Task Performance and Analysis - Science topic

In the context of Industry 4.0, occupational safety faces new challenges with the integration of advanced technologies such as automation, artificial intelligence, robotics, the Internet of Things (IoT), and cyber-physical systems. While these technologies offer significant benefits, they also introduce complex safety risks that must be managed eff...

Body composition refers to the amount and distribution of fat, muscle, bone, and other tissues in the body. It is associated with the risk of, for example, type 2 diabetes (T2D) and cardiovascular disease (CVD). Computed tomography (CT) is an imaging modality that provides detailed internal views, making it a valuable tool for body composition anal...

Individuals' thoughts often wander during sustained performance tasks, particularly when the task at hand is understimulating and monotonous (Smallwood & Schooler, 2015). Often, these episodes are directed towards segments of music that are recalled involuntarily, or "earworms" (Halpern & Bartlett, 2011). While earworms are a normal phenomenon in m...

Mixture-of-Experts (MoE) is widely adopted to deploy Large Language Models (LLMs) on edge devices with limited memory budgets. Although MoE is, in theory, an inborn memory-friendly architecture requiring only a few activated experts to reside in the memory for inference, current MoE architectures cannot effectively fulfill this advantage and will y...

Stabilizing the upright posture of the trunk relies on vestibular and proprioceptive afference. Previous studies found that the feedback responses to sensory afference vary between postures and tasks. We investigated whether and how vestibular and proprioceptive afference contribute to trunk stabilization during different postural tasks, and during...

Multitasking is essential for facing the complexity of everyday life environments, where the simultaneous processing of multiple information streams is ubiquitous, and it often requires an increased deployment of attentional resources to manage concurrent tasks. The physiological cognitive decline associated with aging further depletes cognitive re...

Executive functioning (EF) is an important developing self‐regulatory process that has implications for academic, social, and emotional outcomes. Most work in EF has focused on childhood, and less has examined the development of EF throughout adolescence and into emerging adulthood. The present study assessed longitudinal trajectories of EF from ag...

This study explores the employment of metacognitive strategies (MSs) and their transfer from reading to writing. It investigated fifteen (15) randomly selected Moroccan EFL university freshmen’s use and transfer of MSs in before, amidst and after task completion. It also sought to explore the association between MS transfer and task outcome. With f...

Countless biological processes are fueled by energy-rich molecules like ATP and GTP that supply energy with extreme efficiency. However, designing similar energy-delivery schemes from the bottom up, essential for the development of powered nanostructures and other {\it de novo} machinery, presents a significant challenge: how can an energy-rich str...

Recurrent spiking neural networks (RSNNs) can be implemented very efficiently in neuromorphic systems. Nevertheless, training of these models with powerful gradient-based learning algorithms is mostly performed on standard digital hardware using Backpropagation through time (BPTT). However, BPTT has substantial limitations. It does not permit onlin...

This study is the first to explore the interplay between haptic interaction and avatar representation in Shared Virtual Environments (SVEs). Specifically, how these factors shape users' sense of social presence during dyadic collaborations, while assessing potential effects on task performance. In a series of experiments, participants performed the...

Assistive teleoperation, where control is shared between a human and a robot, enables efficient and intuitive human-robot collaboration in diverse and unstructured environments. A central challenge in real-world assistive teleoperation is for the robot to infer a wide range of human intentions from user control inputs and to assist users with corre...

Endowing robots with tool design abilities is critical for enabling them to solve complex manipulation tasks that would otherwise be intractable. While recent generative frameworks can automatically synthesize task settings, such as 3D scenes and reward functions, they have not yet addressed the challenge of tool-use scenarios. Simply retrieving hu...

Background Traumatic injuries are a significant contributor to pediatric morbidity and mortality, and trauma care necessitates that providers from different specialties and backgrounds be prepared to work together in high acuity settings to provide optimal care. Simulation-based trauma education consistently demonstrates improved knowledge, skill a...

This paper focuses on the problem of collaborative task execution by teams comprising of people and multiple heterogeneous robots. In particular, the problem is motivated by the need for the team members to dynamically coordinate their execution, in order to avoid overlapping actions (i.e. multiple team members working on the same part of the task)...

We present VOICE, a novel approach to science communication that connects large language models' conversational capabilities with interactive exploratory visualization. VOICE introduces several innovative technical contributions that drive our conversational visualization framework. Based on the collected design requirements, we introduce a two-lay...

The development of finger-worn haptic devices requires careful consideration of weight-related design trade-offs. Increased functionality commonly results in additional device weight, potentially burdening the wearer and impairing finger dexterity. Despite the importance of weight in design considerations, the field lacks criteria for acceptable de...

Can we trust AI? It is a question that is asked with increasing frequency and urgency as artificial intelligence becomes ever more adept at performing tasks hitherto performed almost exclusively by human beings. There are certainly reasons to be cautious, among which is the problem of understanding the inner workings of AI. Adapting themselves thro...

Studies of cognitive control using tasks with isolated (single-item) versus multiple (multi-item) item presentation have shown that multi-item tasks may be more effective in capturing limitations of the cognitive control system arising from capacity constraints. Importantly, during multi-item tasks, performance decreases but does not collapse, cons...

(1) Background: This study aimed to assess whether older adults exhibit greater discrepancies between intended and actual motor unit recruitment, which could affect the quality of muscle activation and potentially increase the risk of falls. (2) Methods: Forty-eight physically active older women were assessed (65 ± 6 years, 164 ± 6 cm, and 76 ± 7 k...

Objective To explore the effects of postural control and cognition interference on cortical activation during balance tasks in stroke patients. Methods fNIRS was used to measure cortical activation in the SMC, PMC, and PFC in 30 subjects with supratentorial stroke while performing a postural single task (PST), cognitive single task (CST), and post...

Explainability features are intended to provide insight into the internal mechanisms of an AI device, but there is a lack of evaluation techniques for assessing the quality of provided explanations. We propose a framework to assess and report explainable AI features. Our evaluation framework for AI explainability is based on four criteria: 1) Consi...

Although ingratiation is a tactic widely adopted by subordinates to influence supervisors, findings on its effectiveness are mixed at best. Drawing upon advancements in attribution theory, we propose a dual-pathway model to explicate the supervisor attributional processes triggered by newcomer ingratiation. On the one hand, supervisors engage in su...

As automation becomes increasingly integrated into complex military tasks, its role in supporting human performance under fatigue warrants careful evaluation. A specific military use case in which automatic target cuing (ATC) is integrated is undersea threat detection (UTD). These types of tasks demand sustained vigilance, accurate classification,...

Scaling test time compute has shown remarkable success in improving the reasoning abilities of large language models (LLMs). In this work, we conduct the first systematic exploration of applying test-time scaling methods to language agents and investigate the extent to which it improves their effectiveness. Specifically, we explore different test-t...

State-space models (SSMs) have recently gained attention in deep learning for their ability to efficiently model long-range dependencies, making them promising candidates for edge-AI applications. In this paper, we analyze the effects of quantization on small-scale SSMs with a focus on reducing memory and computational costs while maintaining task...

Previous research has demonstrated that children’s execution of actions consistent with their thinking can enhance cognitive processes. However, it remains unclear whether observing others performing actions consistent with thinking has a similar facilitative effect. In Experiment 1, we compared children’s accuracy and reaction times in an observat...

Neurophysiological evidence suggests that bilinguals show reduced emotional response when reading or producing negative words in their second (L2) relative to their native (L1) language (e.g., Jończyk et al. 2016, 2024; Wu and Thierry, 2012; Zhang et al. 2023). However, little is known about the neural oscillatory dynamics of comprehending and prod...

As digital systems become increasingly integrated into daily life, designing user experiences that go beyond functionality to recognize and adapt to emotional states is gaining importance. Affective computing-an interdisciplinary field that combines computer science, psychology, and cognitive science-enables systems to detect, interpret, and respon...

Introduction. The use of robots is becoming increasingly prevalent each year. Simultaneously, there is a gradual shift from using individual robots to deploying collective robots, as this approach proves to be more efficient for various tasks such as agricultural surveys and irrigation. However, there are specific challenges, particularly the lack...

Extended exposure to virtual reality environments can induce motion sickness, often referred to as cybersickness, which may lead to physiological stress responses and impaired cognitive performance. This study investigates the aftereffects of VR-induced motion sickness with a focus on physiological stress markers and working memory performance. Usi...

In recent years, deep discrete representation learning (DRL) has achieved significant success across various domains. Most DRL frameworks (e.g., the widely used VQ-VAE and its variants) have primarily focused on generative settings, where the quality of a representation is implicitly gauged by the fidelity of its generation. In fact, the goodness o...

Thanks to the push towards sustainable energy, modern electric networks are witnessing the spread of photovoltaic and wind renewable sources, which are the main responsible for the great and great diffusion of converter-interfaced distributed generators. The number of these converter-interfaced sources is increasing at such a level that it is havin...

Constant connectivity through smartphone use represents a major societal challenge, particularly in relation to work performance and work–nonwork boundaries. This research leverages an interdisciplinary theoretical framework, crisis settings, and a cross‐cultural approach (France and the United Kingdom) to specify the impacts of smartphone use on w...

Various approaches have been studied to solve the path planning problem of a mobile robot designing with multiple tasks. However, safe operation for a mobile robot in dynamic environments remains a challenging problem. This paper focuses on safe path planning for a mobile robot executing multiple tasks in an environment with randomly moving humans....

Large Language Models (LLMs) are increasingly used for synthetic tabular data generation through in-context learning (ICL), offering a practical solution for data augmentation in data scarce scenarios. While prior work has shown the potential of LLMs to improve downstream task performance through augmenting underrepresented groups, these benefits o...

Background Manual therapy, including high-velocity low-amplitude spinal manipulation (HVLA-SM), is a complex motor task performed by trained individuals. The ability to modulate the magnitude of applied forces is an attribute of proficiency that is challenging for providers and students. Adopting different biomechanical strategies may facilitate fo...

Machine Deploying machine learning (ML) on microcontroller-class hardware introduces unique challenges due to limitations in memory, computation, and power. This is particularly critical in health monitoring systems, where timely and accurate oxygen dynamics prediction is essential. This systematic review evaluates the use of ML techniques on micro...

Quadruped robots have made significant advances in locomotion, extending their capabilities from controlled environments to real-world applications. Beyond movement, recent work has explored loco-manipulation using the legs to perform tasks such as pressing buttons or opening doors. While these efforts demonstrate the feasibility of leg-based manip...

This article investigates the integration of the Internet of Things (IoT), digital twin (DT), and augmented reality (AR) technologies to advance digital services in the management, monitoring, and control of agricultural greenhouses, addressing the sector's technological demands. By leveraging advanced technologies, this research aims to enhance ef...

Objective Pharmacogenomics can optimize therapeutic outcomes while minimizing adverse events. However, barriers like the lack of trained healthcare professionals impede its widespread adoption. To address this challenge, we developed the PharMe app to return pharmacogenomic results to patients, facilitated by Anni, a custom annotation interface. M...

The introductory programming course (CS1) at the university level is often perceived as particularly challenging, contributing to high dropout rates among Computer Science students. Identifying when and how students encounter difficulties in this course is critical for providing targeted support. This study explores the behavioral patterns of CS1 s...

Virtual hand representation in Head-Mounted Displays (HMDs) offers immersive and intuitive interactions in Virtual Reality (VR). However, current hand tracking algorithms are prone to errors, which can disrupt the user experience and hinder task performance. This paper presents a novel method for providing users with visual feedback when the qualit...

Extended reality (XR) environments, such as simulators, augmented reality, and virtual reality are major techniques in contemporary AI and entertainment systems. Cybersickness (CS) is a motion-sickness experienced by many users of XR. CS causes debilitating nausea, disorientation, and oculomotor issues. Treatment and prevention for motion-sickness...

There is increasing interest in self-efficacy (SE) as a variable to predict learner behavior during tasks, but many tasks involve learners working collaboratively in groups. Collective efficacy (CE) can be used to assess the feelings of the group about their overall ability to complete a task. It has been largely ignored in the field of second lang...

INTRODUCTION Complex perceptual discrimination is supported by tau‐vulnerable regions of the medial temporal lobe (MTL); notably the perirhinal cortex. This research tests whether there is a gene‐dose effect of apolipoprotein E (APOE) e4 on perceptual discrimination in mid‐life. METHODS Three hundred and thirteen adults (45–65 years; grouped by AP...

The objective of this study was to establish a predictive equation that expresses the daily work exposure as a function of variables that define complex work tasks. The equation was verified with data reported in reviewed publications. The ScienceDirect, PubMed, and ProQuest databases were searched using keywords related to variables that character...

Few hospitals in Japan have pharmacists stationed in secondary emergency rooms, and there are limited reports on their roles. This study aimed to investigate the activities of pharmacists in the secondary emergency rooms of Fukuoka Tokushukai Hospital, in addition to providing drug-related information to other healthcare professionals. The study ex...

Background For People with Parkinson's (PwP), motor disturbances affecting the dominant upper extremity often impacts ability to perform tasks such as writing or typing and may confound cognitive test performances with graphomotor responding. Objectives We explored association between upper extremity impairment and graphomotor cognitive test perfo...

Parameter Efficient Fine-Tuning (PEFT) methods have emerged as effective and promising approaches for fine-tuning pre-trained language models. Compared with Full parameter Fine-Tuning (FFT), PEFT achieved comparable task performance with a substantial reduction of trainable parameters, which largely saved the training and storage costs. However, us...

The emergence of prosocial tendencies in early childhood is still not well understood and not commonly tested with direct measures. This study investigated predictors of prosocial behavior (i.e., prosocial decision-making and prosocial creativity) in 3-to-5-year-old children and explored the role of demographic factors on empathy and moral behavior...

Research linking trait gratitude to work outcomes is still limited. In this study, we examined how gratitude relates to employees' performance and motivation. Specifically, we argued that grateful employees would increase their performance as a way to give back to their companies. Moreover, we drew on the self-determination theory and hypothesized...

The spatial distribution of light within one’s field of view plays a moderating role in both visual and non-visual effects. Besides the main vector of light direction, another aspect of the luminous spatial distribution is the perceived size of the light source expressed in a solid angle. In this project, we investigated the effect of frontal light...

The automatic system has been widely applied in the military industry to improve task performance and operational security. However, improper levels of automation (LOAs) could induce human errors. To investigate how LOAs and cognitive secondary tasks influenced the cognitive load of armored vehicle crews, a 3 × 3 factorial design experiment was con...

This study investigates how employees engage in two distinct job crafting strategies by either leveraging their existing strengths (job crafting towards strengths, JC‐strengths) or pursuing personal development (job crafting towards development, JC‐development) through the lens of exploitation and exploration. We propose that JC‐strengths, as an ex...

Machine Deploying machine learning (ML) on microcontroller-class hardware introduces unique challenges due to limitations in memory, computation, and power. This is particularly critical in health monitoring systems, where timely and accurate oxygen dynamics prediction is essential. This systematic review evaluates the use of ML techniques on micro...

This study presents the development and validation of the Task Performance Self-Assessment Scale (TPSAS), a brief self-report instrument designed to assess employees’ perceived effectiveness in executing core job responsibilities. Using a diverse sample of 1,588 workers from Puerto Rico, exploratory and confirmatory factor analyses confirmed a unid...

Neural systems process information across a broad range of intrinsic timescales, both within and across cortical areas. While such diversity is a hallmark of biological networks, its computational role in nonlinear information processing remains elusive. In this study, we examine how heterogeneity in intrinsic neural timescales within the frontal c...

Multi-access Edge Computing (MEC) and Vehicular-Fogs (VFs) are placed nearer to user equipment (UE), reducing propagation latency compared to traditional cloud-based systems and ensuring a high standard of Quality of Service (QoS). Nevertheless, MEC sites can become congested and overloaded during peak traffic periods, such as concerts or sporting...

Humans perform tasks involving the manipulation of inputs regardless of how these signals are perceived by the brain, thanks to representations that are agnostic to the stimulus modality. Investigating such modality-agnostic representations requires experimental datasets with multiple modalities of presentation. In this paper, we introduce and anal...

Being empowered and having a sense of control are central determinants of human well-being. However, there is currently no agreed-upon definition for the sense of control. We offer a prospective characterization as 'a priori readiness to perform tasks that will be announced in the future.' We show that this highlights three underlying factors that...

This study explores the underlying causes and consequences of non-nursing tasks performed by nurses in Jordan through an in-depth qualitative investigation. Utilizing semi-structured interviews with practicing nurses across diverse healthcare settings, the research identifies key factors contributing to the prevalence of non-nursing duties, includi...

A digital transformation of business affects all companies, regardless of their plans, and encourages a constant search for new methods of performing tasks. The implementation and use of new technology is often necessary when introducing changes to current ways of working. Financial technologies - FinTech and robotic process automation (RPA) as one...

This study aims to identify and analyze the key non-nursing tasks performed by nurses within Jordanian healthcare settings. Despite their primary role in direct patient care, nurses often undertake numerous non-nursing duties that may affect their efficiency and the quality of care delivered. Through a mixed-methods approach combining surveys and q...

Understanding how the brain learns may be informed by studying biologically plausible learning rules. These rules, often approximating gradient descent learning to respect biological constraints such as locality, must meet two critical criteria to be considered an appropriate brain model: (1) good neuroscience task performance and (2) alignment wit...

As federated reinforcement learning becomes more decentralized, robustness against faulty or malicious (Byzantine) agents becomes critical. This research proposes a Byzantine-Resilient Aggregation (BRA) algorithm for MA-FRL that detects and mitigates corrupted policy updates without relying on centralized validators. BRA employs a two-stage defense...

Virtual reality (VR) technology has gained considerable attention in recent years due to its potential in providing immersive experiences. However, challenges remain in creating VR environments that balance immersion, usability, and minimizing cybersickness. This study examines the effects of physical and artificial motion on immersion, usability,...

Vision-Language Navigation (VLN) policies trained on offline datasets often exhibit degraded task performance when deployed in unfamiliar navigation environments at test time, where agents are typically evaluated without access to external interaction or feedback. Entropy minimization has emerged as a practical solution for reducing prediction unce...

Large language models frequently rely on both contextual input and parametric knowledge to perform tasks. However, these sources can come into conflict, especially when retrieved documents contradict the model's parametric knowledge. We propose a diagnostic framework to systematically evaluate LLM behavior under context-memory conflict, where the c...

Introduction: The recent paradigm shift in Augmented Reality (AR) technology features the integration of Pass-Through Augmented Reality (PT-AR) into flagship Extended Reality (XR) devices. PT-AR, from a technological standpoint is Virtual Reality (VR) and significantly differs from AR technologies that used in devices like Google Glass, Magic Leap,...

Generalization from past experience is an important feature of intelligent systems. When faced with a new task, one efficient computational approach is to evaluate solutions to earlier tasks as candidates for reuse. Consistent with this idea, we found that human participants (n = 38) learned optimal solutions to a set of training tasks and generali...

Large language models (LLMs) are increasingly expected to perform tasks based only on a specification of the task provided in context, without examples of inputs and outputs; this ability is referred to as instruction following. We introduce the Recognition of Languages In-Context (RELIC) framework to evaluate instruction following using language r...

Heterogeneous multi-robot systems show great potential in complex tasks requiring coordinated hybrid cooperation. However, traditional approaches relying on static models often struggle with task diversity and dynamic environments. This highlights the need for generalizable intelligence that can bridge high-level reasoning with low-level execution...

Purpose: The study aims to revisit Morin's model on the meanings of work by comparing the attributes that give meaning to work based on the perceptions of Brazilian business administration students and administrators. Design/methodology/approach: The research included 30 business administration students and 12 administrators. Data were collected th...

Resting-state functional connectivity (rsFC) is widely studied in relation to behavioral phenotypes. Typically, rsFC-behavior relationships are explained by attributing various psychological processes to the observed patterns of rsFC. Such explanations may seem far-fetched and unrelatable since subjects do not perform tasks that elicit these psycho...

Changes in whole-body center of mass (COM) direction and speed over multiple steps during a maximal effort change of direction (COD) task have not been fully examined. This study aimed to (1) quantify COM direction and speed changes across three steps —approach (APP), execution (EXE), and following (FOL)—during a 45° COD task, and (2) compare force...

This paper introduces Energentic Intelligence, a class of autonomous systems defined not by task performance, but by their capacity to sustain themselves through internal energy regulation. Departing from conventional reward-driven paradigms, these agents treat survival-maintaining functional operation under fluctuating energetic and thermal condit...

Artificial Intelligence (AI) has emerged as a transformative force in modern science, reshaping the way research is conducted, data is analyzed, and knowledge is produced. This article explores the multifaceted role of AI in scientific endeavors, focusing on its core aims, such as accelerating discovery, automating processes, and enhancing data int...

Reinforcement Learning (RL) applications in real-world scenarios must prioritize safety and reliability, which impose strict constraints on agent behavior. Model-based RL leverages predictive world models for action planning and policy optimization, but inherent model inaccuracies can lead to catastrophic failures in safety-critical settings. We pr...

Deep learning representations are often difficult to interpret, which can hinder their deployment in sensitive applications. Concept Bottleneck Models (CBMs) have emerged as a promising approach to mitigate this issue by learning representations that support target task performance while ensuring that each component predicts a concrete concept from...

INTRODUCTION Practice effects are an improvement in task performance with repeated testing. Their absence may indicate compromised learning and may help discriminate healthy from pathological ageing. METHODS We recorded semantic verbal fluency three times in n = 58 healthy older adults or patients with amnestic mild cognitive impairment (MCI) (72....

Background Glove liners (GLs) are worn under impermeable gloves to prevent occlusion effects. Objectives To evaluate the acceptance and tolerability of cotton gloves (COT) and semipermeable Sympatex gloves (SYM) as GLs in patients with hand dermatoses. Methods In a prospective multicenter study, 210 patients with work‐related hand dermatoses were...

Animal behaviour is shaped to a large degree by internal cognitive states, but it is unknown whether these states are similar across species. To address this question, here we develop a virtual reality setup in which male mice and macaques engage in the same naturalistic visual foraging task. We exploit the richness of a wide range of facial featur...

Condition or domain being studied Cognitive function ; Motor function; Hyperthermia This study examines the impact of hyperthermia on cognitive and physical function tests Rationale for the review The purpose of this review is to establish the effect of increased core temperature on physical and cognitive tests, specifically in the firefighter popu...

This study investigated the effects of task complexity, task difficulty, and critical thinking disposition on college students’ writing performance. 201 participants were selected via probability sampling. Each completed three writing tasks of varying complexity, resulting in a corpus of 603 compositions. A follow-up questionnaire assessed task dif...

Vigilance quantification and fatigue modulation are concerned. However, previous vigilance quantification methods often face limitations in label subjectivity and interpretability when monitoring prolonged task performance. To address these challenges, we established a novel three-layer fuzzy logic framework to explore the feasibility of utilizing...

Harmful fine-tuning (HFT), performed directly on open-source LLMs or through Fine-tuning-as-a-Service, breaks safety alignment and poses significant threats. Existing methods aim to mitigate HFT risks by learning robust representation on alignment data or making harmful data unlearnable, but they treat each data sample equally, leaving data vulnera...

Neural oscillation, particularly gamma oscillation, are fundamental to cognitive processes such as attention, perception, and decision-making. Experimental studies have shown that the phase of gamma oscillation modulates neuronal response selectivity, suggesting a direct link between oscillatory dynamics and cognition. However, there remains a lack...

This study evaluates the effectiveness of augmented reality (AR), using the Microsoft™ HoloLens™™ 2, for identifying and localizing PCB components compared to traditional PDF-based methods. Two experiments examined the influence of user expertise, viewing angles, and component sizes on accuracy and usability. The results indicate that AR improved i...

Background Although there is growing evidence that impaired positive future thinking is associated with suicide risk, the relationship between positive future thinking and suicidal thoughts or suicidal behaviours has yet to be completely understood. Therefore, this experimental study explored the role of positive future thinking in those with diffe...