Mobile ambulatory cardiac telemetry (MCOT) use has increased over time; however, data on the prevalence and the impact of emergent arrhythmia notifications with MCOT remains unclear. We sought to determine the prevalence and clinical impact of emergent arrhythmia events in patients undergoing MCOT monitoring. We also analyzed the efficiency of the emergent notification process. We analyzed 8404 consecutive patients from two centers who were prescribed Philips MCOT (K153473) over a 28-month period (September 2018-January 2021). Participants meeting emergent notification criteria were included. The primary outcome was any unscheduled provider intervention after the emergent notification. We also analyzed several time domains of the provider notification process. A total of 122 patients (1.45%) satisfied emergent notification criteria during the study period. The median notification time from arrhythmia onset to provider notification was 42 min. Physician review of the arrhythmia notifications showed agreement with the monitoring technician diagnosis in 102/122 (83.6%). An emergent notification resulted in an unscheduled follow-up visit in 104/122 (85.2%) patients. Time from arrhythmia event to unscheduled follow up visit was < 24 h in 88/104 (84.6%), 24-72 h in 9/104 (8.7%) and > 72 h in 7/104 (6.7%). In 33 patients (27%), emergent notifications resulted in unscheduled interventions including: device implantation (24), ablation (8), and electrical cardioversion (4). Emergent arrhythmias events recorded during ambulatory telemetry monitoring resulted in unscheduled patient contact in 85% of cases and procedures in 27% of cases. The monitoring notification process was efficient, with median time from arrhythmia onset to provider notification of 42 min.

Arthropod-borne pathogens, many of which are neurotropic, can disseminate beyond the central nervous system to infect peripheral organs. In recent years, an increasing number of cardiac dysfunctions have been reported following arthropod-borne viral infections; however, the mechanism underlying these cardiac manifestations remains poorly understood. In this study, we investigated the impact of Venezuelan Equine Encephalitis Virus (VEEV) TC-83 infection on cardiac function and immune-response of human induced-pluripotent stem cell (hIPSC)-derived cardiomyocytes (hIPSC-CMs). We first confirmed the successful differentiation of hIPSCs into spontaneously beating hIPSC-CMs. We then demonstrated that these cells are highly susceptible to VEEV TC-83 infection, which induced pronounced arrhythmias and complete cessation of beating within 24 hours post-infection. To quantify these functional changes, we developed a segmentation-free computational pipeline that converts frame-to-frame motion in brightfield time-lapse movies into a one-dimensional signal reflecting contractile activity and extracts beat timing, beat rate, and rhythm-regularity features in the time and frequency domains. This analysis revealed progressive disruption of beating dynamics following VEEV TC-83 infection, with early rhythm instability and complete loss of coordinated beating by 24 hours post-infection. Furthermore, mass spectrometry analysis of VEEV TC-83-infected hIPSC-CMs supernatants revealed the presence of biomarkers typically associated with heart failure in patients, underscoring a virus-induced cardiac functional impairment. Together, these findings provide new insight into cardiac complications associated with arthropod-borne viral infections and may support advances in preventive medicine.

Abstract We present the first statistical census of emission-line variable active galactic nuclei (EVA) at cosmic noon by combining untargeted and deep Hobby–Eberly Telescope Dark Energy Experiment (HETDEX) spectroscopy with multiepoch spectra from the Sloan Digital Sky Survey, DESI, and LAMOST. Anchoring all candidates to a HETDEX spectroscopic epoch and requiring an active galactic nucleus (AGN) classification in either the HETDEX or external epoch(s), we identify a homogeneous sample of 100 EVA at z ∼ 1.5, including 98 that are newly identified. Emission-line variability is selected primarily through statistically significant line-flux changes, supplemented by extensive visual inspections using contemporaneous photometric light curves. The resulting incidence fraction is f EVA ∼ 0.9%. The rest-frame intervals between spectroscopic epochs span ∼1–10 yr, with brightening and dimming events exhibiting statistically indistinguishable characteristic timescales (Δ T ∼ 2.2 and ∼2.6 yr, respectively). A key result is the characterization of the Baldwin effect in the time domain: while many EVA follow the ensemble Baldwin effect (eBeff) between two epochs, a substantial fraction exhibit apparent anti-eBeff responses. Time-resolved spectroscopy of an individual source reveals that the intrinsic equivalent width–luminosity relation is nonstationary, with the line-to-continuum responsivity systematically evolving from stronger to weaker across successive variability cycles; sparse two-epoch sampling of this evolving intrinsic Baldwin evolution naturally produces both eBeff-like and anti-eBeff behaviors. Finally, EVA show no strong preference for extreme Eddington ratios but exhibit a mild tendency toward lower λ Edd values relative to matched control samples, driven primarily by sources observed in their dim states. Together, these results establish a coherent framework for interpreting emission-line variability in AGN at the peak epoch of cosmic black hole growth.

Integrating in-situ modal testing and numerical modelling based on experimental evidence is a powerful strategy for studying the dynamic behavior of existing constructions and making decisions about their retrofitting or monitoring. This paper applies this strategy to analyze the seismic behavior of an unreinforced masonry arch bridge in Spain, investigating on two different approaches to account for the backfill material. An extensive experimental campaign was conducted to determine the bridge’s mechanical and dynamic properties. Operational modal analysis, carried out using two accelerometer setups, was used to extract frequencies and modal shapes through algorithms in both the time and frequency domains. Two finite-element models of the bridge were built and identified: one that treats the backfill between the masonry wall faces as a structural material and another that does not include the backfill, instead redistributing its mass within the masonry density. The two models’ modal behavior and dynamic responses to a real earthquake were then compared to evaluate the effect of different ways of accounting for backfill.

Flutter is a critical aeroelastic instability of panel structures under aerodynamic loading, which may cause severe vibration and structural failure in high-speed flight. Most flutter analyses in supersonic are conducted with the traditional stable-flow assumption, and the shock-induced instability subjected to spatially varying aerodynamic pressure remains insufficiently explored. The present study investigates the effects of key structural parameters and shock-related aerodynamic variations on the critical aerodynamic pressure and transient vibration response of the cantilever honeycomb sandwich panel in yawed supersonic flow. In the theoretical model, the first-order piston theory is employed in the pre-shock and post-shock regions separately to estimate the aerodynamic pressure discontinuous flow. The aeroelastic governing equations are derived via Hamilton’s principle based on classical plate theory with von Karman strain–displacement relations, and then spatially discretized using the Galerkin method. The flutter boundary is obtained by solving the resulting eigenvalue problem, followed by a systematic parametric study accounting for structural parameters and shock characteristics. Subsequently, the fourth-order Runge–Kutta method is applied to integrate the governing equations in the time domain, and the vibration response of the panel is analyzed through time history and wavelet transform. This study provides guidance for the aeroelastic stability design and optimization of cantilever honeycomb sandwich panels.

The accurate computation of low-energy spectra of strongly correlated quantum many-body systems, typically accessed via Green's functions, is a long-standing problem posing enormous challenges to numerical methods. When the spectral decomposition is obtained from Fourier transforming a time series, the Nyquist-Shannon theorem limits the frequency resolution Δω according to the numerically accessible time domain size T via Δω=2π/T. In tensor network methods, increasing the domain size is exponentially hard due to the ubiquitous spread of correlations, limiting the frequency resolution and thereby restricting this ansatz class mostly to one-dimensional systems with small quasiparticle velocities. Here, we show how this limitation can be overcome by augmenting the time series with complex-time Krylov states. With the example of the critical S-1/2 Heisenberg model and light bipolarons in the two-dimensional Su-Schrieffer-Heeger model, we demonstrate the enormous improvements in accuracy, which can be achieved using this method.

_ In the manufacturing industry, the problem of circle plate packing processing is common and important. In this study, an innovative algorithm is proposed to transform the packing of a circle in a rectangular container into the motion of a disturbed object group. First, the discrete element method (DEM) is used to construct the mathematical model of equal circle motion. By establishing the time domain and complex frequency domain models, the internal stability of the motion system and the feasibility of the algorithm implementation are confirmed. Second, the sweep and prune method and the quadtree method are introduced for collision detection, and the continuous collision detection is used to deal with the tunneling phenomenon caused by high-speed motion. Then, based on the impulse method, the collision circle is processed, and the impulse size is accurately calculated from the two aspects of velocity change and position constraint. The error compensation is introduced to reduce the calculation error, and the calculated impulse updates the circular velocity and position in real time. Finally, the feasibility of the algorithm is verified by an example test, which provides a new direction for solving the circle packing problem. Keywords two-dimensional packing, equal circle packing, stability analysis, collision detection, collision response

Underground power cables are commonly employed for use in urban regions because of safety and reliability benefits. However, it is difficult and time-consuming to identify faults in underground cables. Conventional techniques for identifying faults in underground cables involve manual inspection and the use of equipment. Recently, IoT-based monitoring techniques have been proposed for use in underground cables for real-time fault detection. This paper discusses different techniques for underground cable fault detection, namely Time Domain Reflectometry (TDR), and techniques with IoT.Keywords: Underground Cable Fault Detection, Internet of Things (IoT), Time Domain Reflectometry (TDR), Smart Grid, Real-Time Monitoring, Fault Localisation, Power Distribution Systems.

Dielectric relaxation behavior of ethylene glycol–1-propanol (EG–PR) binary mixtures was investigated using time domain reflectometry over a frequency range of 10 MHz to 30 GHz at temperatures of 10 °C, 15 °C, 20 °C, and 25 °C. Eleven compositions were studied to understand the influence of molecular interactions and hydrogen bonding on dielectric properties. The complex permittivity spectra were analyzed using the Havriliak–Negami model, revealing Cole–Davidson-type relaxation. The static dielectric constant (ε0) increased with EG concentration, while relaxation time (τ) decreased, reflecting faster dipolar reorientation in EG-rich mixtures. Negative excess permittivity and deviations in excess inverse relaxation time indicated strong non-ideal behavior due to specific intermolecular interactions. Kirkwood correlation factors (gₑff >1) and Bruggeman factor deviations confirmed cooperative dipolar alignment and structural heterogeneity. Arrhenius analysis showed thermally activated relaxation with composition-dependent activation energies. The results highlight the critical role of hydrogen bonding and molecular associations in governing dielectric response, providing insight into the cooperative dynamics and non-ideal mixing behavior of polar binary liquids

In this paper, a dual-layer metamaterial structure operating in the microwave band which is composed of nested split-ring resonators (SRRs) was designed. The electromagnetic transmission under two polarization modes are comparatively analyzed through the finite integral time domain method. By scrutinizing the electric field distribution on each resonance frequency, the physical mechanism of the electromagnetically induced transparency (EIT)-like effect is expounded, and the influence of the structure parameters was further investigated. The experimental results obtained from the microwave anechoic chamber closely match with the simulation results. The experimental findings suggest that the metamaterial structure has potential applications in the detection of solid material permittivity.

Typhoon-induced wind loads pose severe threats to transmission systems. However, existing resilience assessment approaches typically rely on sparse meteorological station data and assume spatially uniform wind speed distributions along transmission corridors, which fail to capture the span-level spatial difference of wind fields. To address this limitation, this paper proposes a distributed optical fiber sensing (DOFS)-driven span-level resilience assessment and hardening optimization framework for transmission networks. First, a phase-sensitive optical time domain reflectometry (Φ-OTDR)-based distributed optical fiber sensing system is employed, utilizing optical fibers embedded in existing OPGW cables as sensing media. By capturing vibration responses of the fiber induced by wind–structure interaction, real-time spatiotemporal wind speed sequences at the individual span level are reconstructed through signal processing and inversion algorithms, providing high-spatial-resolution environmental input data for resilience evaluation. Second, a span-level failure probability quantification method is established using a load–strength interference model. On this basis, a resilience evaluation framework—“span-level asset damage cost—line-level critical corridor identification—system-level load shedding assessment”—is constructed, enabling cross-scale resilience quantification from component damage to system-level performance degradation. Third, a span-level gradient hardening optimization model is developed. By adopting a scenario pre-calculation and iterative updating strategy, coordinated solving of reinforcement decisions and failure scenarios is achieved, thereby maximizing resilience enhancement benefits. The proposed framework is validated using DOFS-measured wind speed data collected from a 500 kV transmission line along the Fujian coast during three real typhoon events—Typhoon Shantuo, Typhoon Trami, and Typhoon Koinu—supporting the reliability of the acquired span-level wind speed information. Case studies conducted on a modified IEEE RTS-24 system demonstrate that the proposed span-level hardening strategy can substantially reduce reinforcement cost compared with the conventional line-level hardening strategy. In the reported benchmark case, it achieves zero load-shedding penalty with a markedly lower hardening cost, and under the same budget constraint, it further yields lower expected load shedding and lower expected asset damage.

Arsenic contamination in polymetallic mining areas is closely linked to surrounding iron-rich manganese minerals. However, conclusive evidence remains limited regarding the retention and migration process of As(V) in naturally manganese-rich manganese ores (especially those with different manganese/iron mass ratios) under dynamic flow conditions. This study investigated As(V) adsorption and transport by four natural manganese minerals (FM1-FM4) through batch/column experiments, characterization, and numerical modeling. Their Mn/Fe mass ratios were 22.7 for FM1, 4.2 for FM2, 3.7 for FM3, and 16.4 for FM4. Batch experiments showed that As(V) adsorption on FM1-FM3 was better described by the Freundlich model, indicating heterogeneous adsorption behavior. Under the tested experimental conditions, the apparent Langmuir qm values of these minerals decreased from 0.066 to 0.015 mmol·g-1 with decreasing Mn/Fe ratio. However, As(V) adsorption on FM4, which had the lowest Mn and Fe contents, followed the Langmuir model (qm = 0.012 mmol·g-1), suggesting monolayer adsorption. Column experiments demonstrated rapid As(V) retention for all minerals. In the time domain, increasing the flow rate from 0.5 to 2.0 mL·min-1 generally advanced breakthrough and shortened the desorption tail, although the breakthrough behavior expressed in pore-volume coordinates was not strictly monotonic for all minerals. The Two-Site Kinetic Attachment Model (TSKAM) successfully simulated these dynamics (R2 > 0.90, RMSE < 0.05), revealing adsorption controlled by fast and slow kinetic sites, with slow-site contributions diminishing at higher flow rates. Characterization results indicated that adsorbed arsenic on FM1 remained mainly as As(V) and was immobilized primarily through surface complexation involving surface hydroxyl and Fe/Mn-O groups. XRD and SEM-EDS suggested the participation of Fe/Mn-bearing phases, while XPS on FM1 showed pronounced changes in Mn surface species during adsorption. Therefore, As(V) removal by these natural manganese minerals is a coupled physicochemical process influenced by both mineral properties, including Mn/Fe ratio, specific surface area, pore structure, pHPZC, and Mn surface-state changes, and hydrodynamic conditions in the polymetallic mining areas.

This paper explores advanced methods of electromagnetic (EM) waveform manipulation through temporally-modulated thin sheets. Two configurations are analyzed-a layer with time-varying (TV) conductivity and one with TV permittivity-to determine how temporal modulation of these parameters affects the transmission of incident EM pulses. Analytical and numerical approaches are formulated to solve the corresponding inverse problems, providing the required temporal profiles of material parameters for achieving user-defined transmitted waveforms. Several application examples are presented, including frequency mixing, time-domain (TD) pulse shaping, and spectral shaping, which demonstrate how dynamic control of a layer's conductance or capacitance can tailor the time-domain profile and spectral content of EM pulses. The results were validated using a commercial FEM code and show that a properly designed time variation of the layer's conductance or capacitance enables functions such as pulse compression, spectral reweighting, and generation of new frequency components, making such structures promising for advanced reconfigurable EM systems.

ABSTRACT Vaccination during pregnancy has shifted from simply a maternal protective strategy to one of the most important strategies in protecting both the pregnant individual and the infant in the first weeks of life. Despite this paradigm shift, vaccination recommendations remain fragmented by pathogen, gestational age, and professional organization, often absent a unifying clinical framework. Systematic Review in Accordance with PRISMA 2020 Guidelines: Current Evidence for Maternal Immunization and Alignment of Inter-Society Recommendations With Available Data A systematic search across major bibliographic databases, guideline repositories and reference lists yielded studies that addressed the safety, immunogenicity, effectiveness and implementation of vaccines. Eligible study types were randomized trials, observational cohorts, surveillance reports and systematic reviews. Two Reviewers independently screened records, extracted relevant data and performed risk-of-bias assessment according to each study design. Qualitative synthesis of evidence was conducted and categorized by pathogen, gestational timing, baseline risk, and outcome domain. Fifty-eight studies met our inclusion criteria. For frequently recommended insurances— in particular, influenza, tetanus–diphtheria–acellular pertussis, and COVID-19 —data consistently show maternal safety and substantial reductions in infant morbidity especially when vaccine timing aligns with peak transplacental antibody transfer. Maternal vaccination for respiratory syncytial virus has demonstrated moderate to large reductions in infant hospitalization, though the certainty of this evidence is still evolving. For example, risk-based approaches (e.g., hepatitis B vaccination and rabies post-exposure prophylaxis) demonstrate protective benefits in high-risk contexts with strong evidence largely derived from observational data. There is strong consensus around established vaccines across many guidelines, but newer or context-specific interventions highlight some significant evidence–policy gaps. In summary, maternal immunization should be considered as a risk-stratified intervention that intertwines biological timing with clinical vulnerability and health-system context to guide individualized evidence-based care.

Gastric anastomotic leakage is a life-threatening postoperative complication that necessitates early detection and timely intervention. Implantable electronics offer direct access to deep tissue and enable accurate recognition of homeostatic imbalances yet are constrained by miniaturization, biodegradability, and power sustainability. Here, we propose an implantable-wearable integrated strategy for early detection of gastric anastomotic leakage. Specifically, a bioresorbable hydrogel patch serves as the sole implant, responding to gastric acid to modulate ultrasound echo signals in both time and frequency domains. This enables early leakage detection (within 1 hour) and millimeter-level spatial localization via a wearable ultrasound array. Meanwhile, the hydrogel patch exhibits acid-enhanced leak sealing capability and degrades naturally after the healing period, thereby eliminating the need for surgical removal. We confirmed its capabilities in spatiotemporal monitoring, anastomotic repair, and bioabsorbability in a rat gastric perforation model. Our system operates without complex electronic implants, highlighting its clinical potential for postoperative monitoring and management of gastric anastomotic leaks.

Two-dimensional fractional Brownian motion: analysis in time and frequency domains

This paper presents a 2-GS/s voltage-time hybrid pipelined analog-to-digital converter (ADC) with a 14-bit digital output, implemented in a 28-nm CMOS process. To alleviate the gain-bandwidth-power trade-off in deeply scaled technologies, the proposed architecture employs a SHA-less front-end and a low-gain inverter-based push-pull RA for energy-efficient coarse quantization. The residue is then transferred to the time domain via a highly linear constant-current voltage-to-time converter (CC-VTC) and digitized by a four-channel time-interleaved gated-ring-oscillator (GRO) TDC. To recover dynamic linearity degraded by low-gain amplification and interleaving mismatches, a multiplier-less digital background calibration engine is implemented. Leveraging mean absolute value (MAV) statistics and dither-injected least-mean-squares (LMS) algorithms, it effectively compensates for inter-channel and interstage errors with minimal hardware overhead. The prototype occupies an active area of 0.16 mm2. At 2 GS/s, the ADC achieves a Nyquist SNDR of 63.42 dB and an SFDR of 73.71 dB, corresponding to an ENOB of 10.24 bits. Consuming 86.9 mW from a 1-V supply, it achieves a Walden FoM of 35.9 fJ/conv.-step. Measurement results from multiple chips under a wide range of operating conditions verify the robustness of the proposed ADC.

This study develops a Lagged Backward-Compatible Physics-Informed Neural Network (LBC-PINN) for simulating and inverting one-dimensional unsaturated soil consolidation under long-term loading. To address the challenges of coupled air–water pressure dissipation across multi-scale time domains, the framework integrates logarithmic time segmentation, lagged compatibility loss enforcement, and segment-wise transfer learning. In forward analysis, the LBC-PINN with recommended segmentation schemes accurately predicts pore-air and pore-water pressure evolutions, which are validated against finite element method (FEM) results with mean absolute errors below 10-2 across time up to 1010seconds. A simplified segmentation strategy based on the characteristic air-phase dissipation time improves the computational efficiency while preserving the predictive accuracy. Sensitivity analyses confirm the framework’s robustness across air-to-water permeability ratios ka/kw from 10-3 to 103. In inverse analysis, the LBC-PINN recovers air- and water-phase consolidation coefficients, cva and cvw using both single-stage and two-stage strategies, with the two-stage approach remaining reliable under moderate noise levels. These results demonstrate the potential of LBC-PINN as a stable, mesh-free, and noise-resilient tool for modeling and parameter identification in unsaturated soil consolidation analysis.

ABSTRACT The intensifying climate crisis has acted as a catalyst for structural shifts in the global economic framework, amplifying the inherent instability within energy and financial sectors. Utilizing a Time-Varying Parameter Vector Autoregression (TVP-VAR) methodology, this research provides a comprehensive assessment of the dynamic transmission mechanisms—across both time and frequency domains—linking U.S. climate policy uncertainty (CPU), equity market volatility (EMV), and a spectrum of energy commodities (including crude oil, natural gas, and coal) over the period from March 2005 to March 2025. In the time domain, evidence suggests that coal markets, alongside equity market volatility (EMV), function as the primary catalysts for systemic connectedness and price fluctuations across the analyzed network. Notably, the role of climate policy uncertainty (CPU) has undergone a fundamental transformation; previously a passive recipient of market shocks, it has emerged as a proactive transmitter since 2020, exerting a markedly intensified influence on both energy and financial domains. In the frequency domain, the total spillover effect is the strongest in the short term, during which the impact of CPU on other markets is most pronounced. In the medium to long term, volatility is mainly driven by the EMV, and the CPU’s direct impact largely disappears, with its influence primarily transmitted through policy expectation channels. This study suggests that improving the transparency of climate policies can help mitigate short-term market volatility. It also underscores the need to design differentiated regulatory mechanisms tailored to the transitional nature of the energy sector, and to incorporate the CPU into financial risk monitoring frameworks to help alleviate systemic risk.

In this paper, we propose an orthogonal frequency-division multiplexing (OFDM) weight design mechanism aimed at reducing envelope fluctuations under subcarrier constraints. In the time domain, a new metric is introduced and minimized to guide the OFDM waveform toward a constant-envelope structure. In the frequency domain, the design allows a subset of subcarrier weights to be pre-assigned and imposes upper bounds on the magnitudes of the remaining subcarrier weights. Specifically, we formulate and solve an optimization problem that minimizes the variance of the envelope distribution, subject to subcarrier constraints and a fixed total energy budget. This leads to a non-convex optimization problem. By relaxing certain constraints-specifically, the upper-bound constraints on weight magnitudes-and subsequently reintroducing them, we transform the original non-convex problem into an unconstrained maximization over a unimodular complex vector and develop an iterative solution approach that converges to a local optimum. In addition, the effect of the initial point selection on the resulting weights is analyzed, which motivates a heuristic strategy for roughly controlling weight magnitudes. Numerical results demonstrate that the proposed method effectively suppresses envelope fluctuations while satisfying subcarrier constraints. Compared to existing methods, the proposed mechanism achieves higher computational efficiency and a better approximation to a constant-envelope signal.