory model, achieves the best performance. The research provides the insight of the working memory process from the EEG aspect to become an example of cognitive function analysis and prediction. [ABSTRACT FROM AUTHOR]

[Objective] Stakeholders′ cognition on ecosystem services affects decision-making. Carrying out research and analysis on people′s cognition for ecosystem services in ecological conservation areas and its influencing factors among different stakeholders can lie the solid foundation for ecosystem management, the optimal supply of ecosystem services as well as comprehensive compensatory policy formulation for ecological protection in ecological conservation areas. [Methods] Types and spatial differences of ecosystem services cognition and influencing factors among managers and farmers in Beijing′s ecological conservation areas were analyzed by means of questionnaire survey. [Results]（1)Both managers and farmers believed that the regulating service was the main role of ecosystem. Their cognition levels on gas regulation, environmental purification and cultural services were low. They had significant differences in water conservation, biodiversity maintenance and cultural education. However, farmers only held a fairer perception on supply services than managers.（2)There were obvious cognition differences on the dominant services provided by different ecosystems. Managers held a fairer perception than farmers of water conservation, biodiversity maintenance and cultural education of different ecosystems. Farmers had higher cognition than managers concerning supply services of grassland and farmland, water and soil conservation of forest, gas regulation and leisure and entertainment of wetlands and farmland.（3)Stakeholders in different districts had different perspectives of gas regulation and cultural services in different regions. Managers′ knowledge in gas regulation was comparatively less in Miyun District, while farmers′ perceptions in biodiversity maintenance in Fangshan and Mentougou District were superficial to a certain extent.（4)Education level, intensity of ecological supervision and income level were the main factors affecting managers′ cognition. Two factors of education level and intensity of ecological supervision were in direct proportion to managers′ cognition. Educational level, intensity of ecological supervision and ecological environment training were the main factors affecting the cognition of farmers. Educational level and ecological environment training were the positive correlative factors for farmers. [Conclusion] There were obvious differences in the types and regions of different stakeholders′ cognition of ecosystem services. Education level, intensity of ecological supervision, income level and ecological environment training were the main influencing factors. Ecological environment training, exchange of experiences in different districts for managers, and publicity and education for farmers should be strengthened emphatically in the future. Enhancing the participation of different stakeholders will be conducive to formulating differentiated ecosystem management and service supply policies, and promoting the implementation of ecological protection policies. [ABSTRACT FROM AUTHOR]

On the basis of following the achievements of such sciences as cognitology, psycholinguistics, sociolinguistics aimed at studying human existence, the direction of gender linguistics has been developing at a special pace in Kazakh linguistics over the past 20 years. Gender factors in language served as the basis for determining the relationship between a person and linguistic existence using the methodology of these sciences. Including the study of the intellectual conceptual sphere of a person from the point of view of gender characteristics - will certainly contribute to the methodological sphere of Kazakh gender linguistics. The purpose of this study is to define the Turkic intellectual conceptosphere in terms of gender characteristics of men and women based on the concept of "mind". The article examines the gender features of the concept of "mind" in the Turkic languages on the basis of proverbs and phraseological units. Proverbs and phraseological units reflecting gender semantics are taken as the object of research, and their cognitive models of gender character are determined. In the course of the study, in addition to general scientific and theoretical methods (such as description, interpretation, systematization, comparison), special methods such as generalization and sorting of research materials, semantic classification and grouping, statistical analysis, component analysis of meaning, cognitive modeling, and the method of opposition were used. The studied concept of "mind" is undoubtedly an urgent problem, which is considered comprehensively from the point of view of cognitive analysis, intellectual conceptosphere, gender linguistics and Turkic linguistics. The characterization of the concept "mind", which is the nuclear part of the Turkic intellectual conceptosphere, from the point of view of gender factors emphasizes the relevance of the study. As a result of the study, it was found that the concept of "mind" as a semantic macropole distinguishes semantic cluster micro-supports in its composition and, as a linguocultural and cognitive category, in the process of including gender factors, turns out to be among the categories of gender linguistics. In the conclusion of the analysis, it is formulated that the identified cognitive models of the concept of "mind" determine the features of gender existence in the Turkic linguoculture of this concept. Such studies are important for the further study and development of the gender and intellectual conceptual sphere of the Turkic languages and are necessary for the scientific study of the conceptual sphere of the Turkic languages from the point of view of the national code, ethnic character, linguistic cognition of our cultural and social identity. [ABSTRACT FROM AUTHOR]

In compliance with the priorities determined by the Fourth Industrial Revolution, the present article attempts to address selected aspects that pertain to the role of young learners' cognitive abilities, which are brain-work related skills that individuals develop. This study is interdisciplinary in nature and is backed up by selected theoretical contributions that pertain to meaning construction in language use in intersection with the analysis of slight cognitive level impairment instances, which might result in learners' language perception and production difficulties, where slight cognitive impairment is understood not as illness but as a signal of speaking or comprehension problems, behavioural and mood changes, or memory and concentration fade. Several factors can cause manifestation of slight cognitive impairment in the processes of language perception and production. To investigate why several traits of this impairment type might develop in learners, the authors of this article have studied selected instances that refer to spoken language disorders in a sample group of young learners who were brought up in Latvian repatriate families and who repatriated to Latvia from western countries in the period between 2021 and 2022. As a result, the study has drawn its conclusion: within the framework of the tasks set by the Fourth Industrial Revolution, young learners' cognitive ability manifestation enhances their role in society and depends on: a) objective factors, for example, background knowledge of spoken language production principles, b) subjective factors, for example, language procession adequacy, which in certain groups of learners might be lowered due to some factors deriving from slight cognitive impairment. [ABSTRACT FROM AUTHOR]

Considering the importance of mathematics in modern society, it is crucial to understand the cognitive processes involved in the acquisition of complex mathematical competency. As a new generation of evaluation theory, cognitive diagnosis has its unique advantages in personalized evaluation. Based on the mathematical cognitive framework of Trends in International Mathematics and Science Study (TIMSS)‐2011 and the Chinese mathematics curriculum, this research has formed a mathematical competency model composed of seven cognitive attributes. Sixty‐seven released mathematical items for the fourth grade in TIMSS‐2011 were used as assessment tools in this study. The deterministic inputs, noisy, "and" gate model was selected as the cognitive diagnosis model in this research, and the parameters of the model were evaluated according to the response data, based on which the effectiveness of the assessment tool was further verified, forming the evaluation framework of students' mathematical competency. This framework was used to analyze the data of 573 students' mathematical competency from Shanghai, China, specifically from three aspects: attribute mastery probability, learning path, and knowledge structure. Results show that students' performance in mastering attributes of mathematical cognition is excellent on the whole; some students' learning paths are leapfrog; there are certain differences in students' knowledge structure despite that they have the same total score. This research is performed as a systematic case study of the evaluation of students' mathematical competency and also provides a new perspective in assessing other knowledge and skills. Practitioner points: Students' performance in mastering attributes of mathematical cognition is excellent on the whole.Some students' learning paths are leapfrog.There are certain differences in students' knowledge structure despite that they have the same total score. [ABSTRACT FROM AUTHOR]

Introduction: The proportion lack of physical activity (PA) among adolescents worldwide is increasing. Many studies have analyzed the behavioral determinants of PA among adolescents, but research that analyzes the relationship of all determinants in a conceptual framework is still limited. Social Cognitive Theory (SCT) is one of the concepts that is used as the basis for developing interventions to increase PA in the population. The purpose of this study was to examine the direct and indirect effect of SCT constructs on PA among adolescents in Depok City. Methods: A cross sectional study was conducted. A total of 351 high-school students (aged 14-19 years) completed the questionnaire. The PA level was measured using the Three-Day PA Recall (3DPAR) questionnaire and the data obtained were converted into METs using the Youth Compendium of Physical Activities. Structural Equation Modelling (SEM) was applied to analyze the relationship between SCT variables and PA in adolescents. Results: Self-efficacy had positive effects on outcome expectation (ρ=0.880, P-value 0.000), self-regulation (ρ= 0.243, P-value 0.000), social support (ρ=0.910, P-value 0.000) and PA (ρ=0.489, P-value 0.000). Self-efficacy had negative effect on perceived barriers (ρ=-0.919, P-value 0.000), Outcome expectation had positive effects on PA (ρ=0.919, P-value 0.000) and self-regulation (ρ=0.137, P-value 0.026). Self-regulation had positive effect on PA (ρ=0.188, P-value 0.004). Social support had positive effect on self-regulation (ρ=0.320, P-value 0.000). Perceived barriers had negative effect on self-regulation (ρ=-0.248, P value 0.003). Conclusion: Self-efficacy had the strongest effect on PA, but did not have indirect effect on PA through outcome expectations and self-regulation. [ABSTRACT FROM AUTHOR]

Objective. To analyze the cognitive profile of a clinical sample using the Mex-Cog cognitive battery and establish which cognitive measures and domains contribute most to group separation. Materials and methods. A group of 145 older adults previously diagnosed with dementia (n= 47), mild cognitive impairment MCI (n= 47), or as cognitively normal (n= 51) were assessed with the Mex-Cog cognitive battery. Six linear discriminant analyses (LDA) were estimated to compare dementia vs. cognitively normal, MCI vs. cognitively normal, and MCI vs. dementia, using ten individual measures and six cognitive domains. We used a leave-one-out cross-validation procedure to evaluate the predictive capacity of LDA models. Results. Discriminant functions using individual measures and domains distinguished correctly 100% of dementia and cognitively normal groups showing a memory and executive function profile. The predictive group membership for MCI versus cognitively normal varied between 82 and 85%, with a cognitive profile associated with attention-executive function followed by memory. Group separation between MCI and dementia was between 80 and 87%, characterized by orientation, memory, and visuospatial abilities. Conclusions. The Mex-Cog cognitive battery is useful for identifying cognitive impairment in older adults. [ABSTRACT FROM AUTHOR]

This article examines the relationship between cognitive processing and mastery. While scholars have called for the integration of sociological and cognitive analyses of mastery, sociological research has focused almost exclusively on mapping its social correlates. As a result, sociologists have relied on untested and underspecified assumptions about cognition to explain the efficacy of mastery. Taking an interdisciplinary approach integrating research on mastery, dual-process models of cognition, and intersectionality, we specify and test the hypothesis that deliberate thinking dispositions are associated with a greater sense of control over one's life chances and assess whether this relationship varies across different intersections of social positions. Regression results from survey data in a diverse student sample (N = 982) suggest a positive correlation between deliberate cognitive style and personal mastery. However, results from a quantitative intersectional analysis demonstrate that this relationship does not hold for East Asian women. [ABSTRACT FROM AUTHOR]

This study aims to present an innovative conceptual model of learning, teaching, and training that appears to be applicable to the field of hybrid warfare. It is based on integrating three critical elements such as reference curriculum, teaching methodology, and online support capabilities. By using qualitative research through correlating critical analysis of relevant sources, logical scheme, and cognitive task analysis, each descriptive element is analysed in order to provide an eloquent image of the proposed conceptual model. Also, to gain real feedback on the proposed model as well as on its constitutive elements, the quantitative research using statistical data grouping is performed. The analysis and interpretation of the collected data demonstrate not only a high interest in the designed conceptual model, but also a positive impact at the level of each descriptive element on the academic staff and students from the military and civilian university environment. [ABSTRACT FROM AUTHOR]

This paper designs and analyzes a novel single-channel cognitive radio retrial queueing network wherein a waiting line buffer is deployed for secondary users (SUs). A finite source system generates the primary users (PUs). Apart from these, PUs having preemptive priority over SUs, the effect of retrial/repeated attempts of PUs is taken into consideration. In such a system, the stability condition and the joint steady-state probability distribution of PUs and SUs are studied by using the matrix-analytic method. Several performance metrics of interest, such as blocking probability, throughput, mean waiting time, etc., have been determined. The first-passage time to reach a congestion level in the SUs waiting line buffer and its related characteristics are investigated by employing the first-step principle. In addition, correlation coefficients for various events of SUs and PUs during this period have been assessed. Finally, extensive numerical results are presented graphically for the system insights. [ABSTRACT FROM AUTHOR]

Cybersecurity planning supports the selection of and implementation of security controls in resource-constrained settings to manage risk. Doing so requires considering adaptive adversaries with different levels of strategic sophistication in modeling efforts to support risk management. However, most models in the literature only consider rational or nonstrategic adversaries. Therefore, we study how to inform defensive decision making to mitigate the risk from boundedly rational players, with a particular focus on making integrated, interdependent planning decisions. To achieve this goal, we introduce a modeling framework for selecting a portfolio of security mitigations that interdict adversarial attack plans that uses a structured approach for risk analysis. Our approach adapts adversarial risk analysis and cognitive hierarchy theory to consider a maximum-reliability path interdiction problem with a single defender and multiple attackers who have different goals and levels of strategic sophistication. Instead of enumerating all possible attacks and defenses, we introduce a solution technique based on integer programming and approximation algorithms to iteratively solve the defender's and attackers' problems. A case study illustrates the proposed models and provides insights into defensive planning. Funding: A. Peper and L. A. Albert were supported in part by the National Science Foundation [Grant 2000986]. [ABSTRACT FROM AUTHOR]

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Copyright of Mercados y Negocios is the property of Universidad de Guadalajara, Centro Universitario de Ciencias Economico Administrativas and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To investigate predictors of cognitive outcomes after radiotherapy for brain metastases in clinical trials that randomized patients between whole brain radiotherapy (WBRT) and stereotactic radiosurgery (SRS). The trials' cognitive assessments consisted of the three components of the Hopkins Verbal Learning Test – Revised, Trail-Making Tests A and B, and Controlled Oral Word Association Test administered at standardized times. The trial analyses assumed that missed cognitive assessments and declines of one standard deviation on a single test constituted cognitive events. We wished to investigate predictors of late cognitive decline after the subacute period of reversible encephalopathy. The N0574 trial enrolled 213 participants with up to three brain metastases and the N107C trial enrolled 194 participants with a surgical cavity and up to three brain metastases. Eligible patients for our analysis had a baseline and at least one follow-up cognitive assessment six months or more after radiotherapy. The cognitive endpoint was the difference in the mean Z-scores of all cognitive tests between the baseline and last cognitive assessments. The baseline variables were age, trial, number of brain metastases and SRS versus WBRT. In-brain recurrences before the last cognitive assessment were also included in the linear regression model. The percentage of participants with a baseline and at least one follow-up cognitive panel at 6 months or later was 16.0% (34/213) for N0574, 54.6% (106/194) for N107C, and 34.4% (140/407) for the combined cohort. In the combined cohort, the distribution of last cognitive panels was: 21.4%, 12.1%, 22.1%, 28.6% and 15.7% at 6, 9, 12, 15 and 18 months, respectively. In the model, receipt of WBRT (β = -0.25 [95% CI: -1.60, -0.59], p<0.001) was the only significant predictor of cognitive decline. Age (p = 0.06), trial (p = 0.07), number of brain metastases (p = 0.7), and in-brain recurrence (p = 0.2) did not predict late cognitive outcomes. When considering participants' last cognitive assessments, only receipt of WBRT predicted late cognitive decline in the N0574 and N107C clinical trials. [ABSTRACT FROM AUTHOR]

Radiation therapy is an effective treatment of primary brain tumors. post radiotherapy cognitive deterioration is a major concern. The hippocampus plays important roles in the consolidation of information from short-term memory to long-term memory, and spatial memory. Most of the focused is on the avoidance of radiation to the hippocampus grey matter. The primary purpose of this study is to shown that white matter tracts (memory fibers) of hippocampal function mapped by DTI can be delineate and incorporate into RT planning as an avoidance structure without compromising PTV coverage. In addition to the purpose of this study is to show that with that approach we can minimize damage to the brain thus preserving memory function and decrease cognitive decline secondary to brain radiotherapy. DTI Diffusion tensor imaging (DTI) is an MRI imaging method that allows for imaging of the random diffusion motion of water molecules inside brain's tissues. Integration of DTI into radiation treatment planning has been done in the past and was shown to be feasible and beneficial. This is a prospective trial of single cohort that been approved by the IRB. RT was delivered to a total dose of 54-60Gy in -27-30 fractions according to guidelines. During MRI simulation and before radiation therapy a diffuse sequence was performed. Two different radiation plans were performed by two different independent physicists. One with constrains on all memory fibers tract outside the PTV and one with only to the hippocampi as institution guidelines. In this trial we used the Montreal Cognitive Assessment for cognitive and memory evaluation. Recruitment was completed with 12 patients were analyzed for this analysis. The average age was 56 (42-71) with KPS>80. Dosimetrist analysis: The memory fibers and Hippocampi were successfully contoured in all 12 cases. Volumetric modulated arc therapy spared the memory avoidance structures; with the mean dose to the memory fibers structures was 15.2 Gy (range = 9.4-19.1 Gy) and a maximum dose (D0.03 cm3) range of 25.1-39.8 Gy. For the hippocampi Target coverage was achieved for all plans. For comparison a 2nd plan was created and analyzed with an independent physics without constrains to the Memory fibers. The mean dose was 18.4Gy (range = 18.1-26.9 Gy) and a maximum dose (D0.03 cm3) range of 43.4 Gy (40.1-55.6), P = 0.04 Cognitive analysis All 12 patients completed the MoCA test before the beginning of RT and 4 month after. The average score was 27.1 (23-30) and 26.4 (21-30) respectively, P -0.07. MRI planning using DTI to detect memory fibers and incorporate into RT planning using VMAT techniques allow for sparing of the hippocampi and the white fibers that connecting into and out to the hippocampus with plausibility for memory fibers avoidance without affecting PTV coverage. Phase 2 study will open soon with primary end point for cognitive preservation with new patient's cohort. [ABSTRACT FROM AUTHOR]

Online learning environments have become increasingly popular due to their flexibility and convenience, but they also present new challenges, such as maintaining student motivation and engagement. To address these challenges, it is crucial to understand and predict students’ learning behaviors. This study explores the recognition and management of students’ learning behaviors through cognitive status analysis. By conducting a thorough analysis of students’ cognitive status and applying advanced deep learning models and algorithms, this study demonstrates the effectiveness of recognizing and managing students’ learning behaviors. The proposed model combines convolutional neural networks and long short-term memory networks with attention mechanisms, which incorporate cognitive status evaluation features and use them as filters for text information. The model’s focus on text sentences with distinctive features in cognitive status evaluation leads to more effective recognition and management of students’ learning behaviors. Additionally, by integrating Most Informative Propositions and Semantic Propositional Value into the deep learning model, this study achieved excellent results in cognitive status evaluation recognition tasks. Further experiments show that by mixing different features and using advanced algorithms, the final model achieves high classification accuracy and F1 scores on multiple types of learning behaviors. Continuous assessment of students’ cognitive status and learning behaviors can lead to the development of effective learning strategies and intervention measures, which can enhance students’ mastery of knowledge and overall performance. [ABSTRACT FROM AUTHOR]

Background: Patients with stress-related mental disorders often report cognitive impairment, but studies investigating objective cognitive impairment in patients with stress-related disorders have produced inconsistent findings. Aim: The primary aim of this study was to investigate objective cognitive functioning in patients diagnosed with the stress-related disorders adjustment disorder or exhaustion disorder, compared to a healthy normative group. Secondary aims were to conduct subgroup analyses of cognitive functioning between the diagnostic groups and explore associations between self-reported symptoms and cognitive functioning. Methods: Cognitive test results on a digitally self-administered cognitive test battery from 266 patients (adjustment disorder, n = 131; exhaustion disorder, n = 135) were cross-sectionally compared with results from a healthy normative group (N = 184 to 692) using one-tailed t-tests. ANOVAs were conducted for subgroup analyses, and regression analyses for associations between self-reported symptoms and cognitive functioning. Effect sizes were calculated. Results: Patients performed significantly worse than the normative group on all measures with small to moderate effect sizes ranging from d = -.13 to -.57. Those diagnosed with exhaustion disorder performed worse than norms on more measures than did patients with adjustment disorder, but no significant differences between diagnostic groups were found on any measure. Self-reported memory impairment was weakly associated with one of two memory measures. No clear associations between self-reported burnout symptoms and objective cognitive functioning were found. Conclusions: This study adds to the literature indicative of small to moderate objective cognitive impairments in patients diagnosed with stress-related mental disorders. Further exploration into mechanisms of cognitive functioning in different populations is needed for development of theoretical models that may explain the weak correlation between self-reported symptoms and objective measures. Trial registration: ClinicalTrial.gov: NCT04797273. Trial registration date 15 March 2021. This study was also pre-registered on Open Science Framework (osf.io) with https://doi.org/10.17605/OSF.IO/TQXZV. [ABSTRACT FROM AUTHOR]

Summary: According to the hyperarousal model, insomnia is characterised by increased arousal in the cortical, cognitive, and physiological domains. However, the interaction between these arousal domains is poorly understood. The present observational case–control study aimed to investigate cortical arousal during the night, pre‐sleep cognitive arousal and the relationship between these two domains. A total of 109 patients with insomnia disorder (ID) and 109 age‐and gender matched healthy controls were investigated on two sleep laboratory nights. Electroencephalographic (EEG) spectral power during non‐rapid eye movement (NREM) and REM sleep was analysed as a measure of cortical arousal. In addition, patients completed the Pre‐Sleep Arousal Scale (PSAS), which consists of two subscales, one for cognitive arousal (PSAS‐CA) and one for self‐reported somatic arousal (PSAS‐SA). The relationship between the subscale scores and EEG spectral power was calculated by multi‐ and univariate analyses of variance. During NREM and REM sleep, patients with ID showed significantly increased spectral power in the EEG gamma band. In addition, patients with ID showed significantly increased scores on both subscales of the PSAS. The PSAS‐CA score was significantly associated with increased NREM and REM gamma power, whereas PSAS‐SA was associated with decreases in NREM and REM gamma power. Consistent with our hypothesis, patients with ID showed increased cortical and cognitive arousal. Moreover, there was an association between these two arousal domains, which may indicate that cortical arousal during the night is (at least in part) elicited by pre‐sleep worry and rumination. [ABSTRACT FROM AUTHOR]

Cognition is the practice of processing knowledge through mental processes. Understanding cognitive functions of the brain in young children helps in identifying neurodevelopmental disorders at early stages. Most studies used to diagnose neurodevelopmental disorders are based on behavioral scales. But most children with neurodevelopmental disorders are non-verbal. Thus, the goal of this research is to perform a task-based analysis of cognitive skills in children using electroencephalographic (EEG) signals. Spectral and fractal features of the EEG signals were acquired from pre-primary school children (N = 1 5) during arithmetic and path-finding cognitive tasks. The acquired signals were decomposed into various sub-bands. Investigations on the time-domain Higuchi Fractal Dimension (HFD) analysis and frequency domain Power Spectrum Analysis features demonstrated the dominance of the Theta band over the other subbands. The frontal electrode exhibited more workload in the arithmetic task, indicating the involvement of frontal regions and the temporal areas (T8) which were actively involved throughout the path-finding task, showing the activity related to spatial perception and navigation. Thus, the statistical information obtained from the spectral and fractal analyses seems to provide quantitative evidence of the variations in cognitive skills of young children thereby enhancing inferences about neurodevelopmental disorders. [ABSTRACT FROM AUTHOR]

Educational data mining based on student cognitive diagnosis analysis can provide an important decision basis for personalized learning tutoring of students, which has attracted extensive attention from scholars at home and abroad and has made a series of important research progress. To this end, we propose a noise-filtering enhanced deep cognitive diagnosis method to improve the fitting ability of traditional models and obtain students' skill mastery status by mining the interaction between students and problems nonlinearly through neural networks. First, modeling complex interactions between students and problems with multidimensional features based on cognitive processing theory can enhance the interpretability of the proposed model; second, the neural network is used to predict students' learning performance, diagnose students' skill mastery and provide immediate feedback; finally, by comparing the proposed model with several baseline models, extensive experimental results on real data sets demonstrate that the proposed Finally, by comparing the proposed model with several baseline models, the extensive experimental results on the actual data set demonstrate that the proposed model not only improves the accuracy of predicting students' learning performance but also enhances the interpretability of the neurocognitive diagnostic model. [ABSTRACT FROM AUTHOR]