Information Processing Performance Research Articles

Pure ZrO2 Ferroelectric Thin Film for Nonvolatile Memory and Neural Network Computing.

The recent discovery of ferroelectricity in pure ZrO2 has drawn much attention, but the information storage and processing performances of ferroelectric ZrO2-based nonvolatile devices remain open for further exploration. Here, a ZrO2 (∼8 nm)-based ferroelectric capacitor using RuO2 oxide electrodes is fabricated, and the ferroelectric orthorhombic phase evolution under electric field cycling is studied. A ferroelectric remnant polarization (2Pr) of >30 μC/cm2, leakage current density of ∼2.79 × 10-8 A/cm2 at 1 MV/cm, and estimated polarization retention of >10 years are achieved. When the ferroelectric capacitor is connected with a transistor, a memory window of ∼0.8 V and eight distinct states can be obtained in such a ferroelectric field-effect transistor (FeFET). Through the conductance manipulation of the FeFET, a high object image recognition accuracy of ∼93.32% is achieved on the basis of the CIFAR-10 dataset in the convolutional neural network (CNN) simulation, which is close to the result of ∼94.20% obtained by floating-point-based CNN software. These results demonstrate the potential of ferroelectric ZrO2 devices for nonvolatile memory and artificial neural network computing.

White matter tracts adjacent to the human cingulate sulcus visual area (CSv).

Human cingulate sulcus visual area (CSv) was first identified as an area that responds selectively to visual stimulation indicative of self-motion. It was later shown that the area is also sensitive to vestibular stimulation as well as to bodily motion compatible with locomotion. Understanding the anatomical connections of CSv will shed light on how CSv interacts with other parts of the brain to perform information processing related to self-motion and navigation. A previous neuroimaging study (Smith et al. 2018, Cerebral Cortex, 28, 3685-3596) used diffusion-weighted magnetic resonance imaging (dMRI) to examine the structural connectivity of CSv, and demonstrated connections between CSv and the motor and sensorimotor areas in the anterior and posterior cingulate sulcus. The present study aimed to complement this work by investigating the relationship between CSv and adjacent major white matter tracts, and to map CSv's structural connectivity onto known white matter tracts. By re-analysing the dataset from Smith et al. (2018), we identified bundles of fibres (i.e. streamlines) from the whole-brain tractography that terminate near CSv. We then assessed to which white matter tracts those streamlines may belong based on previously established anatomical prescriptions. We found that a significant number of CSv streamlines can be categorised as part of the dorsalmost branch of the superior longitudinal fasciculus (SLF I) and the cingulum. Given current thinking about the functions of these white matter tracts, our results support the proposition that CSv provides an interface between sensory and motor systems in the context of self-motion.

Correlation and collective behaviour in Adler-type locally coupled oscillators at the edge of chaos

Dynamical systems can be analysed as computational devices capable of performing information processing. In coupled oscillators, enlarged capabilities are expected when the set of units is formed by subsets with collective behaviour within them but weak correlation between the subsets. A system of non-linear oscillators weakly coupled in the phase approximation is studied. The informational distance maps show different regimes of collective behaviour, ranging from independent, local, and global, as the control parameters of the system are changed. This rich set of behaviours happens despite the simple nature of the model used. Complex hierarchies between oscillators can be identified near the edge of chaos region in the informational distance dendrograms. We identify the emergence of local collective regimes, further corroborated by the spatiotemporal maps. Correlation diagrams also exhibit non-trivial dependence for the system at the edge of chaos.

Crowding-Out or Crowding-In? The Impact of Performance Rating on Public Service Motivation: Evidence From a Chinese Local Government

Despite extensive research on Public Service Motivation (PSM), reconciling the debate over whether PSM is a state or a trait remains a challenge among public administration scholars. Studies exploring the antecedents of PSM that engage in this debate often overlook the importance of organizational factors in influencing PSM. Framed within the literature on the behavioral aspects of performance information processing and adopting a propensity-score-matching model with data from a Chinese local government, we examine whether and how performance ratings influence public service motivation of public servants. The results show that performance ratings have a crowding-out effect, underscoring how the ways in which signals of performance feedback are conveyed to public servants can shape PSM. Our findings contribute to understanding the antecedents that preserve and promote public service motivation. We call for future research that focuses on public-value-based performance appraisal systems in centralized regimes.

Experimental distillation of tripartite quantum steering with an optimal local filtering operation

Multipartite Einstein-Podolsky-Rosen (EPR) steering admits multipartite entanglement in the presence of uncharacterized verifiers, enabling practical applications in semi-device-independent protocols. Such applications generally require stronger steerability, while the unavoidable noise weakens steerability and consequently degrades the performance of quantum information processing. Here, we propose the local filtering operation that can maximally distill genuine tripartite EPR steering from N copies of three-qubit generalized Greenberger-Horne-Zeilinger states, in the context of two semi-device-independent scenarios. The optimal filtering operation is determined by the maximization of assemblage fidelity. Analytical and numerical results indicate the advantage of the proposed filtering operation when N is finite and the steerability of initial assemblages is weak. Experimentally, a proof-of-principle demonstration of two-copy distillation is realized with the optical system. The advantage of the optimal local filtering operation is confirmed by the distilled assemblage in terms of higher assemblage fidelity with perfectly genuine tripartite steerable assemblages, as well as the greater violation of the inequality to witness genuine tripartite steerable assemblages. Our results benefit the distillation of multipartite EPR steering in practice, where the number of copies of initial assemblages is generally finite.

The Effect of Acute Physical Fatigue on Information Processing, Pain Threshold and Muscular Performance

This study explores the multifaceted effects of acute physical fatigue on information processing, pain threshold, and muscular performance. Enrolling 28 recreational athletes, we used a high-intensity interval training (HIIT) protocol to induce fatigue and conducted pre- and post-intervention assessments. Our findings revealed significant physiological and performance adaptations following the HIIT sessions. Key observations included increased heart rate and rate of perceived exertion and an enhancement in horizontal jump performance and isometric hand strength but no significant change in cognitive processing speed. Remarkably, participants demonstrated a notable increase in pain threshold and blood lactate levels post-exercise. These results challenge traditional views of fatigue, indicating not only a physiological but also a psychological resilience to high-intensity stress. This study provides new insights into the complex interplay between physical fatigue, cognitive function, and pain perception, highlighting the comprehensive effects of HIIT on both physiological and psychological dimensions of human performance.

A big data quality evaluation method based on group heterogeneity rationality perception information fusion

Big data is complex, and it is difficult to evaluate big data quality with only a few evaluation subjects. This paper designs a universal evaluation method for big data quality based on the idea of group heterogeneity rationality perception information fusion. Group evaluation information is usually large-scale and heterogeneous. The linear programming technique for multidimensional analysis of preference (LINMAP) model has the performance of large-scale evaluation information processing. Because the existing LINMAP models cannot effectively process group evaluation information with heterogeneous rationality, the LINMAP model of heterogeneous rationality (HR-LINMAP) based on group evaluation information is proposed. The research results show: under certain conditions, the LINMAP model of bounded rationality (BR-LINMAP) can be transformed into the LINMAP model of perfect rationality (PR-LINMAP), and the HR-LINMAP is the general form of PR-LINMAP and BR-LINMAP. The scientific research big data resources with mature trading markets are selected as the evaluation objects, and HR-LINMAP is used to analyze the big data quality evaluation cases. The empirical analysis shows that the HR-LINMAP model is feasible and effective, which provides a new idea for big data quality evaluation.

A Study on Learning Strategies and Styles Segmentation of Learner Groups in Online Education Platforms

Abstract Online education is becoming a popular form of education day by day. In order to provide corresponding learning programs according to the types of learning styles and learning strategies of different learners, this paper proposes a learning style recognition algorithm based on the Felder-Silverman model. The Bayesian discriminant analysis algorithm is used to calculate the probability estimation of samples belonging to one category, and then the clustering center is calculated by k-means clustering analysis so as to complete the classification of learning styles. According to the results of learning style identification, the perceptual learning group has the highest level of cooperative communication strategies in the information perception style dimension, with a mean score of 3.575, the linguistic group is the least adept at all strategies in the information input dimension, with a mean score of only 3.55, the sequential group excels in a variety of strategies for information comprehension, and the active group is the most adept at performing information processing. The personalized learning experiment was conducted according to the characteristics of different style groups. It was found that students who received personalized teaching based on their learning styles improved their performance more significantly, with their average scores in each subject increasing from 73.174 to 82.247 in the pre-test. Their scores in the post-test were 5.729 points ahead of those of the control class. The application effects are significant when learning strategies and styles are classified, and teaching programs are improved accordingly.

NoC simulation steered by NEST: McAERsim and a Noxim patch.

Great knowledge was gained about the computational substrate of the brain, but the way in which components and entities interact to perform information processing still remains a secret. Complex and large-scale network models have been developed to unveil processes at the ensemble level taking place over a large range of timescales. They challenge any kind of simulation platform, so that efficient implementations need to be developed that gain from focusing on a set of relevant models. With increasing network sizes imposed by these models, low latency inter-node communication becomes a critical aspect. This situation is even accentuated, if slow processes like learning should be covered, that require faster than real-time simulation. Therefore, this article presents two simulation frameworks, in which network-on-chip simulators are interfaced with the neuroscientific development environment NEST. This combination yields network traffic that is directly defined by the relevant neural network models and used to steer the network-on-chip simulations. As one of the outcomes, instructive statistics on network latencies are obtained. Since time stamps of different granularity are used by the simulators, a conversion is required that can be exploited to emulate an intended acceleration factor. By application of the frameworks to scaled versions of the cortical microcircuit model-selected because of its unique properties as well as challenging demands-performance curves, latency, and traffic distributions could be determined. The distinct characteristic of the second framework is its tree-based source-address driven multicast support, which, in connection with the torus topology, always led to the best results. Although currently biased by some inherent assumptions of the network-on-chip simulators, the results suit well to those of previous work dealing with node internals and suggesting accelerated simulations to be in reach.

Achieving Ultrawide Tunability in Monolithically Fabricated Si Nanoresonator Devices.

Nanoresonators are powerful and versatile tools promising to revolutionize a wide range of technological areas by delivering unparalleled performance in physical, chemical, biological sensing, signal and information processing, quantum computation, etc., via their high-frequency resonant vibration and rich dynamic behavior. Having the ability to tune the resonance frequency and dynamic behavior at the application stage promises further improvement in their effectiveness and enables novel applications. However, achieving significant room-temperature tunability in conventional (monolithically fabricated) nanoresonators is considered challenging. Here we demonstrate ultrawide electrostatic tuning (∼70%) of (initial) resonance-frequency (∼7% V-1) at room temperature in a monolithically fabricated ultrathin Si nanoresonator (width ∼ 40 nm, length ∼ 200 μm) device. Extreme electrostatic tuning of nonlinear behavior is also demonstrated by canceling the cubic-nonlinear coefficient and subsequently flipping its sign. Thus, these results are expected to provide remarkable operational flexibility and new capabilities to microfabricated resonators, which will benefit many technological areas.

Visual stimulation by extensive visual media consumption can be beneficial for motor learning

In this randomized controlled intervention trial, we investigated whether intense visual stimulation through television watching can enhance visual information processing and motor learning performance. 74 healthy young adults were trained in a motor skill with visual information processing demands while being accommodated in a controlled environment for five days. The experimental manipulation (n = 37) consisted of prolonged television watching (i.e., 8 h/day, + 62.5% on average) to induce intense exposure to visual stimulation. The control group (n = 37) did not consume visual media. The groups were compared by motor learning performance throughout the study as well as pre/post visual attention parameters and resting-state network connectivity in functional MRI. We found that the intervention group performed significantly better in the motor learning task (+ 8.21% (95%-CI[12.04, 4.31], t(70) = 4.23, p < 0.001) while showing an increased capacity of visual short-term memory (+ 0.254, t(58) = − 3.19, p = 0.002) and increased connectivity between visual and motor-learning associated resting-state networks. Our findings suggest that the human brain might enter a state of accentuated visuomotor integration to support the implementation of motor learning with visual information processing demands if challenged by ample input of visual stimulation. Further investigation is needed to evaluate the persistence of this effect regarding participants exposed to accustomed amounts of visual media consumption.Clinical Trials Registration: This trial was registered in the German Clinical Trials Register/Deutsches Register klinischer Studien (DRKS): DRKS00019955.

Relationship between speech perception and cortical temporal information processing in noise

It has been known for many years that some listeners with normal hearing report difficulties in speech reception under the presence of competing sounds. The symptom is called hidden hearing loss. For the elucidation of the mechanism of hidden hearing loss, we examined the relationship between speech-in-noise reception performance and cortical temporal information processing. It has been reported that delta and theta oscillations were phase-locked to speech envelopes, and the synchronization depends on the intelligibility of degraded synthesized speech. However, it remains unclear whether and how the slow oscillations reflect speech-in-noise reception performances. We measured slow-rate (below 8 Hz) electroencephalogram (EEG) oscillations during speech reception under noise with different signal-to-noise ratio (-5 dB to -14 dB). In a control condition, EEG oscillations were measured by the same stimuli, but the participants watched a self-selected movie with subtitles, ignoring the stimuli. The power of the EEG oscillations during speech reception was stronger than those while participants ignored the stimuli. However, we did not find any dependences of the slow EEG oscillations on speech intelligibility changes associated with varying SNR. The enhancement of slow oscillations can be triggered by attention but is not likely to reflect listening effort driven by noise contamination.

Vehicle light communication design using an efficient learning model

Vehicle communication is preferable in vehicular visible light communication (VVLC) owing to its low complexity, secure, interference-free characteristics, line of sight exploitation, vehicle light emitting diodes, and vehicle light propagation characteristics. The channels of VVLC are stochastic and give less accuracy during path loss prediction without considering external environmental factors. There is no wireless channel adopted for channel-based frequency response and node multi-access. This work concentrates on modeling a machine learning-based model for VVLC channel modeling and enhancing the accuracy by specifically concentrating on frequency response via multiple variables like environmental factors and vehicle mobility. The proposed model considers variables with the adoption of an Extreme learning model (ELM) with feed-forward neural networks (FFNN). This model performs information processing over the VLC channel to enhance prediction. The accuracy of the proposed model relies on channel modeling and multi-access relays among nodes. The proposed model performance is evaluated with prevailing approaches to produce distance prediction and response among the relay nodes. Some metrics like BER, SNR, MSE, received power, impulse, and frequency response, and received optical power are evaluated and compared with other approaches.

Desempeño cognitivo durante la abstinencia de metanfetaminas

A documentary investigation was carried out to understand the relationship between methamphetamine abstinence and cognitive performance in methamphetamine users. According to regional figures, methamphetamine is the fourth initiation drug and the first illegal impact drug according to statistics (ENA, 2011; ENCODAT, 2016). In a work carried out by Goldstein and Volkow (2011) it is confirmed that there is a disturbance in the prefrontal cortex due to addiction, and that from these alterations emerge compulsive substance use, disadvantageous behaviors that are associated with addiction, and deficits in decision making. Regarding methamphetamine withdrawal, several studies found difficulties in executive functions and working memory during the withdrawal process. In conclusion, we can see that there is a weakening of prefrontal regions responsible for executive functions and a memory deficit compensated by a dopamine deficit. Regarding the altered functions, despite the heterogeneity of the results, we see that there is poor performance in inhibitory control, execution speed and information processing. Although these deficits are also accompanied by a problem with impulse control and social cognition.

A DMA-WSN Based Routing Strategy to Maximize Efficiency and Reliability in a Ship to Communicate Data on Coronavirus

Background: The Sensor Nodes (SNs) are deployed in an environment where human beings are not able to perform the tasks. Wireless Sensor Network (WSN) is used for applications in security, military surveillance, habitat monitoring, agriculture, etc. All these applications require SNs to have good battery backup so that they can perform for a long duration. Recent research shows that agent-based strategies increase the efficiency of WSN in comparison to conventional WSN in which every SN is static. During the current pandemic of Covid-19, various public resources, such as train, bus, hotels, etc., were used for isolating the Covid-19 patients. In a similar way, the ship helps to keep humans away from each other. Methods: In the current work, WSN has been deployed on a ship to monitor the health of Covid-19 patients. A 109 m long ship with 12.8 m altitude and 23 m width along with 6 decks has been considered. The SNs have been deployed on different floors of the modern ship. Six decks have been considered, and on each deck, 50 SNs have been deployed. A Drone-driven Mobile Agent (DMA) routing strategy has been proposed. DMA is a software program that moves across the network around the SNs and collects information from wearable sensors, such as body temperature, SpO2, etc. DMA is capable of aggregating and delivering the data packets to the base station for further processing. DMA performs information processing, local processing, and collaborative signaling. DMA can move randomly or in fixed locations. Results: Results have been compared with multi-sink and mobile sink strategies, which reveal that the proposed and simulated technique enhances the life span and throughput of the network to monitor Covid-19 patients effectively. Conclusion: Results revealed the proposed technique to enhance the lifetime (DMA-fixed: 11633 rounds and DMA-random: 11740 rounds) and throughput (DMA-fixed: 148788 packets sent and DMA-random: 150008 packets sent) of the network.

BIOLOGICAL AND SOCIAL ASPECTS OF HUMAN HEALTH AS DETERMINANTS OF ECONOMIC DEVELOPMENT

The purpose of the study was to analyse the relationship between a person's mental performance, work efficiency and psychophysiological functions (PF) of the body. It is proved that taking into account the biological foundations of a person should be an essential condition for life and health, as well as for the development of a modern democratic country. The use of a typological approach based on psychophysiological criteria optimises professional orientation and provides recommendations on the possibility of mastering certain professions without harming health. This approach contributes to the efficient allocation of human capital, the use of periodic health monitoring, and the prediction of production volumes and quality, as well as its competitiveness. Methodology. The study was aimed at identifying the level of mental performance and efficiency of information processing on a computer in representatives of three groups of employees who differed in strength (mental performance, MP), mobility of nervous processes (MNP), balance (BNP) of nervous processes, speed of sensorimotor reactivity, indicators of situational anxiety (SA), cardiovascular system, and activation processes of the brain. Results. The study found that the examined employees of an office company (77 women and men aged 18-23 years) who had the highest level of MP and work efficiency were characterised by higher heart rate spectral power (HR), SA, and BNP. It is from individuals of this psychophysiological type that one should expect maximum mastery of the profession, relevant competencies associated with the speed of reaction, a minimum of erroneous actions, promotion of income, production volumes and rates, and a low level of injuries. The group of employees with low levels of PF was characterised by low levels of MP and efficiency, but at the same time high levels of SA, demonstrating a high risk of chronic fatigue and general neuroticism. In order to optimise the professional sphere and increase the economic income of this category of people, it is recommended that they be more careful in selecting professions that have a less intensive rhythm of work and a low stress component. Subjects with an average level of sensorimotor reactivity, spectral power indices of HR, SA and BNP showed a high level of RP and work efficiency, but relatively low reserve capabilities of the body. In this case, to prevent a decline in health, deterioration in the quality of life, labour productivity and economic decline, a clear distribution of occupational loads and rest should be followed. Practical implications. Taking into account that the respondents with the highest spectral power indicators of HR, SA, and BNP showed the highest level of MP and efficiency of work performed, it is this category that should be targeted first of all by the main business strategies of the country's development related to economic growth, development of marketing trajectories, and building innovative and exclusive production models. At the same time, it is necessary to systematically introduce various health-saving programmes to enable timely restoration of human physical and psychophysiological potential. Subjects with low characteristics of the psycho-emotional and neurovegetative spheres demonstrated lower MP and work efficiency. Predictably, they are associated with lower ratings of competitiveness and income in a professional field with a high rhythm of tasks, tension and time pressure, but are able to demonstrate sufficient labour potential in other professions. Value/originality. The obtained actual data of the selected groups of employees make it possible to assess the MP, the effectiveness of the work performed by them and can be used as reliable biological markers of economic fluctuations in society. On the other hand, it should be borne in mind that high performance and labour efficiency largely depend on the PFs involved in the state of human health. Thus, timely preservation and maintenance of the population's health at the proper level, combined with the applied typological psychophysiological approach to vocational guidance and individualisation of work regimes, lays a solid foundation for the economic growth of a democratic country.

Beyond Media Education: Assessing News Media Literacy in Media Students of Public and Private Universities in Pakistan

Infiltration of mass media has increased the exigency of tools necessary for countering the hazardous effects of mass media. Media literacy is considered a tool essential in the 21st century for a democratic society that aims to empower the audience and provides autonomy over mass media messages. Media education plays a significant role in educating media students about theoretical and practical knowledge about media industries. The researcher has employed the “Cognitive Model of Media Literacy” proposed by Potter (2004) and seven skills of media literacy suggested by Potter (2019), particularly as related to news content. News media is supposed to be highly objective, but highlighting some news while neglecting others raises questions about the objectivity of news media. The study intends to explore the standard of media education in Pakistan in imparting news media literacy among media students enrolled in BS and Master’s degree programs. To analyze the level of theoretical and practical knowledge of media students regarding news media and their level of news literacy skills, the researcher has collected data using a cross-sectional survey of 300 students (N=300) enrolled in two public and two private universities in Pakistan, including 200 media students and 100 non-media students. Moreover, through content analysis of the curriculum of media studies mentioned in the prospectus of BS and Master’s degree programs, the standard of media education in Pakistan is also assessed. The study’s findings suggest that media students are more news media literate than non-media students, highlighting the significance of media education. Similarly, consciously and excessively consuming news media also positively affects the level of news media literacy in media students. Moreover, this study suggests that while performing information processing tasks, media students are equipped with skills to perform the task of news filtering comparatively better than meaning construction tasks. However, content analysis of the curriculum reveals that the majority of the courses related to news content focus on theoretical and practical knowledge while neglecting the significance of incorporating analytical courses crucial to harness critical thinking skills. The findings elucidate that universities offering analytical courses in their BS and Master levels scored higher in their news media literacy than those not offering analytical courses. Therefore, the study suggests the incorporation of analytical courses at BS and Master level media education curricula to develop essential skills for performing meaning construction tasks effectively.

Effects of acute exercise of different modalities and durations on interference control and response inhibition in healthy young adults

ABSTRACT This study examined the immediate and sustained effects of acute exercise modalities and durations on inhibitory control including response inhibition and interference control. Fifty-nine young adults participated in three exercise interventions and a reading intervention. Three exercise interventions consisted of a 20-min moderate intensity continuous exercise (MICE), a 20-min high intensity interval exercise (HIIE) and a 10-min HIIE. Using a colour-word Stroop task and a Go/no-go task, interference control and response inhibition were assessed before the intervention (t0), immediately after the intervention (t1), and then at 30 min (t2) and 60 min (t3) after the intervention. During the Stroop task, the response time (RT) was significantly shorter for both congruent and incongruent trials immediately after 20-min HIIE compared to that before exercise, and this reduction lasted for 60 min. The improvement in the Stroop task can be maintained for 30 min after 20-min MICE. In addition, the 10-min HIIE intervention immediately reduced the RT of the incongruent trials. However, the Go/no-go results showed no significant change in task performance after the four interventions. The above findings suggest that when compared to MICE for the same exercise time, improvements in interference control were sustained longer and better following 20-min HIIE. In addition, HIIE for 20-min rather than shorter duration was best for both basic information processing and interference control performance. A duration of 20-min HIIE may be a more effective way to improve interference control. Neither HIIE nor MICE had any effect on response inhibition.

Utilizing Augmented Reality to Quantify Information Processing and Motor Performance in Military Personnel to Detect Mild Traumatic Brain Injury (P8-1.002)

<h3>Objective:</h3> Utilize augmented reality (AR) to create military specific scenarios that can be objectively quantified and used to facilitate the detection of and return-to-duty (RTD) following mild traumatic brain injury (mTBI). <h3>Background:</h3> Methods of detecting military mTBI are rooted in neuropsychological tests that measure a construct of executive or motor function. This approach does not lend itself to accurate detection or appropriate RTD. We have demonstrated the HoloLens 2 AR device provides accurate biomechanical data. Placing digital assets in a user’s real-world via AR technology creates an ecological environment to evaluate function. An AR Rifle qualification test (RQT) to evaluate dynamic movement, information processing, shooting performance and decision-making was developed. To evaluate performance in the context of a group or military unit, a room clearing assessment was created. <h3>Design/Methods:</h3> Data were gathered from 157 active-duty service members. The RQT was performed under single- and dual-task conditions. Five room clearing scenarios in which information processing and motor demands were manipulated were completed. Kinematic data from the HoloLens 2 provided biomechanical outcomes characterizing cognitive and motor performance. <h3>Results:</h3> Reaction time (RT) to firing and accuracy of target acquisition in the RQT did not differ between single- and dual-task conditions (<i>p&lt;0.05)</i>. Transition time from kneel to stand did not differ between conditions; however, dual-task sway path (41.2±17.5 cm) post-transition was increased compared to single-task (35.1±14.2 cm). There was a significant increase in processing time as the complexity of the room clearing scenarios increased. <h3>Conclusions:</h3> The objective quantification of information processing (RT) and motor (postural sway and movement time) function while performing ecological AR military tasks can enhance the detection of mTBI using objective functional metrics. The use of AR to deliver realistic digital experiences will facilitate appropriate RTD to ensure the safety of the service member and their unit. <b>Disclosure:</b> Mr. Kaya has nothing to disclose. Anson Rosenfeldt has received personal compensation for serving as an employee of Cleveland Clinic. Anson Rosenfeldt has received personal compensation in the range of $10,000-$49,999 for serving as a Consultant for Enspire DBS. The institution of Anson Rosenfeldt has received research support from Michael J. Fox Foundation. The institution of Anson Rosenfeldt has received research support from National Institute of Health. The institution of Anson Rosenfeldt has received research support from Department of Defense. Anson Rosenfeldt has received intellectual property interests from a discovery or technology relating to health care. Mr. Waltz has nothing to disclose. Mrs. Jansen has nothing to disclose. Ms. Owen has nothing to disclose. Mrs. Dunlap has nothing to disclose. Karissa Hastilow has nothing to disclose. Mrs. Scelina has nothing to disclose. Mr. Zimmerman has nothing to disclose. Morgan McGrath has nothing to disclose. Amanda Penko has nothing to disclose. The institution of Dr. Alberts has received research support from NIH. Dr. Alberts has received intellectual property interests from a discovery or technology relating to health care. Dr. Alberts has received personal compensation in the range of $500-$4,999 for serving as a Member, Health and Wellness Council with Peloton Interactive.

Body temperatures, thermal comfort, and neuropsychological responses to air temperatures ranging between 12°C and 39°C in people with Multiple Sclerosis

The negative effects of thermal stress on Multiple Sclerosis (MS)’ symptoms have long been known. However, the underlying mechanisms of MS heat and cold intolerance remain unclear. The aim of this study was to evaluate body temperatures, thermal comfort, and neuropsychological responses to air temperatures between 12 and 39 °C in people with MS compared to healthy controls (CTR). Twelve MS (5 males/7 females; age: 48.3 ± 10.8 years; EDSS range: 1–7) and 11 CTR participants (4 males /7 females; age: 47.5 ± 11.3 years) underwent two 50-min trials in a climatic chamber. Air temperature was ramped from 24 °C to either 39 °C (HEAT) or 12 °C (COLD) and we continuously monitored participants’ mean skin (Tsk) and rectal temperatures (Trec), heart rate and mean arterial pressure. We recorded participants’ self-reported thermal sensation and comfort, mental and physical fatigue, and we assessed their cognitive performance (information processing). Changes in mean Tsk and Trec did not differ between MS and CTR neither during HEAT nor COLD. However, at the end of the HEAT trial, 83% of MS participants and 36% of CTR participants reported being “uncomfortable”. Furthermore, self-reports of mental and physical fatigue increased significantly in MS but not CTR (p < 0.05), during both HEAT and COLD. Information processing was lower in MS vs. CTR (p < 0.05); yet this cognitive impairment was not exacerbated by HEAT nor COLD (p > 0.05). Our findings indicate that neuropsychological factors (i.e. discomfort and fatigue) could contribute to MS heat and cold intolerance in the absence of deficits in the control of body temperature.