Concurrent Monitoring Research Articles

Mandibular Movements are a Reliable Noninvasive Alternative to Esophageal Pressure for Measuring Respiratory Effort in Patients with Sleep Apnea Syndrome.

PurposeDifferentiation between obstructive and central apneas and hypopneas requires quantitative measurement of respiratory effort (RE) using esophageal pressure (PES), which is rarely implemented. This study investigated whether the sleep mandibular movements (MM) signal recorded with a tri-axial gyroscopic chin sensor (Sunrise, Namur, Belgium) is a reliable surrogate of PES in patients with suspected obstructive sleep apnea (OSA).Patients and MethodsIn-laboratory polysomnography (PSG) with PES and concurrent MM monitoring was performed. PSGs were scored manually using AASM 2012 rules. Data blocks (n=8042) were randomly sampled during normal breathing (NB), obstructive or central apnea/hypopnea (OA/OH/CA/CH), respiratory effort-related arousal (RERA), and mixed apnea (MxA). Analyses were evaluation of the similarity and linear correlation between PES and MM using the longest common subsequence (LCSS) algorithm and Pearson’s coefficient; description of signal amplitudes; estimation of the marginal effect for crossing from NB to a respiratory disturbance for a given change in MM signal using a mixed linear-regression.ResultsParticipants (n=38) had mild to severe OSA (median AH index 28.9/h; median arousal index 23.2/h). MM showed a high level of synchronization with concurrent PES signals. Distribution of MM amplitude differed significantly between event types: median (95% confidence interval) values of 0.60 (0.16–2.43) for CA, 0.83 (0.23–4.71) for CH, 1.93 (0.46–12.43) for MxA, 3.23 (0.72–18.09) for OH, and 6.42 (0.88–26.81) for OA. Mixed regression indicated that crossing from NB to central events would decrease MM signal amplitude by –1.23 (CH) and –2.04 (CA) units, while obstructive events would increase MM amplitude by +3.27 (OH) and +6.79 (OA) units (all p<10−6).ConclusionIn OSA patients, MM signals facilitated the measurement of specific levels of RE associated with obstructive, central or mixed apneas and/or hypopneas. A high degree of similarity was observed with the PES gold-standard signal.

Semi-Synchronized Non-Blocking Concurrent Kernel Cruising

Kernel heap buffer overflow vulnerabilities have been exposed for decades, but there are few practical countermeasure that can be applied to OS kernels. Previous solutions either suffer from high performance overhead or compatibility problems with mainstream kernels and hardware. In this paper, we present KRUISER, a concurrent kernel heap buffer overflow monitor. Unlike conventional methods, the security enforcement of which is usually inlined into the kernel execution, Kruiser migrates security enforcement from the kernel's normal execution to a concurrent monitor process, leveraging the increasingly popular multi-core architectures. To reduce the synchronization overhead between the monitor process and the running kernel, we design a novel semi-synchronized non-blocking monitoring algorithm, which enables efficient runtime detection on live memory without incurring false positives. To prevent the monitor process from being tampered and provide guaranteed performance isolation, we utilize the virtualization technology to run the monitor process out of the monitored VM, while heap memory allocation information is collected inside the monitored VM in a secure and efficient way. We have implemented a prototype of KRUISER based on Linux and the Xen/KVM hypervisor. The evaluation shows that Kruiser can detect realistic kernel heap buffer overflow attacks in cloud environment effectively with minimal cost.

The accuracy of simple, feasible alternatives to polysomnography for assessing sleep in intensive care: An observational study

BackgroundSleep disturbance is common in intensive care patients. Understanding the accuracy of simple, feasible sleep measurement techniques is essential to informing their possible role in usual clinical care. ObjectiveThe aim of the study was to investigate whether sleep monitoring techniques such as actigraphy (ACTG), behavioural assessments, and patient surveys are comparable with polysomnography (PSG) in accurately reporting sleep quantity and quality among conscious, intensive care patients. MethodsAn observational study was conducted in 20 patients admitted to the intensive care unit (ICU) for a minimum duration of 24 h, who underwent concurrent sleep monitoring via PSG, ACTG, nursing-based observations, and self-reported assessment using the Richards–Campbell Sleep Questionnaire. ResultsThe reported total sleep time (TST) for the 20 participants measured by PSG was 328.2 min (±106 min) compared with ACTG (362.4 min [±62.1 min]; mean difference = 34.22 min [±129 min]). Bland–Altman analysis indicated that PSG and ACTG demonstrated clinical agreement and did not perform differently across a number of sleep variables including TST, awakening, sleep-onset latency, and sleep efficiency. Nursing observations overestimated sleep duration compared to PSG TST (mean difference = 9.95 ± 136.3 min, p > 0.05), and patient-reported TST was underestimated compared to PSG TST (mean difference = −51.81 ± 144.1 7, p > 0.05). ConclusionsAmongst conscious patients treated in the ICU, sleep characteristics measured by ACTG were similar to those measured by PSG. ACTG may provide a clinically feasible and acceptable proxy approach to sleep monitoring in conscious ICU patients.

"We threw away the stones": a mixed method evaluation of a simple cookstove intervention in Malawi.

Background: Air pollution exposure is responsible for a substantial burden of respiratory disease globally. Household air pollution from cooking using biomass is a major contributor to overall exposure in rural low-income settings. Previous research in Malawi has revealed how precarity and food insecurity shape individuals' daily experiences, contributing to perceptions of health. Aiming to avoid a mismatch between research intervention and local context, we introduced a simple cookstove intervention in rural Malawi, analysing change in fine particulate matter (PM 2.5) exposures, and community perceptions. Methods: Following a period of baseline ethnographic research, we distributed 'chitetezo mbaula', locally-made cookstoves, to all households (n=300) in a rural Malawian village. Evaluation incorporated village-wide participant observation and concurrent exposure monitoring using portable PM 2.5 monitors at baseline and follow-up (three months post-intervention). Qualitative data were thematically analysed. Quantitative analysis of exposure data included pre-post intervention comparisons, with datapoints divided into periods of combustion activity (almost exclusively cooking) and non-combustion periods. Findings were integrated at the interpretation stage, using a convergent design mode of synthesis. Results: Individual exposure monitoring pre- and post-cookstove interventioninvolved a sample of 18 participants (15 female; mean age 43). Post-intervention PM 2.5 exposures (median 9.9μg/m 3 [interquartile range: 2.2-46.5]) were not significantly different to pre-intervention (11.8μg/m 3 [3.8-44.4]); p=0.71. On analysis by activity, background exposures were found to be reduced post-intervention (from 8.2μg/m 3 [2.5-22.0] to 4.6μg/m 3 [1.0-12.6]; p=0.01). Stoves were well-liked and widely used by residents as substitutes for previous cooking methods (mainly three-stone fires). Commonly cited benefits related to fuel saving and shorter cooking times. Conclusions: The cookstove intervention had no impact on cooking-related PM 2.5 exposures. A significant reduction in background exposures may relate to reduced smouldering emissions. Uptake and continued use of the stoves was high amongst community members, who preferred using the stoves to cooking over open fires.

“We threw away the stones”: a mixed method evaluation of a simple cookstove intervention in Malawi

Background: Air pollution exposure is responsible for a substantial burden of respiratory disease globally. Household air pollution from cooking using biomass is a major contributor to overall exposure in rural low-income settings. Previous research in Malawi has revealed how precarity and food insecurity shape individuals’ daily experiences, contributing to perceptions of health. Aiming to avoid a mismatch between research intervention and local context, we introduced a simple cookstove intervention in rural Malawi, analysing change in fine particulate matter (PM 2.5) exposures, and community perceptions. Methods: Following a period of baseline ethnographic research, we distributed ‘chitetezo mbaula’, locally-made cookstoves, to all households (n=300) in a rural Malawian village. Evaluation incorporated village-wide participant observation and concurrent exposure monitoring using portable PM 2.5 monitors at baseline and follow-up (three months post-intervention). Qualitative data were thematically analysed. Quantitative analysis of exposure data included pre-post intervention comparisons, with datapoints divided into periods of combustion activity (almost exclusively cooking) and non-combustion periods. Findings were integrated at the interpretation stage, using a convergent design mode of synthesis. Results: Individual exposure monitoring pre- and post-cookstove intervention involved a sample of 18 participants (15 female; mean age 43). Post-intervention PM 2.5 exposures (median 9.9μg/m 3 [interquartile range: 2.2–46.5]) were not significantly different to pre-intervention (11.8μg/m 3 [3.8–44.4]); p=0.71. On analysis by activity, background exposures were found to be reduced post-intervention (from 8.2μg/m 3 [2.5–22.0] to 4.6μg/m 3 [1.0–12.6]; p=0.01). Stoves were well-liked and widely used by residents as substitutes for previous cooking methods (mainly three-stone fires). Commonly cited benefits related to fuel saving and shorter cooking times. Conclusions: The cookstove intervention had no impact on cooking-related PM 2.5 exposures. A significant reduction in background exposures may relate to reduced smouldering emissions. Uptake and continued use of the stoves was high amongst community members, who preferred using the stoves to cooking over open fires.

Enteral feeding tube administration with therapeutic drug monitoring of crushed posaconazole tablets and opened isavuconazonium sulfate capsules.

Isavuconazole and posaconazole are commonly used for both prophylaxis and treatment of invasive fungal infections. These agents are formulated for oral administration as a capsule and delayed release (DR) tablet or suspension, respectively. In patients unable to swallow, alternative means of administration, such as crushing posaconazole DR tablets and opening isavuconazole capsules, may be used to avoid IV administration or use of posaconazole suspension, which often produces subtherapeutic concentrations. To assess the feasibility of achieving target plasma drug concentrations with enteral feeding tube (EFT) administration of crushed posaconazole DR tablets and opened isavuconazole capsules. We retrospectively reviewed pharmacy records to identify patients receiving EFT administration of posaconazole or isavuconazole with concurrent therapeutic drug monitoring from October 2019 to June 2021. Plasma concentrations of either agent as well as clinical outcomes were documented. We identified 37 patients receiving 38 courses of EFT isavuconazole or posaconazole. The majority of patients received primary prophylaxis following lung transplantation (64.9%). Plasma concentrations upon first assessment were therapeutic in the majority of patients (posaconazole 71.5%, isavuconazole 83.3%) with a mean level of 1.61 ± 0.77 mg/L for posaconazole and 2.07 ± 1.1 mg/L for isavuconazole. Of those that were subtherapeutic on initial assessment, all but one subsequently achieved target levels upon dose titration. Standard maintenance doses were used in all isavuconazole and most posaconazole patients. Our case series demonstrates that isavuconazole and posaconazole can be administered via EFT with concurrent therapeutic drug monitoring to achieve target plasma concentrations in the majority of patients.

“We threw away the stones”: a mixed method evaluation of a simple cookstove intervention in Malawi

Background:Exposure to air pollution is responsible for a substantial burden of respiratory disease globally. Household air pollution from cooking using biomass is a major contributor to overall exposure in rural low-income settings. Previous research in Malawi has revealed how precarity and food insecurity shape individuals’ daily experiences, contributing to perceptions of health. Aiming to avoid a mismatch between research intervention and local context, we introduced a simple cookstove intervention in rural Malawi, analysing change in fine particulate matter (PM2.5) exposures, and community perceptions.Methods:Following a period of baseline ethnographic research, we distributed‘chitetezo mbaula’, locally made clay cookstoves, to all households (n=300) in a rural Malawian village. Evaluation incorporated village-wide participant observation and concurrent exposure monitoring using portable PM2.5monitors at baseline and follow-up (three months post-intervention). Qualitative data were thematically analysed. Quantitative analysis of exposure data included pre-post intervention comparisons, with datapoints divided into cooking and non-cooking (‘baseline’) periods. Findings were integrated at the interpretation stage, using a convergent design mode of synthesis.Results:Individual exposure monitoring pre- and post-cookstove intervention involved a sample of 18 participants (15 female; mean age 43). Post-intervention PM2.5exposures (median 9.9μg/m3[interquartile range: 2.2–46.5]) were not significantly different to pre-intervention (11.8μg/m3[3.8–44.4]); p=0.71. On analysis by activity, ‘baseline’ exposures were found to be reduced post-intervention (from 8.2μg/m3[2.5–22.0] to 4.6μg/m3[1.0–12.6]; p=0.01). Stoves were well-liked and widely used by residents as substitutes for previous cooking methods (mainly three-stone fires). Most cited benefits related to fuel saving and shorter cooking times.Conclusions:The cookstove intervention had no impact on cooking-related PM2.5exposures. A significant reduction in baseline exposures may relate to reduced smouldering emissions. Uptake and continued use of the stoves was high amongst community members, who preferred using the stoves to cooking over open fires.

Severe Problems of the Voltage‐Clamp Method in Concurrent Monitoring of Membrane Potentials

AbstractIn nerve cells, the concurrent monitoring of multipoint on the axon has been conducted based on the voltage‐clamp method using two long parallel electrodes inside and outside the axon. As the respective membrane potentials have been evaluated by considering the clamping potential, the local current, and the conductance, the membrane potentials were not actually evaluated. We directly measured the actual membrane potentials and local currents of the respective cells using a nerve‐model‐system comprising some liquid‐membrane cells. It is proved that the action potential propagation is artificially facilitated or prevented by both the external electric generator and two long electrodes.

A Cloud Computing Platform Technology Based on Space-based Intelligent Information Network

Based on large-scale storage and networked computing resources, cloud computing technology provides a strong computing platform which could support for massive data storage and big data intelligent application in the different field. Space-based information infrastructure has matured over the years, but most of the satellite systems are independent, which cause the resources of the satellite computing platform are isolated from each other. In this case, storage and computing resources cannot be utilized fully, which also cannot effectively support space-based intelligent application platform[1]. In this paper, a space-based embedded cloud computing platform is designed by combining the application requirements of space-based intelligent computing and ground-based cloud computing system, which includes sharing and using large-scale computing resources, concurrent monitoring and management of multi-tasks, fault-tolerant migration of tasks, and distributed storage retrieval. The results of this paper are committed to building an intelligent information network computing and storage platform, which could support for space-based intelligent infrastructure application.

Metal-Organic Frameworks Encapsulating Carbon Dots Enable Fast Speciation of Mono- and Divalent Copper.

Copper is an essential element to play significant roles in human health associated to the strong redox properties of Cu(I) and Cu(II). The concurrent monitoring of copper species in biological matrixes is highly desired. Herein, a dual-channel fluorescence nanoprobe was designed for the speciation of mono- and divalent copper by conjugating carbon dots (CDs) with Eu-based metal-organic frameworks (Eu-MOFs). The obtained Eu-MOFs@CD nanoprobe exhibits fluorescence at λex/λem = 380/454 nm from CDs and λex/λem = 275/615 nm from Eu-MOFs. Bathocuproine disulfonate (BCS) specifically chelates Cu+ to produce a BCS-Cu+ adduct with absorption at 480 nm, which quenches the fluorescence of CDs at 454 nm due to the inner filter effect. On the other hand, Cu2+ quenches the fluorescence of Eu-MOFs due to the replacement of Eu3+ by Cu2+. Thus, Eu-MOFs@CDs enable extremely fast detection of Cu+ and Cu2+ within 1 min. Furthermore, the nanoprobe is demonstrated by monitoring the variation of Cu+ and Cu2+ in the degradation process of copper nanoparticles and Cu-based MOFs.

Nonparametric multivariate processes monitoring with guaranteed in-control performance for changes in location

Multivariate statistical process control (MSPC) addresses the concurrent monitoring of several measurements. Since multivariate normality is rare in practice, nonparametric schemes become useful alternatives. Inspired by the development of distribution free Shewhart-type control charts to monitor multivariate data streams as a mean to address high-dimensional processes where distance measures are ranked and compared using two-sample test statistics, a novel distribution-free multivariate chart for location that combines Mahalanobis distances with the Mann-Whitney statistic is proposed. By considering, probably for the first time in nonparametric MSPC, practitioner-to-practitioner variation, we account for the uncertainty of the run length distribution, where computational complexity is addressed using the cumulative conditional false alarm probability as a proxy of the conditional average run length. This approach enables quicker determination of control limits that guarantee a minimum performance given a Phase-I sample, a common situation in parametric approaches, but scarcely discussed in nonparametric monitoring. Since no direct alternative exists, results are compared with the traditional approach to show the benefits of a guarantee in-control performance with comparable sensitivity when dealing with medium to large shifts. An implementation is illustrated in a real scenario related to Wine Quality Data.

Blockchain Based Enhanced ERP Transaction Integrity Architecture and PoET Consensus

Enterprise Resource Planning (ERP) software is extensively used for the management of business processes. ERP offers a system of integrated applications with a shared central database. Storing all business-critical information in a central place raises various issues such as data integrity assurance and a single point of failure, which makes the database vulnerable. This paper investigates database and Blockchain integration, where the Blockchain network works in synchronization with the database system, and offers a mechanism to validate the transactions and ensure data integrity. Limited research exists on Blockchain-based solutions for the single point of failure in ERP. We established in our study that for concurrent access control and monitoring of ERP, private permissioned Blockchain using Proof of Elapsed Time consensus is more suitable. The study also investigated the bottleneck issue of transaction processing rates (TPR) of Blockchain consensus, specifically ERP’s TPR. The paper presents system architecture that integrates Blockchain with an ERP system using an application interface.

A novel kernel dynamic inner slow feature analysis method for dynamic nonlinear process concurrent monitoring of operating point deviations and process dynamics anomalies

A novel nonlinear dynamic inner slow feature analysis method is proposed for dynamic nonlinear process concurrent monitoring of operating point deviations and process dynamics anomalies. In this method, the nonlinear correlation and serial autocorrelation are considered meanwhile to extract the serial auto-correlated latent slow features with explicit dynamic representation. In order to approve slow features (SFs) with explicit dynamic representation from nonlinear dynamic process data, a new multi-goal optimization question is formulized with constraints of the extract latent variable catch some variation information and mutually orthogonal. After the nonlinear dynamic inner slow feature analysis model is trained from data, a corresponding detection strategy is also developed to perform process condition concurrent monitoring. Finally, the superiority and effectiveness of the proposed monitoring method are demonstrated by a numerical simulation case and an actual cold rolling mill case.

On Use of Low Cost, Compact GNSS Receiver Modules for Ionosphere Monitoring

AbstractGeodetic or special purpose Global Navigation Satellite System (GNSS) receivers are used for ionosphere monitoring and research. Dual frequency, compact, low‐cost commercial GNSS modules can provide raw GNSS data and are commonly used for positioning applications. This paper presents the applicability of these compact modules for monitoring ionospheric activities. A comparative study between Javad Triumph LS, a costly geodetic receiver, and an Ublox ZED‐F9P, a low‐cost, dual‐frequency, compact module is carried out to explore the potential of the low‐cost devices for ionosphere probing. Studies are carried out on signal strength values (C/N0) and vertical total electron content (VTEC) values. From the concurrently collected GPS data, a bias of 2.2–4.9 dBHz in signal strength values are observed between the two types of receivers depending on the signal frequency band. The VTEC values calculated from the Ublox module are in close agreement with the values obtained from the Triumph LS receiver. Therefore, the compact module shows the potential for use in ionosphere monitoring with clear advantages in cost, size, and power consumption. However, the signal strength values obtained from such compact modules need to be calibrated using standard GNSS receivers. A GNSS‐based Ionosphere Monitoring Unit (GIMU) is also proposed in this manuscript by the integration of a compact, low‐cost GNSS module with a single‐board computer and a wireless data communication module. Real‐time, cost‐effective, concurrent ionosphere monitoring over a geographically distributed network is possible using a network of such units.

Respiratory Aerosol Emissions from Vocalization: Age and Sex Differences Are Explained by Volume and Exhaled CO2

Evidence suggests that airborne transmission of infectious respiratory aerosol plays an important role for the SARS-CoV-2 virus. This work characterized respiratory aerosol emissions from a panel of healthy individuals of varying age and sex while talking and singing in a controlled laboratory setting. Particle number concentrations between 0.25 and 33 μm were measured from 63 participants aged 12–61 years with concurrent monitoring of voice volume and exhaled CO2 levels. On average, singing produced 77% (95% CI: 42,109%) more aerosol than talking, adults produced 62% (CI: 27,98%) more aerosol than minors, and males produced 34% (CI: 0,70%) more aerosol than females. After accounting for participant voice volume and exhaled CO2 (both of which were positively correlated with aerosol emissions) in linear models, the age and sex differences were attenuated and no longer statistically significant. These results support further investigation of voice volume and CO2 as indicators of infection risk indoors.

A novel auto-regressive dynamic slow feature analysis method for dynamic chemical process monitoring

A novel dynamic data modeling method called autoregressive dynamic slow feature analysis (RDSFA) is proposed for dynamic process concurrent monitoring of operating condition deviations and process dynamics anomalies. In this method, a multi-goal optimization question is formulized with constraints of the extract latent variable catch some variation information and mutually orthogonal to extract a group of latent features which change slowly over time and whose autoregressive model are built explicitly. When the proposed method is applied to the process monitoring, in addition to the statistics about slow feature and whose first derivatives with respect to time which have existed in SFA based monitoring frame, we add other two statistics which only contain unpredictable variability information to provide more sensitive monitoring results. Case studies on simulation data, data from a CSTR process are presented to reveal the efficiency and the superiority of the proposed method as compared to other related methods.

Feasibility of spiral fMRI based on an LTI gradient model

Spiral imaging is very well suited for functional MRI, however its use has been limited by the fact that artifacts caused by gradient imperfections and B0 inhomogeneity are more difficult to correct compared to EPI. Effective correction requires accurate knowledge of the traversed k-space trajectory. With the goal of making spiral fMRI more accessible, we have evaluated image reconstruction using trajectories predicted by the gradient impulse response function (GIRF), which can be determined in a one-time calibration step.GIRF-predicted reconstruction was tested for high-resolution (0.8 mm) fMRI at 7T. Image quality and functional results of the reconstructions using GIRF-prediction were compared to reconstructions using the nominal trajectory and concurrent field monitoring.The reconstructions using nominal spiral trajectories contain substantial artifacts and the activation maps contain misplaced activation. Image artifacts are substantially reduced when using the GIRF-predicted reconstruction, and the activation maps for the GIRF-predicted and monitored reconstructions largely overlap. The GIRF reconstruction provides a large increase in the spatial specificity of the activation compared to the nominal reconstruction.The GIRF-reconstruction generates image quality and fMRI results similar to using a concurrently monitored trajectory. The presented approach does not prolong or complicate the fMRI acquisition. Using GIRF-predicted trajectories has the potential to enable high-quality spiral fMRI in situations where concurrent trajectory monitoring is not available.

Measuring radiofrequency field-induced temperature variations in brain MRI exams with motion compensated MR thermometry and field monitoring.

An MR thermometry (MRT) method with motion and field fluctuation compensation is proposed to measure non-invasively sub-degree brain temperature variations occurring through radiofrequency (RF) power deposition during MR exams. MRT at 7T with a multi-slice echo planar imaging (EPI) sequence and concurrent field monitoring was first tested in vitro to assess accuracy in the presence of external field perturbations, an optical probe being used for ground truth. In vivo, this strategy was complemented by a motion compensation scheme based on a dictionary pre-scan, as reported in some previous work, and was adapted to the human brain. Precision reached with this scheme was assessed on eight volunteers with a 5 minute-long low specific absorption rate (SAR) scan. Finally, temperature rise in the brain was measured twice on the same volunteers and with the same strategy, this time by employing a 20-minutes scan at the maximum SAR delivered with a commercial volume head coil. In vitro, the root mean square (RMS) error between optical probe and MRT measurements was 0.02°C with field sensor correction. In vivo, the low SAR scan returned a precision in temperature change measurement with field monitoring and motion compensation of 0.05°C. The 20-minutes maximum SAR scan returned a temperature rise throughout the inner-brain in the range of 0-0.2°C. Brain periphery remained too sensitive with respect to motion to lead to equally conclusive results. Sub-degree temperature rise in the inner human brain was characterized experimentally throughout RF exposure. Potential applications include improvement of human thermal models and revision of safety margins.

Function and Emotion in Everyday Life With Type 1 Diabetes (FEEL-T1D): Protocol for a Fully Remote Intensive Longitudinal Study.

BackgroundAlthough short-term blood glucose levels and variability are thought to underlie diminished function and emotional well-being in people with type 1 diabetes (T1D), these relationships are poorly understood. The Function and Emotion in Everyday Life with T1D (FEEL-T1D) study focuses on investigating these short-term dynamic relationships among blood glucose levels, functional ability, and emotional well-being in adults with T1D.ObjectiveThe aim of this study is to present the FEEL-T1D study design, methods, and study progress to date, including adaptations necessitated by the COVID-19 pandemic to implement the study fully remotely.MethodsThe FEEL-T1D study will recruit 200 adults with T1D in the age range of 18-75 years. Data collection includes a comprehensive survey battery, along with 14 days of intensive longitudinal data using blinded continuous glucose monitoring, ecological momentary assessments, ambulatory cognitive tasks, and accelerometers. All study procedures are conducted remotely by mailing the study equipment and by using videoconferencing for study visits.ResultsThe study received institutional review board approval in January 2019 and was funded in April 2019. Data collection began in June 2020 and is projected to end in December 2021. As of June 2021, after 12 months of recruitment, 124 participants have enrolled in the FEEL-T1D study. Approximately 87.6% (7082/8087) of ecological momentary assessment surveys have been completed with minimal missing data, and 82.0% (82/100) of the participants provided concurrent continuous glucose monitoring data, ecological momentary assessment data, and accelerometer data for at least 10 of the 14 days of data collection.ConclusionsThus far, our reconfiguration of the FEEL-T1D protocol to be implemented remotely during the COVID-19 pandemic has been a success. The FEEL-T1D study will elucidate the dynamic relationships among blood glucose levels, emotional well-being, cognitive function, and participation in daily activities. In doing so, it will pave the way for innovative just-in-time interventions and produce actionable insights to facilitate tailoring of diabetes treatments to optimize the function and well-being of individuals with T1D.International Registered Report Identifier (IRRID)DERR1-10.2196/30901

Failure sequence determination in sandwich structures using concurrent acoustic emission monitoring and postmortem thermography

This study provides a novel approach for damage classification and failure sequence evaluation in sandwich panel composite materials under flexural loading condition merely by using acoustic emission monitoring in interrupted mechanical tests and postmortem lock in thermography analysis. The studied sandwich panels consist of glass fiber reinforced phenolic skins and Nomex honeycomb core which are used extensively in the aerospace industry. While one of the standard flexural samples is mechanically tested up to global failure, the other specimens are loaded till a certain load level and the tests are interrupted. Acoustic emission hits are recorded throughout the mechanical tests by using piezoelectric sensors, and are classified using a well-established clustering algorithm. The damaged samples are then investigated via lock in thermography technique to identify the hidden failure progress inside the sandwich structure. Acoustic emission monitoring is successfully used to mark the change of mechanical response under flexural loading condition. The results of acoustic emission analysis indicated four different clusters associated with four major failure modes occurring due to mechanical loading. Correlating failure progress observed in thermography results with the fraction of acoustic emission clusters registered during mechanical tests helped to attribute each class of acoustic emission hits to a specific failure type. Upon using the interrupted test methodology together with the lock-in thermography technique, one can reliably identify the damage types and their sequence of manifestation during flexural tests. The results show that successful analysis of visually hidden failure progress in sandwich panel composites under out of plane loading condition can be attained by using structural health monitoring techniques and quasi static tests.