Time Metrics Research Articles

Test-retest reliability of short- and long-term heart rate variability in individuals with spinal cord injury

Study designCross-sectional.ObjectivesTo investigate test-retest reliability of heart rate variability (HRV) metrics in SCI without restriction of activity over long (24-h) and shorter durations (5-min, 10-min, 1-h, 3-h and 6-h).SettingsUniversity hospital in Khon Kaen, Thailand.MethodsForty-five participants (11 with tetraplegia and 34 with paraplegia) underwent two 24-h recordings of RR-intervals to derive time and frequency HRV metrics. Relative reliability was assessed by intraclass correlation coefficient (ICC) and absolute reliability by coefficient of variation (CV) and Bland–Altman limits of agreement (LoA).ResultsFor 5- and 10-min durations, eight of eleven HRV metrics had moderate to excellent reliability (ICC 0.40–0.76); the remaining three were poor (ICC < 0.4). HRV values from 1-h and 3-h durations showed moderate to excellent reliability (ICC of 0.46–0.81), except for 1-h reliability of ULF and TP (ICC of 0.06 and 0.30, respectively). Relative reliability was excellent (ICC of 0.77–0.92) for 6-h and 24-h durations in all HRV metrics. Absolute reliability improved as recording duration increased (lower CVs and narrower LoAs). Participants with high AD risk (SCI level at or above T6) showed lower test-retest reliability of HF and LF values than participants with low AD risk.ConclusionRelative reliability of HRV was excellent for 6-h and 24-h. The best absolute reliability values were for 24-h duration. Time-domain outcomes were more reliable than frequency domain outcomes. Participants with high risk of AD, particularly those with tetraplegia, showed lower reliability, especially for HF and LF.

DREAMPlace 4.0: Timing-Driven Placement With Momentum-Based Net Weighting and Lagrangian-Based Refinement

Optimizing timing is critical to the design closure of integrated circuits (IC). However, most existing algorithms for circuit placement focus on the optimization of wirelength instead of timing metrics. This paper presents a timing-driven placement framework. It consists of a global placement stage based on net weighting with momentum, and a detailed placement stage based on Lagrangian multipliers. By improving the preconditioners and timing engines to facilitate net weighting and discrete local search, we have achieved superior timing improvement on benchmarks from ICCAD 2015 contest, including worst negative slack (WNS) and total negative slack (TNS).

Downscaling and bias-correction contribute considerable uncertainty to local climate projections in CMIP6

Efforts to diagnose the risks of a changing climate often rely on downscaled and bias-corrected climate information, making it important to understand the uncertainties and potential biases of this approach. Here, we perform a variance decomposition to partition uncertainty in global climate projections and quantify the relative importance of downscaling and bias-correction. We analyze simple climate metrics such as annual temperature and precipitation averages, as well as several indices of climate extremes. We find that downscaling and bias-correction often contribute substantial uncertainty to local decision-relevant climate outcomes, though our results are strongly heterogeneous across space, time, and climate metrics. Our results can provide guidance to impact modelers and decision-makers regarding the uncertainties associated with downscaling and bias-correction when performing local-scale analyses, as neglecting to account for these uncertainties may risk overconfidence relative to the full range of possible climate futures.

EAEFA: An Efficient Energy-Aware Task Scheduling in Cloud Environment

The scheduling of tasks in the cloud is a major challenge for improving resource availability and decreasing the total execution time and energy consumption of operations. Due to its simplicity, efficiency, and effectiveness in identifying global optimums, electric fish optimisation (EFO) has recently garnered a lot of interest as a metaheuristic method for solving optimisation issues. In this study, we apply electric fish optimisation (EAEFA) to the problem of cloud task scheduling in an effort to cut down on power usage and turnaround time. The objective is to finish all tasks in the shortest possible time, or makespan, taking into account constraints like resource availability and task dependencies. In the EAEFA approach, a school of electric fish is used to solve a multi-objective optimization problem that represents the scheduling of tasks. Because electric fish are drawn to high-quality solutions and repelled by low-quality ones, the algorithm is able to converge to a global optimum. Experiments validate EAEFA's ability to solve the task scheduling issue in cloud computing. The suggested scheduling strategy was tested on HPC2N and other large-scale simulations of real-world workloads to measure its makespan time, energy efficiency and other performance metrics. Experimental results demonstrate that the proposed EAEFA method improves performance by more than 30% with respect to makespan time and more than 20% with respect to overall energy consumption compared to state-of-the-art methods.

The impact of off-hour mechanical thrombectomy therapy on outcomes for acute ischemic stroke: A systematic review and meta-analysis

BackgroundThe impact of off-hours and on-hours mechanical thrombectomy (MT) treatment for acute ischemic stroke (AIS) is not well understood. We conducted a systematic review and met-analysis comparing outcomes between patients undergoing off-hours MT versus on-hours MT. MethodsThis study is reported according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses recommendations. A systematic literature review of the English language literature was conducted using Web of Science, Embase, Scopus, and PubMed databases. We included all original studies comparing off-hour and on-hour outcomes or time metrics in AIS undergoing MT. R software version 4.3.1 and the ‘meta’ statistical package were used to analyze all the data presented in this study. ResultsWe included 26 studies with 82,850 patients. Patients undergoing MT during off-hours achieved lower rates of 90-day functional independence (OR 0.92, 95% CI 0.86–0.99; p = 0.04) and successful recanalization (OR 0.89, 95% CI 0.81–0.98; p = 0.014). Patients undergoing off-hours MT experienced similar rates of 90-day mortality (OR 1.07, 95% CI 0.96–1.19; p = 0.21) and sICH (OR 1.04, 95% CI 0.85–1.28; p = 0.674). Patients in the off-hour group experienced longer onset to door time (MD = 12.23 min; 95% CI 4.53–19.93; p = 0.002), imaging to puncture time (MD = 10.59 min; 95% CI 4.00–17.19; p = 0.002), and door to recanalization time (MD = 13.31 min; 95% CI 4.60–22.03; p = 0.003). ConclusionsPatients undergoing MT for AIS during off-hours experienced lower rates of functional independence. This may be attributed to treatment delays during off-hours. Future studies should work to optimize hospital workflows and identify factors which may contribute to treatment delays.

Harnessing Solar Power: A Review of Photovoltaic Innovations, Solar Thermal Systems, and the Dawn of Energy Storage Solutions

The goal of this review is to offer an all-encompassing evaluation of an integrated solar energy system within the framework of solar energy utilization. This holistic assessment encompasses photovoltaic technologies, solar thermal systems, and energy storage solutions, providing a comprehensive understanding of their interplay and significance. It emphasizes the importance of solar energy as a renewable resource and its role in addressing global energy demand and mitigating climate change. The review highlights the significance of advancements in various solar energy technologies, focusing on their environmental benefits, including greenhouse gas emissions reduction and air and water pollution mitigation. It explores the evolution of photovoltaic technologies, categorizing them into first-, second-, and third-generation photovoltaic cells, and discusses the applications of solar thermal systems such as water heaters, air heaters, and concentrators. The paper examines key advancements in energy storage solutions for solar energy, including battery-based systems, pumped hydro storage, thermal storage, and emerging technologies. It references recent published literature to present findings on energy payback time, carbon footprint, and performance metrics. Challenges to widespread adoption are discussed, including cost and economic viability, intermittency, environmental impacts, and grid integration. Strategies to overcome these challenges, such as cost reduction, policy support, energy storage integration, and sustainable practices, are presented based on published literature. By bridging gaps in existing literature, this comprehensive resource aims to equip researchers, policymakers, and industry professionals with insights into forging a sustainable and renewable energy future.

Predicting Automated Vehicle Takeover Decision During the Nighttime

Conditionally automated vehicles require drivers to take over control occasionally. To date, takeover performance has been mostly evaluated using only re-engagement time and quality metrics. However, the appropriateness of takeover decisions, which has not been considered by previous research, should also be included as a performance indicator as it reflects one’s situation awareness of the takeover scenario. The goal of this study was to use eye-tracking, demographic factors, workload, and non-driving-related task (NDRT) conditions to predict takeover decisions. Forty-three participants drove a simulated conditionally automated vehicle while performing visual NDRTs and needed to decide the most appropriate maneuver around a roadway obstacle. Six classifiers were used to predict takeover decisions. The Random Forest model achieved the best performance, and driving experience and perceived workload were the most influential features. Findings may be used to assist in the design of adaptive algorithms that support drivers taking over from automated vehicles.

Design, Simulation, and Performance Evaluation of Reactive and Proactive Ad-Hoc Routing Protocols

The primary goal of this study is to investigate and evaluate the performance of wireless Ad-Hoc routing protocols using the OPNET simulation tool, as well as to recommend the most effective routing strategies for the wireless mesh environment. Investigations have been testified to analyze the performance of the reactive and proactive Ad-Hoc routing protocols in different scenarios. Application and wireless metrics were configured that were used to test and evaluate the performance of routing protocols. The application metric includes web browsing metrics such as HTTP page response time, voice and video metrics such as end-to-end delay, and delay variation. The wireless network metrics include wireless media access delay, data dropped, wireless load, wireless retransmission attempts, and Packet Delivery Ratio. The simulation results show that the AODV overcome DSR and OLSR in terms of PDR (76%), wireless load (22.692 Mbps), voice delay variation (102.685 ms), HTTP page response time (15.317 sec), voice and video packet end-to-end delay (206.527 and 25.294 ms), wireless media access delay (90.150 ms), data dropped (10.003 Mbps), wireless load (22.692 Mbps), and wireless retransmission attempts (0.392 packets).

An Experimental Protocol for Human Stress Investigation in Manufacturing Contexts: Its Application in the NO-STRESS Project

Stress is a critical concern in manufacturing environments, as it impacts the well-being and performance of workers. Accurate measurement of stress is essential for effective intervention and mitigation strategies. This paper introduces a holistic and human-centered protocol to measure stress in manufacturing settings. The three-phased protocol integrates the analysis of physiological signals, performance indicators, and the human perception of stress. The protocol incorporates advanced techniques, such as electroencephalography (EEG), heart rate variability (HRV), galvanic skin response (GSR), and electromyography (EMG), to capture physiological responses associated with stress. Furthermore, the protocol considers performance indicators as an additional dimension of stress measurement. Indicators such as task execution time, errors, production rate, and other relevant performance metrics contribute to a comprehensive understanding of stress in manufacturing environments. The human perception of stress is also integrated into the protocol, recognizing the subjective experience of the individual. This component captures self-assessment and subjective reports, allowing for a more nuanced evaluation of stress levels. By adopting a holistic and human-centered approach, the proposed protocol aims to enhance our understanding of stress factors in manufacturing environments. The protocol was also applied in the automotive industry and plastic component manufacturing. The insights gained from this protocol can inform targeted interventions to improve worker well-being, productivity, and overall organizational performance.

Towards reuse and recycling of lithium-ion batteries: tele-robotics for disassembly of electric vehicle batteries.

Disassembly of electric vehicle batteries is a critical stage in recovery, recycling and re-use of high-value battery materials, but is complicated by limited standardisation, design complexity, compounded by uncertainty and safety issues from varying end-of-life condition. Telerobotics presents an avenue for semi-autonomous robotic disassembly that addresses these challenges. However, it is suggested that quality and realism of the user's haptic interactions with the environment is important for precise, contact-rich and safety-critical tasks. To investigate this proposition, we demonstrate the disassembly of a Nissan Leaf 2011 module stack as a basis for a comparative study between a traditional asymmetric haptic-"cobot" master-slave framework and identical master and slave cobots based on task completion time and success rate metrics. We demonstrate across a range of disassembly tasks a time reduction of 22%-57% is achieved using identical cobots, yet this improvement arises chiefly from an expanded workspace and 1:1 positional mapping, and suffers a 10%-30% reduction in first attempt success rate. For unbolting and grasping, the realism of force feedback was comparatively less important than directional information encoded in the interaction, however, 1:1 force mapping strengthened environmental tactile cues for vacuum pick-and-place and contact cutting tasks.

Multivariate modeling of magnetic resonance biomarkers and clinical outcome measures for Duchenne muscular dystrophy clinical trials.

Although regulatory agencies encourage inclusion of imaging biomarkers in clinical trials for Duchenne muscular dystrophy (DMD), industry receives minimal guidance on how to use these biomarkers most beneficially in trials. This study aims to identify the optimal use of muscle fat fraction biomarkers in DMD clinical trials through a quantitative disease-drug-trial modeling and simulation approach. We simultaneously developed two multivariate models quantifying the longitudinal associations between 6-minute walk distance (6MWD) and fat fraction measures from vastus lateralis and soleus muscles. We leveraged the longitudinal individual-level data collected for 10 years through the ImagingDMD study. Age of the individuals at assessment was chosen as the time metric. After the longitudinal dynamic of each measure was modeled separately, the selected univariate models were combined using correlation parameters. Covariates, including baseline scores of the measures and steroid use, were assessed using the full model approach. The nonlinear mixed-effects modeling was performed in Monolix. The final models showed reasonable precision of the parameter estimates. Simulation-based diagnostics and fivefold cross-validation further showed the model's adequacy. The multivariate models will guide drug developers on using fat fraction assessment most efficiently using available data, including the widely used 6MWD. The models will provide valuable information about how individual characteristics alter disease trajectories. We will extend the multivariate models to incorporate trial design parameters and hypothetical drug effects to inform better clinical trial designs through simulation, which will facilitate the design of clinical trials that are both more inclusive and more conclusive using fat fraction biomarkers.

Comparing 5G mobile stroke unit and emergency medical service in patients acute ischemic stroke eligible for t-PA treatment: A prospective, single-center clinical trial in Ya'an, China.

This study aims to assess and compare the functional outcomes of patients with acute ischemic stroke (AIS) eligible for tissue plasminogen activator (t-PA) treatment who received care from either a fifth-generation(5G) mobile stroke unit (MSU) or traditional emergency medical service (EMS). The study recruited patients between February 2020 and January 2022, with the final 90-day follow-up concluded in April 2022. Prior to enrollment, patients were assigned to either EMS or MSU care based on predetermined rules. The primary outcome measure was the Modified Rankin Scale (mRS) score at 90 days, with secondary outcome measures including time metrics, mRS and National Institutes of Health Stroke Scale scores at 7-day follow-up, and hospitalization costs. Of the 2281 enrolled patients, 207 were eligible for t-PA treatment, with 101 allocated to MSU care and 106 to EMS care. The percentage of patients achieving a favorable mRS score (0-2) at 90 days was 82.2% in the MSU group compared to 72.6% in the EMS group (p < .05). Median times from symptom onset to thrombolysis were 146 min in the MSU group and 204 min in the EMS group, while median times from ambulance alert to computed tomography (CT)completion were 53 and 128 min, respectively. Hospitalization charges averaged approximately $3592 in the MSU group and $4800 in the EMS group. Our findings indicate that 5G MSU care significantly reduces the time from symptom onset to stroke diagnosis and intravenous thrombolysis in patients with AIS, resulting in improved functional outcomes compared to EMS care. As China continues its deployment of 5G technology and other digital infrastructures, the adoption of 5G MSU care on a broader scale may eventually supplant traditional stroke treatment approaches.

Non-ECG-gated cardiac CT angiography in acute stroke is feasible and detects sources of embolism.

A significant portion of cryptogenic stroke is hypothesized to be secondary to cardiac embolism. However, transthoracic echocardiogram is usually delayed after stroke, and more detailed cardiac imaging is not routinely done. This study aimed to determine whether non-ECG-gated cardiac CT angiography (cCTA) during hyperacute stroke would provide diagnostic quality images and act as an adjunct modality of cardiac imaging to detect sources of emboli. In this single-center prospective cohort study, modified Code Stroke imaging was implemented with a 64-slice CT scanner, where the longitudinal axis of CT angiography was extended from the carina to the diaphragm. The primary outcomes of image quality, recruitment feasibility, impact on hyperacute time metrics, and additional radiation dose were assessed. Secondary outcomes consisted of detection of high-risk cardiac sources of embolism, mediastinal or lung pathology, and impact on etiologic classification. One hundred and twenty eligible patients were enrolled, of which 105 (87.5%) had good/moderate quality images for motion artifact and 119 (99.2%) for contrast opacification. Total CT time, door-to-needle time, and door-to-groin puncture time were unchanged with the addition of cCTA. Eighty-nine patients received a final diagnosis of ischemic stroke, of which 12/89 (13.5%) had high-risk cardioembolic findings on cCTA. Incidental findings, such as pulmonary embolism (PE) (7/89, 7.9%) and malignancy (6/89, 6.7%), were observed. cCTA led to changes in management for 19/120 (15.8%) of all patients, and reclassification of stroke etiology for 8/89 (9%) of patients. Non-ECG-gated cCTA can be feasibly incorporated into Code Stroke and provide diagnostic quality images without delays in hyperacute time metrics. It can detect high-risk cardiac sources, and other findings impacting patient care. This may help reclassify a subset of cryptogenic stroke cases and improve secondary prevention.

Optimal Reactive Power Dispatch in ADNs using DRL and the Impact of Its Various Settings and Environmental Changes.

Modern active distribution networks (ADNs) witness increasing complexities that require efforts in control practices, including optimal reactive power dispatch (ORPD). Deep reinforcement learning (DRL) is proposed to manage the network's reactive power by coordinating different resources, including distributed energy resources, to enhance performance. However, there is a lack of studies examining DRL elements' performance sensitivity. To this end, in this paper we examine the impact of various DRL reward representations and hyperparameters on the agent's learning performance when solving the ORPD problem for ADNs. We assess the agent's performance regarding accuracy and training time metrics, as well as critic estimate measures. Furthermore, different environmental changes are examined to study the DRL model's scalability by including other resources. Results show that compared to other representations, the complementary reward function exhibits improved performance in terms of power loss minimization and convergence time by 10-15% and 14-18%, respectively. Also, adequate agent performance is observed to be neighboring the best-suited value of each hyperparameter for the studied problem. In addition, scalability analysis depicts that increasing the number of possible action combinations in the action space by approximately nine times results in 1.7 times increase in the training time.

Timing and Performance Metrics for TWR-K70F120M Device

Currently, single-board computers (SBCs) are sufficiently powerful to run real-time operating systems (RTOSs) and applications. The purpose of this research was to investigate the timing performance of an NXP TWR-K70F120M device with μClinux OS on concurrently running tasks with real-time features and constraints, and provide new and distinct technical data not yet available in the literature. Towards this goal, a custom-built multithreaded application with specific compute-intensive sorting and matrix operations was developed and applied to obtain measurements in specific timing metrics, including task execution time, thread waiting time, and response time. In this way, this research extends the literature by documenting performance results on specific timing metrics. The performance of this device was additionally benchmarked and validated against commonly used platforms, a Raspberry Pi4 and BeagleBone AI SBCs. The experimental results showed that this device stands well both in terms of timing and efficiency metrics. Execution times were lower than with the other platforms, by approximately 56% in the case of two threads, and by 29% in the case of 32-thread configurations. The outcomes could be of practical value to companies which intend to use such low-cost embedded devices in the development of reliable real-time industrial applications.

Possible Influence of Ethnicity on Computed Tomography Perfusion Parameter Thresholds in Acute Ischaemic Stroke

Introduction: Tissue at risk, as estimated by CT perfusion utilizing Tmax+6, correlates with final infarct volume (FIV) in acute ischaemic stroke (AIS) without reperfusion. Tmax thresholds are derived from Western ethnic populations but not from ethnic Asian populations. We aimed to investigate the influence of ethnicity on Tmax thresholds. Methods: From a clinical-imaging registry of Australian and Indonesian stroke patients, we selected a participant subgroup with the following inclusion criteria: AIS under 24 h and absence of reperfusion therapy. Clinical data included demographics, time metrics, stroke severity, pre-morbid, and 3-month Modified Rankin Score. Baseline computed tomography perfusion and MRI <72 h were performed. Volumes of Tmax utilizing different thresholds and FIVs were calculated. Spearman correlation was used to evaluate relationship involving ordinal variables and calculate the optimal Tmax threshold against FIV in both populations. Results: Two hundred patients were included in the study sample, 100 in Jakarta and 100 in Geelong. The median National Institutes of Health Stroke Scale (IQR) were 6 (3–11) and 3 (1–5), respectively. The median Tmax+6 (IQR) was 0 (0–46.5) in Jakarta group and 0 (0–7.5) in Geelong group. The median FIV (IQR) was 0 (0–30.5) and 0 (0–5.5). Tmax+8 s in Jakarta population against FIV showed Spearman’s coefficient ρ = 0.72, representing the optimal Tmax threshold. Tmax+6 s showed Spearman’s coefficient ρ = 0.51 against FIV in the Geelong population. Conclusion: Tmax thresholds approximating FIV were possibly different in the Asian when compared with the non-Asian populations. Future studies are required to extend and confirm the validity of our findings.

Comparison between different referral strategies for acute ischemic stroke patients in a hub-spoke emergency stroke network: a real-world experience in south-east Lazio.

To describe different referral strategies for acute ischemic stroke (AIS) patients in a Hub-Spoke emergency stroke network with their incidence, time metrics and related outcomes. Referral paradigms were defined as follows: primary transfer to the comprehensive stroke center (CSC) from a remote region, called mothership (MS); secondary transfer to the CSC from a primary stroke center where intravenous thrombolysis was available, called drip and ship (DS); secondary transfer to the CSC from a community hospital where no reperfusion therapy was available, called ship and drip (SD); primary transfer to the CSC from its catchment area, called direct CSC (dCSC). Among 517 anterior circulation AIS patients treated with mechanical thrombectomy between 2015 and 2020, 16.6% of them were SD, in addition to the well-known referral paradigms of MS (21.8%) and DS (18.1%). This rate grew to 30% when only patients whose place of onset was outside the CSC catchment area were considered. In the SD group, onset to CSC and onset to groin were significantly longer (178±80 min vs. 102±60 min, p<0.001, and 277±77 min vs. 211±61 min, p<0.001, respectively), and the risk of any intracranial hemorrhage (ICH) was significantly higher (OR: 2.514; 95%CI: 1.18-5.35, p=0.017) compared to MS. In this hub-spoke stroke network, a high proportion of SD paradigm was found, which was associated with longer times to treatment and higher rates of any ICH. A closer cooperation between hospital stroke physicians, national health system staff, and paramedics is warranted to identify the most appropriate referral strategy for each patient.

Quantitative impact analysis of priority policy applied to BIM-based design validation

Building information modeling (BIM) design validation is primarily aimed at responding quickly to serious design errors. A prompt response to BIM request for information (RFI) can significantly enhance the BIM return on investment (ROI). Although prior research has identified additional factors to consider while assessing the benefits of BIM coordination, it was not possible to conduct an economic assessment. Therefore, this study fills this gap by conducting an economic assessment of the introduction of priority policies in BIM coordination using priority queue model. The findings demonstrate that the introduction of priority policies can impact the optimal BIM staffing and the engineers' waiting cost for high-priority RFIs. We quantify the BIM ROI that can be improved by introducing the priority policy in BIM coordination, using time and cost metrics derived from the queue model.

An Improved Switch Migration Method-Based Efficient Load Balancing for Multiple Controllers in Software-Defined Networks

The present work proposed an improved switch migration method (ISMM) for balancing the controller load to migrate the switch from overloaded to under-loaded controller. This method is used on each controller during controller load balance in order to decide the state of controllers. The implementation was conducted using the Mininet simulation tool. The performance of the proposed solution has been evaluated by using throughput, response time, and packet loss metrics. Accordingly, the simulation results indicated that this method has improved throughput by 7.6% over SSMS and 1.8% over CAMD, improved response time 8.3% over SSMS and 4% over CAMD, and improved the packet loss 8% over SSMS and 1.3% over CAMD during the incoming traffic load between 501p/s and 5000p/s. Thus, the performance of ISMM has shown efficient results over SSMS and CAMD among all assessed metrics by balancing the load between controllers.

Radio frequency identification technology reduce intravenous thrombolysis time in acute ischemic stroke.

To inspect whether time management with radio frequency identification technology (RFID) reduces symptom onset-to-intravenous thrombolysis time (OTT) in acute ischemic stroke (AIS). In the retrospective study, patients with AIS, transferred by Emergency Medical Services (EMS) to Hunan Provincial People's Hospital between September 2019 to June 2022, divided into three groups, as traditional group, in-hospital RFID group and whole process RFID group. Baseline characteristics and time metrics were compared. After the whole emergency process applied with RFID time management, Door to intravenous thrombolysis time (DNT) was reduced from 125.00±43.16 min to 32.59±25.45 min (F = 121.857, p<0.001), and OTT was reduced from 235.53±57.27 min to 144.31±47.96 min (F = 10.377, p<0.001). Time management with RFID is effective in reducing OTT in AIS patients with thrombolysis treatment.