Abstract Time synchronization performance of sensors determines the overall efficiency of Wireless Sensor Networks (WSNs). A scientific topology can provide solid support for time synchronization mechanism. Traditional WSNs face the challenges of insufficient accuracy and excessive energy consumption. This paper proposes a time synchronization optimization algorithm based on constructing the nearest $K$-neighboring (NKN) network topology. First, the $\mathrm{k}$-means clustering method is employed to group all the nodes. Each node communicates with its $K$ nearest neighbors in one group. Then, a node identification mechanism is used to distinguish among reference nodes, neighborhood nodes and receiving nodes. Within each group, local time synchronization is achieved between receiving nodes and the reference node via two-way information exchange. Additionally, neighborhood nodes act as information gateways, forwarding synchronization data from reference nodes via the cross-domain interaction mechanism to achieve multi-region time synchronization. Experimental results show that the proposed topology requires less synchronization convergence time than some typical topologies. Compared with the classical time synchronization algorithm, the algorithm has higher synchronization accuracy and lower energy consumption.

Botulinum toxin (BoNT) is a highly specific molecular enzyme whose therapeutic action is based on the proteolytic cleavage of SNARE proteins, most notably SNAP-25. Despite the deterministic nature of this molecular mechanism, the clinical effects of BoNT exhibit substantial variability in efficacy, spatial extent, and duration that cannot be fully explained by dose-response relationships or diffusion-based models. In this work, we propose the Molecular Probability Field (MPF-BoNT) as a conceptual framework that bridges discrete molecular events and emergent functional outcomes. The MPF is defined as the spatial-temporal distribution of the probability that presynaptic terminals reach a functional silencing state (operationalized via SNAP-25 cleavage exceeding a threshold), shaped by exposure, uptake, target density, and temporal dynamics following toxin exposure. Within this framework, clinical effects arise from the integration of probabilistic molecular events across space and time, rather than from toxin presence or concentration alone. The MPF-BoNT framework accounts for key features of botulinum toxin action, including spread, nonlinearity of dose effects, variability in duration, and differences between technical and biological non-response. By explicitly incorporating molecular variables such as local concentration, exposure time, terminal density, internalization probability, and functional silencing thresholds, the framework provides an integrative interpretation of tissue-level behavior grounded in molecular biology. The MPF-BoNT offers a formal language to describe how established enzymatic events generate observable spatial, temporal, and functional patterns. As a generative framework grounded in explicit testable structure, it establishes a foundation for future experimental and clinical research.

Abstract Precise time scales are the universal base for all measurements. Although the laboratory optical clocks offer better uncertainty and instability at the level of 10-18 or even lower, their reliability and availability have greatly limited the global application to improve the precision of time scale. Here we report the deployment of a compact and transportable optical clock to a timekeeping institution and steering an active hydrogen maser to generate an optical time scale, realizing the upgrade of the local time scale. The optical clock was transported over 1200 km by express delivery and resumed work as normal promptly, and its extremely high uptime of 93.6% in the half-year enabled us to precisely correct the frequency drift of hydrogen maser, ultimately achieving an unprecedented monthly instability of 4×10-17. This steering experiment with a deployable optical clock marks a significant advancement, demonstrating that a timing accuracy below 100 ps per month can be achieved feasibly in various timekeeping institutions where hydrogen masers are typically employed as the primary contributor to timekeeping. In the future, mobile optical time scales based on such transportable optical clocks can be deployed flexibly and rapidly, which is particularly important in scenarios lacking International Atomic Time reference.

ISGylation is a ubiquitin-like post-translational modification that plays a central role in innate immune signaling. Conjugation of interferon-stimulated gene 15 (ISG15) to target proteins is initiated by the E1 enzyme Uba7, transferred to the E2 enzyme UbcH8, and completed by an E3 ligase. Specificity in this cascade is mediated by the ubiquitin-fold domain (UFD) of Uba7, yet the structural and mechanistic basis of E1-E2 recognition remains poorly defined. Here, we present the solution NMR structure and functional characterization of a human Uba7-UFD. NMR chemical shift perturbation experiments combined with site-directed mutagenesis delineate the UbcH8 interaction surface and identify residues critical for E1-E2 binding. The Uba7-UFD adopts a conserved ubiquitin-fold architecture but exhibits conformational flexibility in the unbound state. 15N relaxation measurements show a globally well-folded domain with localized ps-ns time scale dynamics within the β2/β4 E2 binding surface and the acidic loop spanning residues 996-1008. Upon UbcH8 binding, relaxation parameters shift toward those expected for a larger effective molecular size, accompanied by an increased residue-specific heterogeneity at the interface, consistent with binding-coupled changes in local mobility. Mutational analysis identifies C996 as being essential for UFD structural integrity and binding competence. Moreover, targeted alterations in the length and flexibility of the adjacent acidic loop strongly impair UbcH8 binding, demonstrating that the loop architecture is a critical determinant of efficient E2 recruitment. Together, these results provide a structural and dynamic framework for understanding E2 enzyme selection in the ISGylation pathway and highlight the role of UFD conformational dynamics in the E1-E2 complex formation.

The article explains that it will probably soon be possible to travel through time on Earth.. And such a possibility is created by the corrected version of the special theory of relativity (SRT). But the version of SRT studied in all physics textbooks states that time travel on Earth will never be available to people. Nevertheless, ignoring this opinion of the generally recognized service station, currently millions of air passengers already travel through time every day, which is confirmed by the translation of their watches to local time after landing the plane.

Contrast-enhanced ultrasound combined with ultra-high-frequency ultrasound improves preoperative planning for lymphovenous anastomosis: A pilot study.

Process analysis of the impacts of ship emissions on PM2.5 and O3 in the Yangtze River Delta, China.

The Transactional Asset Pricing Approach (TAPA) is able to handle asset valuations on a portfolio level of size constrained markets against the backdrop of low liquidity hindering the estimation of the variance of returns. Prompted by a numerical simulation of the TAPA algorithm, we develop stability conditions associated with the valuation convergence for any maximal positive time period and positive number of assets. We present stability conditions at the local level, both in continuous and discrete algorithmic time, and we develop them by means of log-linearisation about the steady state of its equations’ variables. We conclude on the analytical existence of stability conditions at the local level up to four assets and any positive time period. We adduce analytical applications within such a region and present a solution for a benchmark calibration of the steady state parameters given two time periods and a single asset.

Abstract Cosmological time dilation (CTD) serves as a fundamental probe of cosmic expansion, historically verified through the characteristic $$(1+z)$$ ( 1 + z ) broadening of Type Ia supernova (SNe Ia) light curves. However, significant tensions arise when extending this test to other astrophysical regimes. While discrete, event-based transients such as gamma-ray bursts (GRBs) exhibit large scatter in inferred time-dilation signatures, analyses of stochastic variability in persistent sources – specifically quasars (QSOs) – frequently yield null results. I demonstrate that these discrepancies stem from a previously overlooked distinction between discrete geometric clocks and continuous thermal emission, presenting a resolution within the framework of generalized cosmological time (GCT). The central premise relies on strictly distinguishing global coordinate time, characterized by a generalized lapse function, from the local proper time measured within gravitationally bound systems. I propose that the progenitors of transients – specifically SNe Ia and GRB central engines – are effectively shielded from background time evolution due to strong gravitational binding and environmental decoupling. Consequently, they act as standard clocks tracing pure geometric path dilation, obeying $$\tau _\textrm{obs} \propto (1+z)^{1+b/4}$$ τ obs ∝ ( 1 + z ) 1 + b / 4 . Conversely, the lack of dilation in QSOs is derived as a consequence of observing persistent thermal accretion disks at fixed wavelengths, introducing an intrinsic selection effect ( $$\tau _\textrm{intr} \propto (1+z)^{-2}$$ τ intr ∝ ( 1 + z ) - 2 ) that masks the cosmological signal. This framework reconciles the diverse behaviors of transient and persistent sources without modifying local physical laws.

Under practical operating conditions, intelligent fault diagnosis of permanent magnet synchronous motors (PMSMs) is often hindered by the shortage of effective fault samples. To address this issue, this paper proposes a twin-data-driven transfer learning-based diagnostic method for PMSM inter-turn short-circuit faults. First, a finite element model of the motor is established in Ansys to generate inter-turn short-circuit twin data, thereby enriching the source-domain samples. Second, continuous wavelet transform (CWT) is employed to convert stator current signals into multi-scale time–frequency feature maps, which are then fed into a feature extraction network constructed by integrating a residual network (ResNet) into an efficient channel attention mechanism (ECA) to achieve effective fusion of local and global time–frequency features. Finally, a joint loss function combining multi-kernel maximum mean discrepancy (MK-MMD) and a domain-adversarial neural network (DANN) is introduced to align feature distributions and perform adversarial optimization, enhancing cross-domain invariance and improving fault recognition capability. Experimental results demonstrate that the proposed REDM method achieves higher diagnostic accuracy and robustness than several existing intelligent fault diagnosis approaches.

Real-time processing demands for massive IoT sensor data necessitate reliance on distributed microservice systems within edge clusters. However, pinpointing the root cause of anomalies within these edge microservice clusters poses a critical challenge for intelligent IoT operation and maintenance. To address the issue, a spatio-temporal graph propagation model ST-GraphRCA is proposed for root cause analysis in IoT edge environments. Our approach begins by resolving the fundamental issue of time-series asynchrony across distributed multi-source metrics. A PCA-DTW hybrid feature extraction method is introduced with a dynamic alignment strategy to mitigate the effects of random network delays and data deformation without requiring prior synchronization. Subsequently, ST-GraphRCA constructs a stream-based forward propagation graph based on the flow conservation principle. By integrating dynamic edge weights with node-level input-output anomaly scores, ST-GraphRCA precisely infers fault propagation pathways and identifies potential root cause candidates through causal reasoning. Finally, a topology-constrained high-utility mining algorithm filters these candidates. Using a constraint matrix, the algorithm filters out unreachable service combinations to locate low-frequency and high-risk root causes. Experimental results indicate that ST-GraphRCA achieves an F1-Score of 0.89, outperforming existing methods. In resource-constrained edge scenarios, its average localization time is merely 238.8 ms, representing a six-fold improvement over key benchmarks. Thus, ST-GraphRCA not only provides an efficient anomaly fault tracing solution for large-scale IoT systems but also offers technical support for the intelligent operation and maintenance of distributed microservice systems.

On the Differentiability of Local Times of ($$1+\beta $$)-Stable Super-Brownian Motion

We investigate the statistical correlation between the first-reaction time of a diffusing particle and its boundary local time accumulated until the reaction event. Since the reaction event occurs after multiple encounters of the particle with a partially reactive boundary, the boundary local time as a proxy for the number of such encounters is not independent of, but intrinsically linked to, the first-reaction time. We propose a universal theoretical framework to derive their joint probability density and, in particular, the correlation coefficient. To illustrate the dependence of these correlations on the boundary reactivity and shape, we obtain explicit analytical solutions for several basic domains. The analytical results are complemented by Monte Carlo simulations, which we employ to examine the role of interior obstacles on correlations in disordered media. Applications of these statistical results in chemical physics are discussed.

To report on a volunteer-led program supporting local healthcare providers (L-HCPs) and disaster responders after the 2024 Noto Peninsula Earthquake, focusing on its implementation and immediate outcomes. A volunteer-led initiative established by university alumni deployed medical teams to a local hospital on weekends following the earthquake, providing onsite support to relieve L-HCPs from prolonged strain. The program integrated information and communication technology (ICT) platforms to enable remote support, communication, and structured debriefing sessions for volunteers, facilitating assistance from a wider network. The project effectively sustained the local health care institution's capacity by managing diverse patient needs, including a surge in internal medical conditions. It provided essential respite, allowing local physicians crucial personal time, for which they expressed profound gratitude. Volunteer doctors reported effective stress management through the onsite and ICT-based support structure, and the initiative concluded safely without injury. The project demonstrated that combining onsite medical assistance with strategically implemented ICT effectively mitigates burnout among L-HCPs, providing essential psychological support for deployed volunteers. The findings highlight the significance of sustained recovery-phase support, professional networks, and ICT in disaster response. These experiences highlight the need for comprehensive, system-wide support strategies for all frontline personnel in future disasters.

Abstract Introduction: Preoperative localization of non-palpable breast lesions, whether performed the day before or on the day of surgery, can be anxiety-inducing for patients. The scheduling in a busy operating theater for short procedures is highly sensitive to even minor delays. Localization appointments may cause such delays, as well as raise potential timing confusions between surgery time, arrival time at the care center, and localization time. Moreover, wire-guided localization requires specific radiology sessions and coordination with radiologists specialized in breast imaging. For these reasons, we progressively implemented preoperative localization using a magnetic clip. Placement is done a few days before surgery, which also allows a comprehensive re-review of the radiologic images. The objective is to describe the organizational impact and the re-excision rate of the systematic use of magnetic seeds in a single institution. Methods: Retrospective single-center study. We describe the characteristics of cases with magnetic seed localization and compare these features, as well as ambulatory stay durations, to a historical control group that underwent wire-guided localization. For this comparison, only consecutive patients who had unifocal, unilateral breast cancer and were treated on an outpatient basis were included. Results: Between March 2024 and June 2025, 261 patients were referred to the radiology department for magnetic seed placement before surgery. During imaging review, additional lesions were detected in 21 patients (8%), leading to total mastectomy in 5 cases. Excluding 8 patients (3%) who were scheduled for inpatient admission, 232 underwent magnetic seed placement, including 35 (15%) for benign lesions. We compared 197 patients who had magnetic seed localization for cancer between March 2024 and June 2025 to 60 patients in the historical control group who underwent wire localization for cancer between November and December 2023. The median age in both groups was 62 years (p = 0.98). The control group had a higher proportion of in situ ductal carcinoma (n = 18, 30% vs. n = 27, 15%, p = 0.02), while the magnetic seed group underwent more axillary procedures (n = 170, 86% vs. n = 42, 70%, p = 0.009). Tumor size was slightly larger in the magnetic seed group (10 mm vs. 8 mm, p = 0.04). Fewer re-excisions for positive margins occurred in the magnetic seed group (n = 3, 1.5% vs. n = 8, 13%, p < 0.01). This result was confirmed in multivariate analysis : use of magnetic seed reduced independently the rate of re-excision with an OR of 0.37 (IC95%[0.002-0.001], p=0,0018). Operating time was equivalent in both groups (32 min vs. 33 min, p = 0.87), but ambulatory stay was reduced by more than 2 hours in the magnetic seed group (5h 14 vs. 7h 19, p < 0.01). Conclusion: The use of magnetic seeds enables time savings on the day of surgery, streamlining the operating theater schedule and reducing patient anxiety associated with pre-surgical delays. Re-excision rates is dramatically decreased when using magnetic seeds. Citation Format: D. Hequet, A. Hababou, G. Aubry, R. Salmon, S. Harguem, M. Bou Antoun, J. Seror. Magnetic seed for preoperative localization of non-palpable breast cancer: impact on care pathway organization and re-excision rate [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS2-01-02.

Abstract Background: Nearly 70% of breast cancers are ER positive, and anti-estrogen therapy, such as tamoxifen and aromatase inhibitors (AI), are a mainstay of treatment. Neoadjuvant AI therapy is effective at reducing tumor burden, and may be used to improve surgical outcomes. Non-invasive assessment of response may be helpful in treatment planning, and radiographic treatment response has not been evaluated. Additionally, questions remain as to the social effects of neoadjuvant therapy. Preliminary data from this trial presented at Northern New England Clinical Oncology Society in 2024 showed an 85% adherence to aromatase inhibitor therapy at 1 year in patients who were treated in the neoadjuvant setting, with ongoing data collection, compared to 62% in the adjuvant setting, according to one study. Objective: Determine the ability of tumor imaging to detect the effect of neoadjuvant aromatase inhibitor (AI) therapy on tumor size. Methods: 52 post-menopausal women with Stage I-III ER+, HER2- breast cancer were treated with an aromatase inhibitor for 1-24 weeks (mean 6.7 weeks) prior to surgery and had pre-neoadjuvant imaging available for analysis. 12 patients did not have an imaging exam after neoadjuvant endocrine therapy and prior to surgery, or it was not possible to assess tumor size on pre-operative imaging, resulting in 40 patients for final analysis. Tumor measurements prior to neoadjuvant endocrine therapy were compared to tumor measurements after neo-endocrine therapy at the time of surgery using mammography or ultrasound to determine response to treatment. Post neo-endocrine treatment measurements were compared with pathologic tumor size. Results: Neoadjuvant aromatase inhibitor therapy decreased tumor size evaluated by imaging (mean pre-treatment size 19.4mm, mean post-treatment 14.8mm, p<.001), with size reduction in 68% of patients (AUC=.68). The larger the initial tumor size, the greater the reduction in tumor size (p=0.0017): on average, an additional 10mm increase in initial tumor size results in a 2mm decrease in post-treatment tumor size. The correlation coefficient between pathologic tumor size and post neoadjuvant AI therapy tumor size determined by specimen radiographs or localization imaging (with mammography or ultrasound) was 0.69. Discussion: AI therapy in the neoadjuvant setting could improve overall response to therapy and may improve long-term adherence. Response to therapy can be evaluated with mammography and ultrasound imaging obtained at the time of needle localization or specimen radiograph. Further work is needed to evaluate long-term outcomes with this treatment, and correlation with histology is ongoing. Due to the discordant results in lobular carcinomas, separate analysis of a large subset of lobular carcinomas is planned. Citation Format: L. Lawrence, R. diFlorio-Alexander, J. Marotti, E. Demidenko, M. Chamberlin. Neoadjuvant Aromatase Inhibitor Therapy Decreases Radiographic Tumor Size: Initial Results from the NAOMI Trial [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS3-09-23.

Sporadic E (Es) layers exhibit strong intermittency and highly skewed intensity distributions, exerting significant impacts on high-frequency communication and navigation systems and posing challenges for data-driven prediction. Conventional single-stage regression models are often dominated by abundant non-event samples and therefore tend to underestimate Es intensity during occurrence periods. To address this issue, this study proposes a unified two-stage neural network framework that decouples the prediction of Es occurrence probability from the estimation of Es intensity. The model is trained using multi-station ionosonde observations, incorporating cyclic representations of seasonal and local time variations together with solar and geomagnetic indices and station-aware encoding to enable unified learning across multiple stations. Results show that the proposed two-stage framework achieves event-only MAE values of 0.53–0.76 MHz and RMSE values of approximately 1.0–1.4 MHz at most mid- and low-latitude stations, with larger errors at the high-latitude Casey station (MAE ≈ 1.45 MHz and RMSE ≈ 2.31 MHz). The consistently bounded MRE values (≈0.18–0.23) observed across multiple stations demonstrate that the framework effectively mitigates severe data imbalance and suppresses spurious high-intensity estimates under non-Es conditions.

Abstract This study presents the results from a climatological analysis of thermospheric winds (~ 250 km altitude) in the southern polar cap, based on the first long-sterm ground-based Fabry–Perot Interferometer (FPI) observations at Jang Bogo station (JBS; 80°S geomagnetic latitude), Antarctica, during 2014 − 2022. The winds exhibit pronounced diurnal variations, characterized by persistent anti-sunward flow across all magnetic local time sectors with a slight duskward tilt, primarily driven by ion drag in combination with day-to-night pressure gradients. The seasonal and solar activity dependencies show enhanced wind magnitudes during equinoxes and under high solar activity, likely reflecting stronger ion drag from increased ionospheric densities. The wind patterns are further modulated by increasing geomagnetic activity, which intensifies wind speeds and enhances the duskward tilts, associated with the strengthening of the dusk-side ionospheric convection cell. The orientation of the interplanetary magnetic field (IMF) also influences wind behaviors: a negative IMF Bz component increases wind magnitudes, while the IMF By component induces directional asymmetry by modulating ionospheric convection. These results offer new ground-based constraints on thermospheric wind circulation in the southern polar cap and its possible mechanisms over nearly a solar cycle. Graphical Abstract:

Abstract Slot coating is commonly used for manufacturing functional films, where the spatial distribution of particles strongly influences processability and final product performance. Despite its importance, complex flow behaviors coupled with particle migration during slot coating—such as periodic oscillations of particle concentration—have not been fully elucidated. In this study, the underlying mechanism of these oscillations is investigated using two‐dimensional computational fluid dynamics simulations incorporating shear‐induced particle migration. The results demonstrate that the periodic birth–decay cycle of the feed vortex plays a critical role in sustaining the oscillatory behavior. To facilitate a better conceptual understanding of these oscillations, a practical scaling relation at the onset is proposed. Furthermore, beyond the onset, the oscillation period is found to scale proportionally with the local residence time in the feed slot exit zone within the coating bead.

Abstract This study presents a Real-Time (RT) timing and time transfer receiver that employs Precise Point Positioning (PPP) technology with various International Global Navigation Satellite System (GNSS) Service (IGS) RT products and an independent steering method for time and frequency offsets to synchronize local time signals to GNSS time. We first evaluated the accuracy of the RT precise products used in this study, and then assessed the receiver performance through two experiments that account for hardware delay variations and real-time product reception conditions. For the Xi’an-Sanya long-baseline time transfer experiments, the STDs of time comparison are 0.40 ns, 0.45 ns and 0.37 ns with respect to the results of two-way satellite time and frequency transfer for GFZ, DLR and CAS RT products, respectively. For timing experiments, the STDs of time difference between RT-PPP receiver and UTC(NTSC) are 1.26 ns, 1.02 ns and 0.77 ns for GFZ, CNE and CAS products, respectively, with frequency stability (MDEV) reach 4.1E-15/day for CNE and 2.2E-14/32768 s for CAS. These results conclusively demonstrate that the developed RT-PPP timing receiver realizes sub-nanosecond long-baseline time transfer and nanosecond one-way timing, offering a flexible, cost-effective alternative for high-precision time and frequency transfer users.