Analysis of Local Seismic Events near a Large-N Array for Moho Reflections

Local seismic events recorded by the large-N IRIS Community Wavefield Experiment in Oklahoma are used to estimate Moho reflections near the array. For events within 50 km of the center of the array, normal moveout corrections and receiver stacking are applied to identify the PmP and SmS Moho reflections on the vertical and transverse components. Corrections for the reported focal depths are applied to a uniform event depth. To stack signals from multiple events, further static corrections of the envelopes of the Moho reflected arrivals from the individual event stacks are applied. The multiple-event stacks are then used to estimate the pre-critical PmP and SmS arrivals, and an average Poisson\u27s ratio of 1.77±.02 was found for the crust near the array. Using a modified Oklahoma Geological Survey (OGS) velocity model with this Poisson\u27s ratio, the time-to-depth converted PmP and SmS arrivals resulted in a Moho depth of 41±.6 km. The modeling of wide-angle Moho reflections for selected events at epicenter-to-station distances of 90 to 135 km provides additional constraints, and assuming the modified OGS model, a Moho depth of 40±1 km was inferred. The difference between the pre-critical and wide-angle Moho estimates could result from some lateral variability between the array and the wide-angle events. However, both estimates are slightly shallower than the original OGS model Moho depth of 42 km, and this could also result from a somewhat faster lower crust. This study shows that local seismic events, including induced events, can be utilized to estimate properties and structure of the crust, which in turn can be used to better understand the tectonics of a given region. The recording of local seismicity on large-N arrays provides increased lateral phase coherence for the better identification of pre-critical and wide-angle reflected arrivals

Exploring Variability of Trichodesmium Photophysiology Using Multi-Excitation Wavelength Fast Repetition Rate Fluorometry

Fast repetition rate fluorometry (FRRf) allows for rapid non-destructive assessment of phytoplankton photophysiology in situ yet has rarely been applied to Trichodesmium. This gap reflects long-standing concerns that Trichodesmium (and other cyanobacteria) contain pigments that are less effective at absorbing blue light which is often used as the sole excitation source in FRR fluorometers—potentially leading to underestimation of key fluorescence parameters. In this study, we use a multi-excitation FRR fluorometer (equipped with blue, green, and orange LEDs) to investigate photophysiological variability in Trichodesmium assemblages from two sites. Using a multi-LED measurement protocol (447+519+634 nm combined), we assessed maximum photochemical efficiency (Fv/Fm), functional absorption cross section of PSII (σPSII), and electron transport rates (ETRs) for Trichodesmium assemblages in both the Northwest Pacific (NWP) and North Indian Ocean in the vicinity of Sri Lanka (NIO-SL). Evaluating fluorometer performance, we showed that use of a multi-LED measuring protocol yields a significant increase of Fv/Fm for Trichodesmium compared to blue-only excitation. We found distinct photophysiological differences for Trichodesmium at both locations with higher average Fv/Fm as well as lower σPSII and non-photochemical quenching (NPQNSV) observed in the NWP compared to the NIO-SL (Kruskal–Wallis t-test df = 1, p < 0.05). Fluorescence light response curves (FLCs) further revealed differences in ETR response with a lower initial slope (αETR) and higher maximum electron turnover rate ((Formula presented.)) observed for Trichodesmium in the NWP compared to the NIO-SL, translating to a higher averaged light saturation EK (= (Formula presented.) /αETR) for cells at this location. Spatial variations in physiological parameters were both observed between and within regions, likely linked to nutrient supply and physiological stress. Finally, we applied an algorithm to estimate primary productivity of Trichodesmium using FRRf-derived fluorescence parameters, yielding an estimated carbon-fixation rate ranging from 7.8 to 21.1 mgC mg Chl-a–1 h–1 across this dataset. Overall, our findings demonstrate that capacity of multi-excitation FRRf to advance the application of Chl-a fluorescence techniques in phytoplankton assemblages dominated by cyanobacteria and reveals novel insight into environmental regulation of photoacclimation in natural Trichodesmium population

Adaptive Privacy-Preserving Coded Computing With Hierarchical Task Partitioning

Distributed computing is known as an emerging and efficient technique to support various intelligent services, such as large-scale machine learning. However, privacy leakage and random delays from straggling servers pose significant challenges. To address these issues, coded computing, a promising solution that combines coding theory with distributed computing, recovers computation tasks with results from a subset of workers. In this paper, we propose the adaptive privacy-preserving coded computing (APCC) strategy, which can adaptively provide accurate or approximated results according to the form of computation functions, so as to suit diverse types of computation tasks. We prove that APCC achieves complete data privacy preservation and demonstrate its optimality in terms of encoding rate, defined as the ratio between the computation loads of tasks before and after encoding. To further alleviate the straggling effect and reduce delay, we integrate hierarchical task partitioning and task cancellation into the coding design of APCC. The corresponding partitioning problems are formulated as mixed-integer nonlinear programming (MINLP) problems with the objective of minimizing task completion delay. We propose a low-complexity maximum value descent (MVD) algorithm to optimally solve these problems. Simulation results show that APCC can reduce task completion delay by at least 42.9% compared to other state-of-the-art benchmarks.Comment: 14 pages, 6 figure

Research on the Mechanism of Interaction between Styrene–Butadiene–Styrene (SBS) and Asphalt Based on Molecular Vibration Frequency

Based on the four-component theory of asphalt, molecular models of the saturate, aromatic, resin, and asphaltene were constructed, respectively. The styrene&ndash;butadiene&ndash;styrene (SBS) polymer was used as the modifier. Using density functional theory (DFT) to study the effect of SBS on the molecular vibration of each component of asphalt, the vibration spectrums and binding energy of the systems composed of SBS and each component molecule of asphalt were calculated. Prepared SBS modified asphalt and measured Fourier transform infrared spectroscopy (FTIR) before and after the experiment. The results show that after SBS was added to asphalt, no chemical reaction occurred, and the system was mainly physical blending. The vibrational peak intensity of SBS and the light components of asphalt (saturate and aromatic) is stronger than that of SBS and the heavy components of asphalt (resin and asphaltene). The interaction strengths of asphalt components and polybutadiene (PB) blocks, polystyrene (PS) blocks of SBS are different. The binding energy of SBS and the saturate is the lowest and the bonding of the system is weakest. The bonding of the systems of SBS and the aromatic, resin, asphaltene is stable, and the stability of these systems are all stronger than that of SBS and the saturate

Nanoscale Ferroelectric Characterization with Heterodyne Megasonic Piezoresponse Force Microscopy

10.1002/advs.202003993Advanced Science2003993-200399

Efficient bit error rate estimation for highspeed link by Bayesian model fusion

Abstract-High-speed I/O link is an important component in computer systems, and estimating its bit error rate (BER) is a critical task to guarantee its performance. In this paper, we propose an efficient method to estimate BER by Bayesian Model Fusion. Its key idea is to borrow conventional extrapolated BER value as prior knowledge, and combine it with additional measurement data to &quot;calibrate&quot; the BER value. This method can be viewed as an application of Bayesian Model Fusion (BMF) technique. We further propose some novel methodologies to make BMF applicable in the BER estimation case. In this way, we can sufficiently decrease the number of bits needed to estimate BER value. Several experiments demonstrate that our proposed method achieves up to 8x speed-up over direct estimation method

Evaluation of several recently developed sampling strategies within the coarse pixel scale for validation of coarse-resolution satellite albedo products

Due to the spatial heterogeneity and the spatial scale mismatch between in situ and satellite-based measurements, optimal ground sampling should be made to increase the representativeness of in situ observations. Therefore, many ground sampling strategies have been proposed, but their performance within the coarse pixel has not been evaluated. Hence, this study evaluated four typical methods regarding their ability to obtain pixel scale ground ‘truth’. Random combination (RC) performs best, with the always fewest samples to satisfy representativeness errors (REs) of 3% in the case of a small number of samples. When the goal of sampling is to obtain in situ measurements with REs close to 0 at the expense of increasing the number of samples, cumulative representativeness sampling (CRS) is more effective than RC in less heterogeneous areas. Geo-statistical model-based sampling (GSS) does not work well because the number of samples within the coarse pixel scale cannot support a robust semi-variogram model. Stratified sampling (SS) is highly dependent on spatial heterogeneity and does not work well in the case of small sample sizes. This study gives important guidance for ground sample deployment within the coarse pixel for validation of coarse-resolution satellite albedo products over a heterogeneous surface