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Cerebrovascular disease (CVD) and Alzheimer's disease (AD) often co-occur and may impact specific cognitive domains. This study's goal was to determine effects of CVD and AD burden on cross-sectional and longitudinal executive function (EF) and memory in older adults. Longitudinally followed participants from the National Alzheimer Coordinating Center database (n = 3342) were included. Cognitive outcomes were EF and memory composite scores. Baseline CVD presence was defined by moderate-to-severe white matter hyperintensities or lacunar infarct on MRI. Baseline AD pathology was defined by amyloid positivity via PET or CSF. Linear mixed models examined effects of CVD, AD, and time on cognitive outcomes, controlling for sex, education, baseline age, MoCA score, and total number of study visits. At baseline, CVD associated with lower EF (p < 0.001), while AD associated with lower EF and memory (ps < 0.001). Longitudinally only AD associated with faster declines in memory and EF (ps < 0.001). These results extend our understanding of CVD and AD pathology, highlighting that CVD does not necessarily indicate accelerated decline. • CVD and AD did not synergistically predict cognitive declines in specific domains. • CVD associated with lower baseline executive functioning, not longitudinal decline. • AD associated with lower executive function and memory at baseline and over time. • Findings extend our understanding of CVD and AD effects on cognitive decline. [ABSTRACT FROM AUTHOR]

Examining the relationship between the responses of a number of different cognitive trainings on cognitive functioning in middle-aged and elderly patients with mild cognitive impairment. Randomized controlled experimental studies published publicly from the time of inception to October 30, 2023 were searched through Web of Science, PubMed, Embase, and Cochrane library databases. Traditional and network meta-analyses were performed using Stata 17.0 software. Fifty papers on 4 types of cognitive training were included. Traditional meta-analysis showed that virtual reality training (SMD = 0.53, 95% CI : [0.36,0.70], P = 0.00), neuropsychological training (SMD = 0.44, 95% CI : [0.18,0.70], P = 0.00), cognitive strategy training (SMD = 0.26, 95% CI : [0.16,0.36], P = 0.00), and cognitive behavioral therapy (SMD = 0.25, 95% CI : [0.08,0.41], P = 0.00) all had significant improvement effects on the cognitive function of middle-aged and elderly patients with mild cognitive impairment. Network meta-analysis revealed neuropsychological training as the best cognitive training, and subgroup analysis of cognitive function subdimensions showed that neuropsychological training had the best effects on working memory, lobal cognitive function, memory, and cognitive flexibility improvement. Meanwhile, virtual reality training had the best effects on processing speed, verbal ability, overall executive function, spatial cognitive ability, and attention improvement. Cognitive training can significantly improve the cognitive function of middle-aged and elderly patients with mild cognitive impairment, and neuropsychological training is the best intervention, most effective in interventions lasting more than 8 weeks. [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]

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]

In this paper, we consider stability and latency analysis of a two-user cognitive radio network while considering Age of Information requirements imposed on the data transmissions of the users. We provide two different formulations. In the first formulation, our objective is to maximize the stable throughput of the secondary user subject to Age of Information constraints imposed on the data transmission of the users. While, in the second formulation, we introduce a multi-objective programming approach that investigates the trade-off between the secondary user stable throughput and its Age of Information. Our numerical results characterize the effect of imposing different Age of Information restrictions on the stable throughput region of the network; we show that the stability region, in certain cases, is reduced by only 11 % with strict Age of Information restrictions. Our results also investigate the trade-off between the secondary user throughput and the Age of information. Finally, our results show the potential accuracy of the algorithm adopted in this paper to solve the formulated non-linear optimization problems. [ABSTRACT FROM AUTHOR]

• Serum citrate concentrations in mild dementia could be associated with subsequent cognitive decline. • In mild dementia APOE- ε4 carriers, serum isocitrate concentrations could be associated with subsequent cognitive decline. • Downregulation of the first half of the TCA cycle with upregulation in the latter half, might be indirectly reflected in serum metabolites' networks. Abnormalities in the Tri-Carboxylic-Acid (TCA) cycle have been documented in dementia. Through network analysis, TCA cycle metabolites could indirectly reflect known dementia-related abnormalities in biochemical pathways, and key metabolites might be associated with prognosis. This study analyzed TCA cycle metabolites as predictors of cognitive decline in a mild dementia cohort and explored potential interactions with the diagnosis of Lewy Body Dementia (LBD) or Alzheimer's Disease (AD) and APOE-ε4 genotype. We included 145 mild dementia patients (LBD = 59; AD = 86). Serum TCA cycle metabolites were analyzed at baseline, and partial correlation networks were conducted. Cognitive performance was measured annually over 5-years with the Mini-mental State Examination. Longitudinal mixed-effects Tobit models evaluated each baseline metabolite as a predictor of 5-years cognitive decline. APOE-ε4 and diagnosis interactions were explored. Results showed comparable metabolite concentrations in LBD and AD. Multiple testing corrected networks showed larger coefficients for a negative correlation between pyruvate – succinate and positive correlations between fumarate – malate and citrate – Isocitrate in both LBD and AD. In the total sample, adjusted mixed models showed significant associations between baseline citrate concentration and longitudinal MMSE scores. In APOE-ε4 carriers, baseline isocitrate predicted MMSE scores. We conclude that, in mild dementia, serum citrate concentrations could be associated with subsequent cognitive decline, as well as isocitrate concentrations in APOE-ε4 carriers. Downregulation of enzymatic activity in the first half of the TCA cycle (decarboxylating dehydrogenases), with upregulation in the latter half (dehydrogenases only), might be indirectly reflected in serum TCA cycle metabolites' networks. [ABSTRACT FROM AUTHOR]

Global airport perception levels vary due to natural geographical factors and economic development disparities. Understanding these differences is crucial for assessing regional airport development and its correlation with geographical patterns. However, there are limited methods available to effectively comprehend these disparities. To address this issue, this paper proposes a Salience, Disturbance, and Geographic-knowledge (SDG) approach for the cognitive analysis of global large-scale airport perception differences. Salience is assessed using a two-class deep learning model to evaluate the prominence of known airports. Disturbance is evaluated using an object detection model to measure background interference in large-scale airport perception. Geographic-knowledge analysis considers the correlation between regional airports and their surrounding geographic environment. The results rank perception difficulties for 17 regions worldwide, with Tajikistan exhibiting the highest difficulty at 0.922, while the Jiangsu–Zhejiang–Shanghai region in China has the lowest at 0.102. We also performed correlation analyses to validate the effectiveness of our model. To our knowledge, this paper pioneers the cognitive analysis of target perception difficulty differences across multiple global regions. • A unified model assesses airport perceived difficulty globally. • Main factors affecting regional salience differences are identified. • Factors are quantified for various downstream target calculation frameworks. [ABSTRACT FROM AUTHOR]

• A novel EEG microstates analysis of driver cognitive load is proposed and found capable of distinguishing between different levels of load. • As cognitive load increases, drivers exhibit a simultaneous decreasing and increasing of two microstates. • EEG microstates measured before lead vehicle brake onset were predictive of safety outcomes in a rear-end collision scenario. Engaging in phone conversations or other cognitively challenging tasks while driving detrimentally impacts cognitive functions and has been associated with increased risk of accidents. Existing EEG methods have been shown to differentiate between load and no load, but not between different levels of cognitive load. Furthermore, it has not been investigated whether EEG measurements of load can be used to predict safety outcomes in critical events. EEG microstates analysis, categorizing EEG signals into a concise set of prototypical functional states, has been used in other task contexts with good results, but has not been applied in the driving context. Here, this gap is addressed by means of a driving simulation experiment. Three phone use conditions (no phone use, hands-free, and handheld), combined with two task difficulty levels (single- or double-digit addition and subtraction), were tested before and during a rear-end collision conflict. Both conventional EEG spectral power and EEG microstates were analyzed. The results showed that different levels of cognitive load influenced EEG microstates differently, while EEG spectral power remained unaffected. A distinct EEG pattern emerged when drivers engaged in phone tasks while driving, characterized by a simultaneous increase and decrease in two of the EEG microstates, suggesting a heightened focus on auditory information, potentially at a cost to attention reorientation ability. The increase and decrease in these two microstates follow a monotonic sequence from baseline to hands-free simple, hands-free complex, handheld simple, and finally handheld complex, showing sensitivity to task difficulty. This pattern was found both before and after the lead vehicle braked. Furthermore, EEG microstates prior to the lead vehicle braking improved predictions of safety outcomes in terms of minimum time headway after the lead vehicle braked, clearly suggesting that these microstates measure brain states which are indicative of impaired driving. Additionally, EEG microstates are more predictive of safety outcomes than task difficulty, highlighting individual differences in task effects. These findings enhance our understanding of the neural dynamics involved in distracted driving and can be used in methods for evaluating the cognitive load induced by in-vehicle systems. [ABSTRACT FROM AUTHOR]

Normal aging presents subtle cognitive changes that can be detected before meeting the criteria for Mild cognitive impairment (MCI). Older people with low cognitive reserve and who receive limited cognitive stimulation are at greater risk of deterioration. In this regard, cognitive stimulation (CS) has been identified as an intervention that reduces this risk, provided that its design takes into account the differences in the level of cognitive reserve (CR) acquired throughout life and the baseline level of cognitive functioning. The general objective of this study is to evaluate, through a randomized clinical trial, the effectiveness of a computerized cognitive stimulation program, designed and adapted from Occupational Therapy based on the level of cognitive reserve in older adults in Primary Care. 100 participants will be randomized in a stratified manner according to the level of cognitive reserve (low/moderate/high), assigning 50 participants to the control group and 50 participants to the intervention group. The intervention group will carry out a computerized cognitive stimulation intervention designed and adapted from occupational therapy according to the level of cognitive reserve, through the "stimulus" platform. The main result expected to be achieved is the improvement of higher brain functions. As secondary results, we expect that those cognitive aspects most vulnerable to aging will decrease more slowly (in areas such as memory, executive function, attention and processing speed), and that the cognitive reserve of the participants will increase, in addition to being able to balance gender differences in these aspects. We think that these results can have a positive impact on the creation of adapted, meaningful and stimulating CS programs in older adults to prevent MCI and experience healthier aging. • Rigorous randomized trial assesses program effectiveness. • Primary focus: improvement of higher brain functions • Secondary outcomes include slowing cognitive decline. • Findings inform tailored programs for healthy aging. [ABSTRACT FROM AUTHOR]

The application of the Electroencephalogram (EEG) technology shows promises in uncovering workers' cognitive processes affecting safety performance in construction. Despite the increasing interest in research, it is yet challenging to ensure coherence and mitigate biases when interpreting safety cognition from EEG data. This paper presents a comprehensive review of the applications of EEG in construction safety research, categorising the aims, methodologies, experiment design, data processing methods and evaluation approaches. Furthermore, the review identifies several critical avenues for future research, including deeper exploration of cognitive dynamics in safety-critical environments, technology integration for real-time monitoring, longitudinal analysis of cognitive safety factors, cultural and gender influences on safety practices, and addressing special psychological conditions. This paper emphasises the importance of considering ethical implications, user acceptability, and practical deployment challenges. Overall, the paper makes effort towards guiding effective EEG integration in construction safety research for safer practices. • A comprehensive review of literature applying EEG for construction safety research • A thorough analysis of the themes, methods and limitations of existing studies • Identification of knowledge gaps and future research directions • A decision framework to guide studies using EEG for construction safety research [ABSTRACT FROM AUTHOR]

Cognitive load theory suggests that overloading of working memory may negatively affect the performance of human in cognitively demanding tasks. Evaluation of cognitive load is a difficult task; it is often assessed through feedback and evaluation from experts. Cognitive load classification based on Functional Near-InfraRed Spectroscopy (fNIRS) is now one of the key research areas in recent years, due to its resistance of artefacts, cost-effectiveness, and portability. To make fNIRS more practical in various applications, it is necessary to develop robust algorithms that can automatically classify fNIRS signals and less reliant on trained signals. Many of the analytical tools used in cognitive sciences have used Deep Learning (DL) modalities to uncover relevant information for mental workload classification. This review investigates the research questions on the design and overall effectiveness of DL as well as its key characteristics. We have identified 45 studies published between 2011 and 2023, that specifically proposed Machine Learning (ML) models for classifying cognitive load using data obtained from fNIRS devices. Those studies were analyzed based on type of feature selection methods, input, and DL model architectures. Most of the existing cognitive load studies are based on ML algorithms, which follow signal filtration and hand-crafted features. It is observed that hybrid DL architectures that integrate convolution and LSTM operators performed significantly better in comparison with other models. However, DL models especially hybrid models have not been extensively investigated for the classification of cognitive load captured by fNIRS devices. The current trends and challenges are highlighted to provide directions for the development of DL models pertaining to fNIRS research. [ABSTRACT FROM AUTHOR]

Satisfying the quality of service (QoS) requirements of users in the form of channel availability and service retainability within the resource limited environment has been a major problem in cognitive radio networks. In this connection, several research studies have been carried out in the literature to improve the QoS of users by proposing dynamic channel reservation algorithms. However, the studies have a number of limitations in their conceptual and mathematical modeling of channel availability and service retainability, which render their performance evaluation unreliable. In this paper, we address these limitations for leading to more realistic, reliable, and practically valid modeling. For conceptual modeling, we use connection availability in place of channel availability, motivated by the fact that the latter does not necessarily lead to a successful establishment of connection and, thus, is not a suitable performance indicator. For instance, obtaining a channel for transmission is of no avail if the intended receiver is inaccessible. Similarly, we consider service retainability with accessibility/inaccessibility of the intended receiver incorporated. For mathematical modeling, we use CTMC and the resultant closed from expressions to include all the required states of channel availability yet unsuccessful connection establishment. Additionally, we derive closed form equations for channel availability and service retainability that are in exact conformance with the CTMC model. Results confirm that considering the impact of receiver's accessibility leads to performance difference for the channel availability and service retainability presented in the sate-of-the-art. [ABSTRACT FROM AUTHOR]

The difference of cognitive function between home-based elderly care and non-home-based elderly care is analyzed based on propensity score matching (PSM) method in this paper. Logistic regression is used to screen out the matching variables, and PSM is used to match the data. The balance test is also carried out. And independent t-test analysis is carried out on the data after matching processing to analyze the difference of cognitive function of the elderly under different elderly care models. The study result shows that there are significant differences in the cognitive function of the elderly residents under different elderly care models. The elderly residents who are in home-based elderly care have better cognitive function than those who are in other elderly care models. [ABSTRACT FROM AUTHOR]

The Dual Discrepancy/Consistency (DD/C) pattern of strengths and weaknesses (PSW) method is the most prominent "other alternative research-based procedure" used to identify a specific learning disability (SLD). The DD/C method is intended to be used with multiple data sources, but no research has examined identification decision making using the DD/C PSW analysis of cognitive and academic achievement test scores with other assessment data (e.g., pre-referral intervention data, parent/teacher reports, observations, evaluation of exclusionary factors). This study used an experimental vignette methodology to investigate school psychologists' (N = 343) identification decision making using the DD/C method with multiple data sources. Results showed that school psychologist participants made highly accurate (97.50%) identification decisions when both cognitive and achievement test score patterns and other assessment data were clearly indicative of SLD, but that overall identification accuracy was only 65.60%. Participants made less accurate identification decisions when examining test score data that did not meet DD/C PSW criteria for SLD than when examining test score data that did. Participants made less accurate decisions when other assessment data (interpreted in conjunction with test scores) did not meet DD/C PSW criteria for SLD or were ambiguous than when they did. In addition, male school psychologists were less likely to make accurate identification decisions than female school psychologists, and participants who were Nationally Certified School Psychologists were less likely to make accurate identification decisions than those who were not. Last, more experience with DD/C resulted in less accurate identification decisions, and participants who made accurate decisions reported higher levels of confidence, although the effect size was negligible. Implications for research and practice are discussed. [ABSTRACT FROM AUTHOR]

This article presents a comprehensive analysis of the different tests proposed in the recent ChildCI framework, 1 1 https://github.com/BiDAlab/ChildCIdb%5fv1. proving its potential for generating a better understanding of children's neuromotor and cognitive development along time, as well as their possible application in other research areas such as e-Health and e-Learning. In particular, we propose a set of over 100 global features related to motor and cognitive aspects of the children interaction with mobile devices, some of them collected and adapted from the literature. Furthermore, we analyse the robustness and discriminative power of the proposed feature set including experimental results for the task of children age group detection based on their motor and cognitive behaviours. Two different scenarios are considered in this study: (i) single-test scenario, and (ii) multiple-test scenario. Results over 93% accuracy are achieved using the publicly available ChildCIdb_v1 database (over 400 children from 18 months to 8 years old), proving the high correlation of children's age with the way they interact with mobile devices. • Proposal of over 100 global features related to motor and cognitive aspects. • Usage of the largest and most diverse public dataset on the topic (ChildCIdb_v1). • Results of over 93% accuracy for the children age group detection task. • It seems to be a relationship between children's age and mobile device interaction. [ABSTRACT FROM AUTHOR]

This article has been retracted: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/locate/withdrawalpolicy). This article has been retracted at the request of the Editor-in-Chief. The article has been submitted without the knowledge of the three co-authors whose emails were invented and those three co-authors were not involved in this submission. As such this article represents a severe abuse of the scientific publishing system. The scientific community takes a very strong view on this matter and apologies are offered to readers of the journal that this was not detected during the submission process. [ABSTRACT FROM AUTHOR]

Agrochemicals play a vital role in protecting crops and enhancing agricultural production by reducing threats from pests, pathogens and weeds. The toxicological status of honey bees can be influenced by a number of factors, including pesticides. While extensive research has focused on the lethal and sublethal effects of insecticides on individual bees and colonies, it is important to recognise that fungicides and herbicides can also affect bees' health. Unfortunately, in the field, honey bees are exposed to mixtures of compounds rather than single substances. This study aimed to evaluate the effects of a commercial fungicide and a commercial herbicide, both individually and in combination, on honey bees. Mortality assays, biomarkers and learning and memory tests were performed, and the results were integrated to assess the toxicological status of honey bees. Neurotoxicity (acetylcholinesterase and carboxylesterase activities), detoxification and metabolic processes (glutathione S-transferase and alkaline phosphatase activities), immune system function (lysozyme activity and haemocytes count) and genotoxicity biomarkers (Nuclear Abnormalities assay) were assessed. The fungicide Sakura® was found to activate detoxification enzymes and affect alkaline phosphatase activity. The herbicide Elegant 2FD and the combination of both pesticides showed neurotoxic effects and induced detoxification processes. Exposure to the herbicide/fungicide mixture impaired learning and memory in honey bees. This study represents a significant advance in understanding the toxicological effects of commonly used commercial pesticides in agriculture and contributes to the development of effective strategies to mitigate their adverse effects on non-target insects. [Display omitted] • Effects of commercial fungicide and herbicide, single and in combination, were evaluated. • Mortality assay, biomarkers and learning and memory tests were performed on honey bees. • Neurotoxic effects after both mixture treatments could be attributed to the herbicide. • Herbicide and pesticide mixtures compromise honey bees' behaviour. [ABSTRACT FROM AUTHOR]

The identification of the risk factors of alcohol consumption in youths is crucial for early interventions focused on reducing harmful alcohol use. In our study, 82 college students (40 healthy control (CO group) and 42 with risky alcohol use (RAU group) determined by AUDIT questionnaire) between the ages of 18 and 25 years underwent a comprehensive neuropsychological assessment covering emotional and cognitive functioning. Their resting-state activity was also recorded with an EEG for 10 min with their eyes open (EO) and 10 min with their eyes closed (EC) and analyzed using the Fitting Oscillations & One-Over-F (FOOOF) paradigm. After adjusting for sex, those in the RAU group had higher emotional dysregulation and impulsivity traits. The RAU girls presented more emotional regulation problems, such as dysregulation and negative urgency compared with the RAU boys. The RAU youths had significantly worse functioning in several cognitive domains, such as sustained attention, verbal memory, and executive functions. Cognitive network analysis revealed a different pattern of connections in each group showing that in the RAU group, the verbal memory domain had the highest connection with other cognitive functions. The EEG analyses did not reveal any significant differences between the CO and the RAU groups. However, we observed only in the EO condition that boys the from the RAU group displayed a higher theta/beta ratio than the RAU girls, whereas these differences were not observed within the CO group. Our findings highlight the need to explore more deeply the emotional, cognitive and brain changes underlying the RAU in young people. • The RAU group showed difficulties in emotional regulation and impulsivity. • The RA users showed several cognitive deficits. • The Cognitive network analysis revealed a different pattern of connections between groups. • The Boys from the RAU group displayed a higher TBR than the RAU girls. • Psychological vulnerability markers would enable us to detect young people at risk. [ABSTRACT FROM AUTHOR]

This study aims to explore an effective method to evaluate spatial cognitive ability, which can effectively extract and classify the feature of EEG signals collected from subjects participating in the virtual reality (VR) environment; and evaluate the training effect objectively and quantitatively to ensure the objectivity and accuracy of spatial cognition evaluation, according to the classification results. Therefore, a multi-dimensional conditional mutual information (MCMI) method is proposed, which could calculate the coupling strength of two channels considering the influence of other channels. The coupled characteristics of the multi-frequency combination were transformed into multi-spectral images, and the image data were classified employing the convolutional neural networks (CNN) model. The experimental results showed that the multi-spectral image transform features based on MCMI are better in classification than other methods, and among the classification results of six band combinations, the best classification accuracy of Beta1–Beta2–Gamma combination is 98.3%. The MCMI characteristics on the Beta1–Beta2–Gamma band combination can be a biological marker for the evaluation of spatial cognition. The proposed feature extraction method based on MCMI provides a new perspective for spatial cognitive ability assessment and analysis. • MCMI describes coupling feature of EEG signals for spatial cognitive evaluation well. • The classification performance is best under multiple combination frequency bands. • MCMI is a valid valuable biomarker for spatial cognitive ability evaluation. [ABSTRACT FROM AUTHOR]

Background: In task-oriented studies showed that the chronic pain is effective on dual tasks. Chronic pain is the main health problem that prevents mobility restriction and participation in most rheumatic diseases.Research Question: Do rheumatic diseases have an effect on dual task gait performance?Methods: This comparative-descriptive study included 75 individuals who aged 18-65 years and divided in two groups as Rheumatic Disease Group (RG; 23 women, 14 men) and Control Group (CG; 20 women, 18 men). The individuals have a chronic pain (> 3.4 cm according to Visual Analogue Scale, VAS) and Standardized Mini Mental State Examination score above 24 were included in this study as the RG. The individuals who were did not have any known disease were included in the CG. The health status of RG was evaluated with the Arthritis Impact Measurement Scale 2 (AIMS-2). The 10-meter Walk Test was applied under single and dual task conditions (dual task cognitive, DTcognitive; dual task motor, DTmotor) for assessing gait performance.Results and Significance: The mean age of the individuals in the study was 40.6 ± 11.34 years (RG=43.08 ± 11.30; CG=38.18 ± 11.00). There was a significant difference in favor of CG between the groups both in terms of gait speed in DTcognitive and its cost (p < 0.05). VAS scores correlate with single and DTcognitive and DTmotor gait parameters (p < 0.05). Many subdivisions of AIMS-2 were associated with single, DTcognitive and DTmotor gait parameters (p < 0.05). This study concluded that rheumatic diseases may reduce gait performance in concurrent motor-cognitive dual task conditions due to chronic pain. Single and dual task gait parameters may be related with psychosocial factors. Therefore, applications including pain control and biopsychosocial approach may be beneficial in the management gait disturbances and falls due to a rheumatic disease. [ABSTRACT FROM AUTHOR]

• We analyzed some factors affecting performance reliability of the human behavior in green architecture construction engineering. • We looked the humans and their environment as a whole system to establish the individual performance reliability model. • A novel method for factor validity and reliability performance analysis of the human behavior in green architecture construction engineering is presented. • The presented detailed method and steps can help us to know the influence of green architecture construction management and the environment. • The key factors to improve the reliability of the whole system can be found by the presented method. The factor validity and reliability performance analysis of the human cognitive behavior in green sustainable construction system has a great significant in safeguarding the quality and safety. At first, this paper analyzes factors affecting performance reliability of the human cognitive behavior in green sustainable construction system, and looks the humans and their environment as a whole system to establish the individual performance reliability model based on the Markov chain analysis method. Then, a novel hybrid computational intelligence method for factor validity and reliability performance analysis of the human cognitive behavior in green sustainable construction system is presented. The presented detailed method and steps can help us to know the influence of green construction management and the environment and find the key factors to improve the reliability of the whole system. [ABSTRACT FROM AUTHOR]

Research problem Instructional screencasts are increasingly part of the online tutorial mix offered by academic libraries. However, what makes for effective screencast design? This research provides a snapshot of screencast design in Australian and New Zealand academic libraries and appraises it through the lens of multimedia learning theory. Methodology Evidence-based design principles that promote effective learning for multimedia were identified from the research literature. A cognitive psychological approach was taken, drawing principally from Mayer's cognitive theory of multimedia learning. The principles outlined in Mayer's theory were translated into guidelines applicable to screencast tutorial production. These guidelines formed the basis for an assessment rubric which was applied to screencasts produced by New Zealand and Australian Universities. Content analysis was then applied to determine to what extent screencast tutorials in the sample reflected the principles outlined in Mayer's theory. Results On average, screencasts from the institutions surveyed integrated 7.6 of 9 effective multimedia principles. The low variance across the sample suggests this high standard was approximated or exceeded by most tutorials. Australian and New Zealand libraries were of a comparable standard overall with similar areas of strength and weakness. Implications Mayer's principles provide a useful foundation for designing effective multimedia instruction. The translation of these principles into screencast design guidelines will hopefully serve as useful considerations. Commonly neglected principles (coherence, signalling and segmenting) present areas for design improvement but also opportunities for further research in an academic library context. [ABSTRACT FROM AUTHOR]

Introduction: Working time regulations, senior led service delivery and increasing complexity of surgical technology has led to significant strains in surgical training. Additionally, the current COVID-19 pandemic has placed substantial limitations on surgical training worldwide. Contact free, remote, web-based, validated learning tools which are easily accessible and allows repeated, sustained practice are the need of the hour. Cognitive Task Analysis (CTA) have been used extensively to train pilots and military personnel and has shown excellent early results within orthopaedic training. We designed a femoral nailing CTA tool which showed objective benefits in the enhancement of cognitive knowledge in medical students. The aim of this study was to evaluate the effectiveness of this CTA tool to enhance practical skills in orthopaedic trainees in a real time interactive simulation setting (Distributed Interactive Simulation (DIS)).Methods: This was a double blinded, randomized controlled trial. 14 junior orthopaedic residents who met the inclusion criteria were recruited in the study. They were randomized into two equal groups. The intervention group were given the CTA learning tool, the control group were given a standard operative technique manual used for antegrade femoral intramedullary nailing. The participants were assessed on a high-fidelity phantom femur model with actual femoral nailing instruments in a simulation mobile operating theatre where the candidate had a simulation patient, an acting anesthetist and a scrub nurse (DIS). They were assessed using the modified Objective Structured Assessment of Technical Skills (OSATS) rating scale which has been validated for orthopaedic trauma.Results: The median OSATS score in the intervention group was 49 (±4.93, range 39-55) compared to 17 in the control group (±14.98, range 12-51). The median improvement was by 32 points (p = 0.02). The ICC between the two raters was 0.977.Conclusions: This study has demonstrated objective benefits of a novel femoral nailing CTA tool in the enhancement of practical skills for junior trainees in the DIS setting. This adds to the growing evidence supporting the use of CTA in orthopaedic training. This tool can be accessed remotely, is contact free and allows repeated sustained practice which is key in simulation training. [ABSTRACT FROM AUTHOR]

In this article we review Per Linell's work within the last five decades that led to his dialogism framework, which he defines as a general epistemology of language, cognition and communication. We critically discuss how his contribution on the one hand, altered and qualified existent models within language, communication and cognitive science, because dialogism removed language and cognition from their abstract and mental seat in the brain, and embedded them instead in situational contexts and embodied interaction. In that sense, his dialogism successfully replaced monological assumptions about the mind, action and thinking with more contextual and temporally distributed ones. On the other hand, we also question why Linell has not pursued a more rigorous empirical program for studying human cognition, when he did establish a theoretical apparatus for approaching cognition from a dialogical starting point. In going through Linell's arguments over the past five decades we suggest that this absence of an empirical program is due to his humanistic roots which both have sensitised him to appreciating the contingencies and dynamics of human sense making and cognition, and have impeded him from buying into a necessary condition for pursuing a cognitive analysis, even if he conceptually and methodologically accepts a distributed view on cognition. The outcome of this discussion leads to an empirical-based cognitive analysis of a medical interaction. Altogether, the purpose of this article is to show how Linell's conceptual framework can be put to use in ways that make a dialogical cognitive science achievable. • Provides a critical review of Per Linell's dialogism framework. • Indicates a shift in language and cognition from abstract mental realms to situated contexts and embodied interactions. • Questions why Linell has not pursued a rigorous empirical program for studying human cognition. • Discusses and demonstrates the application of Linell's framework in an empirical-based cognitive analysis. • Showcases the potential for a true dialogical cognitive science. [ABSTRACT FROM AUTHOR]

The proliferation of conspiracy theories has coincided with advancement in communication technologies. Research has consistently identified the social determinants of conspiracy beliefs, such as social media exposure and peer influence, the impact of cognitive abilities, especially executive function (EF), remains unexplored. This study aimed to explore whether conspiracy beliefs varied with different EF profiles. A sample of 194 participants (M = 35.56; SD = 10.01) completed a questionnaire covering beliefs in six common conspiracy theories and tasks assessing working memory (N-Back), cognitive flexibility (Modified Card Sorting Task), and affective decision-making (Iowa Gambling Task). Latent profile analysis on the cognitive tests identified three distinct EF profiles: Low Cool EF, Moderate Cool EF, and High EF. Notably, the Low Cool EF cohort displayed significantly stronger beliefs in five of the six conspiracy theories than the High EF profile. The Moderate Cool EF profile also showed significantly stronger beliefs in conspiracies relating to personal wellbeing, and Covid-19 compared to the High EF profile. Executive functioning plays a pivotal role in shaping an individual's inclination towards or resistance against conspiracy beliefs. Enhanced cognitive flexibility and working memory enables individuals to critically assess information rather than rigidly subscribing to a singular viewpoint, likely fostering resistance to conspiratorial thinking. [ABSTRACT FROM AUTHOR]

Resilient regional development can be favoured employing suitable decision-aiding techniques. Multicriteria Sorting Analysis tools are increasingly being used to deal with complex issues. The Group Analytic Network Process Sorting II method (GANPSort II), which builds on the previous ANPSort II and I, is here developed for the territorial resilience assessment of the Champagne-Ardenne in France, a broad-level Socio-Ecological System. This method can sort a large number of alternatives from the most to the least resilient by reducing the number of pairwise comparisons. In this way, an adaptive response can be provided to system perturbations. The evaluation is supported by cognitive and spatial analyses and allowed the definition of a set of resilience indicators as components of the evaluation model. A pool of multidisciplinary experts joined the evaluation to sort the alternatives into specific resilience classes. GIS completion facilitates the outcomes visualization of both solo and grouped expert sorting. The results demonstrate that the GANPSort II enriches the existing sorting methods scenario in handling planning problems, such as territorial resilience assessment in the regional planning of broad systems, proving its decision-making utility for spatial planners and public bodies engaged in the co-design of resilient strategies. • A decision-aiding model is developed for territorial resilience assessment of SESs. • GANP Sort II can solve problems with interdependencies and numerous alternatives. • The application sorts the territorial resilience of the Champagne-Ardenne, France. • The results support both public bodies and urban planners to design strategies. [ABSTRACT FROM AUTHOR]

Perimenopause is a critical period, with severe cycle irregularity and lower estrogen secretion altering redox state biomarkers, leading to behavioral changes. The estrogen hormonal therapy (EHT) being commonly used to alleviate climacteric effects. Therefore, the aim of this study was to analyze anxiolytic profile, recognition memory (short and long term), ambulation, redox status, cell synaptic activity in locus coeruleus and hippocampus of Wistar rats in the periestropause after EHT. Forty rats participated in the study; 20 were treated with corn oil (group 21Mo/Veh; corn oil/0.2 mL/sc; 2x/week) and 20 were submitted to EHT (group 21Mo/E2; 17β-estradiol/15 μg/Kg/sc; 2x/week) for 120 days. Open field, elevated plus maze, object recognition (RO), and footprint tests were performed immediately before and at the end of the treatment period. From the decapitated brains, isolated hippocampus were destined for biochemical analysis, in turn, perfused brains were destined for histological analysis. The 21Mo/E2 group had a significantly greater total time in the central region and a significantly greater number of entries into the open arms compared to the 21Mo/Veh group, as in crossing, rearing and grooming behaviors, evidencing an anxiolytic profile. In the RO test, the 21Mo/Veh group decreased long-term memory, and the 21Mo/E2 group maintained the same index as at 17 months of age, in addition to a better balance of the hippocampal redox state, prevention of neuronal cell loss and better gait. Based on the results, it appears that exogenous E2 supplementation during periestropause may help preserve neurological functions and potentially prevent neuropsychological and neurodegenerative disorders. • EHT acted by reducing the anxiogenic profile to anxiolytic. • EHT was able to conserve mnemonic processes. • EHT triggered improvements in the ethology, biomechanics and brain biochemistry of aging female. • Exogenous administration of E2 provided benefits in the periestropause period. • Alert for therapy as a preventive resource for neuropsychological and neurodegenerative diseases. [ABSTRACT FROM AUTHOR]

Background: Globally, postural stability and cognitive performance are intimately linked in Parkinson's disease (PD). However, a fundamental gap exists in understanding the precise relationship between a disruption in executive function and its impact on postural stability.Objective: This project aimed to determine the precise effects of cognitive errors on postural stability under dual-task conditions in participants with PD and controls.Methods: Twenty-eight individuals with PD and 27 healthy controls completed a series of postural stability tests under single- and dual-tasks. The dual-task required maintenance of balance while performing an audio number discrimination task.Results: In general, postural stability in PD and control subjects was similar across single-task conditions. In controls, an error in the cognitive task during dual-task conditions did not impact measures of postural sway. In contrast, in PD, postural sway increased in epochs surrounding cognitive errors relative to epochs without errors.Conclusions: Postural task selection plays a critical role when testing for balance deficits in PD compared to healthy controls. Furthermore, time synchronized analysis of cognitive and balance data revealed the greatest episodes of postural instabilities occurred around cognitive errors. The measurement and evaluation of cognitive-motor linkages, relative to postural stability, could provide a patient-specific fingerprint of balance function and provide more sensitive measures for fall risk in PD. [ABSTRACT FROM AUTHOR]

New approach to investigate the two-dimensional regular packing of arbitrary geometric objects (GOs) using cognitive visualization is presented. GO correspond to congruent non-convex polygons with their associated coordinate system. The origins of these coordinate systems are accepted by object poles. The approach considered is based on cognitive processes that are forms of heuristic judgments. According to the first heuristic judgment, regular packing of congruent GOs on the plane have a honeycomb structure, that is, each GO contacts six neighboring GO, the poles of which are vertices of the pole hexagon in honeycomb construction of packing. Based on the visualization of the honeycomb constructions a second heuristic judgment is obtained, according to which inside the hexagon of poles there are fragments of three GOs. The consequence is a third heuristic judgment on the plane covering density with regular packings of congruent GOs. With the help of cognitive visualization it is established that inside the hexagon of poles there are fragments of exactly three objects. The fourth heuristic judgment is related to the proposal of a triple lattice packing for regular packing of congruent GOs. [ABSTRACT FROM AUTHOR]

Cognitive ability plays an important role in mental and physical well-beings in the increasingly ageing populations. Here, based on a sample of 30 cognitive function-discordant monozygotic twin pairs, we aimed to detect specific epigenetic variants potentially related to cognitive function by conducting an epigenome-wide association study (EWAS). Association between methylation level of single CpG site with cognitive function score was tested by linear mixed effect model. Functions of cis-regulatory regions and ontology enrichments were predicted by Genomic Regions Enrichment of Annotations Tool (GREAT). Differentially methylated regions (DMRs) were detected by comb-p python library. A list of 28 CpG sites were identified to reach the level of P < 1 × 10−4, and the strongest association (cor = 0.138, P = 2.549 × 10−6) was detected for DNA CpG site (Chr17: 40,700,490 bp) located at HSD17B1P1. The identified 14,065 genomic CpG sites (P < 0.05) were mapped to 2646 genes, especially HSD17B1P1 , CUL4A , INTS8 , GFI1B , ZNF467 , CDH15 , and PSMA1. GREAT ontology enrichments mainly highlighted nicotine pharmacodynamics pathway, GABA-B receptor II/nicotinic acetylcholine receptor/hedgehog/endothelin/Wnt signaling pathways, Parkinson disease, Huntington disease, glycolysis, neuronal system, and toll-like receptor binding. We detected 15 DMRs located at/near 16 genes, especially LINC01551 , LINC02282 , and FAM32A. And 32 cognitive function-associated differentially methylated genes could be replicated, such as SHANK2 , ABCA2 , PRDM16 , NCOR2 , and INPP5A. Our EWAS in monozygotic twins identify specific epigenetic variations which are significantly involved in functional genes, biological function and pathways that mediate cognitive function. The findings provide clues to further identify new diagnostic biomarkers and therapeutic targets for cognitive dysfunction. • We conducted an epigenome-wide association study on cognitive function in twins. • 28 CpG sites (P < 1 × 10−4) associated with cognitive function were identified. • Lots of well-known enriched terms were identified by GREAT program. • 15 differentially methylated regions related to cognitive function were found. • The findings help to elucidate the pathogenesis of cognitive dysfunction. [ABSTRACT FROM AUTHOR]

This study used hydrogen proton magnetic resonance imaging to detect the changes of white matter and the medial cortex in the prefrontal cortex of patients with type 2 diabetes, analyzed its relationship with cognitive function and blood glucose level, and discussed the recognition of patients with type 2 diabetes from the perspective of brain metabolism. We discuss the neural mechanisms affected by the disorder. The experiment recruited 65 volunteers, including 32 control subjects and 33 patients with type 2 diabetes. All volunteers underwent clinical cognitive function and psychological evaluation, including a simple intelligent mental state examination scale, digital breadth test, Raven intelligence test, Flanker paradigm experiment, connection test, auditory word learning test, depression self-evaluation scale, and anxiety self-rating scale. All subjects underwent multivoxel proton magnetic resonance scanning, and the spectral data were processed and metabolite concentration analysis was completed by Functool software. The detected regions of interest included the bilateral prefrontal white matter and bilateral prefrontal cortex. This study found that the N-acetylaspartate (NAA) and NAA/myo-inositol (MI) of the right prefrontal cortex were reduced, the right prefrontal white matter choline-containing compounds increased, and the MI of the bilateral prefrontal cortex increased in the type 2 diabetes group compared with the control group. The NAA value of the right prefrontal cortex in the type 2 diabetes group was negatively correlated with the glycated hemoglobin concentration. The study found that the right prefrontal cortex NAA value of patients with type 2 diabetes was negatively correlated with the glycated hemoglobin concentration, reflecting that recent blood glucose levels can affect the changes of brain metabolites, and reasonable control of blood glucose can effectively delay brain neurons caused by diabetes. [ABSTRACT FROM AUTHOR]

• Emotion and motivation are crucial psychological processes. • Typical neural perspectives focus on emotion or motivation not both. • New views of integration emphasize merging functionality and brain basis of emotion and motivation. • Key brain regions and circuits of functional integration are explored. • A broad analysis including cognitive, social and cultural influences on these merged or segregated functions is addressed. As a part of a larger Affectome Project (http://neuroqualia.org/background.php) with an overarching goal of mapping and redefining biological substrates of feelings and emotions, we explored the neural underpinnings for the functions of motivation and emotion. Historically emotion and motivation have been placed into distinct neural circuits and examined separately. We propose a novel view of significant neural convergence of emotion and motivation, in contrast to conventional neural-based frameworks emphasizing segregation. Evidence from diverse research areas in emotion and motivation was reviewed, pinpointing key neural regions of overlap. The findings support important neural sharing between emotion and motivation, suggesting that these two functions are tightly intertwined with one another in the brain. Neural overlap does not necessarily imply continuous functional overlap. Even if identical brain regions/systems are activated for motivation and emotion, this activation may involve distinct and unique patterns of connection and information flow as the network shifts functionality. This review highlights the crucial importance of further research to explicate the patterns and modes of responding of these overlapping systems. [ABSTRACT FROM AUTHOR]

The first commercial products of 5G will be released within 2020 and therefore, it becomes an absolute necessity to research whether the key enabling technologies are advantageous for the operators to invest in. One of the most fundamental technologies Cognitive Radio (CR), since there is not much research in the field. This paper develops a techno-economic framework for the CR technology and is contrasted with an already existing model for Software Defined Networks (SDN). A Sensitivity Analysis (SA) indicates the cost parameters that are the most expensive ones and should be reconsidered for the model's wide adoption and viability. [ABSTRACT FROM AUTHOR]

Background: Genome-wide association studies (GWAS) have identified several genetic variants associated with major depression disorder (MDD). However, pinpointing the causal variants which are responsible for the association signal at a risk locus remains a major challenge.Methods: We used Summary data-based Mendelian Randomization (SMR) with Psychiatric Genomics Consortium (PGC) GWAS summary and brain expression quantitative trait loci (eQTL) data to identify genes whose expression levels are causally associated with MDD. Then we performed differential expression analysis, methylation quantitative trait loci analysis, and cognitive genetics analysis to investigate the potential roles of risk genes in the pathogenesis of MDD.Results: Through SMR integrative analysis, we identified the SNP rs10789336 located in Neuronal growth regulator 1 (NEGR1) gene significantly affected the expression level of RPL31P12 in brain tissues and contributed to the risk of MDD (P = 1.96 × 10-6). Consistently, the SNP rs10789336 was associated with the methylation levels of three nearby DNA methylation sites, including cg09256413 (NEGR1, P=1.72 × 10-10), cg11418303 (prostaglandin E receptor 3 [PTGER3], P = 4.78 × 10-6), and cg23032215 (ZRANB2 antisense RNA 2 [ZRANB2-AS2], P = 1.23 × 10-4). Differential expression analysis suggested that the NEGR1 gene was upregulated in prefrontal cortex (P = 5.14 × 10-3). Cognitive genetics analysis showed that the SNP rs10789336 was associated with cognitive performance (P = 2.41 × 10-16), educational attainment (P = 1.75 × 10-14), general cognitive function (P = 2.65 × 10-12), and verbal numerical reasoning (P = 1.36 × 10-12).Conclusion: Collectively, our results revealed that the SNP rs10789336 in NEGR1 might confer risk to MDD. Further investigation of the roles of NEGR1 in the pathogenesis of MDD is warranted. [ABSTRACT FROM AUTHOR]

Background: There is urgent need for development and evaluation of targeted interventions for cognitive deficits in (partially) remitted major depression. Until now the analyses of the moderators of treatment efficacy were only examined in mixed samples of patients with schizophrenia, affective spectrum and schizoaffective disorders. Thus, the aim of our study was to evaluate the predictors of cognitive remediation therapy (CRT) improvement in a sample of (partially) remitted major depressive disorder patients.Methods: Reliable Change Index with corrections for practice effects was calculated for each participant as an indicator for training improvement. Thirty eight patients, who were randomized within our previously conducted CRT clinical trial, were divided into "Improvers" and "Nonimprovers" in the attention domain, to compare them on sociodemographic, psychopathological, neurocognitive, psychosocial and training factors.Results: We detected 13 training participants who improved reliably in the attention domain. Illness duration was the only factor which significantly differentiated between Improvers and Nonimprovers. No significant differences between Improvers and Nonimprovers in terms of other clinical variables, sociodemographic and neuropsychological factors were found.Limitations: Exploratory research results should be taken with caution. Focus on the attention domain could have led to a limited point of view.Conclusion: Our findings represent a first analysis of the predictors of cognitive remediation training improvement in (partially) remitted unipolar depression. Much more work should be done to refine cognitive treatment approaches. An initiation of cognitive training in early stages of the disease could be beneficial for the affected patients. [ABSTRACT FROM AUTHOR]

In the development of a new product, concept generation is a crucial stage, as it determines much of the cost of the product lifetime. The process of generating concepts that meet customer requirements, however, can be challenging due to incomplete information, chaotic design constraints, and complicated design iterations. Deep learning-based pretrained language models can be a potential solution to overcome these limitations. But current methods are limited by the gap between the language used in design-related documents such as patent and the casual spoken language as the latter reflects the thinking process of concept generation. In this paper, we propose a key concepts derivation approach based on cognitive analysis to address challenges in product design and to effectively incorporate prior knowledge. This approach leverages a pretrained language model to extract information from multiple sources of textual data and represents design thinking in a vector space. We conduct a Design-by-Analogy based verbal protocol analysis experiment for high-speed elevators to collect verbal data and establish a design thinking corpus. Based on this, our approach is employed for key concepts derivation in product design and explore how solutions are generated to realize specific customer-required functionality. By analyzing the types of design stimuli, the effectiveness of our approach in deriving key design concepts are demonstrated with respect to novelty and feasibility. • We established a cognitive analysis-based approach for deriving key concepts. • This approach can identify the most important concepts in the product design. • We verified the approach in an analogy-based verbal protocol analysis experiment. [ABSTRACT FROM AUTHOR]

Blood biomarkers can improve the ability to diagnose dementia, providing new information to better understand the pathophysiology and causes of the disease. Some studies with patients have already shown changes in metabolic profiles among patients with pathological cognitive decline or Alzheimer's disease, when compared to individuals with normal cognition. To search for new metabolic biomarkers of dementia, we analyzed serum levels of several metabolites, measured by nuclear magnetic resonance spectroscopy, in elderly individuals, a group with normal cognitive decline (control), and three other groups with cognitive decline. pathological (low, moderate, and severe). Decreased plasma levels of tyrosine, glutamate, valine, leucine, and isoleucine are associated with worsening of pathological cognitive decline. However, the area under analysis of receptor operating characteristics suggests that tyrosine and glutamate have low specificity and sensitivity. Valine, leucine, and isoleucine are influenced by blood glucose or diabetes, but these conditions do not seem to be of great influence in the differences observed. Isobutyrate, histidine, acetone and unknown-1 metabolite also decrease their plasma levels with increasing CD. Isobutyrate ad histidine could have neuroprotective and antioxidant actions, respectively. To elucidate the role of decreased unknown metabolite-1 as a CD biomarker, it will be necessary to previously investigate its identity. To define and elucidate the role of acetone in pathological CD, additional laboratory and clinical studies must be performed. All these metabolites together may constitute a set of biomarkers with capability to identify pathological CD or dementia. Decrease of glutamate, tyrosine, valine, leucine, isoleucine, histidine, isobutyrate, acetone and unknown-1 metabolite together are a set of biomarkers able to identify pathological CD or dementia. Histidine, isobutyrate, acetone and unknown-1 metabolite are more specific biomarkers of CD. [Display omitted] • Glutamate, valine, leucine, isoleucine, isobutyrate, histidine, acetone and unknown-1 metabolite are associated to CD or dementia. • Valine, leucine, and isoleucine (BCAA) are also slightly influenced by glycemia changes. • Glutamate, isobutyrate, and histidine were associated to pathways involved in neurodegeneration. • The role of acetone in CD changes and identity of unknown-1 metabolite must be truly analyzed. [ABSTRACT FROM AUTHOR]

Military information is gradually overloaded due to the diversity of sources and the exponential growth in quantity, which greatly affects the accuracy of intelligence personnel in extracting and analyzing military information. The modern warfare approach has also evolved from the traditional physical domain to the cognitive domain, and competing for advantages in the cognitive domain has become a key objective of combat. Therefore, constructing domain knowledge graphs and mining the relationships between data play an important role in cognitive domain analysis. In this paper, we propose a convolutional network recognition method based on improved two-layer bi-directional BiLSTM networks named the BERT- α BiLSTMs-RECNN-CRF (BDBRC) model. For the difficulties of military entities generally having long names and low extraction accuracy, as well as the existence of a large number of composite entities that are difficult to recognize, an improved two-layer BiLSTM model is devised first. In view of the fact that the BiLSTMs model always extracts features equally in long-distance text sequences without actually considering the different influences of different sentence contexts, contribution factor a is added to extract the contribution of the above and below to the target entity in different sentences respectively. Then, aiming at the strong problem of the domain of military news texts and the high level of inter-entity ambiguity, we propose a method that utilizes a modified convolutional network (RECNN) for partial feature extraction and jointly with a modified two-layer BiLSTM network for entity recognition. The experiment on the self-constructed dataset shows that the F1 value of the model proposed in this paper reaches 93.18%, and the F1 value, P, and H of our model are all better than the baseline model, which verifies the performance of the model. At the same time, we use public data sets MSRA and CLUB2020, and the experimental results show that the model proposed in this paper also has a good performance in the public data set, verifying the universality of the model. It can provide methodological support for the construction of the military knowledge graph. [ABSTRACT FROM AUTHOR]

• Cognitive analysis of students' skills to solve problems in the domain of kinematics. • Development of a practical formative assessment instrument to assist science teachers. • Design of targeted help to improve students' problem solving. In physics education, most teachers provide students feedback on their problem solutions through grades on written tests. The practice of feedback after a summative test does not often meet the needs of many students to improve their problem solving. In this paper we report on the development of a formative assessment instrument to allow teachers to provide more meaningful action-oriented feedback on students' performance on written tests. Our research and development approach comprised three phases.The first phase consisted of a literature guided cognitive analysis of effective problem-solving strategies in the physics domain. This analysis resulted in the identification of three crucial episodes in students' problem-solving approaches during which students engage in specific cognitive activities. The second phase consisted of the design of an assessment instrument to monitor specific cognitive activities during the three crucial episodes when solving physics problems. This resulted in a rating scale with 11 levels to indicate students' efficacy. The third phase consisted of research of the validity, reliability, and practicality of the instrument. Here we trained three teachers to trace students' mistakes on different problems in the domain of kinematics and asked them to rate the mastery of 16 eleventh-grade pre-university students. In this phase we assessed the reliability and validity of this instrument by computing Krippendorff's alpha to indicate teachers' inter-rater reliability. Practicality of the instrument was assessed by examining the variation in students' level of mastery on problems of different complexity. Further research is needed to provide more detailed guidelines for how teachers can use the instrument in formative assessment (in contrast to summative assessment) to help students to develop correct solution methods and foster students' metacognition about problem solving in related physics areas (i.e., knowledge transfer). [ABSTRACT FROM AUTHOR]

Whether cognitive vulnerability to depression exists along a continuum of severity or as a qualitatively discrete phenomenological entity has direct bearing on theoretical formulations of risk for depression and clinical risk assessment. This question is of particular relevance to adolescence, given that cognitive vulnerability appears to coalesce and rates of depression begin to rise markedly during this period of development. Although a dimensional view is often assumed, it is necessary to submit this assumption to direct empirical evaluation. Taxometric analysis is a family of statistical techniques developed directly to test such assumptions. The present study applied taxometric methods to address this question in a community sample of early adolescents (n = 485), drawing on three indices of cognitive vulnerability to depression (i.e., negative inferential style, ruminative response style, self-referent information processing). The results of three taxometric analyses (i.e., mean above minus below a cut [MAMBAC], maximum eigenvalue [MAXEIG], and latent mode [L-Mode]) were consistent in unambiguously supporting a dimensional conceptualization of this construct. The latent structure of the tested indices of cognitive vulnerability to depression in adolescence appears to exist along a continuum of severity rather than as a discrete clinical entity. [ABSTRACT FROM AUTHOR]

As reinforcement learning algorithms are being applied to increasingly complicated and realistic tasks, it is becoming increasingly difficult to solve such problems within a practical time frame. Hence, we focus on a satisficing strategy that looks for an action whose value is above the aspiration level (analogous to the break-even point), rather than the optimal action. In this paper, we introduce a simple mathematical model called risk-sensitive satisficing (RS) that implements a satisficing strategy by integrating risk-averse and risk-prone attitudes under the greedy policy. We apply the proposed model to the K -armed bandit problems, which constitute the most basic class of reinforcement learning tasks, and prove two propositions. The first is that RS is guaranteed to find an action whose value is above the aspiration level. The second is that the regret (expected loss) of RS is upper bounded by a finite value, given that the aspiration level is set to an "optimal level" so that satisficing implies optimizing. We confirm the results through numerical simulations and compare the performance of RS with that of other representative algorithms for the K -armed bandit problems. [ABSTRACT FROM AUTHOR]

Background: In recent years, psychiatry research has increasingly focused on understanding mental illnesses from a cross-diagnostic, dimensional perspective in order to better align their neurocognitive features with underlying neurobiological mechanisms. In this multi-site study, we examined two measures of cognitive control (d-prime context and lapsing rate) during the Dot Probe Expectancy (DPX) version of the AX-Continuous Performance Task in patients with either schizophrenia (SZ), schizoaffective disorder (SZ-A), or Type I bipolar disorder (BD) as well as healthy control (HC) subjects. We hypothesized significantly lower d-prime context and higher lapsing rate in SZ and SZ-A patients and intermediate levels in BD patients relative to HC.Methods: 72 HC, 84 SZ, 77 SZ-A, and 58 BD patients (ages 18-56) were included in the final study sample.Results: Significant main effects of diagnosis were observed on d-prime context (F(3,279) = 9.59, p < 0.001) and lapsing (F(3,279) = 8.08, p < 0.001). A priori linear contrasts suggesting intermediate dysfunction in BD patients were significant (p < 0.001), although post-hoc tests showed the BD group was only significantly different from HC on d-prime context. Group results for d-prime context remained significant after covarying for lapsing rate. Primary behavioral measures were associated with mania and disorganization symptoms as well as everyday functioning.Conclusions: These findings suggest a continuum of dysfunction in cognitive control (particularly d-prime context) across diagnostic categories in psychiatric illness. These results further suggest that lapsing and d-prime context, while related, make unique contributions towards explaining deficits in cognitive control in these disorders. [ABSTRACT FROM AUTHOR]

Cette recherche originale se propose de comparer la position doctrinale, psychopathologique et opérationnelle de l'Inquisition espagnole du xv e siècle (Torquemada) avec celle de l'islamisme radical des années 1988 à 2005 (Al-Qaïda). Sont passés en revue successivement : (a) les principaux textes de codification de la procédure criminelle d'instruction d'un procès du Saint-Office (Directorium inquisitorum) ; (b) la vie et l'action du grand inquisiteur Tomás de Torquemada (1420–1498) ; (c) les relations psychopathologiques entre la passion (psychoses passionnelles, idéalisme passionné, personnalité paranoïaque) et le fanatisme ; (d) « les fous, illuminés, criminels » du terrorisme islamique ; (e) les mobiles cognitifs et émotionnels d'engagement dans la radicalisation djihadiste des personnes jeunes ; (f) les principes communs du fanatisme monothéiste (Inquisition, Al-Qaïda) et les dogmes particuliers du terrorisme islamique de notre temps ; (g) les modes opératoires de l'Inquisition et de la guerre sainte djihadiste. L'auteur conclut que la rigueur et le sérieux de la procédure judiciaire inquisitoriale, qui est précise, individuelle et personnalisée, s'oppose aux pamphlets révolutionnaires d'Al-Qaïda qui ne donnent que les grandes orientations des modes opératoires de la lutte contre les infidèles qui sont habituellement des victimes aléatoires. This original research compares the doctrinal, psychopathological and operational standpoints of the 15th century Spanish Inquisition (Torquemada) with those of radical Islamism from 1988 to 2005 (Al-Qaeda). The following are reviewed: (a) the main texts codifying the procedure for conducting the criminal investigation of a Holy Office trial (Directorium inquisitorum); (b) the life and work of the grand inquisitor Tomás de Torquemada (1420–1498); (c) the psychopathological relations between passion (passionate psychoses, passionate idealism, paranoid personality) and fanaticism; (d) "the madmen, the enlightened and the criminals" of Islamic terrorism; (e) the cognitive and emotional motives for engagement in the jihadist radicalization of young people; (f) the common principles of monotheistic fanaticism (Inquisition, Al-Qaeda) and the particular dogmas of Islamic terrorism in our time; (g) the operating modes of the Inquisition and the Jihadist holy war. The author concludes that the rigour and seriousness of the inquisitorial judicial procedure, which was precise, individual and personalized, contrasts with the revolutionary pamphlets of Al-Qaeda, which only provide broad guidelines for the modus operandi of the fight against infidels, who are usually random victims. [ABSTRACT FROM AUTHOR]

The effects on dehydration and cognitive performance from heat and/or physical activity are well established in the laboratory, although have not yet been studied for personnel working in occupations such as wildland firefighting regularly exposed to these types of conditions. This study aimed to investigate the effects of temperature and dehydration on seventy-three volunteer firefighters (35.7 ± 13.7 years, mean ± standard deviation) during a simulation of wildfire suppression under either control or hot (18-20; or 33-35 °C) temperature conditions. Results showed cognitive performance on the psychomotor vigilance task declined when participants were dehydrated in the heat and Stroop task performance was impaired when dehydrated late in the afternoon. Firefighters may be at risk of deteriorations in simple cognitive functions in the heat whilst dehydrated, although may also experience impairments in complex cognitive functions if dehydrated late in the day, irrespective of the environmental temperature. [ABSTRACT FROM AUTHOR]

Abstract Research exploring how cognitive risk- and protective factors relate following remission from internalizing disorders suggests a central role for resilience. However, it remains unclear what constitutes resilience in this context. Furthermore, previous studies have typically relied on cross-sectional data which do not allow to map the temporal dynamics of such relations. Using a seven-day experience sampling period in 85 remitted depressed patients, we examined the interplay between five transdiagnostic vulnerability- and protective factors in daily life. We present a temporal, contemporaneous, and a between-subjects network, providing an in-depth analysis of how these factors relate to daily life fluctuations in residual symptomatology. Furthermore, we test the role of positive affect as a main resilience factor. Resilience uniquely predicted all other factors over time (temporal network). Higher levels of resilience were related to less momentary use of rumination, more deployment of positive appraisal, and lower occurrence of residual symptoms (contemporaneous network). Participants scoring high on resilience mostly engaged in positive appraisal (between-subjects network). Similar structures were obtained when substituting self-reported resilience by positive affect. This highlights the importance of resilience, and in particular, positive affectivity, to cope with stressors following remission. This may be fostered by facilitating the use of positive appraisal. Highlights • Resilience held a central position in the temporal and contemporaneous network models. • Resilience uniquely predicted transdiagnostic risk- and protective factors over time. • Resilient individuals are characterized by higher use of positive appraisal. • Positive affectivity forms a key resilience factor. • This may be fostered via deployment of positive appraisal. [ABSTRACT FROM AUTHOR]

Abstract Atrial fibrillation (AF) is the most common heart arrhythmia, with the highest prevalence in the elderly. AF has been correlated with silent lesions and cognitive impairment, even in the absence of stroke. The cognitive impairment in AF represents a risk of functional decline, morbidity, mortality and high costs, constituting a public health problem due to the increasing prevalence of this arrhythmia. Cognitive analysis of patients with AF without stroke has shown poor performance in executive, memory and learning functions. The greater loss occurs in speed processing and performance of instrumental tasks leading to functional dependence. Neuroimaging studies have shown both structural and functional abnormalities in individuals with AF even in the absence of cognitive impairment. The mechanisms related to cognitive impairment and cerebral abnormalities in the AF are still a matter of discussion in the literature and, therefore, how to stop its progression is unknown. We reviewed the recent evidence about AF and dementia in patients without stroke, with special emphasis to the reported profile of cognitive dysfunction and the neuroimaging evidence of brain abnormalities. Highlights • Atrial fibrillation is a common heart arrhythmia with increasing prevalence. • Atrial fibrillation appears to be a risk factor for dementia even without stroke. • How stroke-free atrial fibrillation may conduce to dementia is unknown. • Prevent dementia in stroke-free atrial fibrillation may be challenge. [ABSTRACT FROM AUTHOR]