Measurement Interval Research Articles

Effects of vasodilators on beat-to-beat and every fifteen minutes blood pressure variability induced by noradrenaline infusion in rats

Increased blood pressure variability (BPV) was shown to be associated with cardiovascular morbidities and/or mortalities. There are various types of BPV depending on time intervals of BP measurements, ranging from beat-to-beat to visit-to-visit or year-to-year. We previously found that continuous infusion of noradrenaline (NA) for 14 days increased short-term BPV every 15 min in rats. The aims of this study were to examine (1) whether NA infusion increases very short-term beat-to-beat BPV, (2) the effects of azelnidipine and hydralazine on NA-induced BPV, and (3) whether baroreceptor reflex sensitivity (BRS) is affected by NA or NA plus those vasodilators. Nine-week-old Wistar rats infused subcutaneously with 30 μg/h NA were orally treated with or without 9.7 mg/day azelnidipine or 5.9 mg/day hydralazine over 14 days. BP levels were continuously monitored via abdominal aortic catheter with a telemetry system in an unrestrained condition. Standard deviations (SDs) were used to evaluate beat-to-beat BPV and BPV every 15 min which was obtained by averaging BP levels for 10-s segment at each time point. BRS was determined by a sequence analysis. Continuous NA infusion over 14 days increased average BP, beat-to-beat BPV, and BPV every 15 min, lowering BRS. Comparing the two vasodilators, hydralazine reduced BP elevation by NA; meanwhile, azelnidipine alleviated BPV augmentation, preserving BRS, despite a smaller BP reduction. Thus, NA infusion increased both very short- and short-term BPV concomitantly with impaired BRS, while azelnidipine had an inhibitory effect, possibly independent of BP-lowering, on those types of BPV and impairment of BRS.

Reference intervals for various measurements of canine left atrial size and function obtained using two-dimensional and three-dimensional echocardiography

BackgroundMany canine cardiac diseases are associated with left atrial (LA) remodeling and decreased function. For accurate assessment of LA indices, large-scale and prospectively determined reference intervals are necessary. ObjectivesTo generate reference intervals of LA size and function using two-dimensional and three-dimensional echocardiography. AnimalsTwo hundred and one healthy adult dogs. MethodsLeft atrial volume was assessed in right parasternal long-axis, left apical four-chamber and two-chamber views using monoplane Simpson’s method, two-dimensional and three-dimensional speckle tracking. Additionally, LA diameter was measured in right parasternal short-axis and long-axis views. Furthermore, LA function was determined by measuring strain and calculating LA fractional shortening and ejection fraction. All variables were tested for correlation to heart rate, age, and body weight. For LA diameter and volume, scaling exponents and prediction intervals were generated using allometric scaling. Reference intervals for LA function parameters were calculated using nonparametric methods. ResultsLeft atrial diameter and volume showed a strong correlation with body weight. The scaling exponent for LA diameter was approximately 1/3 (0.34–0.40) and approximately one for volume measurements (0.97–1.26). Parameters of LA function showed no clinically relevant correlation with body weight, except for two variables, which showed a mild negative correlation. No clinically relevant correlations with age or heart rate were found. ConclusionsReference intervals for linear, two-dimensional and three-dimensional measurements of LA size and function were established. The wide range of measurement methods offers the opportunity to select the appropriate reference values for LA evaluation depending on the available technical possibilities.

Anodal HD-tDCS on the dominant anterior temporal lobe and dorsolateral prefrontal cortex: clinical results in patients with mild cognitive impairment

ObjectivesMild cognitive impairment (MCI) is a neurocognitive disorder in which the cognitive and mental abilities of humans are declined. Transcranial direct-current stimulation (tDCS) is an emerging noninvasive brain stimulation technique aimed at neuromodulation. In this study, we investigate whether high-definition anodal tDCS stimulation (anodal HD-tDCS) in MCI patients in two different brain regions will be effective in improving cognitive function.MethodsThis study was done as a randomized, double-blind clinical trial. Sixty MCI patients (clinically diagnosed by expert neurologists) were randomly divided into three groups. Two groups received 2-mA anodal HD-tDCS for 20 min for 2 weeks (5 consecutive days in each week, 10 days in total). In the first group (twenty patients), the left dorsolateral prefrontal cortex (left DLPFC) was targeted. In the second group (twenty patients), the target zone was the dominant anterior temporal lobe (DATL). The third group (twenty patients) formed the Sham group. The Montreal Cognitive Assessment (MoCA) and Quality of Life in Alzheimer’s Disease (QoLAD) were considered as the outcome measures.ResultsMCI patients obtained the highest MoCA mean scores in both left DLPFC and DATL groups versus the study baseline 2 weeks after the intervention. In addition, the MoCA mean scores of MCI patients were greater in both intervention groups compared to the Sham group up to 3 months post-stimulation (p-value ≤ 0.05). However, as we moved away from the first stimulation day, a decreasing trend in the MoCA mean scores was observed. Moreover, in the left DLPFC and DATL groups, higher QoLAD mean scores were observed 3-month post-stimulation, highlighting the effectiveness of anodal HD-tDCS in improving the quality of life in MCI patients.ConclusionIn this research, it was shown that applying anodal HD-tDCS at left DLPFC and DATL brain regains for two successive weeks improves cognitive function in MCI patients (by obtaining higher values of MoCA scores) up to 3 months after the intervention compared to the Sham group. This illustrates the positive effects of HD-tDCS, as a non-pharmacological intervention, for improving cognitive function and quality of life in MCI patients.SignificanceTwo weeks after anodal HD-tDCS of the DLPFC and DATL brain regions, the MCI patients achieved the highest MoCA mean scores compared to the Sham group across all measurement intervals.

Efficacy of Cold Atmospheric Plasma on Pathogenicity of Oral Microcosm Biofilms

This study aimed to compare the longitudinal efficacy between chlorhexidine gluconate (CHX; 0.12%) and cold atmospheric plasma (CAP) in reducing oral biofilm pathogenicity, utilizing a quantitative light-induced fluorescence-digital (QLF-D) camera. Oral microcosm biofilms were developed for 2 days on 57 hydroxyapatite disks. These biofilms were treated with distilled water for 1 min, CHX for 1 min, and CAP for 2 min over the course of 6 days. The red fluorescence intensities of the biofilms were measured using a QLF-D and expressed as pre- and post-treatment red/green ratios (RatioR/G). The bacterial viability (ratio of the green-stained area to the total stained area, RatioG/G+R) was calculated using live/dead bacterial staining; the total and aciduric bacterial counts were determined. A significant intergroup difference was found between RatioR/G changes according to the treatment period (p < 0.001). The RatioR/G observed within the CAP-treated group was significantly lower compared with the CHX-treated group at every interval of measurement (p < 0.001). The CAP-treated group also exhibited a lower RatioG/G+R and more weakened bacterial aggregation compared with the CHX-treated group (p < 0.05). In the group treated with CAP, the counts of both total and aciduric bacteria were substantially reduced compared with the DW group, with a statistically significant reduction (p < 0.001). Therefore, CAP may be more effective in minimizing oral microcosm biofilm pathogenicity than 0.12% CHX.

Testing reliability and validity of practitioner-rated parental sensitivity: A novel tool for practice.

Improving parental sensitivity is an important objective of interventions to support families. This study examined reliability and validity of parental sensitivity ratings using a novel package of an e-learning tool and an interactive decision tree provided through a mobile application, called the OK! package. Independent raters assessed parental sensitivity using the OK! package (N=11 raters) and the NICHD Parental Sensitivity rating scales (N=22 raters) on the basis of videotaped mother-child interactions at 10- or 12-months-old (N=294) and at 24-months-old (N=204) from the Dutch longitudinal cohort study Generation2 . Mothers reported on children's externalizing and internalizing problems and social competence when children were 4 and 7years old. Results showed excellent single interrater reliability for raters using the OK! package (mean ICC=.79), and strong evidence for convergent validity at 10- or 12-month-old (r=.57) and 24-month-old (r=.65). Prospective associations of neither parental sensitivity rated using the OK! package or the NICHD Parental Sensitivity rating scales with child developmental outcomes were statistically significant (p>.05), with overlapping 95% confidence intervals for both measures. The OK! package provides a promising direction for testing alternatives to current training and instruction modalities.

Interval estimation of the overlapping coefficients in an exponential family of distributions based on upper record values

This paper investigates interval estimation for measures of overlap, namely Matusita's measure, Weitzman's measure and based on Kullback–Leibler. Two types of sampling procedures, namely, Simple Random Sample and Upper Record Values from two exponential populations. Bootstrap method series approximation is used to construct confidence intervals for the overlap measures. To illustrate the performance of the likelihood confidence intervals obtained for this overlapping coefficient, under our proposal, we carry out some simulation studies that yield adequate coverage frequencies, this study conducts for comparing the performances of various competing estimators. A real data set is analysed to exemplify our proposal.

Validation of Temperature Sensors to Monitor Thermoplastic Splint Wear in Hand Surgery Patients.

The aim of this study was to validate the use of temperature sensors to accurately measure thermoplastic volar forearm splint wear in a healthy cohort of volunteers using 5- and 15-minute temperature measurement intervals. A prospective diagnostic study was performed to evaluate the diagnostic accuracy of temperature sensors in monitoring splint wear in 8 healthy volunteers between December 2022 and June 2023. Temperature sensors were molded into thermoplastic volar forearm splints. Volunteers who were familiar with the study aims were asked to keep an exact log of the time spent wearing the splint ("actual wear time"). Sensors recorded temperatures every 5 or 15 minutes, and separate algorithms were developed to determine the sensor-detected wear time compared with the actual wear time as the gold standard. The algorithms were then externally validated with the total population. The 5-minute and 15-minute algorithms demonstrated excellent sensitivity (99.1% vs 96.6%), specificity (99.9% vs 99.9%), positive (99.4% vs 99.5%) and negative (99.9% vs 99.3%) predictive value, and diagnostic accuracy (99.8% vs 99.3%), respectively. The 5-minute algorithm recorded 99.5% of the total splint hours, whereas the 15-minute algorithm recorded 96.1%. There was no significant difference between the actual time per wear session (5.4 ± 2.7 hours) and the time estimated by the 5-minute algorithm (5.4 ± 2.6 hours; P = .40), but there was a significant difference for the 15-minute algorithm (5.2 ± 2.6 hours; P < .001). Temperature sensors can be used to accurately monitor thermoplastic volar forearm splint wear. Diagnostic II.

Measuring facial mimicry: Affdex vs. EMG.

Facial mimicry is the automatic imitation of the facial affect expressions of others. It serves as an important component of interpersonal communication and affective co-experience. Facial mimicry has so far been measured by Electromyography (EMG), which requires a complex measuring apparatus. Recently, software for measuring facial expressions have become available, but it is still unclear how well it is suited for measuring facial mimicry. This study investigates the comparability of the automated facial coding software Affdex with EMG for measuring facial mimicry. For this purpose, facial mimicry was induced in 33 subjects by presenting naturalistic affect-expressive video sequences (anger, joy). The response of the subjects is measured simultaneously by facial EMG (corrugator supercilii muscle, zygomaticus major muscle) and by Affdex (action units lip corner puller and brow lowerer and affects joy and anger). Subsequently, the correlations between the measurement results of EMG and Affdex were calculated. After the presentation of the joy stimulus, there was an increase in zygomaticus muscle activity (EMG) about 400 ms after stimulus onset and an increase in joy and lip corner puller activity (Affdex) about 1200 ms after stimulus onset. The joy and the lip corner puller activity detected by Affdex correlate significantly with the EMG activity. After presentation of the anger stimulus, corrugator muscle activity (EMG) also increased approximately 400 ms after stimulus onset, whereas anger and brow lowerer activity (Affdex) showed no response. During the entire measurement interval, anger activity and brow lowerer activity (Affdex) did not correlate with corrugator muscle activity (EMG). Using Affdex, the facial mimicry response to a joy stimulus can be measured, but it is detected approximately 800 ms later compared to the EMG. Thus, electromyography remains the tool of choice for studying subtle mimic processes like facial mimicry.

Feasibility of the "Preventing functional decline in acutely hospitalized older patients (PREV_FUNC)" study-A three-armed randomized controlled pilot trial.

Recent studies indicate that in-hospital exercise can mitigate the risk of functional decline in acutely hospitalized older adults. However, there is a lack of studies that compare different types of exercise interventions. This feasibility study was conducted in preparation for a three-armed randomized controlled trial. The aim was to examine the process feasibility (in terms of recruitment and retention rate, intervention compliance and acceptability), and scientific feasibility (in terms of presence of adverse events, and trends with 95% confidence intervals of the outcome measures) of the trial. Patients aged ≥75 years, were included from geriatric medical wards at three hospitals in Stockholm, Sweden. Participants in two groups received a specialized intervention program, i.e., Simple or Comprehensive exercise program, respectively and one group received usual care. Assessments were conducted at hospital admission and discharge, and data were analyzed with descriptive statistics. In the spring 2022, 63 patients met the inclusion criteria and 39 accepted to participate (recruitment rate: 61.9%). COVID-19 affected the inclusion period. A total of 33 participants completed the study (i.e., were assessed at baseline and discharge, retention rate: 84.6%). Participants in the Simple and the Comprehensive exercise programs performed 88.9% and 80% of the possible training sessions, respectively. Both interventions were accepted by the participants and no adverse events were reported. The intervention groups showed a higher median change from admission to discharge than the control group on the Short Physical Performance Battery, the main outcome measure of the trial. The result of this pilot study suggests that the trial design is feasible and potentially useful for preventing functional decline in acutely hospitalized older adults. A full-scale trial will, however, require some considerations with respect to routines and logistics. The trial was registered at ClinicalTrials.gov, 4 May 2022, registration number NCT05366075.

PAS - A Feature Selection Process Definition for Industrial Settings

Industry 4.0, and the accompanying digitalization of industrial processes, lead to a continuously increasing amount of data. One reason is the installation of more sensors on machines and production lines in combination with shorter measurement intervals. The rising amount of data requires elaborate methods to remove redundant and uninformative data to reduce time complexity and required computational resources. This could be achieved by feature selection methods in combination with the right preprocessing and enhancement methods to generate and identify important features. Feature selection methods are mostly described in a methodological way without knowing how data is handled prior to their application, assuming a high-quality dataset. To fill this gap, we define a process for feature selection, focusing on time-series industrial data. The definition consists of three phases for the data adaptation: Preprocessing, Amplification and Selection. Each phase fulfills a specific purpose, ranging from handling missing and censored data to the enhancement of the dataset by higher-order data and aggregations and the selection itself. Our experiments show that the application of these phases on three different industrial use-cases lead to better accuracy results in machine learning models.

Assessing the Impact of Temporal Resolution Using BSM1 on the Performance of Machine Learning

Objectives : This study aims to establish efficient strategies for data-driven operational management by examining the variations in machine learning modeling outcomes and data characteristics based on data acquisition intervals and methods.Methods : The BSM1 was used to simulate wastewater treatment facilities and to generate influent and effluent water quality data at 15-minute intervals. The generated data was processed by volume reduction through down sampling and data characteristic observation via resampling techniques, including up sampling through interpolation. Subsequently, the study involved a comparative analysis of the performance of 30 machine learning models built with the down sampled data.Results and Discussion : As data acquisition interval increased (i.e., down sampling progressed), &lt;i&gt;R&lt;/i&gt;&lt;sup&gt;2&lt;/sup&gt; decreased and RMSE increased. When using the mean value as a representation, data accuracy was high, and error loss was minimal. Utilizing the maximum value as a representation helped maintain data characteristics and reduce information loss. Simple interpolation methods did not yield improved data accuracy. Furthermore, with wider data acquisition intervals, the practical predictive performance of machine learning models decreased, and the models experienced a sharp decline in performance when data became insufficient.Conclusion : For models requiring the ability to detect changes rather than accuracy, utilizing the maximum value over a specific period proves to be effective. The measurement interval of data emerges as a significant factor affecting the performance of machine learning models, with models developed under different measurement intervals often failing to demonstrate the expected performance. In this study, we have implemented all stages of data preprocessing, classification, training, and validation using LabVIEW, confirming the potential for integrating data analysis processes into LabVIEW, a widely used platform in the fields of control and measurement.

Methylprednisolone Does Not Enhance Paraoxonase 1 Activity During Cardiopulmonary Bypass Surgery—A Randomized, Controlled Clinical Trial

ObjectivesCardiopulmonary bypass (CPB) is linked to systemic inflammatory responses and oxidative stress. Paraoxonase 1 (PON1) is an antioxidant enzyme with a cardioprotective role, whose activity is decreased in systemic inflammation, and in patients with acute myocardial and global ischemia. Glucocorticoids counteract the effect of oxidative stress by up-regulating PON1 gene expression. We aimed to determine the effect of methylprednisolone on PON1 activity during cardiac surgery on CPB. DesignProspective, randomized, controlled clinical trial. SettingThe study was conducted at the University Medical Centre Ljubljana, Slovenia. Participants40 adult patients, who underwent complex cardiac surgery on CPB between February 2016 and December 2017, were randomized into methylprednisolone and control group (n=20 each). InterventionsPatients in the methylprednisolone group received 1g of methylprednisolone in the CPB priming solution, while patients in the control group were not given methylprednisolone during CPB. Measurements and Main ResultsWe compared the effect of methylprednisolone from CPB priming solution with standard care during CPB on PON1 activity until the 5. postoperative day. Correlations of PON1 activity with lipid status, mediators of inflammation, and hemodynamics were analyzed as well. No significant differences existed between study groups for PON1 activity, high-density lipoprotein (HDL), and low-density lipoprotein (LDL) in any of the measurement intervals (p>0.016). Methylprednisolone group had significantly lower TNF-a (p<0.001), IL-6 (p<0.001), as well as CRP and procalcitonin (p<0.016) after surgery. No significant difference was found between groups for hemodynamic parameters. A positive correlation existed between PON1 and lipid status, whereas a negative correlation was found between PON1 activity and TNF-a, IL-6, as well as CPB duration. ConclusionsMethylprednisolone doesn't influence PON1 activity during cardiac surgery on CPB.

Free mebrofenin clearance.

To determine if three new simplified equations for measurement of free mebrofenin clearance give similar results to the equations defined by Ekman et. al ., and to evaluate the properties of all four methods. Regional mebrofenin clearance has been used to predict future remnant liver function and liver failure after regional liver therapy, such as partial hepatic resection. The means, standard deviations, and correlations of the free mebrofenin clearance measured by the Ekman method and the three simplified methods were compared in a consecutive series of 26 studies in 20 patients. The fractional change in the blood and free mebrofenin activities were compared, and integrals of normalized blood and free mebrofenin ("effective times") were compared. The average percent free mebrofenin clearance for the Ekman and the first, second and third simplified methods were 13.62 ± 2.88%/min, 12.98 ± 2.97%/min, 12.52 ± 2.81%/min and 15.03 ± 2.27%/min, respectively. The correlations of the new methods with Ekman were 0.97, 0.93 and 0.93. The fractional changes during the measurement interval for the blood and free mebrofenin activities were 0.381 ± 0.065 and 0.329 ± 0.062, difference 0.052, P < 0.5. The integrals of normalized blood and free mebrofenin activities were 2.566 ± 0.160 min and 2.661 ± 0.158 min, difference of 0.094 min and P < 0.05. The results of the three new methods were similar to the Ekman method. The first simplified method was identified as the lead method for clinical validation in a larger population.

Research on optimization technology of excitation coil in downhole annular flow electromagnetic measurement system

External interference and non-uniform velocity distribution influence the downhole annular flow electromagnetic measurement, reducing detection accuracy. Optimizing the structure of the excitation coil can effectively enhance the uniformity of magnetic field distribution, constituting an essential approach for improving measurement accuracy. Aiming at the excitation coil optimization technology of annular flow electromagnetic measurement system, the study first analyzes and obtains the magnetic field model of the excitation coil based on the principle of annular flow electromagnetic measurement, combined with the theory of vector weight function and puts forward the optimization theory of annular excitation coil. Secondly, the simulation models of rectangular and saddle exciting coils are established using finite element software to analyze the magnetic field distribution of annular flow under different coil and core sizes. The optimal structural parameters of the exciting coils in the annular flow electromagnetic measurement system are determined through evaluation indexes for the magnetic field. Finally, an experimental platform was established for optimizing the electromagnetic measurement of annular flow, and this platform was used to conduct comparative experiments. The experimental results show that the maximum reduction of the optimized system is 3.192%, 1.289%, and 1.813% for the single verification relative value error, single-point verification relative value error, and repeatability compared with the rectangular excitation coil annular flow electromagnetic measurement system. In the flow measurement interval of 25–100 m3 h−1, the single-point verification of the optimized system has a maximum relative display value error of 0.378%, and the measurement accuracy reaches 1.0 level and meets the consistency of the transmission of quantity and value. The research findings hold significant guidance for enhancing the measurement accuracy of the downhole annular flow electromagnetic measurement system.

Метричность патриотического воспитания детей дошкольного возраста: диагностический аспект

Patriotic upbringing is an inherent part of preschool education. However, its efficiency is extremely difficult to measure. This article introduces an authentic approach to assessing the results of patriotic education in preschool children. The method was tested as part of an innovative project on the prospects of STEM-education, which integrates Science, Technology, Engineering, and Mathematics. The experiment was supervised by the Federal Institute of Modern Education and covered 64 education institutions in 22 cities and 10 villages of the Russian Federation. It involved children aged 5–7 y.o. Their patriotism was measured quantitatively based on the structural content of this phenomenon. The measurement intervals of the cumulative index were determined for three levels of patriotic orientation in children aged 5–6 and 6–7 y.o. The qualitative analysis relied on a creative task where children were asked to draw a picture of Motherland Russia. The new method demonstrates good pedagogical, methodological, and educational prospects.

Using digital methods in active power measurement

Digitized voltage and current waveforms can be used to estimate active power by processing the obtained samples through two methods: Discrete Integration and Spectral Analysis. The former involves computing the average of the sample-by-sample product of the two waveforms, while the latter uses sine fitting algorithms to estimate the amplitude and initial phase of each waveform. Precision expressions for both estimators are derived as a function of the number of samples acquired and the amount of additive random noise present, which is useful for determining the confidence interval for measurements. The two estimators are compared, and it is concluded that the second method, using sine fitting, is sometimes superior.

Microhardness and Gloss of a New CAD/CAM Hybrid Material Following Accelerated Aging and Coffee Immersion.

To evaluate and compare the effect of accelerated aging and coffee immersion on the microhardness and gloss of a new computer-aided design and computer-aided manufacturing (CAD/CAM) hybrid material (Crystal Ultra) to those of contemporary restorative materials. A total of 160 specimens (12 × 14 × 1 mm ± 0.05 mm) were obtained from IPS e.max (IPS), VITA Enamic (VE), Crystal Ultra (CU), Lava Ultimate (LU), and CeraSmart (CS) high-translucency CAD/CAM blocks. The Vickers microhardness and gloss of the specimens were determined after thermocycling and coffee immersion. Data analysis was performed using SPSS (α = .05). IPS and CS specimens exhibited the highest (572.66 ± 11.30) and lowest (61.92 ± 3.91) microhardness, respectively. The highest gloss was observed with IPS specimens (3.31 ± 0.32), and LU specimens showed the lowest gloss (2.33 ± 0.06). A significant difference in gloss was observed between the materials at all measurement intervals (P < .01), except at T0 (P = .43). IPS specimens showed no significant changes in either group at any measurement interval. The microhardness and gloss of the new CU material were comparable to those of the tested contemporary hybrid restorative materials. Glass-ceramic showed superior hardness and gloss compared to hybrid restorative materials. Accelerated aging with thermocycling and staining significantly affected the microhardness and gloss of all tested CAD/CAM materials.

An introduction to the bootstrap: a versatile method to make inferences by using data-driven simulations.

The bootstrap is a versatile technique that relies on data-driven simulations to make statistical inferences. When combined with robust estimators, the bootstrap can afford much more powerful and flexible inferences than is possible with standard approaches such as T-tests on means. In this tutorial, we use detailed illustrations of bootstrap simulations to give readers an intuition of what the bootstrap does and how it can be applied to solve many practical problems, such as building confidence intervals for many aspects of the data. In particular, we illustrate how to build confidence intervals for measures of location, including measures of central tendency, in the one-sample case, for two independent and two dependent groups. We also demonstrate how to compare correlation coefficients using the bootstrap and to perform simulations to determine if the bootstrap is fit for purpose for a particular application. Our approach is to suggest and motivate what could be done in a situation, with an understanding that various options are valid, though they may help answer different questions about a dataset. The tutorial also addresses two widespread misconceptions about the bootstrap: that it makes no assumptions about the data, and that it leads to robust inferences on its own. The tutorial focuses on detailed graphical descriptions, with data and code available online to reproduce the figures and analyses in the article (OSF: https://osf.io/8b4t5/; GitHub: https://github.com/GRousselet/bootstrap).

CHAT: Accurate Network Latency Measurement for 5G E2E Networks

As numerous latency-sensitive applications have emerged with the popularization of 5G networking, accurate and rapid end-to-end latency measurement has come to play an essential role in network fault diagnosis and optimization. Although the Bloom hash-based timestamp aggregation method has been reported to be scalable and efficient, two shortcomings that reduce its accuracy have yet to be fully considered: frequent hash collisions and its fixed measurement interval. To address these challenges, we construct an end-to-end network latency measurement framework named Cuckoo Hash Adjustive Table exchange (CHAT). By employing an improved cuckoo filter, we decrease the number of hash collisions to assess the latency more accurately. Moreover, CHAT adjusts the receiver-side measurement interval dynamically based on a gain indicator, maximizing the total number of valid packets used for latency estimation. Additionally, the proposed measurement framework minimizes the number of packets transferred over links to avoid interfering with the end-to-end latency measurement in an actual network. Finally, extensive experiments on simulations and a practical real-world environment show the effectiveness and applicability of CHAT.

Afternoons can be a critical time of the day that reflects associations between life‐space mobility and loneliness among living alone older adults: longitudinal analyses with motion sensor data

AbstractBackgroundDaily activity patterns of life‐space mobility can serve as indicators for loneliness and subsequent cognitive change. Assessment of life‐space mobility often uses self‐reported data, and the measurement intervals are often less frequent than needed to capture change over time. This study examined whether the life‐space mobility changed when loneliness was reported weekly.MethodsParticipants were 139 older adults who lived alone (age = 78.1±8.6, 103 (74%) were female, 32 (23%) were African Americans, 19 (14%) had MCI diagnosis) and were enrolled in ORCATECH (ORegon Center for Aging &amp; TECHnology) longitudinal aging studies and Minority Aging Research Study. Passive infrared motion sensors were placed in common rooms of each participant’s home (bathroom; bedroom; kitchen; living room). Time spent in each room across the day (morning; afternoon; evening; night) and out‐of‐home were used as indicators of life‐space mobility and were derived from home sensor data. Participants reported whether they felt lonely on a weekly basis using an online survey sent via email. Generalized estimating equations were used to correlate the time spent in each room and out‐of‐home and the likelihood of feeling lonely. Age, gender, education, race, cognitive status (MCI/ non‐MCI), and average daily time out‐of‐home were controlled in the model.ResultsWe analyzed 4994 weeks of data; 232 weeks had an incidence of loneliness (5%). Spending an additional hour in the bedroom in the afternoon (noon‐6 pm) was associated with a 21% increase in the likelihood of experiencing loneliness (p = .03). Spending an additional hour out‐of‐home in the afternoon was associated with a 13% decrease in the likelihood of experiencing loneliness (p = .02). Time spent in the kitchen, bathroom, and living room in a day was unrelated to weekly loneliness.ConclusionTime spent outside the home may suggest an expansion of life‐space, while spending time in one’s bedroom may indicate contraction of life space. Our findings suggest carefully monitoring a person’s location in the afternoon might help detect loneliness in this population. Frequent and objective measurements of life‐space mobility can produce renewed insights into the experience of loneliness among older adults who live alone, and thus, inform timely interventions for loneliness and prevent cognitive decline.