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Towards a Socio-Technical Ecosystem for Mental Health and Wellbeing Screening and Promotion
No full textData Availability: Given its conceptual nature, this article is not underpinned by any primary data.This concept paper delineates the design of a sociotechnical ecosystem for ethical screening and promotion of mental health and well-being, building on the convergence of digital technologies with modern human-centered design methods. Access to individuals’ health and well-being data will enable the generation of actionable insights with different degrees of granularity, for the benefit of individuals, care providers, and business organizations. Critical to the success of the ecosystem are the proactive involvement of all stakeholders, the definition of incentives to encourage engagement, and the promotion of consistent narratives as public institutional messages. The article posits working hypotheses, including the idea that creative externalization of health and well-being data, augmented by advanced physico-digital interactivity, can sustain positive psychological and behavioral change. The theoretical underpinning consists of the integration of existing frameworks across well-being, behavior change, and sustainable business. The article defines a research agenda for expanding socially inclusive dialogue on data governance and policy implications.No funding was received for conducting this study
A Nested Uzawa Solver for a Dual-Dual Mixed Finite Element Method for Frictional Contact Problems in Linear Elasticity
No full textMSC 2020: 35A15; 65K15; 74B05; 74M10; 74M15.For a dual-dual formulation of a frictional contact problem in linear elasticity we present a mixed finite element method based on PEERS elements and we analyze the performance of a nested Uzawa algorithm
Quantum-enhanced digital twin IoT for efficient healthcare task offloading
Get PDFData availability:
The datasets generated during and/or analyzed during the current study are available from the corresponding author, Hamed Al-Raweshidy, upon reasonable request. Data collected from IoT healthcare sensors (e.g., SpO2, heart rate, body temperature) were simulated for the purpose of this research. Quantum computing experiments were conducted via IBM Quantum cloud services, and corresponding simulation logs are available upon request. Additionally, publicly available anonymized data from the MIMIC-III database were used and can be accessed at https://physionet.org/content/mimiciii/1.4/.Task offloading frameworks play a crucial role in modern healthcare by optimizing resource utilization, reducing computational burdens, and enabling real-time medical decision-making. However, existing Digital Twin (DT)-based healthcare models suffer from high latency, inefficient resource allocation, cybersecurity vulnerabilities, and computational limitations when processing large-scale patient data. These constraints pose significant risks in time-sensitive applications such as ICU monitoring, robotic-assisted surgeries, and telemedicine. To address these limitations, this paper introduces a Quantum-Enhanced DT-IoT framework, integrating Artificial Intelligence (AI), Quantum Computing (QC), DT, and the Internet of Things (IoT) for real-time, secure, and efficient healthcare task offloading. The proposed system introduces two key optimization algorithms: (1) DTH-ATB-MAPPO, which dynamically adjusts task scheduling and resource distribution, and (2) AQDT-IoT, which enhances computational efficiency and cybersecurity compliance in 6 G-enabled IoT networks. By leveraging Approximate Amplitude Encoding (AAE) and Grover’s search, the framework enhances task offloading efficiency, enabling faster decision-making and optimized resource distribution across 6 G-enabled IoT networks. Empirical evaluations show that quantum preprocessing improved Task Offloading Success Rate (TOSR) by 32% and reduced the Error Rate (ER) by 80%, significantly outperforming traditional DT-based healthcare models. These enhancements enable. Additionally, theoretical analysis demonstrates computational speed enhancements, adaptive cybersecurity mechanisms, and improved system scalability, positioning this framework as a viable candidate for future cloud-based quantum healthcare infrastructures, even in resource-constrained hospital environments.This research was supported by Brunel University of London
Circadian rhythmicity in prepulse inhibition of the acoustic startle response: A study of chronotype and time-of-day effects in young healthy adults
Get PDFData availability statement:
Data will be made available via the Brunel data repository (https://brunel.figshare.com).Supplementary Material is available at: https://journals.sagepub.com/doi/10.1177/02698811251337397#supplementary-materials .Background:
Prepulse inhibition (PPI) of the acoustically elicited startle response is a widely used cross-species measure of sensorimotor gating. It is known to be reduced in various psychiatric disorders. Given previous reports of (a) disrupted PPI in young adults following overnight sleep deprivation and (b) disrupted sleep–wake cycles and psychiatric disorders being more common in evening than morning chronotypes, it is possible that there are chronobiological influences on human PPI.
Aims:
We investigated chronotype, time of day (ToD) and synchrony effects (i.e. optimal functioning at preferred ToD) in acoustic PPI in young healthy adults.
Methods:
Thirty-six adults, selected from a larger pool (N = 213) to represent morning, intermediate or evening chronotypes, were assessed on PPI (prepulse-to-pulse intervals: 30, 60 and 120-ms) on two occasions, 1 week apart: once in the morning (8:00–10:00) and once during the late afternoon (16:00–18:00).
Results:
There were no chronotype or synchrony effects on PPI. In the late afternoon, compared to the morning session, (i) there was greater startle amplitude on pulse-alone trials in association with higher schizotypy and (ii) greater PPI on 120-ms (but not 30-ms or 60-ms) PPI trials, but this effect became non-significant after covarying for schizotypy.
Conclusions:
Our findings showed no chronotype or synchrony effect on PPI, and offer further support for PPI to be a stable biomarker that is not significantly modulated by chronotype or ToD in healthy adults. ToD, however, may influence some startle parameters in association with schizotypy and should be considered in future studies of schizotypy and related populations.The author(s) received no financial support for the research, authorship, and/or publication of this article
Real-Time Object Detection and Distance Measurement Enhanced with Semantic 3D Depth Sensing Using Camera–LiDAR Fusion
Get PDFData Availability Statement:
The data used in this study are from the Karlsruhe Institute of Technology and Toyota Technological Institute (KITTI) Vision Benchmark 2D Object Detection Evaluation 2012 dataset. The dataset can be accessed publicly at https://www.cvlibs.net/datasets/kitti/eval_object.php?obj_benchmark=2d (accessed on 10 January 2022).Camera and LiDAR data fusion has been a popular research area, especially in the field of autonomous vehicles. This study evaluates the efficiency and accuracy of different depth point extraction methods, including Point-by-Point (PbyP), Complete Region Depth Extraction (CoRDE), Central Region Depth Extraction (CeRDE), and Grid Central Region Depth Extraction (GCRDE), across object categories such as person, bicycle, car, bus, and truck, and occlusion levels ranging from 0 to 3. The approaches are assessed based on extraction time, accuracy, and root mean squared error (RMSE). Bounding box-based methods, such as PbyP and CoRDE, consistently show slower extraction times compared to segmentation mask methods, with CeRDE being the most efficient in terms of computational speed. However, segmentation mask methods, particularly CeRDE and GCRDE, offer superior accuracy, especially for complex objects like trucks and cars, where bounding box methods struggle, particularly at higher occlusion levels. In terms of RMSE, segmentation mask methods consistently outperform bounding box methods, providing more precise depth estimations, particularly for larger and more occluded objects. Overall, segmentation mask methods are preferred for applications where accuracy is critical, despite their slower processing speed, while bounding box methods are suitable for real-time applications requiring faster depth extraction. GeRDE offers a balance between speed and accuracy, making it ideal for tasks needing both efficiency and precision.This research received no external funding and Ahmet Serhat Yildiz’s Ph.D. is sponsored by the Ministry of National Education of Türkiye
Exploring the effects of wearing facemasks on stair safety characteristics in young adults
Get PDFData Availability: All relevant data are within the manuscript and its Supporting Information files (https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0324333#sec036).Introduction:
Facemasks are worn in many industries to protect from infections and harmful substances. Asian countries historically have a wide adoption of facemasks; though due to the COVID-19 pandemic, facemask wearing is also common in western countries. The lower visual field provides important information for safe stair negotiation. A loose fit facemask may obstruct the lower visual field and negatively affect stair negotiation. Pinching a facemask nose clip provides contour around the nose which may reduce lower visual occlusion and negative stair behaviour effects. Here, we explored the effect of wearing a Type IIR facemask and nose clip pinch adjustment on lower visual field occlusion and stair walking behaviour
Method:
Eight young adults ascended and descended stairs with; 1) no facemask, 2) unadjusted facemask, 3) customised facemask (nose clip pinched). Measurements included peak head flexion, lower visual field occlusion, stair duration, foot clearance, foot placement, margins of stability, Conscious Movement Processing and anxiety.
Results:
Unadjusted increased lower visual occlusion during descent (unadjusted = 32° ± 14° vs no facemask = 11° ± 14°, p < 0.001), (unadjusted vs customised = 21° ± 15°, p = 0.009) and ascent (unadjusted = 47° ± 12° vs no facemask = 25° ± 11°, p < 0.001), (unadjusted vs customised = 35° ± 11°, p = 0.005). Unadjusted increased conscious movement processing during descent (unadjusted = 16 ± 5 vs no face mask 11 ± 4, p = 0.040) and ascent (unadjusted = 16 ± 5 vs no face mask = 10 ± 3, p = 0.044). Bayesian inference indicated moderate evidence for the alternative hypothesis for descent duration, peak head flexion and anxiety. Anecdotal and strong evidence for the alternative hypothesis were found for ascent duration and anxiety respectively. No differences were found in foot kinematics or margins of stability.
Discussion:
Simple adjustments (pinching the nose clip) to a Type IIR facemask have the benefit of reducing the lower visual field occlusion an unadjusted mask creates, and helps improve stair safety characteristics in young adults.The author(s) received no specific funding for this work
Chronic dizziness in older adults: Disrupted sensorimotor EEG beta oscillations during postural instability
Get PDFSupplementary data are available online at: https://www.sciencedirect.com/science/article/pii/S1388245725004523?via%3Dihub#s0080 .Objective:
Chronic dizziness is common in older adults, yet frequently occurs without a clear cause (‘idiopathic dizziness’). Patients experience subjective unsteadiness with minimal objective imbalance, potentially related to small vessel disease. Here we examine the hypothesis that this syndrome is associated with disrupted cortical processing of postural instability.
Methods:
EEG and postural sway were recorded in 33 older adults with chronic, idiopathic dizziness (Age, Mean = 77.3 years, SD = 6.4, 61 % female) and 25 matched controls (Age, Mean = 76.9 years, SD = 6.0, 56 % female). EEG was time-locked to spontaneous instances of postural instability and analysed via time–frequency decomposition.
Results:
Significant between-group differences in EEG were observed during the early phase of postural instability (p 0.720) but to fear of falling (r = -0.44, p = 0.001).
Conclusions:
Previous work implies that suppressing cortical beta enhances the relay of sensory information. We therefore propose that the modulation in beta EEG observed in patients reflects an anxious, top-down strategy to increase sensitivity to instability, which paradoxically causes persistent feelings of subjective imbalance.
Significance:
These results identify associations between idiopathic dizziness and disrupted sensorimotor beta activation during postural instability. Cortical beta during imbalance may be a possible biomarker of chronic, idiopathic dizziness in older adults and/or fear of falling.This research was supported by a Wellcome Trust Sir Henry Wellcome Postdoctoral Fellowship awarded to T.J.E. (Grant Number: 222747/Z/21/Z) and the Dunhill Medical Trust to A.M.B. (Grant number: R481/0516). A.M.B. was further supported by the Imperial College London Biomedical Research Centre. P.C. was funded by a CONICYT scholarship, Chilean government (Reference: 5235/2016)
Efficacy of a single session of anticipatory postural adjustments training to support people with parkinson’s overcoming freezing of gait: a multi-methods approach
Get PDFSupplementary appendix available online at: https://medicaljournalssweden.se/jrm/article/view/42491/50137 .Objective: To assess the efficacy of anticipatory postural adjustments training on the ability to
successfully step from freezing of gait, and to evaluate the contribution of attentional processes to potential benefits using an additional attentional-control training intervention.
Design: Crossover-design.
Subjects/Patients: Nineteen people with Parkinson’s and freezing (females: 10; age:75.5 ± 7.5 years) tested while ON medication.
Methods: Participants navigated a cluttered virtual domestic environment with freeze-provoking tasks. Assessments occurred in the laboratory at baseline, post-anticipatory postural adjustments training, and post-attentional-control training, with randomized training order. All training was video-based. Video annotation was used to identify freezing events. Participants’ immediately recollected thoughts they had during the tasks were analysed with content analysis. Perceived safety and effectiveness of the strategies were reported in follow-up calls held 4 weeks post-assessment.
Results: Successful step initiations increased from 57% at baseline to 77% post-anticipatory postural adjustments training (p = 0.034). Participants rated the interventions as safe and effective, reporting increased balance confidence (70% to 90%), and reduced fear (p = 0.01), after the anticipatory postural training. Attentional-control training alone was perceived as less effective compared with more goal-directed anticipatory postural adjustments training.
Conclusion: Video-based anticipatory postural adjustments training significantly improved step initiation from freezing when used during challenging tasks and in complex environments. Anticipatory postural adjustments training shows promise as an effective “rescue strategy” that could be learned remotely/at home.This work was funded by Parkinson’s UK (G-2007) and was supported by the National Institute for Health and Care Research Exeter Biomedical Research Centre
Recursive Resilient State Estimation for Nonlinear Stochastic Complex Networks With Energy Harvesting Sensors Under Deception Attacks
Get PDFThis paper deals with a resilient estimation problem for certain type of time-varying complex networks of energy harvesting sensors that are vulnerable to deception attacks. Measurement signals of the underlying complex network, as measured by energy harvesting sensors, are only given to a remote estimator when the energy level is adequate to offset the energy consumption, which is at risk of deception attacks during network transmission. The deception attacks under consideration, are depicted as events occurring randomly, governed by a Bernoulli sequence. To meet the desired estimation performance, a resilient scheme is developed that addresses the side effects of random perturbations of the estimator gain when it comes to the implementation. The primary objective is to devise a resilient algorithm that can simultaneously manage energy harvesting sensors, deception attacks, and gain perturbations of the state estimator. Initially, the upper bound of the obtained error covariance is determined by making use of induction and intensive stochastic techniques. The necessary estimator gains are then identified recursively to prudently minimize this acquired bound. An illustrative example is presented ultimately to demonstrate this scheme's efficacy.10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 61933007 and 62273087);
Royal Society of the U.K.;
Alexander von Humboldt Foundation of Germany
A Method for Assessing the Risks to Sustainability Posed by Process Operations
Get PDFWe present a framework for assessing the risks to sustainability posed by any given set of processes. The objective is to improve sustainability by enabling better decision‐making in policy and business contexts. The framework can be applied to any system of processes where available information supports discovery and quantification of sustainability‐risk, defined as risk to the ability of future generations to meet their needs. Processes are screened to identify sustainability‐risks, which are scored on a common scale to avoid arbitrary weighting factors. The method yields an overall risk score for the system, and an analysis of where and how sustainability‐risk arises. We demonstrate the method by applying it to the system that provides for the UK's production and use of liquid biofuels. A set of 18 distinct causes of risk is discovered, and impacts are assessed by triple‐bottom line accounting. The innovation risk optimism bias is the highest‐scoring cause of risk, followed by price volatility associated with competition between markets for bio‐feedstocks. In this case, the wide variety of risk types and severity, and scale of action, suggests that promoting sustainability requires a tailored response to address specific risks
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