Reasoning Tasks Research Articles

A brain-inspired object-based attention network for multiobject recognition and visual reasoning.

The visual system uses sequences of selective glimpses to objects to support goal-directed behavior, but how is this attention control learned? Here we present an encoder-decoder model inspired by the interacting bottom-up and top-down visual pathways making up the recognition-attention system in the brain. At every iteration, a new glimpse is taken from the image and is processed through the "what" encoder, a hierarchy of feedforward, recurrent, and capsule layers, to obtain an object-centric (object-file) representation. This representation feeds to the "where" decoder, where the evolving recurrent representation provides top-down attentional modulation to plan subsequent glimpses and impact routing in the encoder. We demonstrate how the attention mechanism significantly improves the accuracy of classifying highly overlapping digits. In a visual reasoning task requiring comparison of two objects, our model achieves near-perfect accuracy and significantly outperforms larger models in generalizing to unseen stimuli. Our work demonstrates the benefits of object-based attention mechanisms taking sequential glimpses of objects.

Performance-based neuropsychological assessment tools for executive function among preschoolers in China: A systematic review

Objective: There is an increasing demand for the assessment of executive function (EF) among Chinese preschoolers. However, there exists methodological and cross-cultural challenges of performance-based EF assessment. The current review aims to 1) identify and summarize the current application of performance-based EF assessment tools for Chinese preschoolers in China and 2) offer recommendation guidelines for different application scenarios, such as clinical or scientific research, and for related personnel.Method: A literature search was conducted from Web of Science, PubMed, PsycInfo, Scopus and China National Knowledge Infrastructure databases. We focused exclusively on performance-based tools assessing EF among children aged three to six years, encompassing tasks of inhibition, working memory, cognitive flexibility, reasoning, problem solving, and/or planning. Clinical (e.g. children with autism spectrum disorders) and multilingual populations residing outside of China (e.g. Chinese Americans) were excluded. Two authors independently screened, extracted, and evaluated each tool for characteristics (e.g. name, domain, type, version, language, approach of administration, and scoring) and sample information (e.g. sample size, age, and region). Results: A total of 98 articles were included, with 255 tools being identified that were further classified into 44 unique types, covering nine EF domains. Most tools were original or informally sinicized, with notable variations in tool selection, administration, and interpretation process. Given that a complete set of EF tools has not been identified as perfectly suitable for Chinese preschoolers, we also offered recommendations based on empirically adapted evaluation criteria. Conclusions: Our findings highlighted the need for appropriate adaptation, administration, and interpretation of the current EF tools.

The impact of multiple language exposure on cognition during childhood: evidence from the UK Millennium Cohort Study.

Many studies argue that exposure to, and use of, multiple languages in childhood has beneficial effects beyond the linguistic domain, including on executive functions (EFs), although recent evidence remains controversial. EFs encompass abilities necessary for regulating goal-directed behaviours in everyday life and, in children, EFs strongly predict later academic achievement and wellbeing. One theoretical framework distinguishes "hot" EFs, which have a reward or affective component, from "cool" EFs that do not. How exposure to more than one language in early childhood modulates hot and cool EFs in later childhood, alongside other environmental and cognitive factors, remains poorly understood. We analysed data from the UK Millennium Cohort Study, a large-scale, nationally representative longitudinal cohort study, which provides information on perinatal and environmental factors (e.g., languages spoken in the home, maternal education) alongside cognitive measures assessed in English. At 3 years, we examined the effect of multiple language exposure on the Bracken school readiness assessment (knowledge of shapes, letters, etc.), and on naming vocabulary. At age 11, we examined the predictors of cool EF, measured with a spatial working memory task; hot EF, measured using a gambling task; and vocabulary, measured using a verbal reasoning task. Data from 16,134 children were analysed. At age 3, a negative effect of multiple language exposure on school readiness and vocabulary was observed, but the difference was smaller with higher maternal education. At age 11, there was also a negative effect on vocabulary, but smaller than that observed at age 3. There were no direct effects of language exposure on either spatial working memory or gambling scores. For hot EF, the multiple language exposure effects were indirect, mediated by early cognition, and the most significant predictor of gambling strategy was sex. For cool EF, school readiness and vocabulary at age 3 were the strongest predictors. Our findings, based on a UK population sample, highlight the importance of considering socioeconomic status and early-life abilities when interpreting the effects of language environments on hot and cool EFs.

Computer‐based scaffoldings influence students' metacognitive monitoring and problem‐solving efficiency in an intelligent tutoring system

AbstractBackgroundComputer‐based scaffolding has been intensively used to facilitate students' self‐regulated learning (SRL). However, most previous studies investigated how computer‐based scaffoldings affected the cognitive aspect of SRL, such as knowledge gains and understanding levels. In contrast, more evidence is needed to examine the effects of scaffolding on the metacognitive dimension and efficiency outcome of SRL.ObjectivesThis study aims to examine the role of computer‐based scaffolding in students' metacognitive monitoring and problem‐solving efficiency.MethodsSeventy‐two medical students completed two clinical reasoning tasks in BioWorld, an intelligent tutoring system (ITS) designed for promoting medical students' diagnostic expertise. During solving the tasks, students were asked to report their confidence judgements about proposed diagnoses. Computer trace data were used to identify task completion time (CT) and students' use of three scaffolding types, that is, conceptual, strategic, and metacognitive. Then we calculated students' metacognitive monitoring accuracy (i.e., calibration) and problem‐solving efficiency.Results and ConclusionsOne‐sample t‐test demonstrated that students inaccurately monitored their learning processes and were overconfident in both tasks. Linear mixed‐effects models (LMMs) indicated that the intensive use of metacognitive scaffolding positively predicted students' metacognitive monitoring accuracy. Moreover, strategic scaffolding was negatively related to problem‐solving efficiency, whereas metacognitive scaffolding positively influenced problem‐solving efficiency.TakeawaysThis study shows the importance of metacognitive scaffolding in improving the accuracy of metacognitive monitoring and problem‐solving efficiency. Findings from this study provide new insights for instructors and ITS developers to optimise the design of scaffoldings.

The relationship between math anxiety and math performance: The moderating role of visuospatial working memory

According to the processing efficiency theory (PET), math anxiety would interfere with working memory resources, negatively affecting mathematical abilities. To date, few studies have explored how the interaction between math anxiety and working memory would affect different types of math tasks, especially in primary school children. Therefore, the purpose of this study was to explore whether the interplay between math anxiety and working memory would influence performance in numerical operations (i.e., math fluency task) and mathematical reasoning (i.e., math reasoning task) in a group of primary school children (N = 202). Results showed that visuospatial working memory appeared to moderate the relationship between math anxiety and math performance when the math fluency task was considered, indicating that participants with higher levels of working memory were more negatively affected by math anxiety. No interaction effect was found for the math reasoning task in which students’ scores were explained only by visuospatial working memory. The findings suggest that math anxiety and visuospatial working memory interact to influence performance in the math fluency task and that this effect may vary depending on the strategies used to complete the task. On the other hand, results on the math reasoning task showed that visuospatial working memory continues to have a positive effect on the math performance independently of math anxiety. The implications in the educational setting are discussed, pointing to the importance of monitoring and intervention studies on affective factors.

Probability estimation in accounting: subjective numeracy matters

PurposeThis study examined subjective numeracy and its relationship with accounting judgements on probability issues.Design/methodology/approachA subjective numeracy scale (SNS) questionnaire was distributed to 231 accounting students to measure self-evaluated numeracy. Modified Bayesian reasoning tasks were applied in an accounting-related probability estimation, manipulating presentation formats.FindingsThe study revealed a positive relationship between self-evaluated numeracy and performance in accounting probability estimation. The findings suggest that switching the format of probability expressions from percentages to frequencies can improve the performance of participants with low self-evaluated numeracy.Research limitations/implicationsAdding objective numeracy measurements could enhance results. Future numeracy research could add objective numeracy items and assess whether this influences participants' self-perceived numeracy. Based on this sample population of accounting students, the findings may not apply to large populations of accounting-information users.Practical implicationsInvestors' ability to exercise sound judgement depends on the accuracy of their probability estimations. Manipulating the format of probability expressions can improve probability estimation performance in investors with low self-evaluated numeracy.Originality/valueThis study identified a significant performance gap among participants in performing accounting probability estimations: those with high self-evaluated numeracy performed better than those with low self-evaluated numeracy. The authors also explored a method other than additional training to improve participants' performance on probability estimation tasks and discovered that frequency formats enhanced the performance of participants with low self-evaluated numeracy.

Deficits in Analytic and Common-Sense Reasoning in Schizophrenia.

Human rationality has a dual nature including analytic and common-sense thinking. Symptoms of schizophrenia have been suggested to be related to deficits in these aspects of logical reasoning. However, empirical studies investigating logical reasoning errors in schizophrenia and their clinical and neurocognitive correlates are scarce. Formal thought disorder and theory of mind (ToM) might be particularly important for understanding logical reasoning errors in schizophrenia. The current study compared the performances of 80 patients with schizophrenia with those of 49 healthy controls on syllogistic and counterfactual reasoning tasks and investigated clinical, neuropsychological, and social cognitive correlates of logical reasoning in schizophrenia. Patients with schizophrenia were impaired in both analytic and common-sense thinking. ToM impairment was a significant predictor of analytic reasoning abilities in schizophrenia. Executive functions and verbal memory were also significantly associated with analytic reasoning in schizophrenia. Further studies investigating logical reasoning errors in the early phases of the illness are needed.

Three-year-old children's reasoning about possibilities

Recent studies in cognitive development suggest that preschoolers may not be able to represent alternative possibilities, and therefore may lack modal concepts such as possible, impossible, and necessary (Leahy & Carey, 2020). We present two experiments adapted from previous probability studies but have a similar logical structure as those used in the previous modal reasoning tasks (Leahy, 2023; Leahy, Huemer, Steele, Alderete, & Carey, 2022; Mody & Carey, 2016). Three-year-old children have to choose between a gumball machine that must produce the desired gumball color and a gumball machine that merely might produce the desired gumball color. Results provide preliminary evidence that three-year-old children can represent multiple incompatible possibilities, and therefore have modal concepts. Implications for the study of modal cognition, and how possibility and probability may be related are discussed.

Edge Computing Task Offloading for Environmental Perception of Autonomous Vehicles in 6G Networks

The most basic requirement for autonomous vehicles is accurate environmental perception. However, the lack of onboard computing resources makes it difficult for such a vehicle to process all environmental information. Through the edge computing technology and 6G networks, vehicles can offload computing tasks to edge servers for execution, which alleviates the problem of insufficient onboard resources. The environmental perception task offloading problem for autonomous vehicles is studied. The purpose is to improve the environmental perception quality through reasonable task offloading. After assigning dynamic priorities to tasks generated by autonomous vehicles, the multi-vehicle and multi-server task offloading process is abstracted as a Markov decision process, and an offloading decision algorithm based on deep reinforcement learning is designed to select edge nodes for task execution to obtain better long-term benefits. The earliest deadline first algorithm is improved to consider the deadline and priority of each task, allowing the edge node to complete more high-priority tasks within the specified time. Experimental results show that the proposed method can guarantee the basic environmental perception requirements of every vehicle, and performs better than existing methods in terms of the total priority of the discarded tasks in each scheduling period and the completion rate of key tasks.

Experimental investigation of training schedule on home-based working memory training in healthy older adults.

The efficacy of working memory training (WMT) for cognitive enhancement in healthy older adults has been extensively investigated. Typically, WMT results in improved performance on the training task, but limited or no transfer of improvement to other cognitive tasks. Accordingly, there is a need to identify optimal intervention parameters to maximize training and transfer task effects of WMT. The current study aimed to investigate the effect of training schedule on training and transfer task performance of WMT in healthy older adults. A secondary aim was to examine the feasibility of participants performing the intervention online at home, unsupervised, and using their personal devices. Participants (N = 71; mean age: 66 years) completed sixteen WMT or active-control sessions over eight (distributed) or four (intensive) weeks. Adaptive verbal and spatial n-back tasks were used as the WMT tasks. We tested near transfer effects to a digit-span task and far transfer effects to an abstract relational reasoning task. Participants successfully performed the cognitively demanding intervention using their own devices, online at home, and with minimal contact with the researcher. We observed a significant improvement in WMT task performance in the WMT group relative to active-controls, but no evidence of near or far transfer. Similar training effects were observed irrespective of the intensity of the training schedule. Our results suggest that comparable benefits could be observed when using less intensive schedules that may be more easily accommodated into everyday life.

Influence of Body Mass Index (BMI) and Blood Pressure (BP) on Deep Brain Stimulation (DBS) Outcomes in Parkinson’s disease (PD) Patients (P4-11.003)

<h3>Objective:</h3> PD literature supports a complex relationship between preoperative obesity, BP abnormalities, and post-DBS cognitive and motor outcomes. This study aims to improve on evidence associating BMI and BP with cognitive, emotional, and quality-of-life outcomes post-DBS. <h3>Background:</h3> Previous studies indicate obesity and hypertension increase intra-/ post-operative complications. Up to 65% of PD patients may be overweight or obese, with obese patients having less axial motor improvement and worsened cognitive function six months post-DBS. PD patients have also demonstrated increased BP fluctuations compared to healthy controls. <h3>Design/Methods:</h3> PD patients [n=28, Mage=62.6(8.8), 75% male, Medu=16.1(3.0), 92.9% STN) underwent pre-/post-DBS assessment (global cognition, language, memory, attention, processing speed, visuospatial ability) and emotional screenings via TeleNP. Systolic (M=130.0; SD=19.5) and diastolic (M=74.4; SD=16.0) BP (SBP, DBP), weight, and height were measured pre-DBS surgery. BMI was computed (M=27.3; SD=6.1). Logistic regression was used to predict neurocognitive performance using BMI, SBP, and DBP. <h3>Results:</h3> BMI, SBP, and DBP predicted decline in verbal reasoning in post-, compared to pre-, DBS testing, but not other assessed domains. Model coefficient estimates of 0.40 [<i>p</i>=.02, OR=1.5 (95% CI [1.07, 2.10])] for BMI, 0.13 [<i>p</i>=.04, OR=1.13 (95% CI [1.01, 1.28])] for SBP, and −0.15 [<i>p</i>=.08, OR=0.86 (95% CI [0.73, 1.02])] for DBP were indicated. Model fit was robust [X²(3)=14.2, <i>p</i>=.003]. While holding BP constant: each unit increase in BMI predicted a 50% increase in odds of verbal reasoning decline (one-half <i>SD</i> or more), and a unit increase in SBP (or decrease in DBP) predicted a 13% increase in odds (or, respectively, a 14% decrease in odds) of verbal reasoning decline. Post-DBS patient classification using BMI and BP predictors yield a .882 specificity and a .857 sensitivity. <h3>Conclusions:</h3> BMI, SBP, and DBP should be considered in predicting DBS surgical outcomes, particularly on verbal reasoning tasks. This small sample requires replication but is consistent with existing literature. <b>Disclosure:</b> Miss See has nothing to disclose. Dr. Harcourt has nothing to disclose. Annelly Buré-Reyes has nothing to disclose. Dr. Rodriguez has nothing to disclose. Dr. Luca has received personal compensation in the range of $5,000-$9,999 for serving as a Consultant for Boston Scientific. Dr. Luca has received personal compensation in the range of $10,000-$49,999 for serving as a Consultant for Signant Health. Jonathan Jagid has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Medtronic Inc. The institution of Jonathan Jagid has received research support from Boston Scientific. The institution of Jonathan Jagid has received research support from Medtronic Inc. Bonnie Levin has nothing to disclose. Ms. Bullock has nothing to disclose. The institution of Dr. Haq has received research support from NINDS. The institution of Dr. Haq has received research support from the Parkinson’s Foundation. The institution of Dr. Haq has received research support from NIMH. Dr. Haq has a non-compensated relationship as a consultant with Medtronics that is relevant to AAN interests or activities. Dr. Haq has a non-compensated relationship as a consultant with Boston Scientific that is relevant to AAN interests or activities. Dr. Haq has a non-compensated relationship as a consultant with Abbott that is relevant to AAN interests or activities. Dr. Sarno has nothing to disclose.

Pengaruh Tugas Kesenjangan Pendapat, Penalaran, dan Informasi terhadap Keterampilan Berbicara

The purpose of this study was to test the effectiveness of applying the three gap tasks, namely the gaps of reasoning, opinion, and information in improving middle-level students' speaking skills. The research method used in this research is quasi-experimental. The research participants totaled 200 students who were divided into two groups, namely experimental and control. Participants were divided into three experimental groups and one control group. The students' initial ability in each group was tested to ensure that the students' initial speaking ability did not differ much. The treatment of the three gap assignments was given to the experimental group. The results showed that the three experimental groups that received the intervention for gaps in reasoning, opinions, and information experienced a more significant increase in their speaking ability than the control group. Improvement of students' speaking skills can be seen from various aspects both verbally and nonverbally. It can be concluded that these three gaps of opinion, reasoning, and information tasks are more effective than traditional methods in improving students' speaking skills. The implication of the research is that teachers can choose these three gap tasks to train students in speaking as well as organize their talk.

Eye Gaze Patterns during Reasoning Provide Insights Regarding Individual Differences in Underlying Cognitive Abilities.

Sequences of eye movements during performance of a reasoning task has provided insights into the strategies individuals use to solve that specific task; however, prior studies have not examined whether eye gaze metrics reflect cognitive abilities in a way that transcends a specific task. Thus, our study aimed to explore the relationship between eye movement sequences and other behavioral measures. Here, we present two studies that related different eye gaze metrics in a matrix reasoning task with performance on a different test of fluid reasoning and tests of planning, working memory, and cognitive flexibility. Additionally, we related gaze metrics to self-reported executive functioning in daily life, as measured by BRIEF-A. To perform this, we classified the participants' eye gaze in each item of the matrices test using an algorithm and then used LASSO regression models with the cognitive abilities as the dependent variable to select eye-tracking metrics to predict it. Overall, specific and distinct eye gaze metrics predicted 57% variance in the fluid reasoning scores; 17% variance in the planning scores; and 18% variance in the working memory scores. Taken together, these results support the hypothesis that the selected eye-tracking metrics reflect cognitive abilities that transcend specific tasks.

Progress Note Understanding — Assessment and Plan Reasoning: Overview of the 2022 N2C2 Track 3 shared task

Daily progress notes are a common note type in the electronic health record (EHR) where healthcare providers document the patient’s daily progress and treatment plans. The EHR is designed to document all the care provided to patients, but it also enables note bloat with extraneous information that distracts from the diagnoses and treatment plans. Applications of natural language processing (NLP) in the EHR is a growing field with the majority of methods in information extraction. Few tasks use NLP methods for downstream diagnostic decision support. We introduced the 2022 National NLP Clinical Challenge (N2C2) Track 3: Progress Note Understanding — Assessment and Plan Reasoning as one step towards a new suite of tasks. The Assessment and Plan Reasoning task focuses on the most critical components of progress notes, Assessment and Plan subsections where health problems and diagnoses are contained. The goal of the task was to develop and evaluate NLP systems that automatically predict causal relations between the overall status of the patient contained in the Assessment section and its relation to each component of the Plan section which contains the diagnoses and treatment plans. The goal of the task was to identify and prioritize diagnoses as the first steps in diagnostic decision support to find the most relevant information in long documents like daily progress notes. We present the results of the 2022 N2C2 Track 3 and provide a description of the data, evaluation, participation and system performance.

Political ideology and environmentalism impair logical reasoning

People are more likely to think statements are valid when they agree with them than when they do not. We conducted four studies analyzing the interference of self-reported ideologies with performance in a syllogistic reasoning task. Study 1 established the task paradigm and demonstrated that participants’ political ideology affects syllogistic reasoning for syllogisms with political content but not politically irrelevant syllogisms. The preregistered Study 2 replicated the effect and showed that incentivizing accuracy did not alleviate these differences. Study 3 revealed that syllogistic reasoning is affected by ideology in the presence and absence of such bonus payments for correctly judging the conclusions’ logical validity. In Study 4, we observed similar effects regarding a different ideological orientation: environmentalism. Again, monetary bonuses did not attenuate these effects. Taken together, the results of four studies highlight the harm of ideology regarding people’s logical reasoning.

Research on resource allocation technology in highly trusted environment of edge computing

Edge computing can use many edge devices to provide users with real-time computing and storage functions. With the development of the Internet of Things (IOT), edge computing is becoming more and more prevalent currently. However, the consequent challenges in search efficiency, reliability requirements and resource allocation appear followed. Therefore, this article focuses on resource allocation and security performance issues. A lightweight trust evaluation mechanism was constructed and time-varying trust coefficients were introduced as incentives to address the problem of distrust between user terminals and edge server entities in multi-cell and multi-user scenarios. This enables the user terminal to immediately distinguish malicious servers. Considering the limited and dynamic changes of computing resources, the problem of complete migration of multi-user tasks was transformed into an issue of computing resource distribution to reduce the total system energy consumption. As a Markov game model, a system was developed to address the problems of centralized single-agent algorithms, including the explosion of action space and difficulty in convergence with increasing the number of users. Besides, a resource allocation algorithm was proposed based on a trust model and multi-agents that follows a centralized training and distributed implementation architecture. The simulated consequences indicated that the proposed algorithm resists malicious attacks, and can quickly make reasonable task migration decisions based on different system states, thereby efficiently decreasing the consumption of the total system energy, and providing a better user experience.

Санітарно-дезінфекційні загони як складова військової медичної служби Другої УНР

The purpose of the article is to identify the place and role of the Sanitary Disinfectant Squads (SDS) in the structure of the military medical service of the Second Ukrainian People’s Republic based on the analysis of archived documents and achievements of historiography. Th e research methodology is based on general scientifi c methods of analysis, synthesis, and systematicity, which, when applying a concrete-historical approach, allows for sig- nifi cantly deepened knowledge about the military medical service of the Second UPR in general and the SDS in particular. Th e scientifi c novelty lies in the fact that based on new archival data, an attempt has been made to comprehensively cover the process of creation, organization, place, and role in the general structure of the SDS of the military medical service of the Seconds UPR. Conclusions. Th e higher state and military leadership of the Second Ukrainian People’s Republic was aware of the importance of a properly formed and eff ective military sanitary service for the successful armed struggle for the preservation of Ukrainian statehood. To overcome the negative consequences of epidemic diseases among the military, as well as for preventive purposes, in January 1919, a decision was made to create eighteen SDS, which were to be subordinated to the MMMD (Main Military Medical Directorate), and in general to the Ministry of Military Aff airs. Unfortunately, due to the deterioration of the military and political situation of the Directorate of the Ukrainian People’s Republic, the legal and organizational registration of this component of the military medical service was delayed until the summer of this year. Th e functioning of the SDS was provided by orders and resolutions that determined their purpose and tasks as well as regulated and explained the activities in organizational and economic terms. In the spring of 1919, during the retreat of the UPR army, part of the SDS was lost. But the restoration and creation during the off ensive of the army of the Ukrainian People’s Republic in the summer of 1919 showed that the Ukrainian military leadership attached great importance to them for the implementation of proper provision of sanitary and epidemic protection of soldiers and offi - cers. Th roughout 1919, the SDS carried out anti-epidemic work among the Ukrainian military. Unfortunately, the SDS could not entirely fulfi l the assigned tasks for objective and subjective reasons. Th e huge scale of the spread of epidemic diseases, the shortage of medicines and equip- ment, as well as the lack of trained personnel, were the most noticeable. In the autumn of the same year, in the conditions of the collapse of the army of the Ukrainian People’s Republic, the SDS ceased to function, but the experience gained came in handy in the last attempt to preserve Ukrainian statehood in the union with Poland in 1920.

A heuristic mixed real-time task allocation of virtual utilization in multi-core processor

Multi-core processor is widely used as the running platform for safety-critical real-time systems such as spacecraft, and various types of real-time tasks are dynamically added at runtime. In order to improve the utilization of multi-core processors and ensure the real-time performance of the system, it is necessary to adopt a reasonable real-time task allocation method, but the existing methods are only for single-core processors or the performance is too low to be applicable. Aiming at the task allocation problem when mixed real-time tasks are dynamically added, we propose a heuristic mixed real-time task allocation algorithm of virtual utilization VU-WF (Virtual Utilization Worst Fit) in multi-core processor. First, a 4-tuple task model is established to describe the fixed-point task and the sporadic task in a unified manner. Then, a VDS (Virtual Deferral Server) for serving execution requests of fixed-point task is constructed and a schedulability test of the mixed task set is derived. Finally, combined with the analysis of VDS's capacity, VU-WF is proposed, which selects cores in ascending order of virtual utilization for the schedulability test. Experiments show that the overall performance of VU-WF is better than available algorithms, not only has a good schedulable ratio and load balancing but also has the lowest runtime overhead. In a 4-core processor, compared with available algorithms of the same schedulability ratio, the load balancing is improved by 73.9%, and the runtime overhead is reduced by 38.3%. In addition, we also develop a visual multi-core mixed task scheduling simulator RT-MCSS (open source) to facilitate the design and verification of multi-core scheduling for users. As the high performance, VU-WF can be widely used in resource-constrained and safety-critical real-time systems, such as spacecraft, self-driving cars, industrial robots, etc.

Sleep health dimensions and shift work as longitudinal predictors of cognitive performance in the UK Biobank cohort.

The long-term effects of sleep health and shift work on cognitive performance are unclear. In addition, research has been limited by small sample sizes and short follow-up periods. We conducted one of the largest examinations of the longitudinal influence of sleep health dimensions and shift work on cognitive performance in people of middle and old age using data from the UK Biobank. The hypothesis was that poor sleep health and shift work would predict lower cognitive performance. Self-reported sleep duration, daytime sleepiness, insomnia symptoms, chronotype and shift work status were assessed as predictors at baseline. Cognitive performance was operationalised by a touchscreen test battery at follow-up between 7.4 ± 2.2 and 9.0 ± 0.9 years after baseline assessment, depending on the specific task. Models were performed for each cognitive domain including relevant confounders (e.g., depression). The alpha level was set at p<0.01 for all analyses. The study sample comprised 9,394 participants for the reasoning task, 30,072 for the reaction time task, 30,236 for the visual memory task, 2,019 for the numeric memory task and 9,476 for the prospective memory task. Shift work without night shifts (ß= -2.0x10- 1 ± 6.5x10- 2, p=0.002) and with night shifts (ß= -1.9x10- 1 ± 7.2x10- 2, p=0.010) predicted a significantly reduced performance in the reasoning task. Short sleep duration (ß= -2.4x10- 1 ± 7.9x10- 2, p=0.003) and shift work without night shifts (ß= -3.9x10- 1 ± 1.2x10- 1, p=0.002) predicted a significantly lower performance in the task probing prospective memory. Our results suggest that, after controlling for confounding variables, shift work and short sleep duration are important predictors for cognitive performance in people of middle and old age. Further work is required to examine causal mechanisms of the observed associations.

The Broad Reach of Multivariable Thinking

Simple explanations are very often inadequate and can encourage faulty inferences. We examined college students’ explanations regarding illegal immigration to determine the prevalence of single-factor explanations. The form of students’ explanations was predicted by their responses on a simple three-item forced-choice multivariable causal reasoning task in which they selected the strongest evidence against a causal claim. In a further qualitative investigation of explanations by a sample of community adults, we identified positive features among those who scored high on this multivariable causal reasoning task. We consider limitations of single-factor reasoning and means of encouraging more comprehensive explanations to support claims.