Time Shift Research Articles

Combinatorial Quantification of Multi-Features of Coda Waves in Temperature-Affected Concrete Beams.

Coda waves are highly sensitive to changes in medium properties and can serve as a tool for structural health monitoring (SHM). However, high sensitivity also makes them susceptible to noise, leading to excessive dispersion of monitoring results. In this paper, a coda wave multi-feature extraction method is proposed, in which three parameters, the time shift, the time stretch, and the amplitude variation of the wave trains within the time window, are totally derived. These three parameters are each mapped to the temperature variations of concrete beams, and then combined together with their optimal weight coefficients to give a best-fitted temperature-multi-parameter relationship that has the smallest errors. Coda wave signals were collected from an ultrasonic experiment on concrete beams within an environmental temperature range of 14 °C~21 °C to verify the effectiveness of the proposed method. The results indicate that the combination of multi-features derived from coda wave signals to quantify the medium temperature is feasible. Compared to the relationship established by a single parameter, the goodness-of-fit is improved. During identification, the method effectively reduces the dispersion of identification errors and mitigates the impact of noise interference on structural state assessment. Both the identification accuracy and stability are improved by more than 50%, and the order of magnitude of the identification accuracy is improved from 1 °C to 0.1 °C.

Temperature effects on the nanoscale thermoelastic response of a SiO2 membrane

We crossed two femtosecond extreme ultraviolet (EUV) pulses on a 100 nm thick amorphous membrane of SiO2, generating transient gratings (TGs) of light intensity with 84 nm spatial periodicity. The EUV TG excitation gave rise to the efficient generation of Lamb waves (LWs) and of a temperature grating, whose dynamics was studied at two different initial sample temperatures, 50 and 300 K. The short penetration depth of the EUV excitation pulses turned into a strong non-uniformity in the actual temperature as a function of the depth from the sample surface. At the lowest temperature, the LW frequencies presented a sizable shift in time due to the thermal equilibration along the membrane thickness. The analysis of the EUV TG waveforms allowed us to determine the decay time of the thermal grating and the sound attenuation coefficient, both found in reasonable agreement with the literature. The results show how EUV TG can provide information of non-equilibrium thermoelastic dynamics in thin membranes transparent to optical radiation.

Predator-prey interactions across hunting mode, spatial domain size, and habitat complexities.

Predator-prey interactions are a fundamental part of community ecology, yet the relative importance of consumptive and nonconsumptive effects (NCEs) (defined as a risk-induced response that alters prey fitness) has not been resolved. Theory suggests that the emergence and subsequent predominance of consumptive or NCEs depend on the given habitat's complexity as well as predator hunting mode and spatial domain sizes of both predator and prey, but their relative influence on the outcome of predator-prey interactions is unknown. We built agent-based models in NetLogo to simulate predator-prey interactions for three hunting modes-sit-and-wait, sit-and-pursue, and active-while concurrently simulating large versus small spatial domain sizes for both predators and prey. We studied (1) how hunting mode and spatial domain size interact to influence the emergence of consumptive or NCEs and (2) how, when NCEs do dominate, hunting mode and spatial domain separately or additively determine prey shifts in time, space, and habitat use. Our results indicate consumptive effects only dominate for active predators when prey habitat domains overlap completely with the predator's spatial domain and when sit-and-wait and sit-and-pursue predators and their prey both have large spatial domains. Prey are most likely to survive when they shift their time but most frequently shift their habitat. Our paper helps to better understand the underlying mechanisms that drive consumptive or NCEs to be most dominant.

Effects of passive ankle exoskeletons on neuromuscular function during exaggerated standing sway

Wearable robotic exoskeletons designed to assist human movement should integrate with the neuromusculoskeletal system. This means assisting movement while not perturbing motor control. We sought to test if passive ankle exoskeletons, which have been shown to successfully assist human gait, affect neuromuscular control of an exaggerated anterior–posterior standing sway task. Participants actively swayed while wearing an ankle exoskeleton that provided 0, 42 or 85 Nm rad −1 of additional stiffness to the ankle joint in resistance to dorsiflexion. Sway amplitude was controlled via biofeedback to elicit similar ankle angle displacements across conditions. With greater exoskeleton stiffness, participants swayed at lower sway-cycle frequencies and slower centre of pressure speeds. Furthermore, increasing exoskeleton stiffness resulted in longer operating lengths of the medial gastrocnemius and overall reduced plantar flexor muscle activation. For the soleus, there was also a temporal shift in the cross-correlation of its electromyogram with the centre of pressure displacement, meaning that muscle activation peaked later than anterior sway displacement. Together, these data suggest that assistive ankle exoskeletons influence neuromuscular control of ankle-based sway tasks. Changes in fascicle lengths could influence afferent feedback signals and the short-range stiffness of ankle muscles, while shifts in muscle activation timing suggest changes in neural control. The observed neuromuscular adaptations to exoskeleton assistance demonstrate the potential implications for standing balance and overall movement control, prompting future investigations.

Human-mouse comparison of the multistage nature of radiation carcinogenesis in a mathematical model.

Mouse models are vital for assessing risk from environmental carcinogens, including ionizing radiation, yet the interspecies difference in the dose response precludes direct application of experimental evidence to humans. Herein, we take a mathematical approach to delineate the mechanism underlying the human-mouse difference in radiation-related cancer risk. We used a multistage carcinogenesis model assuming a mutational action of radiation to analyze previous data on cancer mortality in the Japanese atomic bomb survivors and in lifespan mouse experiments. Theoretically, the model predicted that exposure will chronologically shift the age-related increase in cancer risk forward by a period corresponding to the time in which the spontaneous mutational process generates the same mutational burden as that the exposure generates. This model appropriately fitted both human and mouse data and suggested a linear dose response for the time shift. The effect per dose decreased with increasing age at exposure similarly between humans and mice on a per-lifespan basis (0.72- and 0.71-fold, respectively, for every tenth lifetime). The time shift per dose was larger by two orders of magnitude in humans (7.8 and 0.046 years per Gy for humans and mice, respectively, when exposed at ~35% of their lifetime). The difference was mostly explained by the two orders of magnitude difference in spontaneous somatic mutation rates between the species plus the species-independent radiation-induced mutation rate. Thus, the findings delineate the mechanism underlying the interspecies difference in radiation-associated cancer mortality and may lead to the use of experimental evidence for risk prediction in humans.

RADIOCARBON VARIATIONS IN ANNUAL TREE RINGS WITH 11-YEAR SOLAR CYCLES DURING 1800–1950

ABSTRACT The results of radiocarbon variation studies observed in annual tree rings from the NW Pacific (USA Northwest) (Stuiver and Braziunas 1993) and Europe (England, Brehm et al. 2021; Slovakia, Povinec 1977, 1987) are reviewed with the aim of better understanding the 11-year radiocarbon cycle and possible impacts of solar proton events on 14C levels in the atmosphere and biosphere. The average Δ14C amplitude in tree rings for the period of 1798–1944 was 1.3 ± 0.3‰, the average periodicity was 11 ± 1 years, and the average time shift between the sunspot numbers and Δ14C records was 3 ± 1 years. A new solar activity minimum (Gleissberg minimum, 1878–1933) has been identified in the Δ14C data sets from the NW Pacific and England, showing Δ14C excess of 7‰, comparable to the Dalton minimum (1797–1823). No significant changes in Δ14C levels were identified that could be associated with solar proton events during 1800–1950.

Modelling seasonal and geographical n-3 polyunsaturated fatty acid contents in marine fish from the Northeast Atlantic Ocean

Demand for n-3 polyunsaturated fatty acids (n-3 PUFAs) exceeds supply. Large-scale studies on effects of season and geography of n-3 PUFAs in marine fish from the Northeast Atlantic Ocean (NEAO) may be used to optimize utilization and improve nutrition security. Using a sinusoid model, seasonal cycles of n-3 PUFAs were determined and found to be species-specific and clearly pronounced for the pelagic zooplankton feeding species. The Greenland halibut showed very little seasonal variation. The n-3 PUFA content in North Sea autumn-spawning (NSAS) herring peaked in summer, while Norwegian spring-spawning (NSS) herring and mackerel had their peak in autumn. A time shift of peaks in n-3 PUFAs between the two herring stocks was detected, likely due to different spawning strategies in addition to a delay of n-3 PUFAs flux in the northern regions of the NEAO. This study demonstrates that consideration of nutrient contents, such as n-3 PUFAs, when organizing and structuring fishery approaches may improve overall nutritional yield. Based on total annual Norwegian fish landings and seasonal variation in n-3 PUFA contents, n-3 PUFAs yield could theoretically be increased from 13.79 kilo ton per year from the current fishing tactics, to 15.54 if the pelagic species were only caught during the time of their seasonal n-3 PUFA peaks. Pelagic fish is a good source for dietary n-3 PUFAs, but harvest timing will also influence n-3 PUFAs intake by human consumers. One portion of fatty fish harvested during winter/spring may not meet the weekly intake reference nutritional guidelines for n-3 PUFAs. Marine n-3 PUFAs yields also varied geographically and decreased southwards, with the lowest values in Skagerrak. This study can serve as a model to understand patterns of reproductive cycles and geographical distribution of n-3 PUFAs in fatty fish from the NEAO and the novel approach may be useful to support sustainable, seasonal fishing programmes for optimization of n-3 PUFAs yields.

ENSEMBLE MODELS FOR FORECASTING FLOODS IN GREAT BRITAIN BASED ON SOLAR ACTIVITY

This study aims to uncover hidden dependencies between streams of solar particles emanating from the Sun and flood events caused by precipitation in the UK. The uniqueness of this work lies in applying solar activity data as input parameters for machine learning and correlating them with real data on precipitation intensity and floods in the UK, which serve as output data. The analysis covered 20 significant floods from October 2001 to December 2019. The analysis was performed on a daily basis, taking into account the time shift between solar emissions and their impact on terrestrial weather conditions, which ranged from 0 to 9 days. The study employs correlation analysis to determine the degree of interrelation between time series of solar activity and floods, laying the foundation for a deeper understanding of possible cause-and-effect relationships. Subsequently, using predictive modeling methods, including decision tree algorithms and ensemble classification models, the potential connection between changes in solar activity and terrestrial floods was explored. An ensemble of models was created using the hard voting method, which takes into account various indicators such as proton density, differential proton flux, and ion temperature, with a time shift of up to 9 days. The analysis showed that these key parameters could effectively predict the occurrence of floods with up to 92% accuracy for the specified period. The results underscore the importance of integrating space weather and solar activity into the models for predicting terrestrial weather conditions, particularly in the context of floods in England. This not only allows for a better understanding of the causes of natural disasters but also enhances the effectiveness of emergency planning and reduces potential damages from them. Thus, this work makes a significant contribution to the field of space weather research and its impact on Earth, particularly in the areas of hydrometeorology and flood risk management.

The Latency Performance Analysis and Effective Relay Selection for Visible Light Networks.

In visible light communication (VLC), the precise latency evaluation of wireless access networks and the efficient forwarding strategy of core networks are the crux for end-to-end reliability provisioning. Leveraging martingale theory, an elegant latency-bounded reliability analysis framework is studied for the VLC network. Considering the characteristic that VLC links are easy to block, the martingale of the service process is constructed. Based on the time shift features, the martingale process related to latency is proposed for the VLC system, which models the influence of entanglement between aggregate arrivals and random service on latency. A stopping time event about latency is defined. Renting the stopping time theory, a tight upper bound of the unreliability with regard to latency is derived. In the core network, a dynamic forward backhaul framework is proposed, which uses the relay selection algorithm based on back-pressure theory to improve data transmission quality. The theoretical latency-bounded reliability matches the simulation results well, which verifies the effectiveness of the proposed analysis framework, and the proposed relay selection algorithm can also improve network performance under data-intensive transmission.

The mechanism of interaction of the animal›s body with the microbiota of the gastrointestinal tract (review)

The intestines of animals are a complex ecosystem consisting of a microbiome, host cells, and nutrients. There are about 100 trillion bacteria in the intestinal tract that form the intestinal microbiota. They are taxonomically classified by genus, family, order, and type. The intestinal microflora mainly consists of six types: Firmicutes, Proteobacteria, Bacteroidetes, Actinobacteria, Fusobacteria and Verrucomicrobia. Bacterioidetes and firmicutes occupy a dominant position in the intestinal tract of animals and play a key role in the nutrient absorption system and help strengthen the intestinal barrier. The composition of the microbial community ecosystem is dynamic, and its composition depends on many factors including genes, medications, and feeding.The purpose of this review is to analyze the microbiome of the gastrointestinal tract of animals and factors affecting their biodiversity. The composition of the microbial community ecosystem is dynamic and depends on many factors, including genes, medications, and feeding. Changes in the feeding diet can cause time shifts (within 24 hours) in a large number of microorganisms. It follows that feeding is also a vital regulator of the intestinal microbiota. The prospects for applying the results of the study of the microbiota of the body of farm animals are obvious, since they can become the basis for creating technologies that allow correcting undesirable changes in the microbiome of animals that arise as negative consequences of the intensification of highly productive agricultural production.

American Strategic Narrative - A Success Story or an Archetypal Rhetoric

Great powers rationalize their position and actions to their people, allies, and opponents. Empirical observations avow the existence of a grand narrative as a fundamental feature in the struggle for supremacy and justification to seize the top position by a great power. The American case is unique; desirous of holding persistent world leadership, it has to constantly adjust its narrative which resonates with the change in time and age shifts. This paper attempts to assess the role of strategic narrative in shaping the US envisaged world order while critically analyzing whether the American strategic narratives have been a success story or just another archetypal rhetoric. While giving an overview of the American narrative from the Monroe Doctrine to the present time, the paper argues that perhaps the American policymakers sometimes overlooked the policy-narrative linkage. Arguably, the American narrative lacked consistency and coherence as it contradicted with actual American foreign policies and created an observable policy-narrative gap. The US's narrative building was characterized by the 'need of time' and it kept mutating from the Cold War to the global war on terror, sometimes entirely contradictory to previously held stances. This paper further highlights that the narratives that the United States adopted during different timeframes were meant to enable the execution of its policy objectives that were set for its path toward world leadership while ensuring that the narratives can gain acceptability as per normative standards and possess enough attraction to be transmitted through various media without catching agonizing criticism.

Managing parking reservations to mitigate congestion in office-oriented garages

ABSTRACT To alleviate the congestion caused by long parking lines in office-oriented garages, we explore the parking reservation management strategy and focus on the optimization of arrival patterns. A k-means algorithm based on dynamic time warping (DTW) is initially applied to extract the representative arrival patterns of parking vehicles. Based on these patterns, a bi-objective arrival optimization model is then developed to decrease traffic delay time and reduce individual discomfort due to arrival time shifts. The Pareto solution set is obtained, suggesting a potentially optimal balance between traffic delay and individual discomfort. The further analysis indicates that, strategically redistributing a small percentage of vehicle arrivals can mitigate congestion under certain conditions. For small-, medium-, and large-sized garages, shifting 9.01%, 6.90% and 11.07%, respectively, of the arrival demand to either of the adjacent time windows can reduce traffic delay time by 32.74%, 49.01% and 63.27%, respectively.

Cholinergic interneurons in the dorsal striatum play an important role in the acquisition of duration memory.

The present study aimed to examine the effect of cholinergic interneuron lesions in the dorsal striatum on duration-memory formation. Cholinergic interneurons in the dorsal striatum may be involved in the formation of duration memory since they are among the main inputs to the dorsal striatal muscarinic acetylcholine-1 receptors, which play a role in the consolidation of duration memory. Rats were sufficiently trained using a peak-interval 20 s procedure and then infused with anti-choline acetyltransferase-saporin into the dorsal striatum to cause selective ablation of cholinergic interneurons. To make the rats acquire new duration-memories, we trained them with a peak interval 40 s after lesion. Before lesion, the peak times (an index of duration memory) for sham-lesioned and lesioned groups were similar at approximately 20 s. In the peak interval 40 s session, the peak times for the sham-lesioned and lesioned groups were approximately 30 and 20 s, respectively. After additional peak interval 40 s sessions, the peak times of both groups were shifted to approximately 40 s. Those results suggest that the cholinergic interneuron lesion delayed new duration-memory acquisition. Subsequent experiments showed that cholinergic interneuron lesions did not retard the shift of peak time to the original target time (20 s). Following experiment without changing the target time after lesion showed that cholinergic interneuron lesions did not change their peak times. Our findings suggest that cholinergic interneurons in the dorsal striatum are involved in new duration-memory acquisition but not in the utilization of already acquired duration memory and interval timing.

Quadriceps and Hamstrings Activation Peaks Earlier as Athletes Repeatedly Hop, but There are Differences Depending on ACL Reconstruction Technique.

After Anterior Cruciate Ligament Reconstruction (ACLR) athletes face the challenge of regaining their previous competitive level while avoiding re-injury and early knee joint cartilage degeneration. Quadriceps and hamstrings strength reductions and neuromuscular alterations potentially related to risk of re-injury are present after ACLR and relate to deficits in muscle activation. Cross-sectional laboratory study. To examine quadriceps and hamstrings muscle activation during repeated hops in healthy pivoting-sport athletes and those who had undergone ACLR (bone-tendon-bone and semitendinosus graft) who had met functional criteria allowing return to training. Surface electromyography (SEMG) was recorded from vastus medialis and lateralis and medial and lateral hamstrings bilaterally during 30 seconds' repeated hopping in male athletes on average eight months after ACLR surgery (5-12 months). All patients underwent hamstring (HS) (n=24) or bone-tendon-bone (BTB) reconstruction (n=20) and were compared to healthy controls (n=31). The SEMG signals were normalized to those obtained during maximal voluntary isometric contraction. A significant time shift in peak muscle activation (earlier) was seen for: vastus medialis and vastus lateralis activation in the control group, in the BTB group's healthy (but not injured) leg and both legs of the HS group. A significant time shift in peak muscle activation was seen for lateral hamstrings (earlier) in all but the BTB group's injured leg and the medial hamstrings in the control group only. Lower peak activation levels of the vastus lateralis (p\<0.001) and vastus medialis (p\<0.001) were observed in the injured compared to healthy legs and lower peak lateral hamstrings activity (p\<0.009) in the injured leg compared to control leg. Decline in medial hamstring peak activation (p\<0.022) was observed between 1st and 3rd phase of the hop cycle in all groups. Repeated hop testing revealed quadriceps and hamstring activation differences within ACLR athletes, and compared to healthy controls, that would be missed with single hop tests. 3.

Handling of problematic ion chromatograms with the Automated Target Screening (ATS) workflow for unsupervised analysis of high-resolution mass spectrometry data

Liquid chromatography (LC) or gas chromatography (GC) coupled to high-resolution mass spectrometry (HRMS) is a versatile analytical method for the analysis of thousands of chemical pollutants that can be found in environmental and biological samples. While the tools for handling such complex datasets have improved, there are still no fully automated workflows for targeted screening analysis. Here we present an R-based workflow that is able to cope with challenging data like noisy ion chromatograms, retention time shifts, and multiple peak patterns. The workflow can be applied to batches of HRMS data recorded after GC with electron ionization (GC-EI) and LC coupled to electrospray ionization in both negative and positive mode (LC-ESIneg/LC-ESIpos) to perform peak annotation and quantitation fully unsupervised. We used Orbitrap HRMS data of surface water extracts to compare the Automated Target Screening (ATS) workflow with data evaluations performed with the vendor software TraceFinder and the established semi-automated analysis workflow in the MZmine software. The ATS approach increased the overall evaluation performance of the peak annotation compared to the established MZmine module without the need for any post-hoc corrections. The overall accuracy increased from 0.80 to 0.86 (LC-ESIpos), from 0.77 to 0.83 (LC-ESIneg), and from 0.67 to 0.76 (GC-EI). The mean average percentage errors for quantification of ATS were around 30% compared to the manual quantification with TraceFinder. The ATS workflow enables time-efficient analysis of GC- and LC-HRMS data and accelerates and improves the applicability of target screening in studies with a large number of analytes and sample sizes without the need for manual intervention.Graphical

Novel Phase-Sensitive Full-Waveform Tomography for Seismic Imaging

Abstract Full-waveform tomography (FWT) is increasingly recognized as a pivotal technique for delineating high-resolution subsurface properties. Despite its significant potential, practical applications of FWT encounter persistent challenges, particularly in dealing with local minima and cycle-skipping problems. These difficulties often arise and are intensified by the least-squares (L2) norm’s intrinsic insensitivity to phase mismatches. To address these challenges, we have redefined the traditional L2 norm misfit function by incorporating a time shift within the synthetic waveform. This shift is determined by the temporal discrepancies between the observed and synthetic waveforms, identified through a cross-correlation technique. This approach, termed phase-sensitive FWT, integrates phase differences into the new misfit function, thus significantly mitigating the cycle-skipping problem. Numerical experiments demonstrate that PSFWT reduces dependence on the initial model and achieves more accurate inversion results compared with the traditional L2 norm method, highlighting its potential for enhancing the precision and reliability of seismic imaging.

Elephants rest more when the poaching risk is high and do not recover the lost time within a diel cycle

Poaching for ivory has caused disturbances in the behaviour of elephants. The nature and magnitude of such disturbance are not yet fully understood. Here, we studied the daily activity cycles of 10 elephants tracked for a minimum of two years each in the Samburu ecosystem in Kenya. The elephants were tracked over a spatial or temporal gradient of poaching risk in their distribution area. Laikipia Samburu landscape is shared with humans and is a mosaic of land ownership and management practices, all of which lead to varied levels of illegal killing. Using movement data of elephants tracked on various dates between 2002 and 2016, we studied the daily activity cycle when they were in their different core areas. Using Generalized Additive Models, we found that elephants moved less around midday in high poaching areas. Despite the adaptive shift in activity times, elephants were moving for fewer hours per day in areas with higher risk, reducing total movement daily in risky areas or times. The elephants lost one hour daily from their usual movement time when they went into high-risk areas, which they did not compensate for despite increased activity at dawn and dusk. The level of illegal killing was the best explanatory variable for altering the activity cycle. We infer that such risk avoidance behaviour culminates in the potential reduction of foraging efforts in a risky area. A deficit in their activity time may have consequences for their social life, reproduction, or overall foraging success, aspects of elephant ecology that are not fully understood yet. We discuss the results in light of the increasing need for more fine-scale temporal analyses of the influence of risk on the diel activity of elephants for sites that achieve both movement data and verified records of causes of elephant deaths.

Subspace Identification of Bridge Frequencies Based on the Dimensionless Response of a Two-Axle Vehicle.

As an essential reference to bridge dynamic characteristics, the identification of bridge frequencies has far-reaching consequences for the health monitoring and damage evaluation of bridges. This study proposes a uniform scheme to identify bridge frequencies with two different subspace-based methodologies, i.e., an improved Short-Time Stochastic Subspace Identification (ST-SSI) method and an improved Multivariable Output Error State Space (MOESP) method, by simply adjusting the signal inputs. One of the key features of the proposed scheme is the dimensionless description of the vehicle-bridge interaction system and the employment of the dimensionless response of a two-axle vehicle as the state input, which enhances the robustness of the vehicle properties and speed. Additionally, it establishes the equation of the vehicle biaxial response difference considering the time shift between the front and the rear wheels, theoretically eliminating the road roughness information in the state equation and output signal effectively. The numerical examples discuss the effects of vehicle speeds, road roughness conditions, and ongoing traffic on the bridge identification. According to the dimensionless speed parameter Sv1 of the vehicle, the ST-SSI (Sv1 < 0.1) or MOESP (Sv1 ≥ 0.1) algorithm is applied to extract the frequencies of a simply supported bridge from the dimensionless response of a two-axle vehicle on a single passage. In addition, the proposed methodology is applied to two types of long-span complex bridges. The results show that the proposed approaches exhibit good performance in identifying multi-order frequencies of the bridges, even considering high vehicle speeds, high levels of road surface roughness, and random traffic flows.

Coronavirus Disease 2019 Infections Among Emergency Health Care Personnel: Impact on Delivery of United States Emergency Medical Care, 2020

ObjectiveIn the early months of the COVID-19 pandemic and prior to vaccine availability, there were concerns that infected emergency department (ED) healthcare personnel (HCP) could present a threat to the delivery of emergency medical care. We examined how the pandemic affected staffing levels and whether COVID-19 positive staff were potentially infectious at work in a cohort of U.S. ED HCP in 2020. MethodsThe COVID-19 Evaluation of Risks in Emergency Departments (Project COVERED) project was a multicenter prospective cohort study of U.S. ED HCP conducted from May to December 2020. During surveillance, HCP completed weekly electronic surveys and underwent periodic serology and nasal RT-PCR testing for SARS-CoV-2, and investigators captured weekly data on healthcare facility COVID prevalence and HCP staffing. Surveys asked about symptoms, potential exposures, work attendance, personal protective equipment (PPE) use, and behaviors. ResultsWe enrolled 1,673 HCP who completed 29,825 person-weeks of surveillance. Eighty-nine (5.3%) HCP documented 90 (0.3%; 95% CI 0.2-0.4%) person-weeks of missed work related to documented or concerns for COVID-19 infection. HCP experienced symptoms of COVID-19 during 1,256 (4.2%) person-weeks and worked at least one shift while symptomatic during 1,042 (83.0%) of these periods. Seventy-five (4.5%) participants tested positive for SARS-CoV-2 during the surveillance period, including 43 (57.3%) who indicated they never experienced symptoms; 74 (98.7%; 95% CI 90.7%-99.9%) infected HCP worked at least one shift during the initial period of infection, and 71 (94.7%) continued working until laboratory confirmation of their infection. Physician staffing was not associated with the facility or community COVID-19 levels within any time frame studied (Kendall tau’s 0.02, 0.056, and 0.081 for no shift, one-week time-shift, and two-week time shift, respectively). ConclusionDuring the first wave of the pandemic, COVID-19 infections in ED HCP were infrequent, and the time lost from the workforce was minimal. HCP frequently reported for work while infected with SARS-CoV-2 prior to lab confirmation. ED staffing levels were poorly correlated with facility and community COVID-19 burden.

Consistency of Lorentz-invariance violation neutrino scenarios in time delay analyses

Modifications inspired by quantum gravity in the kinematics of special relativity can manifest in various ways, including anomalies in the time of flight of massless particles and the emergence of decay channels for otherwise stable particles. Typically, these effects are studied independently; however, it may be necessary to combine both to perform a consistent analysis. In this work, we study the interplay between time-of-flight anomalies and neutrino instability in the context of a flavour-independent high-energy Lorentz-invariance violation (LIV) in the neutrino sector. Ensuring compatibility between both types of effects imposes strong constraints on the existence of early neutrinos with energies exceeding a maximum value determined by the scale of new physics. Such constraints depend on the specific LIV scenario and should be integrated into searches for high-energy neutrinos from gamma-ray bursts exhibiting LIV time shifts.