A rapid-screening analytical framework for PFAS health risk assessment in groundwater: Managing plume evolution and exposure from point sources.

Resting-state fMRI coherence is selectively diminished around 0.1 Hz in patients with unilateral carotid artery stenosis.

A GRASPxVNS approach for the flexible job shop scheduling with generic minimal time lags

We report the case of Takotsubo syndrome in a 32-year-old man with no particular medical history who presented with acute heart failure associated with severe renal failure following intense emotional stress. Cardiac and renal dysfunction gradually resolved without specific treatment, although there was a time lag between cardiac recovery (day 15) and renal recovery (day 30). Several factors make this observation particularly interesting: the young age and male gender of the patient; the presence of an exclusively emotional trigger in a man, which is unusual; and the severity of the renal damage, which took several weeks to improve. This severe acute kidney failure resulted from a complex interaction between renal hypoperfusion, massive neurohormonal activation, and direct renal vasospasm, leading to acute tubular necrosis. This observation highlights the importance of considering Takotsubo syndrome in the differential diagnosis of acute renal failure associated with unexplained cardiac dysfunction, particularly in patients who do not fit the typical demographic profile.

Abstract Spectral time lag is an important temporal property of gamma-ray bursts (GRBs) and provides insight into both emission physics and potential propagation effects. Conventional methods for extracting spectral lags, such as cross-correlation or pulse fitting, typically rely on comparisons between narrow energy bands and require relatively high signal-to-noise ratios. In this work, we propose a new method to estimate spectral time lag based on the Full Width at Half Maximum (FWHM) of GRB light curve structures. By combining light curves from multiple energy bands and optimizing their relative offsets to minimize the normalized FWHM of the merged signal, this method exploits information from a broad energy range and is therefore suitable for relatively faint GRBs. We demonstrate the procedure using GRB 131030A and estimate uncertainties through Monte Carlo simulations. A statistically consistent time lag is obtained between adjacent energy bands. Assuming, as an extreme case, that the measured lag is entirely attributed to Lorentz invariance violation, we derive a corresponding lower limit on the quantum gravity energy scale. This method provides a complementary approach to existing lag extraction techniques and may enable spectral timing studies for GRBs that are inaccessible with traditional methods.

In this study, we compared the in-site ground-based climate variables (1982-2016) with a multiyear normalized difference vegetation index (NDVI) dataset to characterize climate change and vegetation-climate interactions at Ergune, Inner Mongolia, China, using the time series analysis, the correlation analysis and the principal component analysis (PCA). To reveal the time lag effects in climate-vegetation relationship, vector auto regression (VAR) model was constructed and the impulse-response analysis, the causality analysis were conducted. We found that the regional climate change over the past decades could be summarized as climate warming and drying. And the regional climate warming was mostly contributed by summer warming, rather than the widely reported winter warming in the north hemisphere. Climate variables were highly correlated. The PCA analysis revealed that the 1st principal component represented the temperature related variables, and the 2nd principal component represented the humidity related variables. At seasonal scale, however, the humidity and temperature was the 1st principal component for summer and winter respectively. VAR analysis revealed that, the precipitation has higher impact on NDVI than the temperature. The feedback of NDVI to humidity was significant, but feedback of NDVI to Temperature was non-significant. VAR model had better performance in prediction of NDVI than the multi-linear regression approach. This study investigated the climate-vegetation relationship with full considerations on the co-linearity and the time lag effect in climate system. The cause-effect in climate-vegetation relationship indicated the feedback of NDVI to climate variability and the ecological function of vegetation in mitigating and regulating the regional climate.

Addressing the problem of illicit drug trafficking for non-medical use remains a global challenge for the global community, and remains relevant in the 21st century. Determining global, national, and regional trends in narcotic and psychotropic substance consumption, assessing the epidemiological situation (incidence, prevalence), harm structure, and law enforcement indicators (seizures, trafficking routes) are necessary for developing a systemic response to drug-related violence at all levels. This article explores the rationale for transitioning the Kabardino-Balkarian Republic’s anti-drug policy from a reactive model to proactive management based on the principles of a cybernetic viable system and anticipatory governance. Based on an analysis of global and regional trends, it has been established that the drug situation has entered a synthetic-polytoxicological phase, with a predominance of preclinical risk, an increase in acute poisonings, and a lack of synchronicity between law enforcement and medical indicators. The study’s materials included regional administrative reports (Forms No. 11 and No. 37) for the period from 2014 to 2024, records of the Anti-Drug Commission and the Ministry of Internal Affairs of the Kabardino-Balkarian Republic, and structured tables on mortality and poisoning. Descriptive statistical methods were used, including comparative-analytical, structural-functional, and modeling research methods. The study demonstrated the effect of asymmetric adaptation — the ability of the illegal market to change chemical formulas and distribution channels faster than control measures can be updated. The aim of the study was to justify the need to implement a three-loop anticipatory management system: monitoring predictive patterns, scenario-based predictive assessment of probabilistic trajectories, and adaptive adjustment of measures in real time. According to the researchers, the proposed digital toxicology surveillance architecture will reduce the time lag between risk and response, shift from recording consequences to managing probabilities, and increase the resilience of the regional healthcare system to new forms of drug addiction.

The latency between neural drive to a muscle and the resulting force production during continuous contractions is described by the neuromechanical delay (NMD). NMD shortens with increasing contraction intensity and speed, varies between muscle groups and fascicle lengths, and lengthens under pain sensation. However, it remains unclear how NMD changes during fatigue. We investigated the NMD of the vastii muscles during a sustained sinusoidal contraction performed to exhaustion. Ten healthy adults (9 males) performed maximum voluntary contractions (pre-MVCs), the biofeedback-controlled contraction to exhaustion at a mean force of 30% MVC, and a post-MVC. High-density electromyographic signals were recorded from the vastii muscles and decomposed into motor unit discharge timings. Cross-correlation between neural drive and force was used to determine NMD as the time lag between the two signals. We did not find any differences in neural drive measures or NMD between muscles (P > 0.05). Post-MVC force was significantly reduced by 19% compared to pre-MVC (P < 0.001). NMD increased from 113 (± 19) to 168 (± 16) ms from the initial 10% to 100% of exhaustion time (P < 0.001). The observed NMD prolongation likely reflects slowed and diminished force transmission due to fatigue-induced accumulation of myofibrillar metabolites, which alter twitch characteristics and mechanical properties of the motor units. Prolongation of the NMD may serve as a key indicator of fatigue, as delays in action potential transmission to force production can generate inhomogeneous muscle forces, thereby potentially increasing the risk of injury.

Femtosecond laser-pumped spintronic terahertz (THz) emissions have attracted intense academic interest, thanks to their intrinsic capability to generate ultrafast THz pulses that cover a wide spectral range. To gain deep insight into the interplay between the ultrafast thermal dynamics in ferromagnets and the spin-to-charge conversion is critical for advancing this field, yet up to now it has not been fully explored, partially due to a lack of efficient tools to measure these two processes simultaneously. Here, we experimentally employ optical-pump THz-probe (OPTP) spectroscopy to promote this study in a typical ferromagnet (Ni80Fe20) nano-film. It not only elucidates the electron and lattice temperature dynamics by quantifying the optical-pump-induced THz transmission changes, but also provides time-resolved THz spectral maps to analyze the sub-picosecond changes, which determines a time lag of 63 ± 8 fs between THz emission and laser excitation. This is an intrinsic parameter constraining the upper frequency limit of spintronic THz emission. Our work deepens the fundamental understanding of ultrafast laser excitation mechanisms for spintronic THz emissions and may offer a new perspective to achieve high-performance THz emitters.

Statistical time lags in streamer inception for CO2/O2/C4F7N gas mixtures

Hand, foot and mouth disease (HFMD) constitutes a global public health concern. Internet search data offers advantages including vast data volumes, provision of real-time information, and the potential for earlier infectious disease surveillance. The objective of this study is to utilise Baidu Search Index (BSI) to construct a predictive model for HFMD epidemiological surveillance, thereby enhancing HFMD incidence forecasting and early warning capabilities. HFMD cases reported by the National Health Commission of the People's Republic of China from January 2011 to March 2025 were collected. Keywords highly correlated with HFMD were identified using Spearman's rank correlation and cross-correlation analysis, and a comprehensive search index (CSI) for HFMD was constructed. Subsequently, based on the monthly number of HFMD cases and the CSI, autoregressive integrated moving average (ARIMA) and autoregressive integrated moving average with exogenous inputs (ARIMAX) models were established. Finally, the predictive accuracy of the models was evaluated using mean absolute error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE), and standardised mean absolute percentage Error (SMAPE). From January 2011 to March 2025 (total of 171 months), China reported a total of 24,856,589 HFMD cases, with an average of 145,360.2 cases per month. The highest incidence of HFMD occurred between May and July each year. After correlation analysis, five keywords highly associated with HFMD were ultimately included, with a potential time lag of 0 months. The CSI of HFMD exhibits a high Spearman rank correlation (rs=0.937) with monthly reported HFMD cases. The developed ARIMAX(2,0,1)(1,1,1)(12) + CSI(Lag = 0) performs better in terms of fitting and prediction compared to the ARIMA(2,0,1)(1,1,1)(12). The MAE values for ARIMAX and ARIMA are 42,085.93 and 80,260.93, respectively, the RMSE values are 52,235.39 and 98,444.62, respectively, the MAPE values are 0.96% and 2.10%, respectively, and the SMAPE are 0.86% and 0.82%, respectively. The ARIMAX(2,0,1)(1,1,1)(12) + CSI(Lag = 0) model constructed from extensive internet search data in this study has effectively enhanced the prediction of HFMD incidence. Furthermore, it can serve as an early warning system for HFMD. This research provides valuable support for HFMD surveillance.

Verbal communication transmits information across diverse linguistic levels, with neural synchronization (NS) between speakers and listeners emerging as a putative mechanism underlying successful speech exchange. However, the specific speech features that drive this synchronization, and how language-specific versus universal characteristics facilitate information transfer, remain poorly understood. We developed a novel feature-based interbrain encoding modeling approach to disentangle the contributions of acoustic and linguistic features to speaker-listener NS during Mandarin storytelling and listening, as measured via magnetoencephalography (MEG). A female speaker and 22 listeners (12 females and 10 males) were recruited and analyzed. We observed strong NS across frontotemporal-parietal networks, with systematic time lags between the speaker and listeners. Crucially, suprasegmental lexical tone features (i.e., tone categories, pitch height, and pitch change), which are essential for lexical meaning in Mandarin, contributed more significantly to NS than either acoustic elements or universal segmental units (i.e., consonants and vowels). These tonal features produced unique spatiotemporal NS patterns, forming language-specific interbrain neural connections that enabled effective transmission of representations between the speaker and listeners. The strength and patterns of NS, driven by these speech features, further predicted listeners' understanding of the speaker's storytelling. These findings demonstrate the interbrain neural mechanisms underlying shared representations during verbal exchange and highlight how language-specific speech features shape neural alignment between speakers and listeners, supporting information transfer.Significance Statement Human communication depends on shared neural representations between speakers and listeners, but the specific features that promote this alignment remain unclear. Using MEG and a feature-based interbrain analysis approach, we show that speaker-listener neural synchronization is driven more by linguistic content than by acoustics alone. Language-specific lexical tones and pitch cues have a stronger influence than segmental features and can predict how effectively listeners comprehend the speaker's stories. These findings highlight the importance of language-specific tonal information in driving interbrain alignment and introduce a new method to distinguish the roles of different speech features. The study provides insights into how production and perception systems are coordinated across brains in space and time, depending on linguistic features during the transfer of verbal information.

Cardiovascular problems affect nearly half of all American adults and are the leading cause of death. Mental health problems like anger/hostility, anxiety, and depression are associated with hypertension and hypotension, but the mechanisms underlying these associations remain unclear. Based on the perseverative cognition hypothesis and Selye's stress model, trait repetitive negative thinking (RNT) may represent one such mechanism. We conducted a two-wave study with a 2-week time lag. The sample included104 participants who were largely White (77.9%), non-Hispanic (92.3%), heterosexual (68.3%), women (73.1%), and assigned female at birth (79.8%) with at least some post-secondary education (53.8%). After controlling for self-reported aggression, anxiety symptoms, and depressive symptoms, we examined the associations between self-reported trait anger rumination, brooding, reflection, stress-reactive rumination, and worry measured at wave 1 and resting systolic (SBP) and diastolic blood pressure (DBP) measured at wave 2. Our regression analyses revealed that trait brooding was negatively associated with SBP and DBP. Trait anger rumination and worry were negatively associated with DBP only. Trait reflection, stress-reactive rumination, and the mental health problems (aggression, anxiety, and depressive symptoms) were not associated with blood pressure. Our findings are consistent with predictions derived from the third (exhaustion) phase of Selye's stress response model. Additional research is needed, particularly multi-year prospective studies and clinical trials demonstrating that psychological interventions targeting RNTs (particularly brooding) and mental health also affect cardiovascular outcomes. These findings provide preliminary evidence to support the integration of psychological interventions targeting RNTs in the prevention and treatment of cardiovascular health problems.

Cape Town, a microcosm of one of the most unequal societies in the world, remains both socially and spatially segregated. In this research, we address whether or not that separation is related to recorded COVID-19 cases in the city. We estimate both the temperature and relative humidity relationship to cases, via distributed-lag nonlinear model (DLNM) components, since the relationship between environmental factors and health can be delayed. The DLNM framework describes the additional time (lag) of the exposure-response association, capturing both the nonlinear exposure-response and the delays. We also expand the discussion to include lockdown measures, their association with infections and socio-economic status in Cape Town. We find that (i) relative humidity, more than temperature, is associated with changes in reported COVID-19 risk; (ii) at relatively high temperatures (21 °C), relative case risk is lower in the low socio-economic status areas; (iii) case risk is generally higher in the same areas.

Global climate changehas led to frequent extreme hot and humid events. The Humidex, as a comprehensive temperature and humidity indicator, is closely related to infectious diseases. Other infectious diarrhea is an important public health issue, but the expode-response relationship between it and Humidex, especially the seasonal effect modification and lag effect patterns, still lacks systematic research. This study aims to evaluate the impact of Humidex on the incidence of other infectious diarrhea and explore its seasonal heterogeneity and time lag effect. Using daily OID case and meteorological data from Guangdong Province (2014-2023), a Distributed Lag Non-linear Model was applied to assess the cumulative effects of Humidex, adjusting for season, day of the week, and holidays. Analyses included establishing the overall exposure-response relationship, stratifying by warm (May-October) and cold (November-April) seasons to examine effect modification, and conducting sensitivity analyses to verify robustness. At the extreme Humidex exposure level (P95, 42.27), the cumulative relative risk (CRR) for OID was 1.183 (95% CI: 1.057-1.323), indicating a significant 18.3% increase in risk, with an attributable fraction (AF) of 15.4%. Conversely, a protective effect was observed at the low Humidex level (P5, 11.3) (RR = 0.832, 95% CI: 0.748-0.926). Lag analysis at high Humidex levels (e.g., P75, P90) showed that the highest risk occurred within 0-2 days after exposure, indicating a short-term lag effect. Seasonal stratification revealed significant effect modification: during the cold season, extreme Humidex showed a protective effect (RR = 0.523, 95% CI: 0.319-0.856), while the effect was non-significant in the warm season (RR = 0.957, 95% CI: 0.880-1.040), with a seasonal effect ratio of 1.83. Sensitivity analyses confirmed the robustness of the findings to variations in lag periods and degrees of freedom for splines. Humidex is significantly associated with OID incidence, showing a non-linear exposure-response relationship and clear seasonal effect modification. While extreme Humidex generally increases OID risk, anomalously high levels during the cold season exhibit a protective effect. These findings support the development of season-specific early warnings and targeted public health interventions based on the Humidex index.

Abstract The Artemis II and IV missions mark the first visit to the moon for human beings for over 50 years. During their voyage, the astronauts will experience time-lags in their communications with Earth owing to the inherent limitations of radio communication: nothing, not even radio waves, can travel faster than the speed of light. Should humanity venture into ‘deep space’, the time lag will increase in proportion to the distance travelled from Earth, moving from a few seconds to many minutes. This brings significant challenges for law and legal processes. If human beings travel as far as Mars, the disconnect could be anywhere up to 24 min at the furthest distance. Cross-examination or the deployment of leading questions becomes ineffective as an investigatory technique between parties on Earth and parties in deep space. Questions arise as to the commencement dates of statutes, whether they commence at the same time on Earth as they do by the frame of reference of a deep space crew. Routine contractual matters such as offer and acceptance also become uncertain between parties on Earth and those in deep space. Should human beings develop the technology to travel close to the speed of light, not only will these problems still be evident, they will also be compounded by the phenomenon of ‘time dilation’. As matters involving communication and symbols, what extent can these problems be examined through legal semiotics?

Grain drying is a pivotal post-harvest process that safeguards the storage safety and quality of grain. Conventional drying control strategies, however, predominantly rely on empirical operations and single-parameter monitoring. Although the concept of accumulated temperature has been applied in grain drying, few studies have systematically investigated the dynamic characteristics of drying accumulated temperature windows, resulting in a lack of quantitative and stable control criteria for the drying process. This study first defines the drying accumulated temperature window and further classifies it into three types: the equivalent window, actual window, and good window. On this basis, the window characteristics during continuous grain drying are systematically analyzed, accurate calculation methods for equivalent and actual accumulated temperature are established, and a feasible judgment criterion for the good window is proposed. A MATLAB 2022-based simulation model for continuous corn drying is constructed to verify the proposed methods. Experimental results show that three types of windows exhibit distinct dynamic response characteristics: the equivalent accumulated temperature responds instantaneously to changes in drying conditions, while the actual accumulated temperature has a time lag of one complete drying cycle. After the drying process stabilizes, the absolute difference between equivalent and actual accumulated temperature is controlled within 1500 °C·min. A drying process is identified to enter the good window state when the outlet moisture content stably maintains at 14.5 ± 0.5% for more than 3 h. The established simulation model demonstrates high prediction accuracy, with the mean relative errors of key indicators maintained at approximately 5%. This study clarifies the dynamic mechanism of accumulated temperature windows in continuous grain drying and provides a practical quantitative basis for the intelligent control and efficiency improvement of the grain-drying process.

Background The rural locations of telemedicine and urgent care are slowed down by communication latency as a result of the poor network infrastructure and overreliance on centralized cloud computing that adds to time lag in responding. Even with the development of networking technology, reliable low-latency systems to support rural areas are yet to be developed. Methods The current paper suggests a Fog-5G Latency Optimization (F5GLO) application framework, which integrates 5G connectivity and fog computing to permit local data processing. To reduce the transmission delay and latency, healthcare data is stored at local fog nodes to allow predictive mobility of the fog node activation and low latency routing algorithms to utilize resources effectively and guarantee efficiency in transfer. Results The model is capable of cutting end to end latency by up to 87 percent in comparison to the conventional cloud-based models thereby enhancing critical healthcare applications such as remote patient monitoring and emergency medical services. It is also strong in various network traffic conditions. Conclusions Fog computing plus 5G networks introduce agility to the healthcare service delivery in the remote environment where quick processing of clinical data locally and transmission can improve the reliability of the given services by transmitting information to decision makers faster. This is a realistic incremental solution to the issue of healthcare provision to the populations that are not within reach of the giant facilities.

In recent decades, the potency of cannabis resin increased globally, raising concerns, as higher potency has been associated with increased risk of psychiatric harms at the individual level. The aim here was to examine whether changes over time in the potency of seized cannabis resin samples were associated with psychiatric harms at the population level. Data on ∆-9-tetrahydrocannabinol (THC) concentration in seized cannabis resin were obtained from forensic departments in Denmark (2000-2022), the country reporting the highest potency in Europe. Data on admissions to cannabis treatment, incidence of cannabis-induced psychosis, and dual diagnosis (schizophrenia and cannabis use disorder) were obtained from national registers. Time-dependent associations between potency and the outcomes were examined with mixed-effects linear regression models and associations across age and sex were explored. Candidate time lags were 0-10years. THC concentration increased almost fourfold: mean 8.3-31.2% from 2000 to 2022. In fully adjusted models, THC was positively associated with first-time cannabis treatment entry at lags of 0-6, strongest at year 0 (p<0.0001); incidence of cannabis-induced psychosis at lags of 0-4, strongest at year 0 (p<0.0001); and incidence of dual diagnosis at lags of 0-1, strongest at year 0 (p<0.01). No positive associations were found in unadjusted models. Subgroup analyses indicated associations in older patients and women. Potency of seized cannabis resin increased almost fourfold from 2000 to 2022. Changes in cannabis potency were positively associated with psychiatric harms at the population level across all outcomes.

This work reports the first alkali-activated material (AAM) that directly incorporates a commercially available, non-microencapsulated paraffinic phase-change material (PCM), yielding a composite potentially suitable for building envelopes, aiming at bridging the gap between effective passive thermal management and both economic and environmental sustainability. AAM matrices were produced with two PCM loadings (∼3.7 and 8.3 wt%) alongside a PCM-free control sample. DSC identified a melting transition near 28 °C with apparent enthalpies of ∼1 and ∼7 J g−1, consistent with effective PCM content and distribution. Preliminary thermal tests, carried out on testing boxes exposed to real summer conditions, allowed the determination of the delay and of the reduction in the propagation of the heat wave passing from the outer to the inner surface of the walls. AAM/PCM samples were able to reduce the inner temperature of the testing box of around 2 °C with respect to the outer temperature, showing a decrement factor of 0.78 and a time lag of around 2 h.