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Greenspace in schools might enhance students' academic performance. However, the literature—dominated by ecological studies at the school level in countries from the Northern Hemisphere—presents mixed evidence of a beneficial association. We evaluated the association between school greenness and student‐level academic performance in Santiago, Chile, a capital city of the Global South. This cross‐sectional study included 281,695 fourth‐grade students attending 1,498 public, charter, and private schools in Santiago city between 2014 and 2018. Student‐level academic performance was assessed using standardized test scores and indicators of attainment of learning standards in mathematics and reading. School greenness was estimated using Normalized Difference Vegetation Index (NDVI). Linear and generalized linear mixed‐effects models were fit to evaluate associations, adjusting for individual‐ and school‐level sociodemographic factors. Analyses were stratified by school type. In fully adjusted models, a 0.1 increase in school greenness was associated with higher test scores in mathematics (36.9 points, 95% CI: 2.49; 4.88) and in reading (1.84 points, 95% CI: 0.73; 2.95); as well as with higher odds of attaining learning standards in mathematics (OR: 1.20, 95% CI: 1.12; 1.28) and reading (OR: 1.07, 95% CI: 1.02; 1.13). Stratified analysis showed differences by school type, with associations of greater magnitude and strength for students attending public schools. No significant associations were detected for students in private schools. Higher school greenness was associated with improved individual‐level academic outcomes among elementary‐aged students in a capital city in South America. Our results highlight the potential of greenness in the school environment to moderate educational and environmental inequalities in urban areas. Plain Language Summary: Vegetation in the school environment might help students learn and perform better in cognitive‐demanding tasks. We linked standardized test records of 281,695 students in 1,498 schools in Santiago, Chile with measurements of vegetation around schools derived from satellite data, in order to investigate the association between school greenness and students' academic performance. We found that students who attended schools with more greenery had higher test scores in both mathematics and reading and were more likely to achieve learning standards in these subjects, even after taking into account differences between schools and students' socioeconomic contexts. The study also found that these beneficial associations were more substantial for students attending public schools than for those in private schools. These results highlight the potential benefits of having green spaces in schools, especially for students in urban areas, and suggest that this could be a way to address educational and environmental inequalities. Key Points: Higher school greenness was associated with improved individual‐level academic performance in a capital city of the Global SouthAssociations of greater magnitude and strength for students in public schools. No significant associations detected in private schoolsGreenness around schools might aid in reducing educational and environmental inequalities in urban areas [ABSTRACT FROM AUTHOR]

A theoretical model describing young students' (Grade 3) arithmetic-algebraic structure sense was formulated and validated empirically (n = 130), hypothesizing that young students' arithmetic-algebraic structure sense consists of five distinct but correlated factors; structure in numerical equivalence and word-problem modeling, structure in arithmetic, mathematical structure in number sequences, varying quantities and number correspondences, structure in patterns, and structure in functions. Data analysis suggested that arithmetic and arithmetic-algebraic tasks can be categorized based on the proposed model. Analysis traced three categories of students that represent different profiles of students. Students of the basic arithmetic structure sense profile approach flexibly simple arithmetic and patterning tasks that do not require generalization; students of the advanced arithmetic structure profile exhibit an awareness of local relations by describing the underlined relations in a variety of numerical situations. Students of the emergent arithmetic-algebraic profile utilize the awareness of mathematical structural relations to symbolize functional relations. A structural model showed the importance of grasping structure in patterns and describing the mathematical structure in numerical situations to develop structure in functions. [ABSTRACT FROM AUTHOR]

Edge-cloud computing is an emerging approach in which tasks are offloaded from mobile devices to edge or cloud servers. However, Task offloading may result in increased energy consumption and delays, and the decision to offload the task is dependent on various factors such as time-varying radio channels, available computation resources, and the location of devices. As edge-cloud computing is a dynamic and resource-constrained environment, making optimal offloading decisions is a challenging task. This paper aims to optimize offloading and resource allocation to minimize delay and meet computation and communication needs in edge-cloud computing. The problem of optimizing task offloading in the edge-cloud computing environment is a multi-objective problem, for which we employ deep reinforcement learning to find the optimal solution. To accomplish this, we formulate the problem as a Markov decision process and use a Double Deep Q-Network (DDQN) algorithm. Our DDQN-edge-cloud (DDQNEC) scheme dynamically makes offloading decisions by analyzing resource utilization, task constraints, and the current status of the edge-cloud network. Simulation results demonstrate that DDQNEC outperforms heuristic approaches in terms of resource utilization, task offloading, and task rejection. [ABSTRACT FROM AUTHOR]

Estimation is a primary activity in everyday life, so getting it "right" in primary school provides a foundational basis in mathematical reasoning. This study focuses on numerosity estimation in primary mathematics, which is one of four types of estimation reported in literature. In numerosity estimation, a nonnumerical quantitative representation is typically translated into a number. While it is assumed that fostering numerosity estimation has a great impact on the development of mathematical skills, research indicates that math achievement is influenced by non-cognitive aspects such as students' math interests. So, math interest could also influence the accuracy in numerosity estimation. In this study, we investigate the relationship between accuracy in numerosity estimation, math achievement, and math interest in third-grade students. For capturing accuracy in numerosity estimation in a standardized way, we developed an online numerosity estimation test. For assessing the construct of math interest, we used an existing questionnaire. Math achievement was assessed by a standardized math test that includes two subtests focusing on arithmetic and application tasks. The sample was comprised of 185 third-grade students. We analyzed the data using correlation and multiple linear regression analysis. The results showed a significant positive correlation between math interest and math achievement. However, no relationship was found between accuracy in numerosity estimation and math interest nor between accuracy in numerosity estimation and math achievement. These partly unexpected findings suggest further studies dedicated to numerosity estimation and its relationship to other constructs. [ABSTRACT FROM AUTHOR]

The current study investigated whether and how each component of the working memory model was associated with kindergarten children's arithmetic performance. A total of 103 Chinese kindergarten children were administered tests of the visuospatial sketchpad, the phonological loop, the central executive, and basic number processing (i.e., number line estimation, nonverbal numerosity estimation and numerical magnitude comparison). The results showed that among the three working memory components, the central executive accounted for a significant proportion of the variance in young children's arithmetic performance. In terms of basic number processing, number line estimation and numerical magnitude comparison had significant influences on young children's arithmetic performance. Furthermore, numerical magnitude comparison played a mediating role between the visuospatial sketchpad and early arithmetic skills. These findings highlight the importance of working memory and basic number processing in early arithmetic skills and reveal different pathways through which the three working memory components influence young children's arithmetic performance. [ABSTRACT FROM AUTHOR]

Specific neurocognitive functions related to attention-deficit hyperactivity disorder (ADHD) affect their academic performance. However, whether neurocognitive functions in children with ADHD play the same role in both mathematics and language performance is unclear. This study aimed to investigate the effects of attention on academic performance of children with ADHD. A cognitive function assessment and Integrated Visual and Auditory Continuous Performance Test (IVA-CPT) were used to assess 639 children (aged 7–17 years) diagnosed with ADHD. Hierarchical regressions analyses were performed with cognitive function and IVA-CPT quotients as predictor variables and with performance on mathematics and language as dependent variables. The attention quotient in IVA-CPT assessing sustained attention significantly contribute to mathematical performance (number comparison and arithmetic) rather than language performance (word semantics and character rhyming) after controlling for other cognitive abilities. Among children with ADHD, attention ability rather than other cognitive functions can significantly predict mathematical performance but not language performance. [ABSTRACT FROM AUTHOR]

People learn adaptively from feedback, but the rate of such learning differs drastically across individuals and contexts. Here, we examine whether this variability reflects differences in what is learned. Leveraging a neurocomputational approach that merges fMRI and an iterative reward learning task, we link the specificity of credit assignment--how well people are able to appropriately attribute outcomes to their causes--to the precision of neural codes in the prefrontal cortex (PFC). Participants credit task-relevant cues more precisely in social compared vto nonsocial contexts, a process that is mediated by high-fidelity (i.e., distinct and consistent) state representations in the PFC. Specifically, the medial PFC and orbitofrontal cortex work in concert to match the neural codes from feedback to those at choice, and the strength of these common neural codes predicts credit assignment precision. Together this work provides a window into how neural representations drive adaptive learning. [ABSTRACT FROM AUTHOR]

Reward and cognitive control play crucial roles in shaping goal-directed behavior. Yet, the behavioral and neural underpinnings of interactive effects of both processes in driving our actions towards a particular goal have remained rather unclear. Given the importance of inhibitory control, we investigated the effect of reward prospect on the modulatory influence of automatic versus controlled processes during response inhibition. For this, a performance-contingent monetary reward for both correct response selection and response inhibition was added to a Simon NoGo task, which manipulates the relationship of automatic and controlled processes in Go and NoGo trials. A neurophysiological approach was used by combining EEG temporal signal decomposition and source localization methods. Compared to a non-rewarded control group, rewarded participants showed faster response execution, as well as overall lower response selection and inhibition accuracy (shifted speed-accuracy tradeoff). Interestingly, the reward group displayed a larger interference of the interactive effects of automatic versus controlled processes during response inhibition (i.e., a larger Simon NoGo effect), but not during response selection. The reward-specific behavioral effect was mirrored by the P3 amplitude, underlining the importance of stimulus–response association processes in explaining variability in response inhibition performance. The selective reward-induced neurophysiological modulation was associated with lower activation differences in relevant structures spanning the inferior frontal and parietal cortex, as well as higher activation differences in the somatosensory cortex. Taken together, this study highlights relevant neuroanatomical structures underlying selective reward effects on response inhibition and extends previous reports on the possible detrimental effect of reward-triggered performance trade-offs on cognitive control processes. [ABSTRACT FROM AUTHOR]

In this study, the technique associated with the capturing involuntary changes in voice elements caused by diseases is applied to diagnose them and a voice index is proposed to discriminate mild cognitive impairments. The participants in this study included 399 elderly people aged 65 years or older living in Matsumoto City, Nagano Prefecture, Japan. The participants were categorized into healthy and mild cognitive impairment groups based on clinical evaluation. It was hypothesized that as dementia progressed, task performance would become more challenging, and the effects on vocal cords and prosody would change significantly. In the study, voice samples of the participants were recorded while they were engaged in mental calculational tasks and during the reading of the results of the calculations written on paper. The change in prosody during the calculation from that during reading was expressed based on the difference in the acoustics. Principal component analysis was used to aggregate groups of voice features with similar characteristics of feature differences into several principal components. These principal components were combined with logistic regression analysis to propose a voice index to discriminate different mild cognitive impairment types. Discrimination accuracies of 90% and 65% were obtained for discriminations using the proposed index on the training and verification data (obtained from a population different fromthe training data), respectively. Therefore, it is suggested that the proposed index may be utilized as a means for discriminating mild cognitive impairments. [ABSTRACT FROM AUTHOR]

Previous studies set out profound cognitive impairments in subjects with treatment-resistant depression (TRD). However, little is known about the course of such alterations depending on levels of improvement in those patients followed longitudinally. The main objective of this study was to describe the course of cognitive impairments in responder versus non-responder TRD patients at one-year follow-up. The second aim was to evaluate the predictive aspect of cognitive impairments to treatment resistance in patients suffering from TRD. We included 131 patients from a longitudinal cohort (FACE-DR) of the French Network of Expert TRD Centers. They undertook comprehensive sociodemographic, clinical, global functioning, and neuropsychological testing (TMT, Baddeley task, verbal fluencies, WAIS-4 subtests, D2 and RLRI-16) at baseline (V0) and one-year follow-up (V1). Most patients (n = 83; 63.36%) did not respond (47 women, 49.47 ± 12.64 years old), while one-third of patients responded (n = 48, 30 women, 54.06 ± 12.03 years old). We compared the cognitive performances of participants to average theoretical performances in the general population. In addition, we compared the cognitive performances of patients between V1 and V0 and responder versus non-responder patients at V1. We observed cognitive impairments during the episode and after a therapeutic response. Overall, each of them tended to show an increase in their cognitive scores. Improvement was more prominent in responders at V1 compared to their non-responder counterparts. They experienced a more marked improvement in code, digit span, arithmetic, similarities, and D2 tasks. Patients suffering from TRD have significant cognitive impairments that persist but alleviate after therapeutic response. Cognitive remediation should be proposed after therapeutic response to improve efficiency and increase the daily functioning. [ABSTRACT FROM AUTHOR]

This paper describes a deep reinforcement learning (DRL) approach that won Phase 1 of the Real Robot Challenge (RRC) 2021, and then extends this method to a more difficult manipulation task. The RRC consisted of using a TriFinger robot to manipulate a cube along a specified positional trajectory, but with no requirement for the cube to have any specific orientation. We used a relatively simple reward function, a combination of a goal‐based sparse reward and a distance reward, in conjunction with Hindsight Experience Replay (HER) to guide the learning of the DRL agent (Deep Deterministic Policy Gradient [DDPG]). Our approach allowed our agents to acquire dexterous robotic manipulation strategies in simulation. These strategies were then deployed on the real robot and outperformed all other competition submissions, including those using more traditional robotic control techniques, in the final evaluation stage of the RRC. Here we extend this method, by modifying the task of Phase 1 of the RRC to require the robot to maintain the cube in a particular orientation, while the cube is moved along the required positional trajectory. The requirement to also orient the cube makes the agent less able to learn the task through blind exploration due to increased problem complexity. To circumvent this issue, we make novel use of a Knowledge Transfer (KT) technique that allows the strategies learned by the agent in the original task (which was agnostic to cube orientation) to be transferred to this task (where orientation matters). KT allowed the agent to learn and perform the extended task in the simulator, which improved the average positional deviation from 0.134 to 0.02 m, and average orientation deviation from 142° to 76° during evaluation. This KT concept shows good generalization properties and could be applied to any actor‐critic learning algorithm. [ABSTRACT FROM AUTHOR]

• Perceived burdensomeness (PB) is a salient risk factors for suicide. • PB is fluid in nature and may serve as a corrective target for intervention. • Decreased PB may mediate decreases in baseline to follow-up suicidal ideation. Perceived burdensomeness (PB), defined by an intractable perception of burdening others, often reflects a false mental calculation that one's death is worth more than one's life and has been supported as a significant risk factor for suicide. Because PB often reflects a distorted cognition, it may serve as a corrective and promising target for the intervention of suicide. More work on PB is needed in clinically severe and in military populations. Sixty-nine (Study 1) and 181 (Study 2) military participants at high baseline suicide risk engaged in interventions targeting constructs relating to PB. Baseline and follow-up measures (at 1, 6, 12, 18, and 24 months) of suicidal ideation were administered, and various statistical approaches—including repeated-measures ANOVA, mediation analyses, and correlating standardized residuals—explored whether suicidal ideation decreased specifically by way of PB. In addition to utilizing a larger sample size, Study 2 included an active PB-intervention arm (N = 181) and a control arm (N = 121), who received robust care as usual. In both studies, participants improved considerably regarding baseline to follow-up suicidal ideation. The results of Study 2 mirrored those of Study 1, corroborating a potential mediational role for PB in treatment-related improvements in suicidal ideation in military participants. Effect sizes ranged from.07–.25. Interventions tailored at decreasing levels of perceived burdensomeness may be uniquely and significantly effective in reducing suicidal thoughts. [ABSTRACT FROM AUTHOR]

Introduction: Several previous studies have reported that hypoxia accidents of fighter pilots are rarer than gravity-induced loss of consciousness and spatial disorientation; however, the risk is greater. Therefore, this study aimed to investigate the relationship between physical fitness and body composition on time of useful consciousness (TUC) in hypobaric hypoxia. Materials and Methods: Body composition and physical fitness testing on human participants were performed; subsequently, they were exposed to hypobaric hypoxia at a simulated altitude of 25,000 ft. Cognitive testing of the participants was accomplished by having them perform arithmetic task tables until they stopped writing for a period exceeding 5 seconds, at which point, they were placed on 100% oxygen. TUC was measured from the time the participants removed their oxygen masks to the time when the oxygen masks were placed back on them. Pearson's correlation was used to determine the relationship between TUC and other variables, and multiple regression was performed to determine the independent variables that best explain the TUC. Results: TUC was positively correlated with the maximum oxygen uptake, stroke volume, arteriovenous oxygen difference, and endurance (sit-up and push-up). The maximum heart rate on the ground, high altitude, body fat mass, and percent body fat were negatively correlated with TUC. A regression analysis showed that 84.5% of the TUC can be explained by body composition and physical fitness. Conclusions: Our results revealed that increased cardiorespiratory fitness and decreased body fat mass could significantly impact the TUC. Therefore, for Air Force pilots who are frequently at high altitudes and at risk for exposure to hypoxia, aerobic exercise is significant to hypoxia tolerance. [ABSTRACT FROM AUTHOR]

Multivariate analysis approaches provide insights into the identification of phenotype associations in brain connectome data. In recent years, deep learning methods including convolutional neural network (CNN) and graph neural network (GNN), have shifted the development of connectome-wide association studies (CWAS) and made breakthroughs for connectome representation learning by leveraging deep embedded features. However, most existing studies remain limited by potentially ignoring the exploration of region-specific features, which play a key role in distinguishing brain disorders with high intra-class variations, such as autism spectrum disorder (ASD), and attention deficit hyperactivity disorder (ADHD). Here, we propose a multivariate distance-based connectome network (MDCN) that addresses the local specificity problem by efficient parcellation-wise learning, as well as associating population and parcellation dependencies to map individual differences. The approach incorporating an explainable method, parcellation-wise gradient and class activation map (p-GradCAM), is feasible for identifying individual patterns of interest and pinpointing connectome associations with diseases. We demonstrate the utility of our method on two largely aggregated multicenter public datasets by distinguishing ASD and ADHD from healthy controls and assessing their associations with underlying diseases. Extensive experiments have demonstrated the superiority of MDCN in classification and interpretation, where MDCN outperformed competitive state-of-the-art methods and achieved a high proportion of overlap with previous findings. As a CWAS-guided deep learning method, our proposed MDCN framework may narrow the bridge between deep learning and CWAS approaches, and provide new insights for connectome-wide association studies. • A CWAS-guided deep learning framework for imaging diagnosis of ASD and ADHD. • Parcellation and population-wise learning to address the local specificity problem. • Functional abnormalities of the PFCdPFCm cortices detected in ASD and ADHD. [ABSTRACT FROM AUTHOR]

Extracting k -order maximal-sum principal submatrix from an n -order real matrix is a typical combinatorial optimization problem and an NP-hard problem. To improve the computational efficiency of solving this problem, we, in this paper, propose an accelerated algorithm with row-by-row updates, called the fusion row update accelerated algorithm, which works by reducing the number of addition operations for submatrix elements. The new algorithm is applied to accelerate color combination selection and maximize color difference, which improves the readability of data visualization results; it is also applied to accelerate stock investment portfolio selection and minimize correlation degree, which decreases the investment risk in the view of daily return volatility. [ABSTRACT FROM AUTHOR]

In the present study, we worked with 49 students (26 women and 23 men) of which two present hearing impairment (1 woman and 1 man) from the Thomas Alva Edison Elementary School in the City of Morelia, Michoacán. The research was qualitative with the objective of applying technological tools for learning mathematics with the participating population. Two digital applications were implemented: Monster Numbers and The King of Mathematics that are oriented to the resolution of basic arithmetic operations (addition, subtraction, multiplication, and division). The results indicate that all the participating students had a fruitful learning in mathematical achievement with the use of technological tools because they were able to solve problems, reason, improve their memory and perform mental calculations in a dynamic, interactive and attractive way for obtaining prizes for the passage of levels in the technological game; achieving in this way the execution of a diversified strategy for the intervention with the population that presents the condition of hearing disability. [ABSTRACT FROM AUTHOR]

In recent decades, several Russian schools have been implementing a world-unique education program of mathematics for elementary schools. In it, the landscape of school arithmetic is radically expanded due to the basic objects of modern mathematics and computer science. These objects and their operations are visual, making them much more comprehensible than traditional arithmetic. The range of activities also expands due to, for example, the introduction of strategies for enumeration, game winning, and algorithms (also operating in a visual environment). At the same time, the student's position changes: they independently discover and build mathematics and constantly solve personally new, but feasible tasks that are "not-known-how-to-solve." The student's resources are saved by using a computer to perform routine arithmetic operations that have already been discovered and understood. The implementation of this approach is discussed in detail and is illustrated by examples of actual tasks that are representative of the program under consideration and the whole approach. [ABSTRACT FROM AUTHOR]

Most studies of mathematics teacher noticing employ information-processing-based models of noticing. While information processing has been used productively to research the cognitive requirements of noticing, critics have argued that these accounts conceptualise noticing as a relatively passive and mental act. This paper demonstrates how an alternative perception/action cycle model of noticing can draw attention to how teacher noticing is supported by active interaction with the classroom environment mid-lesson. Data from two primary mathematics lessons were gathered using a head-mounted camera technique. These data are analysed using the perception/action cycle model to demonstrate the model's capacity to enable productive research. The model draws attention to aspects of teacher behaviour that support noticing that are given little weight when information processing informs analysis. By contrasting the noticing of one experienced and one beginning teacher, differences in the way that each teacher deployed their attention and looked for information mid-lesson can be ascertained. The experienced teacher took action that increased the likelihood that students would create mathematical representations that enabled perception of students' mathematical thinking and deployed their attention so that they were more likely to be in the right place at the right time to notice. The perception/action cycle model draws attention to these under-researched aspects of mathematics teacher noticing. [ABSTRACT FROM AUTHOR]

Yoga has been shown to reduce stress and to provide health benefits for a number of stress-related disorders. However, the effects and mechanism of an acute bout of yoga practice on relieving stress remain unclear. The aim of this study was to examine the effect of a single bout of yoga on heart rate (HR) and heart rate variability (HRV) response to and recovery from mental stress. This study was conducted with a randomised, counterbalanced, crossover design. A total of 44 participants (mean age 24.58 ± 3.84) completed two conditions (yoga and video watching (VW)) in a randomly assigned order. After each condition, participants underwent a Stroop task and mental arithmetic task. HR and HRV, measured via electrocardiogram, were recorded and analyzed at rest, during each condition, and during the stress and recovery periods. HR was significantly lower during the yoga condition as compared to that during the VW condition. There was no significant difference in HRV observed between the conditions. During both mental stress and recovery periods, there was no significant difference in HR or HRV responses between the yoga and VW conditions. These findings suggested that an acute bout of yoga practice was not superior to quiet sitting in reducing HR and HRV reactivity to and recovery from mental stress. Future studies may consider investigating individuals with exaggerated cardiovascular reactivity to further examine the potential reactivity-lowering effect of yoga. [ABSTRACT FROM AUTHOR]

Background: Intertemporal decision-making, which involves making choices between outcomes at different time points, is a fundamental aspect of human behavior. Understanding the underlying mental processes is vital for comprehending the complexities of human decision-making and choice behavior. Objective: The main objective of this study is to investigate the interplay of mental processes, specifically cognitive evaluation, subjective valuation, and comparison, in the context of intertemporal decision-making, with a specific focus on understanding the discounting process. Methodology: Development of a mathematical representation of the discounting process that incorporates the mental processes associated with intertemporal decision-making. Result: Our findings indicate that hyperbolic discounting aligns well with the cognitive processes underlying intertemporal decision-making. Subsequent research will employ qualitative questionnaires to establish the discount function relevant to specific groups, thereby enhancing our comprehension of the discounting process within intertemporal decision-making. [ABSTRACT FROM AUTHOR]

In Gärtner & Gyuris (2017) we defined the “bias profileˮ of an individual polar interrogative clause type as a non-empty choice from the power sets of evidential bias options, (...({+ev,− ev,%ev})−{Ø}), and epistemic bias options, (...({+ep,− ep,%ep})−{Ø}), for each of its expressive instantiations as positive polar question (PPQ), and negative polar questions with inside (IN-NPQ) and outside negation (ON-NPQ) in the sense of Ladd (1981). By simple arithmetic we predicted the existence of (7x7)³ = 117649 such bias profiles. We then explored the “spaceˮ of bias profiles and demonstrated a numerical reduction to just (4x2)³ = 512 permissible types. This was based on differential choices from the sets of evidential and epistemic biases, formulated in terms of the principle of Static Complementarity (together with the principle of Convexity). In the current brief note, we will show how to considerably cut down options further by in addition imposing a bi-uniqueness constraint on the evidential bias of IN-NPQs. [ABSTRACT FROM AUTHOR]

People respond faster to smaller numbers in their left space and to larger numbers in their right space. Here we argue that movements in space contribute to the formation of spatial-numerical associations (SNAs). We studied the impact of continuous isometric forces along the horizontal or vertical cardinal axes on SNAs while participants performed random number production and arithmetic verification tasks. Our results suggest that such isometric directional force do not suffice to induce SNAs. [ABSTRACT FROM AUTHOR]

A way of presenting information in visual representations of technical systems influences the progress and the outcome of the engineering design process. Consequently, improving the means by and through which information is utilised during the process is one suggested approach to advancing engineering design. Engineers' interaction with visual representations of technical systems is mainly visual and virtual. Although such interactions are cognitively complex, little is known about cognition (mental information processing) underlying the utilisation of design information during engineering design. To narrow the research gap, this study explores how visual representations of technical systems affect engineers' brain activity while generating computer-aided design (CAD) models based on them. More precisely, the brain activity of 20 engineers is captured and analysed using electroencephalography (EEG) during the visuospatially-intensive design tasks of CAD modelling in two conditions; when technical systems are presented with orthographic and isometric projections in technical drawings. The results imply the sensitivity of engineers' brain activity in CAD modelling to the visual representation from which a technical system is interpreted. In particular, significant differences are found in theta, alpha, and beta task-related power (TRP) over the cortex when interpreting the technical drawings and CAD modelling from them. Furthermore, the results reveal significant differences in theta and alpha TRP when considering the individual electrodes, the cortical hemispheres, and the cortical areas. In particular, theta TRP over the right hemisphere and the frontal area seems essential in distinguishing neurocognitive responses to the orthographic and isometric projections. As such, the conducted exploratory study sets the foundations for exploring engineers' brain activity while performing visuospatially-intensive design tasks, whose segments are relatable to the aspects of visuospatial thinking. Future work will explore brain activity in other design activities that are highly visuospatial, with a larger sample size and an EEG device of a higher spatial resolution. [ABSTRACT FROM AUTHOR]

To overcome the fault of convolutional networks, which can be over-smooth, blurred, or discontinuous, a novel transformer network with cross-window aggregated attention is proposed. Our network as a whole is constructed as a generative adversarial network model, and by embedding the Window Aggregation Transformer (WAT) module, we improve the information aggregation between windows without increasing the computational complexity and effectively obtain the image long-range dependencies to solve the problem that convolutional operations are limited by local feature extraction. First, the encoder extracts the multi-scale features of the image with convolution kernels of different scales; second, the feature maps of different scales are input into a WAT module to realize the aggregation between feature information and finally, these features are reconstructed by the decoder, and then, the generated image is input into the global discriminator, in which the discrimination between real and fake images is completed. It is experimentally verified that our designed Transformer window attention network is able to make the structured texture of the restored images richer and more natural when performing the restoration task of large broken or structurally complex images. [ABSTRACT FROM AUTHOR]

With the development of edge computing and artificial intelligence (AI) technologies, edge devices are witnessed to generate data at unprecedented volume. The edge intelligence (EI) has led to the emergence of edge devices in various application domains. The EI can provide efficient services to delay‐sensitive applications, where the edge devices are deployed as edge nodes to host the majority of execution, which can effectively manage services and improve service discovery efficiency. The multilevel index model is a well‐known model used for indexing service, such a model is being introduced and optimized in the edge environments to efficiently services discovery while managing large volumes of data. However, effectively updating the multilevel index model by adding new services timely and precisely in the dynamic edge computing environments is still a challenge. Addressing this issue, this article proposes a designated key selection method to improve the efficiency of adding services in the multilevel index models. Our experimental results show that in the partial index and the full index of multilevel index model, our method reduces the service addition time by around 84% and 76%, respectively when compared with the original key selection method and by around 78% and 66%, respectively when compared with the random selection method. Our proposed method significantly improves the service addition efficiency in the multilevel index model, when compared with existing state‐of‐the‐art key selection methods, without compromising the service retrieval stability to any notable level. [ABSTRACT FROM AUTHOR]

Consciousness arises from the spatiotemporal neural dynamics, however, its relationship with neural flexibility and regional specialization remains elusive. We identified a consciousness-related signature marked by shifting spontaneous fluctuations along a unimodal-transmodal cortical axis. This simple signature is sensitive to altered states of consciousness in single individuals, exhibiting abnormal elevation under psychedelics and in psychosis. The hierarchical dynamic reflects brain state changes in global integration and connectome diversity under task-free conditions. Quasi-periodic pattern detection revealed that hierarchical heterogeneity as spatiotemporally propagating waves linking to arousal. A similar pattern can be observed in macaque electrocorticography. Furthermore, the spatial distribution of principal cortical gradient preferentially recapitulated the genetic transcription levels of the histaminergic system and that of the functional connectome mapping of the tuberomammillary nucleus, which promotes wakefulness. Combining behavioral, neuroimaging, electrophysiological, and transcriptomic evidence, we propose that global consciousness is supported by efficient hierarchical processing constrained along a low-dimensional macroscale gradient. The neuroanatomical basis of consciousness is not fully understood. Here the authors show that a global state of consciousness might not depend on a specific brain region or location in Euclidean space; rather, it is linked to a low-dimensional dynamic pattern in topological space, as shown through the analysis of different experimental paradigms, imaging techniques, and species. [ABSTRACT FROM AUTHOR]

With the rapid development for the technology of Mobile edge computing (MEC), tasks tend to be more diversified and personalized, but fewer scholars considered differentiated quality of service requirements from diverse tasks in task offloading studies. In order to guarantee the real-time performance of latency-sensitive tasks and the throughput of latency-tolerant tasks, we propose a task offloading strategy in a MEC system with a two-tier edge structure. We establish a system model composed of a local model and an edge model to capture the workflow of tasks based on our proposed task offloading strategy, and we derive the key performance measures in terms of the average delay of a latency-sensitive task, the average delay of a latency-tolerant task, the utility of MBS Cluster I and the average power of the MEC system. We carry out experiments with analysis and simulation out to evaluate the long-term performance and validate the effectiveness of our proposed task offloading strategy. Finally, by trading off the average delay of a task and the average power of the MEC system, we formulate an optimization problem with inequality constraints for the average delay of a latency-sensitive task and the stability conditions of the MEC system. Furthermore, we develop an improved Powell–Hestenes–Rockafellar algorithm based on Lagrangian multiplier method to jointly optimize the offloading probabilities of the two types of tasks. [ABSTRACT FROM AUTHOR]

Why is math anxiety usually related to less efficient math processing? According to attentional control theory, anxiety leads to reduced attentional control, which often entails a greater investment of resources (e.g., more time or effort) to carry out a cognitive task. The executive functions mainly affected by anxiety are inhibition and shifting. Previous studies suggest that math anxiety may impair the inhibitory function. In the present study, the relationship between math anxiety and shifting efficiency when switching between two‐digit additions and subtractions was examined. Twenty highly math‐anxious and 20 low math‐anxious individuals participated in an event‐related potential (ERP) transition‐cueing experiment. Math anxiety was expected to delay the shifting process, leading to a larger switch cost in response time and no centroparietal cue‐locked switch‐specific positivity registered in the electroencephalogram during the cue‐target interval. Highly math‐anxious individuals showed a larger switch cost than their low math‐anxious peers. Asymmetrical switch effects between operations in response time were found in both groups, which might be due to larger sequential difficulty effects after subtractions than after additions. The cue‐locked switch‐specific positivity was present only in the low math‐anxious group. The present results suggest that highly math‐anxious individuals take longer to shift task sets. Additionally, the highly math‐anxious group showed a more positive frontal P2 after the cue that announced a switch to subtraction, probably indicating stronger attentional capture by this cue, because the most threatening condition is anticipated. Taken together, these data suggest that math anxiety also impairs attentional control when switching between arithmetic tasks. [ABSTRACT FROM AUTHOR]

Math learning programs were expected to revolutionize students' learning, but their effects so far have mostly been disappointing. Following the debate about why to continue research on math learning programs, we aimed to reformulate this question into how to continue this research. Investigations to date have neither considered a sufficiently wide set of outcome variables nor differentiated between performance measures (e.g., measuring addition and subtraction performance separately) and affective-motivational variables. Moreover, as students can only benefit from a program if they use it, researchers need to take practice behavior into account. Thus, we investigated whether the adaptive arithmetic learning program Math Garden fostered students' addition and subtraction performance, their math self-concept, and a reduction of their math anxiety. We also investigated how practice behavior (practiced tasks/weeks) affected these outcomes. We used a randomized pretest-posttest control group design with 376 fifth-grade students in Germany. Students in the experimental condition practiced with Math Garden for 20.7 weeks and had an increase in math self-concept. The more subtraction tasks the students practiced, the more they improved their subtraction performance. We found no effects on math anxiety. The results are discussed in terms of providing a starting point for new directions in future research. [ABSTRACT FROM AUTHOR]

Accurate quantification of cortical engagement during mental imagery tasks remains a challenging brain‐imaging problem with immediate relevance to developing brain–computer interfaces. We analyzed magnetoencephalography (MEG) data from 18 individuals completing cued motor imagery, mental arithmetic, and silent word generation tasks. Participants imagined movements of both hands (HANDS) and both feet (FEET), subtracted two numbers (SUB), and silently generated words (WORD). The task‐related cortical engagement was inferred from beta band (17–25 Hz) power decrements estimated using a frequency‐resolved beamforming method. In the hands and feet motor imagery tasks, beta power consistently decreased in premotor and motor areas. In the word and subtraction tasks, beta‐power decrements showed engagements in language and arithmetic processing within the temporal, parietal, and inferior frontal regions. A support vector machine classification of beta power decrements yielded high accuracy rates of 74 and 68% for classifying motor‐imagery (HANDS vs. FEET) and cognitive (WORD vs. SUB) tasks, respectively. From the motor‐versus‐nonmotor contrasts, excellent accuracy rates of 85 and 80% were observed for hands‐versus‐word and hands‐versus‐sub, respectively. A multivariate Gaussian‐process classifier provided an accuracy rate of 60% for the four‐way (HANDS‐FEET‐WORD‐SUB) classification problem. Individual task performance was revealed by within‐subject correlations of beta‐decrements. Beta‐power decrements are helpful metrics for mapping and decoding cortical engagement during mental processes in the absence of sensory stimuli or overt behavioral outputs. Markers derived based on beta decrements may be suitable for rehabilitation purposes, to characterize motor or cognitive impairments, or to treat patients recovering from a cerebral stroke. [ABSTRACT FROM AUTHOR]

Copyright of Necatibey Faculty of Education Electronic Journal of Science & Mathematics Education is the property of Balikesir University, Necatibey Faculty of Education 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.)

Copyright of Journal of the College Of Basic Education is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) 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.)

Copyright of Journal of the College Of Basic Education is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) 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.)

Cognitively demanding tasks have been shown to support students' understanding of mathematics. How a task is launched, or introduced, determines how students engage with the task, as well as the type of work the teacher engages in during the task implementation. The authors designed a unit focused on launching a task where prospective teachers (PSTs) planned and enacted a task launch as part of their methods of teaching secondary mathematics courses. Participants in the study spanned three institutions. Using a curricular noticing framework, this paper describes how the prospective teachers (PSTs) interpreted their task by identifying key contextual features, mathematical relationships, and common language, and then focuses on how they responded to their interpretations as they planned to elicit and develop their students' understanding of those key aspects. This paper also describes how the PSTs responded to their interpretations in planning to maintain the cognitive demand of the task. Findings suggest that the prospective teachers valued student-centered approaches and used a range of pedagogical methods to launch cognitively demanding tasks. We also found the prospective teachers needed support identifying context in tasks and in determining how much to tell while maintaining the cognitive demand of the task. We conclude with implications and suggestions for methods courses on both launching a cognitively demanding task and on teaching practices more generally. [ABSTRACT FROM AUTHOR]

The knowledge graph with relational abundant information has been widely used as the basic data support for the retrieval platforms. Image and text descriptions added to the knowledge graph enrich the node information, which accounts for the advantage of the multi-modal knowledge graph. In the field of cross-modal retrieval platforms, multi-modal knowledge graphs can help to improve retrieval accuracy and efficiency because of the abundant relational information provided by knowledge graphs. The representation learning method is significant to the application of multi-modal knowledge graphs. This paper proposes a distributed collaborative vector retrieval platform (DCRL-KG) using the multimodal knowledge graph VisualSem as the foundation to achieve efficient and high-precision multimodal data retrieval. Firstly, use distributed technology to classify and store the data in the knowledge graph to improve retrieval efficiency. Secondly, this paper uses BabelNet to expand the knowledge graph through multiple filtering processes and increase the diversification of information. Finally, this paper builds a variety of retrieval models to achieve the fusion of retrieval results through linear combination methods to achieve high-precision language retrieval and image retrieval. The paper uses sentence retrieval and image retrieval experiments to prove that the platform can optimize the storage structure of the multimodal knowledge graph and have good performance in multi-modal space. [ABSTRACT FROM AUTHOR]

An analysis is made of the ecological and economic relationships between the development of the forest sector of the economy and ways to achieve the desired quality of the forest environment based on assessing the assimilation service of forests to self-restoration after logging, fires, and other negative influences. The relevance of this study is determined by the fact that the issues of assessing the assimilation service of forest capital have not been adequately studied. At the same time, such research is complicated by the need to analyze the relationship between the environmental and economic consequences of logging and forest conservation measures that reduce their negative impact on the forest environment. The methodological approach to assessing these relationships as proposed in this paper implies the category of "external costs" in forest management and its value assessment as a set of environmental costs and damage prevented thanks to forest conservation measures. The results of calculations carried out for the model territories of the Far Eastern border regions have shown that the use of environment-saving selective logging methods increases the cost of logging, which is compensated by lower costs of reforestation and the preservation of the forest environment, thus allowing forests to fully perform socioregulatory services. The study also made it possible to assess the impact of regional forest management systems on the provision and quality of assimilation potential of the model territories. This analysis is necessary for elaborating mechanisms to coordinate the development of the forest complex and conservation activities in the forest regions of the Russian Federation. [ABSTRACT FROM AUTHOR]

Despite their significance, how interactions of plant diversity at multiple spatial scales and soil microbial stoichiometry alter a series of ecosystem functions (multifunctionality, EMF) in response to anthropogenic nitrogen (N) input and herbivores are poorly known. We conducted a 17‐year sheep grazing experiment with 6‐year N addition to explore the impacts of grazing (0, 2.7, 5.3 and 8.7 sheep ha−1) and N addition (N0, N5, N10 and N20, i.e., 0, 5, 10 and 20 g N m−2 yr−1, respectively) on grassland functions and EMF via changes in plant α‐and β‐diversity, and carbon to nitrogen ratio (C:N) of soil microbes in a typical steppe. The results show that grazing or N addition alone significantly affected EMF with a treatment order of 2.7 and 8.7 sheep ha−1 > 0 and 5.3 sheep ha−1 for grazing intensity or N5 > N10 and N20 > N0 for N addition, which resulted in a significant higher EMF in the combination treatment of 2.7 sheep ha−1 and 5 g N m−2 yr−1. Plant α‐and β‐diversity, and soil microbial C:N were the predominant drivers of changes in EMF. Grazing reduced EMF indirectly by decreasing the plant β‐diversity. N addition promoted EMF indirectly by decreasing plant α‐diversity. In addition, lower plant α‐diversity enhanced EMF indirectly by increasing soil microbial C:N. Our results suggest that the negative effects of herbivore on EMF were stronger at larger spatial scales compared to the smaller local communities, while N addition could maintain a higher level of EMF at smaller scales rather than at the larger ones. Our results highlight that multiple spatial scales should be considered to fully unravel the effects of herbivore and eutrophication on ecosystem functions. Our results also demonstrate the important role of soil microbe in maintaining higher grassland multifunctionality, thus we should include the soil microbial functions (i.e., C and N transformation) in further studies. Our results suggest that grazing at a low grazing intensity of 2.7 sheep ha−1 with a low N supplementation of 5 g N m−2 yr−1 could maintain the most important ecosystem functions. Our work provides important insight into grassland conservation and management, aiming to maintain the capacity of grasslands to sustainably supply ecological and productive functions. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Research in Education Sciences is the property of National Taiwan Normal University 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.)

Objectives: To test if inhibitory control was a significant predictor for arithmetic in children with ADHD and if the relationship between inhibitory control and arithmetic was mediated by working memory. Methods: Eighty-four children (ADHD, n = 54; Non-ADHD, n = 30) were tested on their interference control, behavioral inhibition, working memory, and arithmetic. Regression analysis was used to test the predictive role of inhibitory control in arithmetic. Moreover, mediation analysis was done to test whether working memory mediated the relationship between inhibitory control and arithmetic memory. Results: Interference control but not behavioral inhibition was a significant predictor for arithmetic. In addition, interference control had direct and indirect effects via working memory on arithmetic. Conclusions: Results demonstrated that inhibitory control contributed to arithmetic in children with ADHD. Furthermore, interference control had direct and indirect effects via working memory on arithmetic, suggesting interventions for arithmetic difficulties should involve training on both inhibition and working memory. [ABSTRACT FROM AUTHOR]

Background: Studies have investigated the effects of achievement goals on learning interests and mathematics performance above the elementary-school level. However, few studies have explored this topic among kindergarteners based on sound theoretical frameworks. Methods: Through the enrollment of 15 kindergarten teachers and 180 kindergarteners, this study re-validated newly developed measurements of kindergarteners’ achievement goals and learning interests and used these measures to further clarify the effects of achievement goals on learning interests and mathematics performances using structural equation modeling. Results: The results indicate that (1) task-approach goals have positive effects on situational interest and advanced arithmetic performance, whereas task-avoidance goals have positive effects on individual interest. (2) Self-based goals have null effects on most learning interests and mathematics performance, but they have significant negative effects on numbering and counting performance. However, most of these null effects represent negative tendencies. (3) Other-approach goals have positive effects on situational interest and basic arithmetic performance, whereas other-avoidance goals have null effects on these outcomes but have an almost significant positive effect on numbering and counting performance. (4) Task-based goals and self-approach goals are generally beneficial for learning interests and mathematics performance. Conclusion: These results suggest that task-based goals and other-approach goals may be implemented with consideration of the potential long-term detrimental effects of social comparison on learning outcomes. Furthermore, possible negative effects of self-based goals must be monitored to prevent them from undermining learning outcomes. This study revealed consistent, inconsistent, and new evidence that, respectively, verifies, complements, and contradicts findings on the learning outcomes of students above the elementary-school level. [ABSTRACT FROM AUTHOR]

Background: Participants with Parkinson's disease (PD) may experience difficulty during certain dual-task (DT) tests. Thus, it is necessary to keep the cognitive load within the limits of their ability. Objective: To identify cognitive overload and its influence on the walking and auditory addition and subtraction (AAS, all values within the range of 0–20) DT performance of patients with PD. Study design: A cross-sectional observational study with convenience sampling. Setting: Outpatient clinic of the Department of Neurology. Subjects: Sixteen patients with PD and 15 sex- and age- matched people elderly healthy controls (HCs). Methods: Verbal calculation responses and gait parameters were collected from the two groups in the 2-min single arithmetic task (2-min SAT), 2-min single walking task (2-min SWT), and 2-min walking–arithmetic dual task (2-min WADT). Results: The group differences in the lower-limb gait parameters increased in the 2-min WADT (P < 0.01), and those in the arm, trunk, and waist parameters did not change (P > 0.05). In the 2-min SAT, the calculation speed of the PD group was significantly lower than that of the HC group (P < 0.01). In the 2-min WADT, both groups made more errors (P < 0.05), especially the PD group (P = 0.00). PD group miscalculations occurred in the first half of the 2-min SAT but were uniformly distributed in the 2-min WADT. The HC group and PD group had subtraction self-correction rates of 31.25% and 10.25%, respectively. The PD group tended to make subtraction errors when the value of the first operand was 20 or 13.46 ± 2.60 and when the value of the second and third operands were 7.75 ± 2.51 (P = 0.3657) and 8.50 ± 4.04 (P = 0.170), respectively. Conclusions: Cognitive overload was observed in patients with PD. This was mainly reflected in the failure of gait control and accurate calculation, indicated by gait parameters of the lower limbs and accuracy of calculation. To impose a constant cognitive load, the amount added or subtracted, especially in subtraction with borrowing, should not be mixed during a sequential arithmetic problem in the DT, and equations with the value of the first operand equal to 20 or approximately 13, the value of the second operand approximately 7, or the value of the third operand of approximately 9 should be excluded in the AAS DT. Trial registration: Clinical trial registration number: ChiCTR1800020158. [ABSTRACT FROM AUTHOR]

Objective: This study aims to evaluate the test-retest reliability of kinematics and kinetics during single and dual-task stair walking in the elderly. Methods: Fifteen healthy elderly adults were recruited. Kinematic and kinetic parameters were measured using an infrared motion analysis system (Vicon, Oxford Metrics Ltd., Oxford, United Kingdom) and force platforms (Switzerland, Kistler 9287BA and 9281CA). Participants were tested under single-task and dualtask (serial 3 subtractions or carrying a cup of water) conditions. Each participant completed two sessions on two separate days with a 1-week interval. Intraclass correlation coefficients (ICC), Pearson correlation coefficient (r), and Bland-Altman plot were used to assess the reliability of stair walking. Results: When ascending stairs, the ICC of kinematics and kinetics ranged from fair to excellent (ICC = 0.500-0.979) in the single and dual tasks, except for step length (ICC = 0.394) in the single task. The r value of kinematics and kinetics ranged from 0.704 to 0.999. When descending stairs, the ICC of kinematics and kinetics ranged from good to excellent (ICC = 0.661-0.963), except for min hip moment (ICC = 0.133) and min ankle moment (ICC = 0.057) in the manual task. The r value of kinematics and kinetics ranged from 0.773 to 0.960 in the single and dual tasks. In the Bland-Altman plots, all the zero values and most of the dots fell in the 95% confidence interval, and the mean difference was found to be close to zero for all the parameters during stair walking. Conclusion: These results obtained from this study show the good test-retest reliability of step cadence, step speed, and step width during single- and dual-task stair walking in the elderly, and the poor reliability of step length during ascending stairs. All the kinetic parameters, including min hip moment, max knee moment, and min ankle moment, had good test-retest reliability during single- and dualtask stair walking, but min hip moment and min ankle moment had poor reliability during manual-task descending stair. These results may help researchers in the assessment of biomechanics of dual-task stair walking in the elderly and to interpret the effect of interventions in this population. [ABSTRACT FROM AUTHOR]

In Mimosa pudica plants, local and global responses to environmental stimuli are associated with different types of electrical activity. Non-damaging stimuli (e.g. cooling) generate action potentials (APs), whereas damaging stimuli (e.g. heating) are associated with variation potentials (VPs). Local cooling of Mimosa branches resulted in APs that propagated up to the branch-stem interface and caused drooping of the branch (local response). This electrical activation did not pass the interface. If the branch was triggered by heat, however, a VP was transferred to the stem and caused activation of the entire plant (global response). VPs caused by heat were always preceded by APs and summation of the two types of activation appeared to be necessary for the activation to pass the branch-stem interface. Mechanical cutting of leaves also resulted in VPs preceded by APs, but in those cases a time delay was present between the two activations, which prevented adequate summation and transmission of activation. Simultaneous cold-induced activation of a branch and the stem below the interface occasionally resulted in summation sufficient to activate the stem beyond the interface. To investigate the effect of activation delay on summation, a similar structure of excitable converging pathways, consisting of a star-shaped pattern of neonatal rat heart cells, was used. In this model, summation of activation was not hindered by a small degree of asynchrony. The observations indicate that summation occurs in excitable branching structures and suggest that summation of activation plays a role in the propagation of nocuous stimuli in Mimosa. [ABSTRACT FROM AUTHOR]

Although the multifactorial nature of falls in Parkinson's disease (PD) is well described, optimal assessment for the identification of fallers remains unclear. Thus, we aimed to identify clinical and objective gait measures that best discriminate fallers from non-fallers in PD, with suggestions of optimal cutoff scores. METHODS: Individuals with mild-to-moderate PD were classified as fallers (n = 31) or non-fallers (n = 96) based on the previous 12 months' falls. Clinical measures (demographic, motor, cognitive and patient-reported outcomes) were assessed with standard scales/tests, and gait parameters were derived from wearable inertial sensors (Mobility Lab v2); participants walked overground, at a self-selected speed, for 2 min under single and dual-task walking conditions (maximum forward digit span). Receiver operating characteristic curve analysis identified measures (separately and in combination) that best discriminate fallers from non-fallers; we calculated the area under the curve (AUC) and identified optimal cutoff scores (i.e., point closest-to-(0,1) corner). RESULTS: Single gait and clinical measures that best classified fallers were foot strike angle (AUC = 0.728; cutoff = 14.07°) and the Falls Efficacy Scale International (FES-I; AUC = 0.716, cutoff = 25.5), respectively. Combinations of clinical + gait measures had higher AUCs than combinations of clinical-only or gait-only measures. The best performing combination included the FES-I score, New Freezing of Gait Questionnaire score, foot strike angle and trunk transverse range of motion (AUC = 0.85). CONCLUSION: Multiple clinical and gait aspects must be considered for the classification of fallers and non-fallers in PD. [ABSTRACT FROM AUTHOR]

Responsive photonic crystals (RPCs) assembled by monodisperse colloidal particles have attracted enormous interest recently due to their tremendous applications in smart devices. Their structural colors can be determined by particle sizes. However, the lack of a reliable way to tune the sizes in situ limits their development. Herein, we present an efficient route to solve this problem through the fabrication of spherical polymeric particles with light‐triggered reversible swelling behavior via surfactant‐free reversible addition‐fragmentation chain transfer (RAFT) emulsion polymerization‐induced self‐assembly (PISA). Amphiphilic macro‐RAFT agents containing azobenzene groups were synthesized and subsequently employed to mediate the polymerization of methyl methacrylate. Uniform submicron spheres were obtained by modulating solid contents and other parameters. Benefiting from the photoisomerization of azobenzene moieties, the particle sizes expanded and contracted upon alternative ultraviolet/visible‐light irradiation accordingly. This strategy will be a supplement to the emulsion PISA and especially give aid to the progress of the RPC materials. [ABSTRACT FROM AUTHOR]

Background: There are different teaching methods and learning content in the academic field of mathematics between school and university. Many students fail in their studies when the proportion of mathematics is high. Additionally, dropout rates, due to mathematical performance, are high. However, there are different strategies used to improve mathematical skills. Based on the process model of self-regulated learning, an analysis of the association between motivational aspects in the pre-action phase as well as seven special cognitive learning strategies for mathematics in the action phase was conducted. The variables were compared with student performance. The study drew on data from 548 retrospective interviews of cooperative students, using a cross-sectional research design. Results: The analysis via structural equation modeling shows a direct association between motivational aspects, such as academic self-concept and curiosity, and the seven learning strategies in mathematics. Furthermore, there is a direct effect of academic self-concept on performance. However, the learning strategy of practicing was the only variable with associations to performance. Additionally, the indirect effect of curiosity on performance via practicing is analyzed. Conclusion: It can be seen, that curiosity on its own is not enough to ensure a good level of performance in mathematics. The findings suggest student learning strategies focusing on harnessing their curiosity and on practicing. A high academic self-concept is also relevant to the performance level achieved. Lecturers should create a learning environment to support such student behavior. [ABSTRACT FROM AUTHOR]

Finger-based representation of numbers is a high-level cognitive strategy to assist numerical and arithmetic processing in children and adults. It is unclear whether this paradigm builds on simple perceptual features or comprises several attributes through embodiment. Here we describe the development and initial testing of an experimental setup to study embodiment during a finger-based numerical task using Virtual Reality (VR) and a low-cost tactile stimulator that is easy to build. Using VR allows us to create new ways to study finger-based numerical representation using a virtual hand that can be manipulated in ways our hand cannot, such as decoupling tactile and visual stimuli. The goal is to present a new methodology that can allow researchers to study embodiment through this new approach, maybe shedding new light on the cognitive strategy behind the finger-based representation of numbers. In this case, a critical methodological requirement is delivering precisely targeted sensory stimuli to specific effectors while simultaneously recording their behavior and engaging the participant in a simulated experience. We tested the device's capability by stimulating users in different experimental configurations. Results indicate that our device delivers reliable tactile stimulation to all fingers of a participant's hand without losing motion tracking quality during an ongoing task. This is reflected by an accuracy of over 95% in participants detecting stimulation of a single finger or multiple fingers in sequential stimulation as indicated by experiments with sixteen participants. We discuss possible application scenarios, explain how to apply our methodology to study the embodiment of finger-based numerical representations and other high-level cognitive functions, and discuss potential further developments of the device based on the data obtained in our testing. [ABSTRACT FROM AUTHOR]

An e-learning system should recommend learners appropriate learning resources according to their actual needs and cognitive status for improving their learning performance. To overcome the deficiencies of existing approaches (e.g., poor interpretability, limited efficiency and accuracy of recommendation), we propose a new recommendation approach to learning resources via knowledge graphs and learning style clustering. In this approach, the knowledge graphs of an online learning environment are constructed based on a generic ontology model, and the graph embedding algorithm and graph matching process are applied to optimize the efficiency of graph computation for identifying similar learning resources. By introducing learning style theory, learners are clustered based on their learning styles. Based on the clustering results, the learners' degrees of interest in similar learning resources are measured, and the recommendation results are obtained according to the degrees of interest. Finally, the experiments demonstrate that the proposed approach significantly enhances the computational efficiency and the quality of learning resource recommendation compared with the existing approaches in large-scale graph data scenarios. [ABSTRACT FROM AUTHOR]