Time Variability Research Articles

Analysis of Intravenous Ketamine Bolus in Pediatric Emergency Care

Considering the increasing use of intravenous ketamine in pediatric emergency care, particularly for sedation, analgesia, and management of severe conditions such as traumatic brain injury and suicidal ideation, there is a need to critically evaluate its efficacy and safety in these settings. This study aims to systematically review and analyze various studies that have investigated the use of intravenous ketamine bolus in pediatric emergency care, focusing on its clinical outcomes, safety profile, and overall effectiveness. To achieve this, a narrative literature review was conducted, examining studies published between 2014 and 2023. The review included randomized controlled trials, observational studies, and case reports sourced from reputable databases such as PubMed, Scopus, and Web of Science. The results of the review indicate that intravenous ketamine is effective in providing rapid sedation and analgesia, with a favorable safety profile when administered by trained healthcare professionals. Specifically, it was observed that ketamine significantly reduces pain intensity, lowers suicidal ideation, and effectively manages intracranial pressure in children with severe traumatic brain injury. However, the review also highlights the variability in recovery times and the incidence of mild to moderate side effects, such as dizziness, nausea, and drowsiness. In addition, the need for rescue doses was more frequent in intravenous administration compared to intramuscular routes, though intravenous administration offered quicker onset and shorter duration of action. It is concluded that while intravenous ketamine is a valuable tool in pediatric emergency care, its administration should be carefully monitored, particularly in high-risk patients, to mitigate potential adverse effects. Further research is needed to refine dosing strategies, explore long-term outcomes, and establish standardized protocols to maximize the therapeutic benefits of ketamine while minimizing risks.

Cardiac autonomic responses in relation to cognitive workload during simulated military flight

Understanding the operator's cognitive workload is crucial for efficiency and safety in human–machine systems. This study investigated how cognitive workload modulates cardiac autonomic regulation during a standardized military simulator flight. Military student pilots completed simulated flight tasks in a Hawk flight simulator. Continuous electrocardiography was recorded to analyze time and frequency domain heart rate variability (HRV). After the simulation, a flight instructor used a standardized method to evaluate student pilot's individual cognitive workload from video-recorded flight simulator data. Results indicated that HRV was able to differentiate flight phases that induced varying levels of cognitive workload; an increasing level of cognitive workload caused significant decreases in many HRV variables, mainly reflecting parasympathetic deactivation of cardiac autonomic regulation. In conclusion, autonomic physiological responses can be used to examine reactions to increased cognitive workload during simulated military flights. HRV could be beneficial in assessing individual responses to cognitive workload and pilot performance during simulator training.

Investigations of sequential excavation and reinforcement in tunnels based on the extended three-dimensional discontinuous deformation analysis method

The unloading effect of excavation is the key factor leading to rock mass instability, and bolt support is the key means of controlling the stability. However, the original three-dimensional discontinuous deformation analysis method (3D DDA) can only simulate rock mass instability and bolt support after the tunnel is excavated, which makes it difficult to study the effect of tunnel excavation and bolt support on rock mass stability. Therefore, an algorithm to confirm the excavated blocks and reinforced blocks based on the volume judgment method (VJM) was proposed in this paper. Sequential excavation and reinforcement in tunnels can be simulated by introducing the time variables of block excavation and bolt deployment into the 3D DDA method. By embedding these two algorithms in the 3D DDA method, an extended 3D DDA method for sequential excavation and reinforcement in tunnels was developed, named the 3D DDA_ES method. Based on the 3D DDA_ES method, the collapse that occurred during the construction of the Huangjiazhuang Tunnel was simulated, and the displacement of key blocks and the axial force of the bolts were analyzed. According to the simulation results, the axial force on the bolts is strongly related to the position of the key blocks, and the axial force on the bolts at the tunnel roof is much greater than that at the tunnel arch shoulder. In this regard, these bolts with axial forces less than 1 kN are removed during the simulation, and the key blocks remain stable with a maximum displacement of 12 cm. The research results can provide a theoretical basis for tunnel construction and reinforcement parameter optimization for similar projects.

A prescriptive analytics approach for evaluating two production systems: Simulation optimization algorithm

Production systems influence cost performance and carbon emissions. Environmental concerns compel companies to optimize energy efficiency in their production processes. This study explores the dilemma associated with fixed-time and fixed-lot systems during random disruptions and how these systems can improve performance. We employ simulation optimization models in business analytics using the discrete event simulation provided by the SimPy library within a Python environment. The study is based on the statistical analysis of data collected from 624,000 simulated hours. Our analysis reveals that a higher service level tilts the balance, favoring adopting a fixed-time production system in scenarios characterized by significant disruptions. A system with higher demand variability and lower standalone workstation availability (indicative of more variable production) tends to favor a fixed-time batch production approach. When workstations operate at low-capacity utilization combined with high standalone availability, the fixed-lot batch production system becomes more cost-effective. Overall, the fixed-time system demonstrates a superior capacity to accommodate higher production variability levels than the fixed-lot system. This paper contributes to the existing literature by providing simulation-optimization evidence to assess the relative efficiencies of fixed-size and fixed-time lot batch production systems. This paper considers the impact of random disruptions on operational efficiency within fixed-size lot batch production systems, highlighting the consequences of variability in lot completion times. The study also contributes to strategically selecting production systems to optimize energy usage in manufacturing processes.

Morphological characteristics of activated sludge recovered from biological reactors impact on the energy requirement for centrifugal dewatering

The effect of sludge dewatering on handling and transport costs as well as the impact of various parameters like sludge characteristics, the used dewatering equipment and the adopted specific operating conditions, on the efficiency of this step, were considered in the present study. The influence of a laboratory-scale centrifugation for dewatering activated sludge (AS) was also investigated. Additionally, models to describe the relationships between independent variables like centrifugation speed, AS volume and fixed time and dependent variables like the percentage of solid cake (% GS). The used approach was based on the response surface methodology (RSM) along with a central composite design experiment, considering three distinct types of AS: healthy (BS), partially bulking (BF), and deflocculated (BD) sludges. The morphological characteristics of the sludge do have an effect on the operating conditions for the centrifugation, hence the energy consumption for a desired dewatering level. For the case of BS sludge, a centrifugation at 2600 rpm for 10 min, using a 10.3 mL plug, led to a solid cake of 12.65 %, whereas for BD sludge, with a higher centrifugation at 3000 rpm for 17.30 min and a smaller plug volume (8 mL) led to 6.82 %, roughly half of the previous percentage.

Multifractal Hopscotch in Hopscotch by Julio Cortázar.

Punctuation is the main factor introducing correlations in natural language written texts and it crucially impacts their overall effectiveness, expressiveness, and readability. Punctuation marks at the end of sentences are of particular importance as their distribution can determine various complexity features of written natural language. Here, the sentence length variability (SLV) time series representing Hopscotch by Julio Cortázar are subjected to quantitative analysis with an attempt to identify their distribution type, long-memory effects, and potential multiscale patterns. The analyzed novel is an important and innovative piece of literature whose essential property is freedom of movement between its building blocks given to a reader by the author. The statistical consequences of this freedom are closely investigated in both the original, Spanish version of the novel, and its translations into English and Polish. Clear evidence of rich multifractality in the SLV dynamics, with a left-sided asymmetry, however, is observed in all three language versions as well as in the versions with differently ordered chapters.

Modeling and Optimization of Ellagic Acid from Chebulae Fructus Using Response Surface Methodology Coupled with Artificial Neural Network.

The dried ripe fruit of Terminalia chebula Retz. is a common Chinese materia medica, and ellagic acid (EA), isolated from the plant, is an important bioactive component for medicinal purposes. This study aimed to delineate the optimal extraction parameters for extracting the EA content from Chebulae Fructus (CF), focusing on the variables of ethanol concentration, extraction temperature, liquid-solid ratio, and extraction time. Utilizing a combination of the response surface methodology (RSM) and an artificial neural network (ANN), we systematically investigated these parameters to maximize the EA extraction efficiency. The extraction yields for EA obtained under the predicted optimal conditions validated the efficacy of both the RSM and ANN models. Analysis using the ANN-predicted data showed a higher coefficient of determination (R2) value of 0.9970 and a relative error of 0.79, compared to the RSM's 2.85. The optimal conditions using the ANN are an ethanol concentration of 61.00%, an extraction temperature of 77 °C, a liquid-solid ratio of 26 mL g-1 and an extraction time of 103 min. These findings significantly enhance our understanding of the industrial-scale optimization process for EA extraction from CF.

The interplay of dopaminergic genotype and parent-child relationship in relation to intra-individual response time variability in preschoolers: A replication study.

Intra-individual response time variability (IIRTV) during cognitive performance is increasingly recognized as an important indicator of attentional control (AC) and related brain region function. However, what determinants contribute to preschoolers' IIRTV received little attention. The present study explored the interaction of dopaminergic polygenic composite score (DPCS) and the parent-child relationship in relation to preschoolers' IIRTV. In the initial sample, 452 preschoolers (M age=5.17, SD=0.92) participated in the study. The modified Flanker task was used to evaluate children's IIRTV and their parents were requested to complete the Parent-Child Relationship Scale to assess the parent-child relationship (closeness/conflict). DNA data were extracted from children's saliva samples, and a DPCS was created by the number of COMT, DAT1, and DRD2 alleles associated with lower dopamine levels. Results showed that DPCS significantly interacted with the parent-child closeness to impact preschoolers' IIRTV. Specifically, preschoolers with higher DPCS exhibited lower IIRTV under higher levels of the parent-child closeness, and greater IIRTV under lower levels of the parent-child closeness compared to those with lower DPCS, which supported the differential susceptibility theory (DST). A direct replication attempt with 280 preschoolers (M age=4.80, SD=0.86) was conducted to investigate whether the results were in accordance with our exploratory outcomes. The interactive effect of DPCS and the parent-child closeness on IIRTV was confirmed. Additionally, the significant interactive effect of DPCS and the parent-child conflict on IIRTV was found in the replication study. The findings indicate that preschoolers' IIRTV, as an indicator of AC and related brain region function, is influenced by the interactions of dopaminergic genotypes and the parent-child relationship. RESEARCH HIGHLIGHTS: We investigated the Gene × Environment mechanism to underline the intra-individual response time variability as an indicator of attentional control (AC) in Chinese preschoolers. Dopaminergic polygenic composite score (COMT, DAT1, and DRD2) interacted with the parent-child relationship to predict preschoolers' intra-individual reaction time variability. A direct replication attempt has been conducted, and the results were in accordance with our exploratory outcomes, which increased the credibility of the present findings. The findings highlight the importance of considering precursors, including polygenic and environmental factors, which contribute to the development of early cognitive performance such as AC.

Analytical solution to the two-dimensional inverse heat conduction problem in an axisymmetric cylindrical coordinate system

The inverse heat conduction problem involves estimating an unknown cooling or heating action based on internal temperature histories in a body. Such a problem is ill-posed because the estimated results are highly sensitive to input data noise. An analytical solution is developed for the two-dimensional inverse heat conduction problem in an axisymmetric cylindrical coordinate system using the Laplace transform technique. On the basis of the known temperatures at multiple measuring points distributed on two cylindrical measuring surfaces along the axial direction inside the solid, the expressions for the surface temperature and heat flux are explicitly obtained in the form of a power series of time and eigenfunctions of the space variable. A comprehensive estimation error assessment is conducted using the internal temperature distribution that is obtained using a direct heat conduction analysis under the prescribed stationary and moving boundary conditions. The constant thermal condition is well reproduced using the present inverse solution, except in the vicinity of the discontinuity point. In addition, the effective heat flux and effective heat transfer coefficient are introduced to obtain the best estimation of the transient heat transfer in the major cooling area of the rotating cylinder.

Stoking the fires of professional resistance: Trainees' efforts across time.

Researchers who study acts of resistance largely focus on efforts when they are at their peak, giving the impression that those who resist are in a constant state of arousal. What is missing in such studies is the variable of time, which is theorised to be intimately connected to power and resistance. To explore this aspect, we followed a group of trainees engaged in professional resistance against social injustice over the period of 1 year to understand how their efforts shifted across time. This longitudinal approach was meant to capture the temporality of resistance, specifically how time affects resistance efforts. Using a constructivist grounded theory approach for data collection and analysis, we conducted follow-up interviews with 13 trainees approximately 10 months apart. Interviews were analysed using holistic narrative analysis, in which we analysed contexts, subjectivities and interactions across the two time points. We then conducted a cross-case analysis and restoried the data to develop an understanding of how resistance shifts across time. Finally, we contextualised the data using the metaphor of open and zombie wildfires. The findings demonstrate that when trainees transition to new institutions or professional positions, their access to power and interactions with colleagues shift, thus making it challenging for them to resist in ways they had done so earlier. In transitions where trainees were given power, the flames of resistance continued to blaze visibly. In other cases, without an appreciable change in power, resistance resembled more of a 'zombie fire', smouldering quietly underfoot. Examining trainees' acts of resistance across time demonstrates that the work of advocacy and resistance is extremely taxing for trainees. Therefore, when they experience shifts in their context or subjectivity, they conserve energy and strategise their next move. This study provides new insight on the relationship between time and resistance.

A human centered design approach to define and measure documentation quality using an EHR virtual simulation.

Electronic health record (EHR) documentation serves multiple functions, including recording patient health status, enabling interprofessional communication, supporting billing, and providing data to support the quality infrastructure of a Learning Healthcare System. There is no definition and standardized method to assess documentation quality in EHRs. Using a human-centered design (HCD) approach, we define and describe a method to measure documentation quality. Documentation quality was defined as timely, accurate, user-centered, and efficient. Measurement of quality used a virtual simulated standardized patient visit via an EHR vendor platform. By observing and recording documentation efforts, nurse practitioners (NPs) (N = 12) documented the delivery of an Age-Friendly Health System (AFHS) 4Ms (what Matters, Medication, Mentation, and Mobility) clinic visit using a standardized case. Results for timely documentation indicated considerable variability in completion times of documenting the 4Ms. Accuracy varied, as there were many types of episodes of erroneous documentation and extra time in seconds in documenting the 4Ms. The type and frequency of erroneous documentation efforts were related to navigation burden when navigating to different documentation tabs. The evaluated system demonstrated poor usability, with most participants scoring between 60 and 70 on the System Usability Scale (SUS). Efficiency, measured as click burden (the number of clicks used to navigate through a software system), revealed significant variability in the number of clicks required, with the NPs averaging approximately 13 clicks above the minimum requirement. The HCD methodology used in this study to assess the documentation quality proved feasible and provided valuable information on the quality of documentation. By assessing the quality of documentation, the gathered data can be leveraged to enhance documentation, optimize user experience, and elevate the quality of data within a Learning Healthcare System.

Noninvasive quantification of [18F]SynVesT-1 binding using simplified reference tissue model 2.

[18F]SynVesT-1, a positron emission tomography (PET) radiotracer for the synaptic vesicle glycoprotein 2A (SV2A), demonstrates kinetics similar to [11C]UCB-J, with high brain uptake, fast kinetics fitting well with the one-tissue compartment (1TC) model, and excellent test-retest reproducibility. Challenges arise due to the similarity between k2 and [Formula: see text] (efflux rate of the reference region), when applying the simplified reference tissue model (SRTM) and related methods in [11C]UCB-J studies to accurately estimate [Formula: see text]. This study evaluated the suitability of these methods to estimate [18F]SynVesT-1 binding using centrum semiovale (CS) or cerebellum (CER) as reference regions. Seven healthy participants underwent 120-min PET scans on the HRRT scanner with [18F]SynVesT-1. Six participants underwent test and retest scans. Arterial blood sampling and metabolite analysis provided input functions for the 1TC model, serving as the gold standard for kinetic parameters values. SRTM, coupled SRTM (SRTMC) and SRTM2 estimated were applied to estimate [Formula: see text](ref: CS) and DVRCER(ref: CER) values. For SRTM2, the population average of [Formula: see text] was determined from the 1TC model applied to the reference region. Test-retest variability and minimum scan time were also calculated. The 1TC k2 (1/min) values for CS and CER were 0.031 ± 0.004 and 0.021 ± 0.002, respectively. Although SRTMC [Formula: see text] was much higher than 1TC [Formula: see text], SRTMC underestimated BPND(ref: CS) and DVRCER by an average of 3% and 1% across regions, respectively, due to similar bias in k2 and [Formula: see text] estimation. SRTM underestimated BPND(ref: CS) by an average of 3%, but with the CER as reference region, SRTM estimation was unstable and DVRCER underestimation varied by region (mean 10%). Using population average [Formula: see text] values, SRTM2 BPND and DVRCER showed the best agreement with 1TC estimates. Our findings support the use of population [Formula: see text] value in SRTM2 with [18F]SynVesT-1 for the estimation of [Formula: see text] or DVRCER, regardless of the choice of reference region.

Synthesis of the acidic/magnetic catalyst x-MoO3/Ni0.5Zn0.5Fe2O4 by combustion reaction and evaluation of its catalytic potential/reuse in biodiesel production

The objective of this work was to synthesize a new catalyst x-MoO3/Ni0.5Zn0.5Fe2O4 using the combustion reaction method and to evaluate its catalytic potential and reuse in biodiesel production from waste oil, optimizing the process through experimental design. The catalysts were characterized in terms of structure by X-ray diffraction and phase quantification by Rietveld refinement, surface area by the Brunauer-Emmett-Teller technique, experimental density by helium pycnometry, acidity tests by ammonia desorption at programmed temperature, chemical analysis by X-ray fluorescence, morphology by scanning and transmission electron microscopy, and catalytic properties. The products of the simultaneous transesterification and esterification reactions were characterized by gas chromatography and acidity index. The results indicate the formation of catalysts with surface area ranging from 1.5 to 1.7 m2/g and density ranging from 4.5 to 5.1 g/cm3, composed of major crystalline phases of MoO3 in the orthorhombic configuration and cubic Ni0.5Zn0.5Fe2O4 ferrite, with total acidity ranging from 70 to 182 μmol/g of NH3. Morphological characterization revealed that the catalyst comprises irregular plates of various sizes and shapes with a wide range of cluster sizes. In the simultaneous transesterification and esterification reactions of residual oil, the catalysts were active under all conditions tested, with emphasis on the catalyst containing 50 % Mo ions and 50 % Ni0.5Zn0.5Fe2O4 presenting the best catalytic performance with a conversion of 95 % in ethyl esters and a reduction of 71 % in acidity, with a service life of 6 cycles, an average conversion of 90 % and good thermal and structural stability after use. The experimental design was significant and predictive, with a confidence level of 95 %. Statistical analysis identified that all input variables (temperature, time, and amount of catalyst) were significant for the adopted design. The new catalyst composed of molybdenum, iron, nickel, and zinc has a positive impact on biodiesel synthesis from frying oil and ethanol.

A Measure of Departure from Marginal Homogeneity using Continuation Odds for Square Contingency Tables with Ordered Categories

For the analysis of square contingency tables with ordinal classifications, the marginal homogeneity (MH) model is the one of important models. Some measures for analyzing the degree of departure from the MH model have been proposed. This study proposes a new measure using the continuation odds. Continuation odds may be considered as discrete time hazard. The proposed measure is expressed in the form of Cressie-Read’s power-divergence (including the Kullback-Leibler divergence) or Patil and Taillie’s diversity index (including Shannon entropy). This study derives a plug-in estimator of the proposed measure and an approximate confidence interval for the proposed measure. Through numerical examples, we evaluate the performances of them. Additionally. the usefulness of the proposed measure is demonstrated by applying it to real data that the row and column variables are the discrete survival time variables.

Accounting for cellular-level variation in lysis: implications for virus-host dynamics.

Viral impacts on microbial populations depend on interaction phenotypes-including viral traits spanning the adsorption rate, latent period, and burst size. The latent period is a key viral trait in lytic infections. Defined as the time from viral adsorption to viral progeny release, the latent period of bacteriophage is conventionally inferred via one-step growth curves in which the accumulation of free virus is measured over time in a population of infected cells. Developed more than 80 years ago, one-step growth curves do not account for cellular-level variability in the timing of lysis, potentially biasing inference of viral traits. Here, we use nonlinear dynamical models to understand how individual-level variation of the latent period impacts virus-host dynamics. Our modeling approach shows that inference of the latent period via one-step growth curves is systematically biased-generating estimates of shorter latent periods than the underlying population-level mean. The bias arises because variability in lysis timing at the cellular level leads to a fraction of early burst events, which are interpreted, artefactually, as an earlier mean time of viral release. We develop a computational framework to estimate latent period variability from joint measurements of host and free virus populations. Our computational framework recovers both the mean and variance of the latent period within simulated infections including realistic measurement noise. This work suggests that reframing the latent period as a distribution to account for variability in the population will improve the study of viral traits and their role in shaping microbial populations.IMPORTANCEQuantifying viral traits-including the adsorption rate, burst size, and latent period-is critical to characterize viral infection dynamics and develop predictive models of viral impacts across scales from cells to ecosystems. Here, we revisit the gold standard of viral trait estimation-the one-step growth curve-to assess the extent to which assumptions at the core of viral infection dynamics lead to ongoing and systematic biases in inferences of viral traits. We show that latent period estimates obtained via one-step growth curves systematically underestimate the mean latent period and, in turn, overestimate the rate of viral killing at population scales. By explicitly incorporating trait variability into a dynamical inference framework that leverages both virus and host time series, we provide a practical route to improve estimates of the mean and variance of viral traits across diverse virus-microbe systems.

Prediction model for the bond behaviour of low-corrosion reinforced concrete considering corrosion time variability

Corrosion greatly affects the bond behaviour of reinforced concrete. In the case of reinforcing low-corrosion reinforced concrete, the bond strength of steel bars and concrete is at an enhanced stage. Accurate prediction of bond behaviour at this stage is crucial for the rational reinforcement. This study designed ten groups, totalling 30 pull-out specimens, were accelerated corroded with various current densities and electrification times. Through 3D scanning and image analysis technology, we observed that increasing the current density yielded less homogeneous corrosion, creating pit-like rust marks. Meanwhile, we developed a model for predicting the corrosion level. The model is applicable to the corrosion level design of accelerated corrosion. Pull-out tests showed that as corrosion increased, the specimen failure mode changed from pull-out to splitting and back to pull-out, with the bond strength first increasing and then decreasing. A bond-slip prediction model for corroded reinforced concrete was also established, considering the effects of corrosion on bond strength in different stages, especially the enhancement stage. The model performs well in predicting the bond behaviour of low-corrosion reinforced concrete and can be used in conjunction with corrosion prediction models and provides guidance for reinforcement.

Balancing efficacy and computational burden: weighted mean, multiple imputation, and inverse probability weighting methods for item non-response in reliable scales.

Scales often arise from multi-item questionnaires, yet commonly face item non-response. Traditional solutions use weighted mean (WMean) from available responses, but potentially overlook missing data intricacies. Advanced methods like multiple imputation (MI) address broader missing data, but demand increased computational resources. Researchers frequently use survey data in the All of Us Research Program (All of Us), and it is imperative to determine if the increased computational burden of employing MI to handle non-response is justifiable. Using the 5-item Physical Activity Neighborhood Environment Scale (PANES) in All of Us, this study assessed the tradeoff between efficacy and computational demands of WMean, MI, and inverse probability weighting (IPW) when dealing with item non-response. Synthetic missingness, allowing 1 or more item non-response, was introduced into PANES across 3 missing mechanisms and various missing percentages (10%-50%). Each scenario compared WMean of complete questions, MI, and IPW on bias, variability, coverage probability, and computation time. All methods showed minimal biases (all <5.5%) for good internal consistency, with WMean suffered most with poor consistency. IPW showed considerable variability with increasing missing percentage. MI required significantly more computational resources, taking >8000 and >100 times longer than WMean and IPW in full data analysis, respectively. The marginal performance advantages of MI for item non-response in highly reliable scales do not warrant its escalated cloud computational burden in All of Us, particularly when coupled with computationally demanding post-imputation analyses. Researchers using survey scales with low missingness could utilize WMean to reduce computing burden.

Absolute and Relative Reliability of Spatiotemporal Gait Characteristics Extracted from an Inertial Measurement Unit among Senior Adults Using a Passive Hip Exoskeleton: A Test-Retest Study.

Seniors wearing a passive hip exoskeleton (Exo) show increased walking speed and step length but reduced cadence. We assessed the test-retest reliability of seniors' gait characteristics with Exo. Twenty seniors walked with and without Exo (noExo) on a 10 m indoor track over two sessions separated by one week. Speed, step length, cadence and step time variability were extracted from one inertial measurement unit (IMU) placed over the L5 vertebra. Relative and absolute reliability were assessed using the intraclass correlation coefficient (ICC), standard error of measurement (SEM) and minimal detectable change (MDC). The relative reliability of speed, step length, cadence and step time variability ranged from "almost perfect to substantial" for Exo and noExo with ICC values between 0.75 and 0.87 and 0.60 and 0.92, respectively. The SEM and MDC values for speed, step length cadence and step time variability during Exo and noExo were <0.002 and <0.006 m/s, <0.002 and <0.005 m, <0.30 and <0.83 steps/min and <0.38 s and <1.06 s, respectively. The high test-retest reliability of speed, step length and cadence estimated from IMU suggest a robust extraction of spatiotemporal gait characteristics during exoskeleton use. These findings indicate that IMUs can be used to assess the effects of wearing an exoskeleton on seniors, thus offering the possibility of conducting longitudinal studies.

Emergency Severity Index Version 4 and Triage of Pediatric Emergency Department Patients

Most emergency departments (EDs) across the US use the Emergency Severity Index (ESI) to predict acuity and resource needs. A comprehensive assessment of ESI accuracy among pediatric patients is lacking. To assess the frequency of mistriage using ESI (version 4) among pediatric ED visits using automated measures of mistriage and identify characteristics associated with mistriage. This cohort study used operational measures for each ESI level to classify encounters as undertriaged, overtriaged, or correctly triaged to assess the accuracy of the ESI and identify characteristics of mistriage. Participants were pediatric patients at 21 EDs within Kaiser Permanente Northern California from January 1, 2016, to December 31, 2020. During that time, version 4 of the ESI was in use by these EDs. Visits with missing ESI, incomplete ED time variables, patients transferred from another ED, and those who left against medical advice or without being seen were excluded. Data were analyzed between January 2022 and June 2023. Assigned ESI level. Rates of undertriage and overtriage by assigned ESI level based on mistriage algorithm, patient and visit characteristics associated with undertriage and overtriage. This study included 1 016 816 pediatric ED visits; the mean (SD) age of patients was 7.3 (5.6) years, 479 610 (47.2%) were female, and 537 206 (52.8%) were male. Correct triage occurred in 346 918 visits (34.1%; 95% CI, 34.0%-34.2%), while overtriage and undertriage occurred in 594 485 visits (58.5%; 95% CI, 58.4%-58.6%) and 75 413 visits (7.4%; 95% CI, 7.4%-7.5%), respectively. In adjusted analyses, undertriage was more common among children at least 6 years old compared with those younger 6 years; male patients compared with female patients; patients with Asian, Black, or Hispanic or other races or ethnicities compared with White patients; patients with comorbid illnesses compared with those without; and patients who arrived by ambulance compared with nonambulance patients. This multicenter retrospective study found that mistriage with ESI version 4 was common in pediatric ED visits. There is an opportunity to improve pediatric ED triage, both in early identification of critically ill patients (limit undertriage) and in more accurate identification of low-acuity patients with low resource needs (limit overtriage). Future research should include assessments based on version 5 of the ESI, which was released after this study was completed.

ANALISIS KORELASI ANTARA SUDUT SIMPANGAN DAN WAKTU RATAAN PADA BANDUL FISIS DENGAN LATIN SQUARE DESIGN

This study aims to examine the relationship between the angle of deviation and the average time length of a physical pendulum. This study uses primary data, namely practicum report data in a physics laboratory. Data collection was conducted under closed conditions with control variables (shaft length, number of oscillations, and radius of gyration) and dependent variables (angle of deviation and average time). The analysis technique used is a statistical approach technique, namely Latin Square Design analysis. The findings of this study indicate that the variables of deviation angle and average time on the physical pendulum have a strong and unidirectional correlation relationship. This result is evident from the value of F0 &gt; Fcritical and the value of Pr (&gt; P) &gt; 0, 05(significant level) where both of these prove that there is a strong reason to reject H0 which means that there is at least 1 difference in the effect of the angle of deviation on the average time. It shows that the angle of deviation affects the average time of the physical pendulum