To provide a ground-based experimental reference for free-space optical time-frequency synchronization in future space applications, this paper investigates the impact of beam drift and dynamic link-state variations on free-space laser links. A bidirectional free-space laser time-frequency synchronization and ranging system is established and the synchronization process is uniformly modeled. An improved Kalman filtering method based on innovation consistency is proposed in which a strong tracking mechanism enhances adaptability to model mismatch and abnormal observations; at the same time, an adaptive observation noise modeling strategy based on online statistical estimation characterizes the time-varying noise properties of free-space optical links. Experimental validation is conducted using an equivalent free-space laser link of approximately 321 m. The results show that the proposed method improves the time synchronization accuracy from 78.32 ps to 45.64 ps, corresponding to an enhancement of about 41%. In terms of time stability, the time deviation (TDEV) is reduced from 7.14×10-11 s to 4.33×10-11 s at an averaging time of τ=1 s, and from 4.20×10-12 s to 7.01×10-13 s at τ=800 s. For ranging performance, the system achieves an average measured distance of 321.56 m with a ranging standard deviation of 15.2 mm. These results demonstrate that the proposed approach enables high-precision and stable state estimation for integrated free-space laser time-frequency synchronization and ranging systems.
This paper investigates the fixed-time drive-response synchronization problem of delayed inertial memristive neural networks under denial-of-service (DoS) attacks. To address the complex dynamics arising from inertial effects, time-varying delays, uncertainties in memristive switching, and the interplay of intermittent DoS attacks, a fixed-time control scheme is proposed based on fixed-time stability theory. By constructing an appropriate Lyapunov function, several sufficient conditions are derived to guarantee synchronization within a fixed-time under DoS attack scenarios. Furthermore, an explicit expression for the upper bound of the settling time is provided, quantitatively revealing the dependence of settling time on controller parameters and the intensity of DoS attacks. The impact of attack intensity on synchronization performance is also analyzed. Notably, the proposed theoretical framework applies not only to aperiodic DoS attacks but also covers periodic DoS attacks, and remains effective even under normal operating conditions without DoS attacks, thereby significantly broadening the applicability and generality of the results. Finally, numerical simulations are presented to further validate the effectiveness and robustness of the proposed control strategy.
This study proposes a digital twin-based CPR compression measurement system (DTCMS) architecture for real-time monitoring of CPR compression. The system combines a load cell, an inertial measurement unit (IMU), a LabVIEW acquisition platform, and a CNN module to capture multi-modal motion characteristics during CPR repetitive compression training. A calibration-aware sensor fusion framework synchronizes heterogeneous signals, reduces drift, and enhances robustness under high-frequency operation. Real-time data acquisition, latency-controlled transmission, and digital twin visualization enable synchronized physical-virtual interaction. Experimental results demonstrate high accuracy (R2 > 0.99), stable repeatability (coefficient of variation: CV < 3.5%), and reliable dynamic tracking. The compression depth error was maintained within ±1.5 mm, and synchronization latency remained below 0.2 s. Results confirm the proposed DTCMS architecture as a robust solution for real-time biomechanical monitoring and digital twin-based interactive systems. Compared with conventional single-sensor CPR monitoring systems, the proposed framework improves synchronization stability and sensing robustness through calibration-aware multi-sensor fusion.
The study of figs (Ficus spp., Moraceae) has received considerable attention in the scientific literature, due to the genus' large number of species (700), pollination mutualism with Agaonid wasps, and its role as a keystone food resource in tropical ecosystems. Temporal sexual separation in hermaphroditic Ficus and asynchronous flowering among individuals within populations creates problems in supporting a viable population of dependent pollinator wasp species. To maintain the short-lived wasp populations, Ficus populations must provide a continuous temporal sequence of flowering trees, which are havens for the pollinating, termed the Critical Population Size (CPS). CPS was defined at the threshold between parameter settings yielding no wasps at the end of any simulation run and those in which at least one tree retained wasps for all 100 model runs for a setting within a scenario. A theoretical model of fig-wasp persistence dynamics incorporating temporal and spatial components was developed to examine CPS in monoecious species. Parameterization of this model is from literature and applicable to many species of Ficus. Because male and female fig flowers occur sequentially within a tree, the model represents the timing of the male and female phases separately rather than combining them into a single flowering period. Distance wasps can fly is essential in sustainable populations of Ficus. The influence of other model parameters on the system and how the system responds when longer simulation times are conducted. The model developed here can examine the transfer of pollen and catalog the links between trees, essentially allowing the examination of a network that varies temporally but not spatially. This model develops a new concept on what is deemed a viable pollinating population and includes spatial attributes and the ability to track individual trees and wasps.
Astrocytes play essential roles in neuronal development, function, and disease, yet existing methods to derive astrocytes from human pluripotent stem cells (hPSCs) are complex and can involve months of in vitro maturation. We developed a genomic safe-harbor knock-in system for inducible expression of the astrogenic transcription factors NFIA, NFIB, and SOX9, enabling rapid and robust generation of functional induced astrocytes (iAstrocytes). Across five hPSC lines, NFIB-SOX9 and NFIA-NFIB-SOX9 combinations efficiently generated highly pure populations expressing astrocyte-specific and synaptogenic genes. iAstrocytes displayed cytokine-induced expression of complement factors C3 and C4 and were amenable to CRISPR interference (CRISPRi) gene expression knockdown. Optimization of culture conditions enabled survival of NFIB-SOX9 iAstrocytes in co-culture with human induced neurons (iNeurons). Through pharmacological and genetic perturbations, we uncovered a previously undescribed phenomenon in which co-culture with iAstrocytes promoted the development of synchronized iNeuron network calcium activity mediated by specific gap junction proteins. This rapid and genetically tractable iAstrocyte platform provides a robust model to dissect human genetic and environmental effects on astrocyte-neuron interactions.
In passive-source seismic exploration, even after seismic instruments complete unified start-up acquisition and hardware synchronization, long-duration continuous records may still contain small residual timing errors, which in turn broaden cross-correlation peaks and degrade event-location results. To address this problem, this study proposes a wavefield-domain residual timing refinement method. The method uses stable noise windows and controlled artificial events in continuous records as constraints, and performs data-window preprocessing, reference cross-correlation function construction, pairwise residual lag estimation, confidence-weighted multi-station joint fusion, and smoothing-constrained fitting of a continuous correction curve to achieve a posterior refinement of residual timing errors after hardware synchronization. Fractional-delay interpolation is then used for waveform correction. Validation using a 60 min continuous record from a local six-station array shows that the proposed method can serve as an effective supplement to hardware synchronization, suppress residual timing errors, and improve the temporal consistency, waveform stackability, and interpretation reliability of passive-source seismic exploration data.
Synchronization of coupled oscillators is observed in many natural and engineered systems and emerges due to the interactions within the system. It can be both beneficial, e.g., in power grids, and harmful, e.g., in epileptic seizures. In the latter case, efficient control methods to desynchronize the systems are crucial. Recent studies have shown that interactions are not always pairwise, but higher-order, i.e., many-body, and this greatly affects the dynamics. For instance, higher-order interactions increase the linear stability of synchronized states but simultaneously shrink their attraction basin, with potentially opposite effects on control methods. Here, we use a minimally invasive pairwise control based on Hamiltonian control theory and investigate its efficiency on phase oscillators with higher-order interactions. We show that, if the initial phases are close to the synchronized state, higher-order interactions make desynchronization more difficult to achieve. Otherwise, a non-monotonic effect appears: intermediate strengths of higher-order interactions impede desynchronization while larger ones facilitate it. In all cases, the control can desynchronize the system with a sufficient number of controlled nodes and intensity.
Early detection of cognitive decline remains one of the major challenges in contemporary neurology. Although event-related potentials associated with cognitive processes, particularly the P300 component, as well as resting-state EEG analysis, have long been investigated as potential functional biomarkers of dementia, their clinical application is often limited by methodological heterogeneity and insufficient transparency of signal processing procedures. In this article, we present a reproducible EEG-ERP methodology based on proprietary software for stimulus generation, synchronization, and deterministic averaging of visual event-related potentials, combined with quantitative analysis of resting-state EEG frequency. The approach integrates precise stimulus timing, transparent offline synchronization using an audio marker recorded on the ECG channel, and a fully deterministic averaging procedure. Pilot clinical data obtained from patients with mild cognitive impairment and dementia are included to illustrate the feasibility of the proposed workflow. • Software-controlled visual stimulation with fixed inter-stimulus intervals and explicit offline synchronization using an audio marker. • Deterministic ERP averaging enabling reliable estimation of P300 latency in routine clinical EEG recordings. • Integration of resting-state EEG frequency and P300 latency as interpretable electrophysiological markers of cognitive decline.
High-precision time synchronization among high-dynamic platforms is an important foundation for distributed detection, cooperative sensing, and networked operation of high-speed mobile platforms. In high-dynamic two-way microwave links, rapid variations in propagation geometry, Doppler-related frequency offsets, and link-quality fluctuations can break the approximate symmetry between uplink and downlink propagation. Although geometric and motion compensation can remove the dominant propagation-asymmetry term, residual asymmetric errors caused by propagation modeling errors, compensation mismatch, and link degradation may still remain and couple into clock-offset estimation, thereby reducing synchronization stability and accuracy. To address this problem, this paper proposes a modeling and joint estimation method for residual asymmetric errors in high-dynamic two-way microwave links. The post-compensation residual error is modeled as a recursively estimable dynamic state, and its rate of change is introduced to characterize the short-term evolution of the residual term. Meanwhile, a four-timestamp and frequency-offset joint observation model is constructed, in which frequency-offset information is used as an observation-level auxiliary constraint to enhance local separability among the clock offset, frequency offset, and residual link state. On this basis, a link-state-information-assisted IMM-IEKF is adopted to realize online joint estimation of clock parameters and link residual errors. Under the equivalent stochastic-error simulation setting, the proposed method effectively suppresses post-compensation residual asymmetric errors and achieves sub-nanosecond synchronization accuracy under strong-dynamic and degraded-link conditions.
Mobile apps and wearable devices may help to facilitate early detection of mental health conditions by providing objective, real-time data to supplement other forms of feedback and diagnoses. Few studies have investigated the acceptability and feasibility of using a mobile app to track survey- and wearable-based data in mental health research in Sub-Saharan Africa. This pilot study evaluated the feasibility and acceptability of using a mobile app and wearables to capture mental health-based survey data and passively sensed data among Kenyan health care workers. A mixed methods study was conducted among health care workers employed at 4 hospitals in Nairobi, Kenya, over 30 days. A mobile app was used to collect and integrate active (baseline questionnaire and daily mood) and passive (wearable) data. The baseline questionnaire gathered information on sociodemographics, work environment, and mental health assessments on depression, anxiety, personality, early family environment, posttraumatic stress disorder, and substance use. A wearable device was used to gather data on steps, heart rate, and sleep. Qualitative interviews were conducted post trial to gain in-depth insights into participants' experiences during the study. Fifty-one participants enrolled in the pilot study. They were primarily nurses (47%) and female (70%), with a median (IQR) age of 32 (29-36) years. Attrition over 30 days was low, with only one participant dropping out due to device malfunction, which was a broken screen. Completeness of the baseline survey was high, with participants completing 96.1% of the questions. Further, 58% of the daily mood ratings were completed over the 30 days. For the wearable measures, participants submitted steps, heart rate, and sleep data on 93%, 73%, and 51% of study days, respectively. The proportion of days the wearable was worn for over 10 hours was 63%. Interviews revealed 2 primary themes. The first was intrinsic and extrinsic motivation; participants indicated that they liked having their health metrics tracked and receiving congratulatory messages from the app, encouraging increased step counts. The second theme was technical and usability challenges; 48% (10/21) of the participants reported discomfort wearing the watch while sleeping and challenges with synchronization of data due to the nonautomated nature of the process. Participants suggested additional prompts to remind them to complete the daily mood question. This pilot study demonstrates the feasibility of deploying mental health surveys, collecting data through wearable devices, and integrating such data within a single mobile platform under real-world infrastructure constraints. Health care workers in Kenya were willing to provide sensitive information through mental health assessments using a mobile app. To improve adherence, future studies should consider addressing some contextual factors such as daily prompts, enhanced data synchronization methods, and comfort concerns to improve adherence, especially during sleep.
A numerical research work is carried out to examine fluid-structure interaction in flow over six inline square cylinders undergoing transverse oscillations via the lattice Boltzmann method. The impact of the oscillation frequency ratio ([Formula: see text]), where imposed oscillation frequency is represented as [Formula: see text] and [Formula: see text]is the natural vortex shedding frequency of a stationary cylinder, on wake dynamics and flow patterns is examined. Simulations are performed at Reynolds number of Re = 80, with a non-dimensional gap spacing (s/d = 1.0) and an oscillation amplitude ratio of A/d = 0.2. The frequency ratio is varied in the range 0.1 < [Formula: see text]≤ 2.0. Three distinct flow patterns are identified: synchronous lock-on (0.8 ≤ [Formula: see text]≤ 1.4), quasi-periodic lock-on-I (1.6 ≤ [Formula: see text] ≤ 2.0) and quasi-periodic non-lock-on-I (0.1 ≤ [Formula: see text]≤ 0.6). The synchronization range is wider than that reported for single oscillating cylinder. A single coherent wake envelops the entire cylinder array, with wake recovery occurring at higher oscillation frequencies due to merging of vortex and formation of multi-polar vortices downstream of final cylinder. The first cylinder experiences highest mean drag, followed by a reduction and gradual increase along the downstream cylinders.
Wearable inertial sensors offer a portable alternative to laboratory-grade force plates for postural stability assessment; however, their validity across progressively challenging balance tasks remains under-explored. This study evaluated the reliability and concurrent validity of inertially sensed metrics compared with force-plate-derived postural sway metrics across a five-level spectrum of unstable surfaces (Floor, Foam Pad, Rotating Disc, Air Disc, Bosu). Twenty-five healthy young women (22.1 ± 3.6 years, 1.64 ± 0.04 m, 58.44 ± 8.21 kg) performed five trials of single-leg standing (40 s each) on each surface. Postural sway was computed from antero-posterior (AP) and medio-lateral (ML) center of pressure (CoP) recordings using a force plate (Kistler, 9286 AA, Winterthur, Switzerland, sampling at 500 Hz) in synchronization with a lateral shank-mounted inertial sensor (Bionomadix BN-ACCL3, Biopac Systems, Inc., Santa Barbara, CA, USA, sampling at 100 Hz). In addition to reliability, a two-tiered analysis evaluated global concordance (unstandardized slopes) and method agreement (standardized z-scores). Intraclass correlation coefficients (ICCs) for the inertial sensor were excellent (range: 0.95-0.96), surpassing the force plate (range: 0.85-0.92) as trials accumulated. Analysis revealed moderate-to-good global concordance in the AP direction (r = 0.60, p = 0.001) and good-to-excellent in the ML one (r = 0.85, p < 0.001), validating the progressive intensifying effect of the surface graduation. Individual ranking agreement-evaluated via standardized z-scores-was also significant in both the AP (r = 0.61, p < 0.001) and the ML (r = 0.85, p < 0.001) directions, indicating a convergence into how the two modalities rank individual performance. Bland-Altman plots confirmed high absolute agreement between standardized scores, though a predictable proportional bias was observed in raw units, where the inertial sensor's underestimation of sway magnitude increased linearly with task difficulty. The five-level postural challenge graduation is a highly reliable framework for balance assessment. While the shank-mounted sensor exhibits proportional underestimation of sway magnitude compared to the CoP at extreme intensities, its high internal stability and sensitivity to task difficulty make it a valid and robust tool for longitudinal clinical monitoring.
Many factors may negatively affect dairy cattle productivity, among which imprecise estrus detection is a major contributor to low reproductive efficiency. Given that artificial insemination is widely used in the dairy industry, accurate estrus detection is of great importance. Estrus synchronization using hormonal treatments is a common approach to regulate the estrous cycle and to improve the efficiency of estrus detection. Estrus detection using artificial intelligence-aided data analyses is a new development. Biomarker-based chemical sensors and activity based wearable and implantable sensors are also available for monitoring. Behavioral datasets have been used in machine learning and other approaches; however, such datasets must be validated for their applicability in detecting estrus before being utilized by dairy farmers. The cumulative knowledge of estrus detection approaches, their merits, demerits, applicability, and cost-effectiveness is highly warranted. Therefore, here, we provide an update on the recent approaches and technologies used for estrus detection, particularly in dairy cattle, and discuss emerging experimental technologies with potential for future applications.
In this study, it was aimed to compare the effects of embryo transfer performed via laparotomy and laparoscopy on thiol-disulphide homeostasis and some oxidative stress markers in Tuj ewes. In the study, 10 Tuj ewes were randomly divided into two groups (laparotomy, n = 5; laparoscopy, n = 5). A progesterone-based synchronization protocol was applied to all animals. Blood samples were collected immediately before surgery, immediately after surgery, and at 24 and 48 h postoperatively. Serum levels of glutathione (GSH), malondialdehyde (MDA), total thiol (TT), native thiol (NT), disulphide (Ds) and thiol-disulphide ratios were determined. Group, time, and group × time interactions were found to be statistically significant for GSH, MDA, TT, and NT parameters (p < 0.05). In the laparotomy group, GSH, TT, and NT levels markedly decreased during the postoperative period (p < 0.05), whereas MDA levels showed a significant increase, particularly at 48 h (p < 0.05). In the laparoscopy group, changes in oxidative stress markers were found to be more limited. Although no significant differences were observed between the groups in terms of disulphide levels and thiol-disulphide ratios (p > 0.05), time-dependent changes in these parameters were statistically significant (p < 0.05). In the laparotomy group, significant negative correlations were detected between MDA and antioxidant parameters (p < 0.05), while strong positive correlations were observed among thiol parameters (p < 0.01). As a result, it was concluded that the surgical approach used in embryo transfer affects the systemic oxidative stress response and that thiol-disulphide homeostasis can be considered a sensitive biomarker for revealing these differences. It was determined that the laparoscopic embryo transfer method disrupts redox balance to a lesser extent and better preserves the antioxidant defence system compared with laparotomy.
We demonstrate a reconfigurable microwave frequency measurement (MFM) scheme based on the period-one (P1) dynamics of an optically injected semiconductor laser. Unlike conventional architectures relying on electrical frequency-sweeping, our approach utilizes the P1 oscillation to generate a wideband linear optical chirp. A spectral gating mechanism is introduced, where an optical bandpass filter creates a negative temporal marker by rejecting free-running component of distributed feedback laser (DFB), thereby eliminating the need for external synchronization or pilot tones. The measurement range is flexibly tunable by adjusting the injection parameters, enabling a measurement range from 10 to 48 GHz. Experimental results demonstrate a frequency resolution of 50 MHz with chirp rate of 1 GHz/μs and a root-mean-square (RMS) error below 15 MHz, confirming the validity of this all-optical, self-referenced frequency-to-time mapping technique.
Pancreatic ductal adenocarcinoma (PDAC) carries a poor prognosis, particularly in metastatic disease where surgical resection is traditionally not recommended. However, the concept of oligometastatic disease-characterized by limited metastatic spread with a presumed more favorable oncological prognosis-has prompted reconsideration of metastasis-directed therapies, including surgery, in carefully selected patients. A selective literature review was conducted using PubMed to identify studies reporting surgical treatment for oligometastatic PDAC, including synchronous or metachronous metastases. Studies were included if they reported outcomes after resection of the primary tumor and/or metastatic lesions in patients with limited metastatic burden. Results were presented in a narrative way. Retrospective studies suggest that surgical resection of the primary tumor and metastases may be feasible, safe and associated with prolonged survival in selected patients with oligometastatic PDAC. Favorable prognostic factors across studies include response to systemic chemotherapy prior to resection, low tumor marker levels, limited number of metastases, and the possibility of achieving complete macroscopic resection. Patients with isolated pulmonary metastases appear to have particularly favorable outcomes. However, existing evidence is derived exclusively from retrospective analyses and is subject to considerable selection bias. Current evidence indicates that surgery for oligometastatic PDAC may benefit highly selected patients within a multimodal treatment strategy. The results of ongoing prospective and randomized clinical trials are expected to clarify the role of surgery in this setting. Until these results become available, treatment decisions should be individualized and made within multidisciplinary tumor boards.
Accurate measurement of chewing events in natural eating conditions is important for unobtrusive monitoring of feeding behavior and masticatory function. Yet, existing methods often rely on contact sensors, dedicated wearables, or manual annotation. This work presents a non-contact, video-based framework for chewing-event detection using frontal facial video, normalized 3D facial landmark dynamics, and recurrent temporal modeling. To obtain physiologically grounded reference labels, synchronized bilateral anterior temporalis surface electromyography was acquired during real-meal sessions and used to derive chewing-event annotations during dataset construction, whereas inference relied exclusively on video. Facial motion was represented from frame-wise 3D landmarks and processed by recurrent neural networks, with model selection performed through Bayesian hyperparameter optimization. On an independent hold-out test set comprising five sessions and 18,836 frames, the proposed method detected 577 chewing events versus 589 ground truth events, corresponding to a mean absolute error of 4.4 chews/session and a mean absolute percentage error of 4.32%. A comparison with a related rule-based video method from the literature showed substantially larger counting errors (MAE = 39.4, MAPE = 30.39%), particularly in sessions that included concurrent activities such as speaking, suggesting that the proposed approach can reduce counting errors relative to the considered rule-based baseline under the specific meal conditions tested in this feasibility study. The effect of landmark-localization uncertainty on the predicted chewing probability was assessed through Monte Carlo propagation, showing limited impact for most prediction instants and greater sensitivity for intermediate probability values. Finally, the ONNX implementation achieved a mean latency of 8.96 ± 5.74 ms on CPU and 6.89 ± 3.58 ms with CUDA execution on the test workstation, supporting real-time applicability. To support practical deployment, the pipeline was also implemented as a native Kotlin Android application and tested on a commercial tablet, achieving real-time operation at 20 fps.
This study presents the first clinical integration and experimental demonstration of a nozzle-mounted Compton camera prompt gamma imaging (PGI) system for in vivo proton range verification. Four position-sensitive solid-state Compton camera modules, each containing four cadmium zinc telluride (CdZnTe) detector crystals, were integrated into a modified range shifter mounted directly on the treatment nozzle of a clinical proton therapy gantry. This compact fixed-geometry configuration maintained alignment with the proton beam axis throughout irradiation and enabled stable synchronized data acquisition during pencil-beam scanning delivery. The system was evaluated under realistic clinical proton beam delivery conditions using single-energy and spread-out Bragg peak (SOBP) irradiations at gantry angles of 90° and 270°, delivered doses of 2 Gy and 7.5 Gy, and controlled distal range shifts of up to 10 mm. Prompt gamma events were reconstructed into three-dimensional emission distributions using a physics-based Compton scatter reconstruction framework. The system operated reliably during all irradiations and produced reproducible prompt-gamma localization across repeated measurements. Reconstructed emission distributions remained geometrically consistent across gantry angles and demonstrated sensitivity to controlled distal range perturbations, with measurable upstream shifts of the emission hotspot corresponding to reduced proton penetration depth. These results demonstrate the feasibility of a clinically integrated nozzle-mounted quad-camera Compton PGI system for detecting millimeter-scale proton range variations during beam delivery and represent an important step toward clinically deployable prompt gamma-based in vivo treatment verification in proton therapy.
Noncommunicable diseases (NCDs) account for over 70% of global deaths, with hypertension and diabetes serving as major contributors. The COVID-19 pandemic disrupted traditional health care services for NCDs and highlighted telehealth as a crucial alternative. Telehealth-encompassing synchronous and asynchronous electronic communication to deliver clinical services remotely-can overcome geographical barriers and enhance patient engagement. However, telehealth usability among health care professionals (HCPs) remains under-studied across low-, middle-, and high-income countries. This study aimed to examine which telehealth engagement patterns, technical infrastructure factors, and user profiles were most strongly associated with usability among HCPs and to descriptively compare these across 4 diverse countries: Brazil (high- to middle-income country), Ghana (low- to middle-income country), Honduras (low- to middle-income country), and the United Kingdom (high-income country). A multinational cross-sectional survey was conducted with 290 HCPs across 4 countries. Participants completed the System Usability Scale and provided data on telehealth engagement (eg, frequency, duration, and number of systems used), technical infrastructure (connection stability and support satisfaction), and their user profile (demographics, job role, and training received). Descriptive statistics summarized these patterns and usability scores. Multiple linear regression with bootstrap-based sensitivity analyses identified factors associated with telehealth usability. Given the nonprobability design, no formal inferential comparisons were made between countries. Instead, observed patterns were reported descriptively. Higher telehealth usability scores were associated with greater connection stability (b=5.06, 95% CI 3.06-7.05), higher satisfaction with online support information (b=5.02, 95% CI 3.27-6.75), more frequent use (b=3.05, 95% CI 1.36-4.73), longer duration of use (b=1.59, 95% CI 0.49-2.68), and being a physician by profession (b=3.82, 95% CI 0.23-7.40). Average usability scores were highest among users in Ghana (mean 79.75, SD 14.19) and the United Kingdom (mean 79.00, SD 14.71), followed by Brazil (mean 72.01, SD 14.62) and Honduras (mean 63.09, SD 15.57). According to System Usability Scale guidelines, scores corresponded to "good" usability for users in Ghana, the United Kingdom, and Brazil and were below the "good" threshold for users in Honduras. While most users in Ghana (97/111, 87.4%), Honduras (31/38, 81.6%), and Brazil (57/80, 70.4%) reported using only 1 telehealth system, two-thirds of UK users (40/60, 66.7%) reported using 2 or more systems. User profiles also varied; prepandemic use was highest in Ghana (84/111, 75.7%) and lowest in Honduras (7/38, 18.4%). Other engagement patterns across countries were reported. Telehealth usability is driven by technical infrastructure reliability, a robust online support infrastructure, and an "experience effect" from frequent and long-term engagement. Descriptive differences in engagement patterns and infrastructure highlight the need for tailored strategies to address setting-specific challenges. These are essential to optimize telehealth integration and improve health care outcomes for patients with NCDs worldwide.
Integrating single-cell transcriptomic and epigenomic data provides a robust framework for investigating gene regulation mechanisms. Existing analyses typically treat these modalities as synchronized features that can be translated in a static manner; however, the temporal delays that underpin cellular kinetics are intrinsic to dynamic biological systems. To address this limitation, we propose utilizing the "molecular asynchrony" within regulatory hierarchies to determine the thermodynamic properties of individual cells. Here, we present SeqTag, a single-cell multiomics sequencing method that simultaneously profiles the transcriptome, chromatin accessibility, and histone modifications, supported by an analytical framework to identify asynchronous states across regulatory layers for characterization of single-cell kinetics. By measuring the epigenetic priming potential and remodeling rates during adult mouse oligodendrogenesis, we delineated a sequential program for bivalency resolution as maturing cells traverse Waddington's landscape. This process becomes increasingly decoupled with age, a change linked to a drift in progenitor cell-fate probabilities. By identifying entropy-driving regulatory elements, we characterized the aging-related decline in cell identity across various cell types and proposed a dynamic model linking static genetic variants to the risk of late-onset diseases. In summary, our integrated approach established a unified framework for employing multimodal single-cell genomics to model the kinetics of complex cellular processes.