Local Time Research Articles

Resolvent stochastic processes

A family r λ r_\lambda , λ ∈ C \lambda \in \mathbb {C} , of complex stochastic processes is introduced, which makes it possible to construct a probabilistic representation for the resolvent of the operator − 1 2 d 2 d x 2 -\frac {1}{2}\frac {d^2}{dx^2} . For λ = 0 \lambda =0 , the process r λ r_\lambda coincides with the Brownian local time process.

Temperature Dependence of the Dielectric Constant on the Lunar Surface Based on Mini-RF and Diviner Observations

Radar observation is an effective way to understand subsurface structures in terms of the dielectric constant, whose controlling factors include chemical composition, packing density, and water/ice content. Recently, laboratory measurements have shown that the dielectric constant of lunar regolith simulants also depends on the temperature, which has never been evaluated from remote sensing data. In this study, we estimated the dielectric constant from the Miniature Radio Frequency (Mini-RF) data on a lunar crater floor in the north polar region at two different local times (i.e., different surface temperatures). We calculated the dielectric constant using the inversion method and obtained the bolometric surface temperature from the Diviner Lunar Radiometer Experiment (Diviner) data. The histograms of the estimated dielectric constant values are different between the two local times. This could be interpreted as a result of the temperature dependence of the dielectric constant, while further evaluation of the influence of topography on the incidence angle and small surface roughness is needed. Nevertheless, our result suggests that the temperature dependence of the dielectric constant should be considered when interpreting S-band radar observations of the Moon and other celestial bodies with large surface temperature differences.

CTM: Cross-time temporal module for fine-grained action recognition

Dynamic contextual attribute information in the time dimension is the key to fine-grained action recognition. Temporal contextual relationships cannot be captured by conventional 2D CNNs; good local time can be obtained by the 3D CNNs, but the 3D CNNs are computationally intensive and lack capability for global time. A parallel cross-time temporal module-CTM is proposed in this article, which aims to efficiently capture dynamic contextual information of both local and global temporal dimensions. With our study, we think that the 2D CNNs can better mine temporal features to enrich the contextual relationships of temporal dimensions. The CTM can be embedded into any existing 2D CNNs baseline in a plug-and-play manner, yielding a feature framework that can capture complex spatio-temporal modeling (CTNet) with a tiny additional computational cost. In the extensive validation experiments on three datasets(i.e., SomethingV1&V2, Jester, Diving48), both action recognition accuracy and runtime inference speed are obviously better than existing temporal contextual baseline optimization schemes with similar computational cost complexity, when the CTM embedded into any 2D CNNs framework to enhance the baseline.

The structure of the local time of Markov processes indexed by Lévy trees

AbstractWe construct an additive functional playing the role of the local time—at a fixed point x—for Markov processes indexed by Lévy trees. We start by proving that Markov processes indexed by Lévy trees satisfy a special Markov property which can be thought as a spatial version of the classical Markov property. Then, we construct our additive functional by an approximation procedure and we characterize the support of its Lebesgue-Stieltjes measure. We also give an equivalent construction in terms of a special family of exit local times. Finally, combining these results, we show that the points at which the Markov process takes the value x encode a new Lévy tree and we construct explicitly its height process. In particular, we recover a recent result of Le Gall concerning the subordinate tree of the Brownian tree where the subordination function is given by the past maximum process of Brownian motion indexed by the Brownian tree.

Prevalence and electrocardiographic and electrophysiological characteristics of idiopathic ventricular arrhythmias originating from the septal left ventricular summit

AbstractIntroductionThe left ventricular summit (LVS) is the highest point on the epicardial surface of the left ventricle. A part of the LVS that is located between the left coronary arteries (lateral‐LVS) is one of the major sites of idiopathic ventricular arrhythmia (VA) origins. Some idiopathic epicardial VAs can be ablated at endocardial sites adjacent to the epicardial area septal to the lateral‐LVS (septal‐LVS). This study examined the prevalence and electrocardiographic and electrophysiological characteristics of septal‐LVS VAs.MethodsWe studied consecutive patients with idiopathic VAs originating from the LVS (67 patients) and aortic root (93 patients).ResultsBased on the ablation results, among 67 LVS VAs, 54 were classified as lateral and 13 as septal‐LVS VAs. As compared with the lateral‐LVS VAs, the septal‐LVS VAs were characterized by a greater prevalence of left bundle branch block with left inferior‐axis QRS pattern, later precordial transition, lower R‐wave amplitude ratio in leads III to II, lower Q‐wave amplitude ratio in leads aVL to aVR, and later local ventricular activation time relative to the QRS onset during VAs (V‐QRS) in the great cardiac vein. The electrocardiographic and electrophysiological characteristics of the septal‐LVS VAs were similar to those of the aortic root VAs. However, the V‐QRS at the successful ablation site was significantly later during the septal‐LVS VAs than aortic root VAs (p < .0001). The precordial transition was significantly later during the septal‐LVS VAs than aortic root VAs (p < .05).ConclusionsSeptal‐LVS VAs are considered a distinct subgroup of idiopathic VAs originating from the left ventricular outflow tract.

An Analog of Local Time of Complex Brownian Motion Process

An Analog of Local Time of Complex Brownian Motion Process

An Analog of Local Time for a Class of Lévy Processes

An Analog of Local Time for a Class of Lévy Processes

Temporal characteristics and health effects related to NO2, O3, and SO2 in an urban area of Iran

This study reports on temporal variations of NO2, O3, and SO2 pollutants and their related health effects in urban air of Khorramabad, Iran using AirQ 2.2.3 software. Based on data between 2015-2021, hourly NO2, O3, and SO2 concentrations increase starting at 6:00 AM local time until 9:00 PM, 3:00 PM, and 7:00 PM local time, respectively, before gradually decreasing. The highest monthly NO2, O3, and SO2 concentrations are observed in October, August, and September, respectively. Annual median NO2, O3, and SO2 concentrations range between 17 ppb - 38.8 ppb, 17.5 ppb - 36.6 ppb, and ∼14 ppb - 30.8 ppb, respectively. Two to 93 days and 17 to 156 days between 2015-2021 exhibit daily concentrations of NO2 and SO2 ≤ WHO AQGs, respectively, while 187 to 294 days have 8-h maximum O3 concentrations ≤ WHO AQGs. The mean excess mortality ascribed to respiratory mortality, cardiovascular mortality, hospital admissions for COPD, and acute myocardial infraction are 121, 603, 39, and 145 during 2015-2021, respectively. O3 is found to exert more significant health effects compared to SO2 and NO2, resulting in higher cardiovascular mortality. The gradual increase in NO2 and possibly O3 over the study period is suspected to be due to economic sanctions, while SO2 decreased due to regulatory activity. Sustainable control strategies such as improving fuel quality, promoting public transportation and vehicle retirement, applying subsidies for purchase of electric vehicles, and application of European emission standards on automobiles can help decrease target pollutant levels in ambient air of cities in developing countries.

Spatiotemporal variation and annual emission of CH4 in Shaoxing, China studied by a portable CH4 detector on the UAV

Methane (CH4) is the second greenhouse gas and has a profound impact on global climate change due to its high global warming potential and concentration. By 2022, the CH4 concentration was approximately 1.9 ppm, which was 264 % of the pre-industrial level. The spatiotemporal distribution of CH4 was investigated by a portable CH4 detector on an unmanned aerial vehicle and electric bicycles in Shaoxing, a city situated in the Yangtze River Delta, China. The vertical distribution revealed CH4 concentration generally decreased slowly with height. However, the inversion condition and low atmospheric boundary layer height (ABLH) leaded to the enhancement of CH4 with height. The highest CH4 concentration (2.2 ± 0.1 ppm, n = 1428) was observed in winter and the lowest (2.0 ± 0.2 ppm, n = 1530) in spring. Regarding the daily variation, CH4 concentration peaked at 5:00 local time (LT) and reached its lowest level at 14:00 LT, which was attributed to the daily variation of ABLH, lowest in the early morning and highest in the noon. In urban areas, CH4 concentrations showed higher levels near restaurants, natural gas stations and sewerage well, with a maximum value of 13.1 ppm, which was caused by CH4 emission and natural gas leakage from these places. The annual CH4 emission in Shaoxing were estimated to be approximately 69 ton/(km2·year) by the mass balance approach. Compared with other cities in the world, the CH4 emission is in higher level which imply some control measures should be conducted to reduce CH4 emission in Shaoxing.

Convolutional Neural Networks To Study Contrast-Enhanced Magnetic Resonance Imaging Based Skeletal Calf Muscle Perfusion In Peripheral Artery Disease

Peripheral artery disease (PAD) is associated with impaired blood flow in the lower extremities and histopathological changes of the skeletal calf muscles resulting in abnormal microvascular perfusion. We studied the use of convolutional neural networks (CNNs) to differentiate PAD patients from matched controls by utilizing perfusion pattern features from contrast-enhanced magnetic resonance imaging (CE-MRI) of the skeletal calf muscles. We acquired CE-MRI based skeletal calf muscle perfusion in 56 individuals (36 PAD patients, 20 matched controls). Microvascular perfusion imaging was performed post reactive hyperemia at the mid-calf level with a temporal resolution of 409 ms. We analyzed perfusion scans up to 2 minutes indexed from the local pre-contrast arrival time frame. Skeletal calf muscles including the anterior muscle (AM), lateral muscle (LM), deep posterior muscle group (DM), and the soleus (SM) and gastrocnemius muscles (GM) were segmented semi-automatically. Segmented muscles were represented as 3D DICOM stacks of CE-MRI perfusion scans for deep learning analysis. We tested several CNN models for the 3D CE-MRI perfusion stacks to classify PAD patients from matched controls. Two of the best performing CNNs (resNet and divNet) were selected to develop the final classification model. A peak accuracy of 75% was obtained for both resNet and divNet. Specificity was 80% and 94% for resNet and divNet, respectively. In conclusion, deep learning utilizing CNNs, and CE-MRI skeletal calf muscle perfusion can discriminate PAD patients from matched controls. Deep learning methods may be of interest for the study of PAD.

Long-Term Ultrasound Twinkling Detectability and Safety of a Polymethyl Methacrylate Soft Tissue Marker Compared to Conventional Breast Biopsy Markers—A Preclinical Study in a Porcine Model

ObjectiveWe have studied the use of polymethyl methacrylate (PMMA) as an alternative biopsy marker that is readily detectable with ultrasound Doppler twinkling in cases of in vitro, ex vivo, or limited duration in vivo settings. This study investigates the long-term safety and ultrasound Doppler twinkling detectability of a PMMA breast biopsy marker following local perturbations and different dwell times in a 6-mo animal experiment. MethodsThis study, which was approved by our Institutional Animal Care and Use Committee, involved three pigs and utilized various markers, including PMMA (Zimmer Biomet), 3D-printed, and Tumark Q markers. Markers were implanted at different times for each pig. Mesh material or ethanol was used to induce a local inflammatory reaction near certain markers. A semiquantitative twinkling score assessed twinkling for actionable localization during monthly ultrasounds. At the primary endpoint, ultrasound-guided localization of lymph nodes with detectable markers was performed. Following surgical resection of the localized nodes, histomorphometric analysis was conducted to evaluate for tissue ingrowth and the formation of a tissue rind around the markers. ResultsNo adverse events occurred. Twinkling scores of all markers for all three pigs decreased gradually over time. The Q marker exhibited the highest mean twinkling score followed by the PMMA marker, PMMA with mesh, and Q with ethanol. The 3D-printed marker with mesh and PMMA with ethanol had the lowest scores. All wire-localized lymph nodes were successfully resected. Despite varying percentages of tissue rind around the markers and a significant reduction in overall twinkling (p < 0.001) over time, mean PMMA twinkling scores remained clinically actionable at 6 and 5 mo using a General Electric C1-6 probe and 9L-probe, respectively. ConclusionsIn this porcine model, the PMMA marker demonstrates an acceptable safety profile. Clinically actionable twinkling aids PMMA marker detection even after 6 mo of dwell time in porcine lymph nodes. The Q marker maintained the greatest twinkling over time compared to all the other markers studied.

Longitudinal Variations of Mars Thermosphere CO2, Ar, N2, and O Densities From MAVEN: Dependencies on Species Mass, Solar Flux, and Local Time

AbstractMeasurements of CO2, Ar, N2, and O densities between 150 and 200 km from the Mars Atmosphere and Volatile Evolution Neutral Gas and Ion Mass Spectrometer during February 2015 to February 2022 are analyzed to provide a comprehensive analysis of their longitudinal wavenumber k = 1, 2, and 3 components. Variations in density amplitudes (Ak) with solar flux are marginally detectable during this period. The Ak binned and averaged in latitude, local solar time and Ls are referenced to diurnal‐ and zonal‐mean backgrounds in accord with how tides and stationary planetary waves (SPWs) are defined in theory and modeling. The resulting global Ak distributions are the interference patterns formed by superposition of diurnal tides, SPWs and/or semidiurnal tides; consequently, a simple dependence on species mass consistent with thermal expansion (diffusive equilibrium) that might exist for some individual wave components is obscured. Additionally, vertical winds likely contribute to deviations from diffusive equilibrium. Complementary analyses of the Mars Climate Database indicate that the major contributors to the Ak are DE2, SE1, DE1, and SPW1, 2, 3; support the absence of significant variability due to solar flux; and indicate a more well‐defined sensitivity to species mass. The Ak and their phases (longitudes of maxima) for the whole data set are available as part of Supporting Information S1.

A Comparison of Auroral Oval Proxies With the Boundaries of the Auroral Electrojets

AbstractThe boundaries of the auroral oval and auroral electrojets are an important source of information for understanding the coupling between the solar wind and the near‐earth plasma environment. Of these two types of boundaries the auroral electrojet boundaries have received comparatively little attention, and even less attention has been given to the connection between the two. Here we introduce a technique for estimating the electrojet boundaries, and other properties such as total current and peak current, from 1‐D latitudinal profiles of the eastward component of equivalent current sheet density. We apply this technique to a preexisting database of such currents along the 105° magnetic meridian, estimated using ground‐based magnetometers, producing a total of 11 years of 1‐min resolution electrojet boundaries during the period 2000–2020. Using statistics and conjunction events we compare our electrojet boundary data set with an existing electrojet boundary data set, based on Swarm satellite measurements, and auroral oval proxies based on particle precipitation and field‐aligned currents. This allows us to validate our data set and investigate the feasibility of an auroral oval proxy based on electrojet boundaries. Through this investigation we find the proton precipitation auroral oval is a closer match with the electrojet boundaries. However, the bimodal nature of the electrojet boundaries as we approach the noon and midnight discontinuities makes an average electrojet oval poorly defined. With this and the direct comparisons differing from the statistics, defining the proton auroral oval from electrojet boundaries across all local and universal times is challenging.

Spatial-temporal characteristics analysis of solar irradiance forecast errors in Europe and North America

Accurate photovoltaic (PV) power forecast is crucial to power systems. Solar irradiance forecast is the fundamentals of PV power forecast. Current researches merely focus on improving the forecast accuracy. There hasn't been comprehensive study on the spatial-temporal characteristics of solar irradiance forecast errors. Thus, this paper analyzed the error characteristics of solar irradiance forecast provided by European Centre for Medium-Range Weather Forecasts (ECMWF), one of the most accurate numerical weather prediction (NWP) products. ECMWF's forecasts were compared with ERA5 solar irradiance reanalysis data to reveal the error distribution characteristics. Four-year (2017–2020) data from the geographical region bounded by 63°N, −126°W, 21°S, and 36°E (covering most parts of Europe and North America) were studied. Experiments show that solar irradiance forecast errors peak at noon of the local time. Furthermore, correlations between solar irradiance forecast errors and other weather variables were also revealed. Experiments show that solar irradiance forecast errors have negative correlation with low cloud cover forecast errors and positive correlation with air temperature forecast errors. The possible reasons for the correlation relationship were also analyzed in detail. This paper systematically reveals the spatial-temporal characteristics of solar irradiance forecast errors and provides a useful guideline for solar PV system operation.

The Third Plasma Density Peak at Poleward of EIA Crest: Swarm and ICON Observations

AbstractIn this study, we focus on the presence of the ionospheric third plasma density peak associated with the equatorial ionization anomaly (EIA) based on observations from the ESA's Swarm constellation. By statistically analyzing the third peaks observed by the Swarm A and B at two different altitudes, we found that such structure appears mainly around ±20° magnetic latitude (Mlat), namely the poleward of the EIA crests. In the meanwhile, the third peak shows prominent season and local time dependences, that are mainly observed in the summer hemisphere during solstice seasons and with the highest occurrence in the afternoon hours. However, no clear solar flux and magnetic activity dependences are found. By further analyzing the simultaneous neutral wind measurements from the ionospheric connection explorer satellites, we found that the summer‐to‐winter hemispheric meridional wind is responsible for causing the third peak as well as its seasonal dependence (higher occurrence in the summer hemisphere). In addition, the third‐peak structure shows prominent longitudinal dependence. In regions where the magnetic declination directs eastward, it has a larger occurrence in the southern hemisphere, while in regions where the magnetic declination reverses, it has a larger occurrence in the northern hemisphere. Such a longitudinal dependence suggests that the zonal wind, which has a magnetic field‐aligned component at favorable magnetic declination regions, contributes also to the formation of the third‐peak structure.

Error analysis of second-order local time integration methods for discontinuous Galerkin discretizations of linear wave equations

This paper is dedicated to the full discretization of linear wave equations, where the space discretization is carried out with a discontinuous Galerkin method on spatial meshes which are locally refined or have a large wave speed on only a small part of the mesh. Such small local structures lead to a strong Courant–Friedrichs–Lewy (CFL) condition in explicit time integration schemes causing a severe loss in efficiency. For these problems, various local time-stepping schemes have been proposed in the literature in the last years and have been shown to be very efficient. Here, we construct a quite general class of local time integration methods preserving a perturbed energy and containing local time-stepping and locally implicit methods as special cases. For these two variants we prove stability and optimal convergence rates in space and time. Numerical results confirm the stability behavior and show the proved convergence rates.

Diurnal Warm Layers in the Ocean: Energetics, Nondimensional Scaling, and Parameterization

Abstract Diurnal warm layers (DWLs) form near the surface of the ocean on days with strong solar radiation, weak to moderate winds, and small surface-wave effects. Here, we use idealized second-moment turbulence modeling, validated with large-eddy simulations (LES), to study the properties, dynamics, and energetics of DWLs across the entire physically relevant parameter space. Both types of models include representations of Langmuir turbulence (LT). We find that LT only slightly modifies DWL thicknesses and other bulk parameters under equilibrium wave conditions, but leads to a strong reduction in surface temperature and velocity with possible implications for air–sea coupling. Comparing tropical and the less frequently studied high-latitude DWLs, we find that LT has a strong impact on the energy budget and that rotation at high latitudes strongly modifies the DWL energetics, suppressing net energy turnover and entrainment. We identify the key nondimensional parameters for DWL evolution and find that the scaling relations of Price et al. provide a reliable representation of the DWL bulk properties across a wide parameter space, including high-latitude DWLs. We present different sets of revised model coefficients that include the deepening of the DWL due to LT and other aspects of our more advanced turbulence model to describe DWL properties at midday and during the DWL temperature peak in the afternoon, which we find to occur around 1500–1630 local time for a broad range of parameters.

Characteristic Analysis of the MS6.0 Ma'erkang Earthquake Sequence on Jun. 10, 2022

On June 10, 2022, the MS6.0 Ma'erkang earthquake sequence occurred in the Bayan Har block. In this paper, the temporal and spatial distribution and attenuation characteristics of earthquake sequence is analyzed based on the regional structure, the temporal and spatial distribution of earthquake sequence, the focal mechanism solution, and the parameters of earthquake sequence, using the data of Sichuan Seismic Network and the temporary stations incorporated into the network. The results show that: (1) The MS6.0 Ma'erkang earthquake sequence is generally distributed in NW-SE direction, and the long axis of this series is basically consistent with the nearby Songgang fault. (2) As the earthquake sequence is formed by three large events with MS ≥5.0, the frequency of small earthquakes in the earthquake sequence area generally attenuates relatively slowly, while the activity level (magnitude) of aftershocks attenuates rapidly. (3) After the MS5.2 earthquake, the sequence parameters obtained show that the h-value is 1.09 and the p-value is stable at 1.02, indicating that the intensity and frequency attenuation of the earthquake sequence are gradually stable and tend to be normal. The b-value is 0.95, indicating that the maximum aftershock magnitude of the series is estimated to be ML5.1, and the b-value gradually tended to be stable, indicating that the stress in the region gradually tended to be balanced after the MS5.2 earthquake. The MS4.4 (ML5.0) earthquake that occurred at 4:37 on June 10 (local time) is the largest aftershock after the MS5.2 earthquake in the sequence. (4) The Songgang fault with NW-SE trend is presumed to be the main seismogenic tectonics, but the migration of three earthquakes with MS≥5.0 may also indicate that the Songgang fault is not a single seismogenic tectonics, which requires further field scientific investigation and analysis.

Lunar South Polar Water Cycle and Water Resources: Diurnal and Spatial Variations in Surficial Hydration From Repeated Moon Mineralogy Mapper Observations

AbstractThe diurnal variation and distribution of lunar surficial hydration (OH/H2O) is of great significance for understanding the solar wind implantation and water cycle on the Moon. Lunar south pole is an ideal place to study the diurnal variation of surficial hydration due to the large number of repeat observations of the same region, which is very limited in mid‐ or low‐latitudes. Here we showed clear 0.5‐hr interval diurnal variation of surficial hydration at lunar south pole. The variation of hydration band depth with local time is exactly the opposite to the variation of temperature, indicating that lunar surficial hydration changes sufficiently with temperature. This relationship indicates that both the diurnal variation and hydration content are latitude dependent. Our observations support the hypothesis that the diurnal variation of hydration on the Moon is due to the formation of metastable hydroxyl.

Multipath Attention and Adaptive Gating Network for Video Action Recognition

3D CNN networks can model existing large action recognition datasets well in temporal modeling and have made extremely great progress in the field of RGB-based video action recognition. However, the previous 3D CNN models also face many troubles. For video feature extraction convolutional kernels are often designed and fixed in each layer of the network, which may not be suitable for the diversity of data in action recognition tasks. In this paper, a new model called Multipath Attention and Adaptive Gating Network (MAAGN) is proposed. The core idea of MAAGN is to use the spatial difference module (SDM) and the multi-angle temporal attention module (MTAM) in parallel at each layer of the multipath network to obtain spatial and temporal features, respectively, and then dynamically fuses the spatial-temporal features by the adaptive gating module (AGM). SDM explores the action video spatial domain using difference operators based on the attention mechanism, while MTAM tends to explore the action video temporal domain in terms of both global timing and local timing. AGM is built on an adaptive gate unit, the value of which is determined by the input of each layer, and it is unique in each layer, dynamically fusing the spatial and temporal features in the paths of each layer in the multipath network. We construct the temporal network MAAGN, which has a competitive or better performance than state-of-the-art methods in video action recognition, and we provide exhaustive experiments on several large datasets to demonstrate the effectiveness of our approach.