Task Performance Research Articles

ANALISIS MEDIASI PSYCHOLOGICAL EMPOWERMENT PADA PENGARUH PERCEIVED ORGANIZATIONAL SUPPORT TERHADAP KINERJA KARYAWAN SUPPERDAZZLE YOGYAKARTA

Employee performance research is still popular in various organizations, including for-profit companies. Performance issues are also a concern in Supperdazzle; not all employees consistently meet sales targets, consumer complaints regarding service performance have not been fully handled, tasks are not completed on time, employees are not ready to work according to standard operational procedures. This study is intended to analyze the impact of perceived organizational support (POS) on task performance through psychological empowerment (PE). The research method used is a quantitative method. Researchers determined all 49 SupperDazzle employees as respondents through a questionnaire and analyzed using the classic assumption test and using multiple linear regression. This classic assumption test includes normality, multicollinearity and heteroscedasticity tests. Mediation testing uses the Sobel test. The results showed a positive influence of POS and PE on task performance. The significant influence of POS on PE also has an impact on the mediating role of PE on the influence of POS on task performance. Organizations can strengthen antecedents to improve employee performance.

Studying the Role of Visuospatial Attention in the Multi-Attribute Task Battery II

Task batteries mimicking user tasks are of high heuristic value. Supposedly, they measure individual human aptitude regarding the task in question. However, less is often known about the underlying mechanisms or functions that account for task performance in such complex batteries. This is also true of the Multi-Attribute Task Battery (MATB-II). The MATB-II is a computer display task. It aims to measure human control operations on a flight console. Using the MATB-II and a visual-search task measure of spatial attention, we tested if capture of spatial attention in a bottom-up or top-down way predicted performance in the MATB-II. This is important to understand for questions such as how to implement warning signals on visual displays in human–computer interaction and for what to practice during training of operating with such displays. To measure visuospatial attention, we used both classical task-performance measures (i.e., reaction times and accuracy) as well as novel unobtrusive real-time pupillometry. The latter was done as pupil size covaries with task demands. A large number of analyses showed that: (1) Top-down attention measured before and after the MATB-II was positively correlated. (2) Test-retest reliability was also given for bottom-up attention, but to a smaller degree. As expected, the two spatial attention measures were also negatively correlated with one another. However, (3) neither of the visuospatial attention measures was significantly correlated with overall MATB-II performance, nor with (4) any of the MATB-II subtask performance measures. The latter was true even if the subtask required visuospatial attention (as in the system monitoring task of the MATB-II). (5) Neither did pupillometry predict MATB-II performance, nor performance in any of the MATB-II’s subtasks. Yet, (6) pupil size discriminated between different stages of subtask performance in system monitoring. This finding indicated that temporal segregation of pupil size measures is necessary for their correct interpretation, and that caution is advised regarding average pupil-size measures of task demands across tasks and time points within tasks. Finally, we observed surprising effects of workload (or cognitive load) manipulation on MATB-II performance itself, namely, better performance under high- rather than low-workload conditions. The latter findings imply that the MATB-II itself poses a number of questions about its underlying rationale, besides allowing occasional usage in more applied research.

Characterising the physical demands of critical tasks across the Royal Australian Air Force.

Militaries have historically utilised generic physical fitness tests to assess physical readiness, but there has been a recent shift to develop physical employment standards (PES) based on actual job demands. The purpose of this investigation was to characterise the physical demands of critical tasks performed by Royal Australian Air Force (RAAF) personnel to inform PES development. Job task analysis were performed for 27 RAAF trades. Criterion tasks were identified through a systematic approach involving workshops and field-observations. The identified tasks were assessed for dominant physical capacity and grouped into movement-based clusters. Psychophysiological measures were collected from personnel performing the tasks. Of 87 criterion tasks, 92% were characterised as manual handling dominant. Across these 87 tasks the principal physical capacities were: muscular strength (59%), muscular endurance (52%) and cardiorespiratory endurance (39%). The most common movement clusters were Lift to Platform (44%) and Lift and Carry (38%). Lift to Platform tasks required lifting to a median height of 1.32 m (1.20 -1.65 m) and a median mass of 25.0 kg (21.0 -28.9 kg) per person. Median carry mass was 25.0 kg (22.4 -36.1 kg) per person and distance was 26.0 m (17.5 -50.0 m). Median task mean 'Vdot;O2, HR and RPE were 1.8 L.min-1 (1.5-2.2 L.min-1), 137 b.min-1 (120-144) and 13 (12-14). The high proportion of manual handling criterion tasks emphasises the importance of these activities and the underlying physical capacities for RAAF personnel. Current fitness assessments are unlikely to predict job task performance.

Application of Neural Rehabilitation Manipulator Training in Upper Limb Rehabilitation of Stroke Patients with Hemiplegia

Objective: To analyze the application of neural rehabilitation manipulator training in upper limb rehabilitation of stroke patients with hemiplegia. Methods: 94 patients with hemiplegia after stroke were selected from January 2021 to January 2023. The patients were randomly divided into a control group and an observation group, with 47 cases in each group. The control group received routine rehabilitation training while the observation group received neural rehabilitation manipulator training. The upper limb and nerve function, daily task performance ability, quality of life, and rehabilitation training satisfaction were compared between the two groups. Results: There was no significant difference in upper limb and nerve function between the two groups before training, P > 0.05. After training, the observation group had 51.45 ± 8.75 points in ARAT and 52.59 ± 8.48 points in FMA-UE, which were higher than those in the control group with 43.81 ± 6.67 points and 45.51 ± 7.31 points respectively, P < 0.05. The observation group had 5.71 ± 1.53 points in NIHSS, which was lower than those in the control group with 8.04 ± 2.39 points, P < 0.05. In terms of daily task performance ability and quality of life, there was no significant difference between the two groups before training, P > 0.05. After training, the observation group had 78.54 ± 10.63 scores in MBI and 171.93 ± 19.12 scores in SS-QOL, which were higher than those in the control group with 70.51 ± 9.25 scores and 160.13 ± 18.42 scores respectively, P < 0.05. In terms of satisfaction, the total satisfaction rate of the observation group was 93.62%, which was higher than that of the control group with 74.47%, P < 0.05. Conclusion: The application of neural rehabilitation manipulator training in the upper limb rehabilitation of stroke patients with hemiplegia can significantly improve the upper limb function of patients, relieve nerve defects, improve daily task performance ability and quality of life, and increase patient satisfaction with rehabilitation training.

Time perspectives and collaborative performance in creative tasks

PurposeThe relationship between variation in time perspectives and collaborative performance is scarcely explored, and even less is known about the respective mechanisms that lead to varying task performance. Thus, we aim to further the literature on time perspectives and collaborative performance, shedding light on the underlying behavioral patterns.Design/methodology/approachWe report a quasi-experiment analyzing the impact of past, present and future orientation variation in dyads (N = 76) on their quantitative and qualitative performance when confronted with a simple incentivized creative task with constraints. Subsequently, we offer a qualitative analysis of comments given by the participants after the task on the collaboration.FindingsResults indicate that a dyad's elevation of past orientation and diversity in future orientation negatively affect collaborative performance. At the same time, there is a positive effect of elevation of future orientation. The positive effect is driven by clear communication and agreement during the task, while the negative effect arises from work sharing and complementation.Practical implicationsThis study provides insights for organizations on composing individuals regarding their temporal focus for collaborative tasks that should be executed rapidly and require creative solutions.Originality/valueOur study distinguishes by considering the composition of past, present and future time perspectives in dyads and focuses on a creative task setting. Moreover, we explore the mechanisms in the dyads with a substantial elevation of/diversity in future orientation, leading to their stronger/weaker performance.

Dynamic Classification Ensembles for Handling Imbalanced Multiclass Drifted Data Streams

Machine learning models often encounter significant difficulties when dealing with multiclass imbalanced data streams in nonstationary environments. These challenges can lead to biased and unreliable predictions, which ultimately impact the overall performance of the models. To address these issues, we propose an innovative approach that integrates dynamic ensemble selection, an adaptive technique for managing imbalanced multiclass data streams, with a concept drift detector for recognizing stream changes and the K-nearest neighbor (KNN) algorithm to tackle issues related to class overlap. The primary objective was to improve the classification of imbalanced multiclass drifted data streams. The adaptive oversampling method generates synthetic samples to mitigate the issues associated with imbalanced data streams. This method utilizes KNN to ensure that the generated samples do not overlap. To handle incoming data streams, a drift detector assists in deciding whether to retain the existing classifiers or create a new one. Dynamic Ensemble Selection (DES) was utilized to select the most appropriate classifier for incoming data, aiming to optimize the performance of the classification task. The proposed method offers an effective solution for achieving an accurate and resilient classification in the context of imbalanced multiclass drifted data streams. To evaluate the effectiveness of our proposal, we conducted experiments on a variety of datasets, including benchmark datasets, real application stream datasets, and synthetic data streams. The experimental results demonstrate the superiority of our contribution in addressing the challenges posed by imbalanced multiclass drifted data streams.

Cooperation of The National Police of Ukraine with civil society on the basis of partnership under the conditions of the state of martial

The article examines the prospects for the interaction of the National Police of Ukraine with the population on the basis of partnership under martial law and analyzes the recently implemented projects, the purpose of which is the effective implementation of the tasks assigned by the state, primarily related to the protection of the highest values of the state, which include man and his rights and freedom. It is emphasized that the introduction of martial law in Ukraine requires not only the solution of tasks related to the introduction and implementation of measures of the legal regime of martial law, since in the course of repelling armed aggression against Ukraine, police bodies participate in the performance of territorial defense tasks, carry out increased patrolling, escort appropriate cargoes, protection of property of victims, protection of destruction sites, delivery of offenders, restriction of traffic on dangerous routes, conducting exercises with representatives of the population, etc. The main problems that arise during the interaction of the National Police with the population at the current stage under the conditions of the legal regime of martial law in Ukraine are highlighted, the ways to solve them are outlined, it is proposed to develop a normative legal act on the organization of the interaction of the police with the population, in which the goal should be fixed interactions, tasks, define individual concepts, define subjects and heads of interaction bodies, types and forms of interaction, features of mutual information, channels of information transmission, methods and deadlines for checking the effectiveness of interaction, determine principles, as well as directions of interaction in the conditions of the legal regime of military state in Ukraine.
 It is concluded that the legal regulation of the interaction of the National Police bodies with the population under the conditions of the legal regime of martial law in Ukraine should be understood as the system of legal means (elements), the totality of techniques and methods of legal influence on social relations that arise during such interaction, with the help of which a complex of organizational and special measures aimed at protection against illegal encroachments, as well as ensuring the personal safety of citizens, countering offenses is defined.

Development and analysis of medical instruction-tuning for Japanese large language models

In the ongoing wave of impact driven by large language models (LLMs) like ChatGPT, the adaptation of LLMs to the medical domain has emerged as a crucial research frontier. Since mainstream LLMs tend to be designed for general-purpose applications, constructing a medical LLM through domain adaptation is a huge challenge. While instruction-tuning, particularly based on low-rank adaptation (LoRA), has become a frequently employed strategy to fine-tune LLMs recently, its precise roles in domain adaptation remain unknown. Here, we investigated how LoRA-based instruction-tuning improves the performance of Japanese medical question-answering tasks by employing a multifaceted evaluation of multiple-choice questions, including scoring based on “Exact match” and “Gestalt distance” in addition to the conventional accuracy. Our findings suggest that LoRA-based instruction-tuning can partially incorporate domain-specific knowledge into LLMs, with larger models demonstrating more pronounced effects. Furthermore, our results underscore the potential of adapting English-centric models for Japanese applications in domain adaptation, while also highlighting the persisting limitations of Japanese-centric models. This initiative represents a pioneering effort in enabling medical institutions to fine-tune and operate models without relying on external services.

Analysis of reading-task-based brain connectivity in dyslexic children using EEG signals.

Developmental dyslexia, a neurodevelopment reading disorder, can impact even children with average intelligence. The present study examined the brain connectivity in dyslexic and control children during the reading task using graph theory. 19-channel electroencephalogram (EEG) signals were recorded from 15 dyslexic children and 15 control children. Functional connectivity was estimated by measuring the EEG coherence at 19 electrode locations, and graph measures were calculated using the graph theory method. Reading task results identified deprived task performance in dyslexic children against controls. Graph measures revealed longer path length, reduced clustering coefficient and reduced network efficiencies (in theta and alpha bands) of dyslexic group. At the nodal level, we found a significant increase in delta strength (T4 and T5 electrode locations) and reduced strength in theta (T6, P4, Fp1, F8 and F3) and alpha bands (T4, T3, P4 and F3) during the reading task in dyslexic group. In conclusion, the present study identified distinct graph measures between groups when performing a reading task and showed possible evidence for compromised brain networks in dyslexic group.

Ecological validity of common behavioral decision making tasks: evidence across two samples

ABSTRACT Background Clinicians and scholars routinely use behavioral decision tasks to assess real-world decision making capabilities. However, many common behavioral decision making tasks lack data on the extent to which they predict real-world risky behaviors. Across two pre-registered studies, and two timepoints, we assessed decision making abilities using common behavioral tasks and predicted participants’ real-world risky decision making from task performance. Method In Study 1, 918 Mechanical Turk (MTurk) workers completed three decision making tasks in addition to assessments of real-world risk behavior: preventive health behaviors, COVID-19 vaccination status, and virtual social distancing task performance. In Study 2, 221 college student participants completed the Study 1 tasks plus additional assessments of decision making and real world risk and protective behaviors. Results Across both studies, the selected behavioral decision tasks rarely predicted real world behavior and, when they did, the relationship was weak at best. Conclusions These data suggest that these behavioral decision making tasks may not be good predictors of real world risky behavior at present, with some evidence that the specificity of the behavior being assessed matters (i.e. the closer the task was to the specific behavior being predicted), calling for additional ecological validity research, with a greater variety of tasks in the future.

Therapeutic Chatbots as Cognitive-Affective Artifacts

AbstractConversational Artificial Intelligence (CAI) systems (also known as AI “chatbots”) are among the most promising examples of the use of technology in mental health care. With already millions of users worldwide, CAI is likely to change the landscape of psychological help. Most researchers agree that existing CAIs are not “digital therapists” and using them is not a substitute for psychotherapy delivered by a human. But if they are not therapists, what are they, and what role can they play in mental health care? To answer these questions, we appeal to two well-established and widely discussed concepts: cognitive and affective artifacts. Cognitive artifacts are artificial devices contributing functionally to the performance of a cognitive task. Affective artifacts are objects which have the capacity to alter subjects’ affective state. We argue that therapeutic CAIs are a kind of cognitive-affective artifacts which contribute to positive therapeutic change by (i) simulating a (quasi-)therapeutic interaction, (ii) supporting the performance of cognitive tasks, and (iii) altering the affective condition of their users. This sheds new light on why virtually all existing mental health CAIs implement principles and techniques of Cognitive Behavioral Therapy — a therapeutic orientation according to which affective change and, ultimately, positive therapeutic change is mediated by cognitive change. Simultaneously, it allows us to conceptualize better the potential and limitations of applying these technologies in therapy.

Graph analysis of functional brain networks under varying working memory load: An EEG-based minimum spanning tree approach

Conventional graph theory approach implemented in prior studies to understand brain topology during performance of cognitive tasks is biased and limits comparison of results across studies. This study employed minimum spanning tree (MST) analysis, an unbiased approach, to quantify changes in brain network organization under varying working memory (WM) load. We used 28-channel electroencephalography dataset of 26 subjects performing cognitive (0-, 2- and 3-back) tasks. We computed functional connectivity across channels using weighted phase lag index (wPLI) in multiple frequency bands and constructed MSTs of brain networks under varying WM conditions. Results reveal 0- back had significantly higher parietal alpha wPLI, lower frontal theta wPLI and lower central theta wPLI, than other conditions. In theta band, we observed more star-like topology in 0- back condition than 2- back or 3- back conditions. Our findings suggest sensitivity of these metrics to alterations in brain network topology under varying cognitive demand.

Timing along the cardiac cycle modulates neural signals of reward-based learning

Natural fluctuations in cardiac activity modulate brain activity associated with sensory stimuli, as well as perceptual decisions about low magnitude, near-threshold stimuli. However, little is known about the relationship between fluctuations in heart activity and other internal representations. Here we investigate whether the cardiac cycle relates to learning-related internal representations – absolute and signed prediction errors. We combined machine learning techniques with electroencephalography with both simple, direct indices of task performance and computational model-derived indices of learning. Our results demonstrate that just as people are more sensitive to low magnitude, near-threshold sensory stimuli in certain cardiac phases, so are they more sensitive to low magnitude absolute prediction errors in the same cycles. However, this occurs even when the low magnitude prediction errors are associated with clearly suprathreshold sensory events. In addition, participants exhibiting stronger differences in their prediction error representations between cardiac cycles exhibited higher learning rates and greater task accuracy.

An exploratory, randomised, crossover study to investigate the effect of nicotine on cognitive function in healthy adult smokers who use an electronic cigarette after a period of smoking abstinence

BackgroundAs well as being associated with serious negative health outcomes, smoking has been reported to have an array of physiological and psychological effects, including effects on mood and cognitive function. Post-cessation, loss of such effects (including temporary deficits in cognitive function) have been cited as reasons for resumption of smoking. The effects of e-cigarettes and nicotine delivered by e-cigarettes on these functions have not been widely researched but may play a role in the effectiveness of e-cigarettes as a satisfactory alternative to combustible cigarettes for people who smoke, and in encouraging individuals who would otherwise continue to smoke, to transition to e-cigarettes.MethodsThe study was an exploratory, randomised, partially-blinded, single-centre, five-arm crossover trial that recruited 40 healthy male and female people who smoke. At 5 study sessions, following a 12-h period of nicotine abstinence, participants were randomly assigned to use either a combustible cigarette, an e-cigarette of three varying nicotine strengths (18 mg/mL, 12 mg/mL or 0 mg/mL respectively) or observe a no product usage session. Participants completed pre- and post-product usage assessments to examine the product usage effect on cognitive performance (using the Cambridge Neuropsychological Test Automated Battery (CANTAB)), subjective mood and smoking urges.ResultsA significant improvement in sustained attention task performance was observed following use of both the nicotine containing e-cigarettes and combustible cigarette compared to no product use. Additionally, there were no significant differences between the nicotine containing products, indicating that nicotine use enhanced sustained attention regardless of delivery format. Nicotine containing e-cigarette and combustible cigarette use also significantly improved overall mood of participants compared to no product use, with no significant differences observed between the nicotine containing products. Nicotine containing e-cigarette and combustible cigarette use significantly reduced smoking urges compared to no product use, though combustible cigarette use elicited the greatest reduction in smoking urges.ConclusionsOverall, the nicotine containing products improved sustained attention and mood while reducing smoking urges, with the studied e-cigarettes having comparable effects to combustible cigarettes across the assessed cognitive parameters and mood measures. These results demonstrate the potential role of e-cigarettes to provide an acceptable alternative for combustible cigarettes among people who would otherwise continue to smoke.Trial registration ISRCTN (identifier: ISRCTN35376793).

Motivation and emotional distraction interact and affect executive functions

Previous research on cool-hot executive function (EF) interactions has examined the effects of motivation and emotional distraction on cool EF separately, focusing on one EF component at a time. Although both incentives and emotional distractors have been shown to modulate attention, how they interact and affect cool EF processes is still unclear. Here, we used an experimental paradigm that manipulated updating, inhibition, and shifting demands to determine the interactions of motivation and emotional distraction in the context of cool EF. Forty-five young adults (16 males, 29 females) completed the go/no-go (inhibition), two-back (updating), and task-switching (shifting) tasks. Monetary incentives were implemented to manipulate motivation, and task-irrelevant threatening or neutral faces were presented before the target stimulus to manipulate emotional distraction. We found that incentives significantly improved no-go accuracy, two-back accuracy, and reaction time (RT) switch cost. While emotional distractors had no significant effects on overall task performance, they abolished the incentive effects on no-go accuracy and RT switch cost. Altogether, these findings suggest that motivation and emotional distraction interact in the context of cool EF. Specifically, transient emotional distraction disrupts the upregulation of control activated by incentives. The present investigation has advanced knowledge about the relationship between cool and hot EF and highlights the importance of considering motivation–emotion interactions for a fuller understanding of control.

Two are better than one: Differences in cortical EEG patterns during auditory and visual verbal working memory processing between Unilateral and Bilateral Cochlear Implanted children

Despite the proven effectiveness of cochlear implant (CI) in the hearing restoration of deaf or hard-of-hearing (DHH) children, to date, extreme variability in verbal working memory (VWM) abilities is observed in both unilateral and bilateral CI user children (CIs). Although clinical experience has long observed deficits in this fundamental executive function in CIs, the cause to date is still unknown. Here, we have set out to investigate differences in brain functioning regarding the impact of monaural and binaural listening in CIs compared with normal hearing (NH) peers during a three-level difficulty n-back task undertaken in two sensory modalities (auditory and visual). The objective of this pioneering study was to identify electroencephalographic (EEG) marker pattern differences in visual and auditory VWM performances in CIs compared to NH peers and possible differences between unilateral cochlear implant (UCI) and bilateral cochlear implant (BCI) users. The main results revealed differences in theta and gamma EEG bands. Compared with hearing controls and BCIs, UCIs showed hypoactivation of theta in the frontal area during the most complex condition of the auditory task and a correlation of the same activation with VWM performance. Hypoactivation in theta was also observed, again for UCIs, in the left hemisphere when compared to BCIs and in the gamma band in UCIs compared to both BCIs and NHs. For the latter two, a correlation was found between left hemispheric gamma oscillation and performance in the audio task. These findings, discussed in the light of recent research, suggest that unilateral CI is deficient in supporting auditory VWM in DHH. At the same time, bilateral CI would allow the DHH child to approach the VWM benchmark for NH children. The present study suggests the possible effectiveness of EEG in supporting, through a targeted approach, the diagnosis and rehabilitation of VWM in DHH children.

Effectiveness of stress arousal reappraisal and stress-is-enhancing mindset interventions on task performance outcomes: a meta-analysis of randomized controlled trials

Stress arousal reappraisal (SAR) and stress-is-enhancing (SIE) mindset interventions aim to promote a more adaptive stress response by educating individuals about the functionality of stress. As part of this framework, an adaptive stress response is coupled with improved performance on stressful tasks. The goal of this meta-analysis is to evaluate the effectiveness of these interventions on task performance. The literature search yielded 44 effect sizes, and a random-effects model with Knapp-Hartung adjustment was used to pool them. The results revealed an overall small significant improvement in task performance (d = 0.23, p < 0.001). The effect size was significantly larger for mixed interventions (i.e., SAR/SIE mindset instructions combined with additional content, k = 5, d = 0.45, p = 0.004) than SAR-only interventions (k = 33, d = 0.22, p < 0.001) and SIE mindset-only interventions (k = 6, d = 0.18, p = 0.22) and tended to be larger for public performance tasks than cognitive written tasks (k = 14, d = 0.34, p < 0.001 vs. k = 30, d = 0.20, p = 0.002). Although SAR and SIE mindset interventions are not “silver bullets”, they offer a promising cost-effective low-threshold approach to improve performance across various domains.

Information-based rhythmic transcranial magnetic stimulation to accelerate learning during auditory working memory training: a proof-of-concept study.

Rhythmic transcranial magnetic stimulation (rhTMS) has been shown to enhance auditory working memory manipulation, specifically by boosting theta oscillatory power in the dorsal auditory pathway during task performance. It remains unclear whether these enhancements (i) persist beyond the period of stimulation, (ii) if they can accelerate learning and (iii) if they would accumulate over several days of stimulation. In the present study, we investigated the lasting behavioral and electrophysiological effects of applying rhTMS over the left intraparietal sulcus (IPS) throughout the course of seven sessions of cognitive training on an auditory working memory task. A limited sample of 14 neurologically healthy participants took part in the training protocol with an auditory working memory task while being stimulated with either theta (5 Hz) rhTMS or sham TMS. Electroencephalography (EEG) was recorded before, throughout five training sessions and after the end of training to assess to effects of rhTMS on behavioral performance and on oscillatory entrainment of the dorsal auditory network. We show that this combined approach enhances theta oscillatory activity within the fronto-parietal network and causes improvements in auditoryworking memory performance. We show that compared to individuals who received sham stimulation, cognitive training can be accelerated when combined with optimized rhTMS, and that task performance benefits can outlast the training period by ∼ 3 days. Furthermore, we show that there is increased theta oscillatory power within the recruited dorsal auditory network during training, and that sustained EEG changes can be observed ∼ 3 days following stimulation. The present study, while underpowered for definitive statistical analyses, serves to improve our understanding of the causal dynamic interactions supporting auditory working memory. Our results constitute an important proof of concept for the potential translational impact of non-invasive brain stimulation protocols and provide preliminary data for developing optimized rhTMS and training protocols that could be implemented in clinical populations.

Effects of triceps surae exercise-induced delayed onset muscle soreness on control of body stability in different postures

This research aimed to determine whether triceps surae delayed onset muscle soreness (DOMS) affects stability while performing different postural control tasks requiring upright and landing stabilization. Twenty-four participants who self-reported as healthy were recruited. Pre and 48 h after a protocol to induce DOMS in the triceps surae, participants were evaluated for DOMS perception, pressure pain threshold, and postural control (assessed by the center of pressure, CoP) during different standing and landing stabilization tasks. We found higher DOMS perception and lower pressure pain threshold 48 h after the exercise. Mediolateral CoP displacement was more sensitive to DOMS across different postural tasks, but no effects were found for bilateral standing. The landing time to stabilization elicited high individual variability in the presence of DOMS. Effects of DOMS in the performance of less challenging tasks, such as bipedal standing, were not found. We conclude that DOMS in the triceps surae impairs mediolateral postural control during challenging tasks such as unilateral standing and body forward lean. It highlights the need for caution and individualized approaches when incorporating movements requiring frontal plane control in training and rehabilitation sessions under the presence of DOMS.

Dual-channel deep graph convolutional neural networks.

The dual-channel graph convolutional neural networks based on hybrid features jointly model the different features of networks, so that the features can learn each other and improve the performance of various subsequent machine learning tasks. However, current dual-channel graph convolutional neural networks are limited by the number of convolution layers, which hinders the performance improvement of the models. Graph convolutional neural networks superimpose multi-layer graph convolution operations, which would occur in smoothing phenomena, resulting in performance decreasing as the increasing number of graph convolutional layers. Inspired by the success of residual connections on convolutional neural networks, this paper applies residual connections to dual-channel graph convolutional neural networks, and increases the depth of dual-channel graph convolutional neural networks. Thus, a dual-channel deep graph convolutional neural network (D2GCN) is proposed, which can effectively avoid over-smoothing and improve model performance. D2GCN is verified on CiteSeer, DBLP, and SDBLP datasets, the results show that D2GCN performs better than the comparison algorithms used in node classification tasks.