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Using three-wave longitudinal data, this study tested the potential mediating roles of teacher-student relationship quality and teachers' career support efficacy in the association between Chinese adolescents' family socioeconomic status (SES) and career development (N = 1410). Results showed that adolescents' family SES at Wave 1 was negatively associated with their career ambivalence at Wave 3 via positive associations with both teacher-student relationship quality and teachers' career support efficacy at Wave 2. Moreover, adolescents' family SES at Wave 1 was positively related to career adaptability at Wave 3 via its positive association with teachers' career support efficacy at Wave 2. This study highlighted the important role of teacher-student interaction in adolescents' career development.

High-accuracy interferometric measurement is crucial for integrated photonic interferometric imaging. In this paper, we propose an online calibration approach for large-scale integrated photonic beam combination that can realize high-accuracy measurement. By leveraging a simple four-step switching condition and the optical path differences between interferometric beams, the instrumental characteristics of the beam combiner, including the transmittances, visibilities, and phase relations, could be calibrated accurately. Compared to the conventional approach, the calibration procedure and estimation method are greatly simplified in our proposed scheme. The effectiveness of the proposed approach is validated using a photonic integrated circuit with two interferometric channels. The calibration results show that the differences between the phase relations are less than 1.41% between the proposed and conventional approaches. The proposed scheme shows significant advantages in optical synthetic aperture imaging systems using photonic integrated circuits especially for applications in harsh environments.

As one variant of the conventional flipped model, online flipped learning is increasingly implemented and it becomes important to explore how learners may be ready for it and how learner readiness may relate to motivation, attitude, and support. Informed by a multidimensional conceptualization of learner readiness and motivation and engagement, this study investigates the current situation of learner readiness, focusing on the moderating roles of learner attitude and environmental support in moderating the interrelationships between learner readiness and motivation and engagement in online flipped learning. Based on survey responses from 6,364 English learners across 11 Chinese universities, the results reveal that the students exhibited a generally high level of readiness for online flipped learning, though with significant demographic differences. The results also indicate that learner attitudes and environmental support moderated the impact of learner readiness upon learner motivation and engagement in online flipped learning. The findings call for attention to examine closely what dimensions of learner readiness could shape what aspects of motivation and engagement rather than simply assuming a linear causal relationship between readiness and motivation and engagement. A potential polarizing effect in online flipped learning is also highlighted, with implications discussed. [ABSTRACT FROM AUTHOR]

The array‐based frequency‐Bessel transform method has been demonstrated to effectively extract dispersion curves of higher‐mode surface waves from the empirical Green's functions (EGFs) of displacement fields reconstructed by ambient noise interferometry. Distributed acoustic sensing (DAS), a novel dense array observation technique, has been widely implemented in surface wave imaging to estimate subsurface velocity structure in practice. However, there is still no clear understanding in theory about how to accurately extract surface‐wave dispersion curves directly from DAS strain (or strain rate) data. To address this, we extend the frequency‐Bessel transform method by deriving Green's functions (GFs) for horizontal strain fields, making it applicable to DAS data. First, we test its performance using synthetic GFs and verify the correctness of extracted dispersion spectrograms with theoretical results. Then, we apply it to three field DAS ambient‐noise data sets, two recorded on land and one in the seabed. The reliability and advantages of the method are confirmed by comparing results with the widely used phase shift method. The results demonstrate that our extended frequency‐Bessel transform method is reliable and can provide more abundant and higher‐quality dispersion information of surface waves. Moreover, our method is also adaptable for active‐source DAS data with simple modifications to the derived transform formulas. We also find that the gauge length in the DAS system significantly impacts the polarity and value of extracted dispersion energy. Overall, our study provides a theoretical framework and practical tool for multimodal surface wave dispersion measurement using DAS data. Plain Language Summary: Ambient noise surface wave imaging is one of the most widely used methods for estimating the Earth's internal shear wave velocity structure, exploiting the dispersion characteristics of surface waves. The array‐based frequency‐Bessel transform method has been proven effective in extracting dispersion curves of higher‐mode surface waves from empirical Green's functions (EGFs) retrieved via ambient noise interferometry. Distributed acoustic sensing (DAS), which is a novel dense array observation technique, has become widely adopted in practical surface wave imaging. Nevertheless, there remains a theoretical gap in our understanding of how to accurately extract surface‐wave dispersion curves directly from DAS strain (or strain rate) data. To bridge this gap, starting from the perspective of strain field theory, we propose an extension of the frequency‐Bessel transform method, which can account for Green's functions of horizontal strain fields and the reconstructed EGFs from DAS ambient noise data. Both synthetic tests and applications to field DAS data demonstrate that our proposed frequency‐Bessel transform method can be confidently and effectively utilized for multimodal dispersion measurement of surface waves derived from DAS observation data. This work can offer a theoretical basis and practical tool for DAS‐based surface wave imaging. Key Points: We derive Green's functions for horizontal strain fields, extending the frequency‐Bessel transform method for applications in distributed acoustic sensing (DAS) dataThe extended frequency‐Bessel transform method reliably measures multimodal surface‐wave dispersion in both synthetic and field DAS recordsThe method excels in extracting high‐quality multimodal dispersion information from both active and passive DAS data for surface waves [ABSTRACT FROM AUTHOR]

Based on 4 annual waves of data from a large sample of Chinese college students (N = 2,329, M[subscript age] = 18.40 years old, SD = 0.85; 63.10% females), this study examines the within-person and between-person effects in the association between problematic Internet use (PIU) and mental health issues. Results of analyses using the developmental equilibrium model (i.e., an autoregressive, cross-lagged panel model) demonstrate a "reciprocal" positive association between PIU and mental health issues consistently across waves. In contrast, results of analyses utilizing the random intercept, cross-lagged panel model (i.e., a model that can disaggregate within-person and between-person effects) indicate a "unidirectional" positive within-person effect from PIU to mental health issues (rather than the reverse) consistently over time, while controlling for the between-person effects that exist when comparing different individuals. Such findings highlight the importance of disaggregating within-person and between-person effects in understanding the nature of the temporal dynamics of the association between PIU and mental health.

As a strong interference source for the all-time optical imaging surveillance of maritime targets, sea surface glare is difficult to mitigate accurately because of its time-varying characteristics due to lighting conditions and seawater fluctuations. In this paper, we propose an adaptive suppression approach to sea surface glare, which establishes a geographic polarization suppression model based on real-time information regarding geographic positioning and the orientation information of the floating platform, and also combines dynamic polarization control and pixel normalization to achieve adaptive suppression of sea surface glare. Experimental results show that this approach can mitigate the influence of rapidly changing glare effectively, and the SSIM indexes between the images without glare and those with glare suppression of the same scenes exceed 0.8, which is suitable for all-time glare suppression on the sea surface under natural lighting conditions. [ABSTRACT FROM AUTHOR]

Ambient Noise Imaging (ANI) of subsurface structures relies on seismic interferometry of diffuse seismic wavefields. However, the lack of effective methods to quantify and identify highly diffuse waves hampers applications of ANI, particularly in evaluating seismic attenuation and monitoring structural changes with high temporal resolution. Conventional ANI approaches require data normalization, which effectively suppresses the non‐diffuse component with large amplitude but also results in significant loss of amplitude and phase information in the continuous seismic records. In this study, we propose a frequency domain method to quantitatively evaluate the degree of diffuseness of seismic wavefields by analyzing their statistical characteristics of modal amplitudes for stationarity and randomness. Tests on synthetic waveform and field nodal records show that the proposed method can effectively distinguish between diffuse and non‐diffuse waveforms for either single‐ or three‐component data. As an application, we identify a 60‐s‐long diffuse coda of a local M 2.2 earthquake recorded by a dense nodal array on the San Jacinto Fault Zone, and successfully extract high‐quality dispersion curve and Q‐value without performing data normalization. These results are consistent with those obtained by conventional methods that assess the correlation between coherency and the Green's function, and by modeling ballistic waves generated by road traffic. Our proposed method can advance the imaging of subsurface velocity and attenuation structures as well as monitoring temporal changes for scientific studies and engineering applications. Plain Language Summary: Earthquakes, explosions, and traffic events can generate seismic waves that travel through the Earth. As these direct waves encounter heterogeneous earth interior, they scatter and change direction, leading to more diffusive propagation. Fully diffuse waves can be used to image the subsurface structures. In this study, we develop a reliable and efficient method to measure how diffuse a seismic wavefield is at different frequencies. Tests on synthetic and field data show that the developed method can reliably differentiate between diffuse and non‐diffuse waves. This method can improve our ability to use spread out wavefields for imaging and monitoring the Earth's interior. Key Points: We present an efficient methodology to quantify seismic wavefield diffuseness based on stationarity and randomness in the frequency domainThe method avoids waveform normalization and extracts reliable empirical Green's functions from interferometry using diffuse waveformsWe validate the method by extracting dispersion curves and Q‐values from the 60‐s‐long diffuse coda of a local M 2.2 earthquake [ABSTRACT FROM AUTHOR]

Complex networks are widespread in real-world environments across diverse domains. Real-world networks tend to form spontaneously through interactions between individual agents. Inspired by this, we design an evolutionary game model in which agents participate in a prisoner's dilemma game (PDG) with their neighboring agents. Agents can autonomously modify their connections with neighbors using reinforcement learning to avoid unfavorable environments. Interestingly, our findings reveal some remarkable results. Exploiting reinforcement learning-based adaptive networks improves cooperation when juxtaposed with existing PDGs performed on homogeneous networks. At the same time, the network's topology evolves from homogeneous to heterogeneous states. This change occurs as players gain experience from past games and become more astute in deciding whether to join PDGs with their current neighbors or disconnect from the least profitable neighbors. Instead, they seek out more favorable environments by establishing connections with second-order neighbors with higher rewards. By calculating the degree distribution and modularity of the adaptive network in a steady state, we confirm that the adaptive network follows a power law and has a clear community structure, indicating that the adaptive network is similar to networks in the real world. Our study reports a new phenomenon in evolutionary game theory on networks. It proposes a new perspective to generate scale-free networks, which is generating scale-free networks by the evolution of homogeneous networks rather than typical ways of network growth and preferential connection. Our results provide new aspects to understanding the network structure, the emergence of cooperation, and the behavior of actors in nature and society. [ABSTRACT FROM AUTHOR]

Based on three-annual-wave data from 3,196 Chinese adolescents across the high school years (Mage = 15.55 years old, SD =.44; 52.8% girls at Wave 1, 10th grade), this study examined the curvilinear associations between adolescents' perceived parental career expectation and their career adaptability and ambivalence and also tested the potential mediating role of adolescents' internalizing problems in such associations. Results showed that, after controlling for a set of critical covariates and the baseline levels of outcome variables, there was an inverted U-shaped curvilinear association between adolescents' perceived parental career expectation at Wave 1 and their career adaptability at Wave 3 via adolescent internalizing problems at Wave 2. Similarly, a U-shaped curvilinear association also was identified between adolescents' perceived parental career expectation at Wave 1 and their career ambivalence at Wave 3 via their internalizing problems at Wave 2. These findings suggest that adolescents' perceived parental career expectation may have "too-much-of-a-good-thing" effects on their career development. Implications for future research and practice were discussed. Public Significance Statement: Findings of this study suggests that too high or too low levels of adolescents' perceived parental career expectation might contribute to adolescents' heightened levels of depressive and anxious symptoms, which, in turn, may ultimately compromise adolescents' career adaptability as well as increase adolescents' career ambivalence. Overall, this study yields empirical evidence supporting the "too-much-of-a-good-thing" effect of adolescents' perceived parental career expectation for adolescents' career development, particularly in the Chinese culture context. [ABSTRACT FROM AUTHOR]

We image the shallow seismic structure across the Southern San Andreas Fault (SSAF) using signals from freight trains and trucks recorded by a dense nodal array, with a linear component perpendicular to SSAF and two 2D subarrays centered on the Banning Fault and Mission Creek Fault (MCF). Particle motion analysis in the frequency band 2–5 Hz shows that the examined traffic sources can be approximated as moving single‐ or multi‐point sources that primarily induce Rayleigh waves. Using several techniques, we resolve strong lateral variations of Rayleigh wave velocities and Q‐values across the SSAF, including 35% velocity reduction across MCF toward the northeast and strong attenuation around the two fault strands. We further resolve 10% mass density reduction and 45% shear modulus decrease across the MCF. These findings suggest that the MCF is currently the main strand of the SSAF in the area with important implications for seismic hazard assessments. Plain Language Summary: Imaging the internal structure of fault zones is essential for understanding earthquake properties and processes. Here we utilize seismic data generated by trains and trucks in the Coachella valley and recorded by a dense seismic array to image the subsurface structure of two main strands of the Southern San Andreas Fault (SSAF). Several types of analyses allow us to resolve seismic velocities, attenuation coefficients, and mass density across the entire San Andreas Fault zone. The results show a clear contrast in physical properties across the Mission Creek strand of the SSAF, highlighting the presence of a bimaterial fault interface and suggesting that it is the main active strand of SSAF. The research opens up possibilities for using common rail and road traffic signals to derive high resolution imaging results of subsurface seismic properties at other locations. Key Points: We detect frequent seismic signals from rail and road traffic in a dense array across the southern San Andreas fault zoneWe use the traffic signals to image shallow structural properties across the Banning and Mission Creek fault strandsThe resolved velocity and density contrasts across the Mission Creek fault suggest it is the main active strand of the Southern San Andreas Fault in the area [ABSTRACT FROM AUTHOR]

Background: Autism spectrum disorder (ASD) is a neurodevelopmental disorder that is difficult to diagnose. Inflammatory bowel disease (IBD) is a common chronic digestive disease. Previous studies have shown a potential correlation between ASD and IBD, but the pathophysiological mechanism remains unclear. The purpose of this research was to examine the biological mechanisms underlying the differentially expressed genes (DEGs) of ASD and IBD using bioinformatics tools. Methods: Limma software was used to evaluate the DEGs between ASD and IBD. The GSE3365, GSE18123, and GSE150115 microarray data sets were acquired from the Gene Expression Omnibus (GEO) database. We then performed 6 analyses, namely, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional annotation; weighted gene coexpression network analysis; correlation analysis of hub genes with autophagy, ferroptosis and immunity; transcriptional regulation analysis of hub genes; single-cell sequencing analysis; and potential therapeutic drug prediction. Results: A total of 505 DEGs associated with ASD and 616 DEGs associated with IBD were identified, and 7 genes overlapped between these sets. GO and KEGG analyses revealed several pathways enriched in both diseases. A total of 98 common genes related to ASD and IBD were identified by weighted gene coexpression network analysis (WGCNA), and 4 hub genes were obtained by intersection with the 7 intersecting DEGs, which were PDGFC, CA2, GUCY1B3 and SDPR. We also found that 4 hub genes in the two diseases were related to autophagy, ferroptosis or immune factors. In addition, motif–TF annotation analysis showed that cisbp__M0080 was the most relevant motif. We also used the Connectivity Map (CMap) database to identify 4 potential therapeutic agents. Conclusion: This research reveals the shared pathogenesis of ASD and IBD. In the future, these common hub genes may provide new targets for further mechanistic research as well as new therapies for patients with ASD and IBD. [ABSTRACT FROM AUTHOR]

Using three-wave longitudinal data, this study tested the potential mediating roles of teacher–student relationship quality and teachers' career support efficacy in the association between Chinese adolescents' family socioeconomic status (SES) and career development (N = 1410). Results showed that adolescents' family SES at Wave 1 was negatively associated with their career ambivalence at Wave 3 via positive associations with both teacher–student relationship quality and teachers' career support efficacy at Wave 2. Moreover, adolescents' family SES at Wave 1 was positively related to career adaptability at Wave 3 via its positive association with teachers' career support efficacy at Wave 2. This study highlighted the important role of teacher–student interaction in adolescents' career development. [ABSTRACT FROM AUTHOR]

We use a dense seismic array of 1,108 vertical‐component geophones within a 600‐m footprint to detect thousands of small earthquakes near an active strand of the San Jacinto fault zone in southern California during a 26‐day period. We first correct site effects using multichannel cross‐correlations of the P‐waves of 256 cataloged earthquakes, and then perform beamforming analysis on the continuous waveforms in a slowness range from −0.4 to 0.4 s/km in both the east and north directions. At each time step, we identify the beam slowness with maximum amplitude and apply a picking algorithm to identify 13,408 events. These detections include over 55.6% of the events in the Quake Template Matching (QTM) catalog for all of southern California during the same time period and 70% of those within 100 km of the array. In addition, we detect over 10,000 new events, not in the QTM catalog. Many of these events can also be seen in records from nearby borehole seismic stations. Measured slownesses for the catalog and newly‐discovered events group into clusters that can be associated with QTM earthquake locations, but with slowness values considerably distorted from predictions based on a 1‐D velocity model, presumably owing to strong velocity heterogeneity near the San Jacinto Fault. Amplitudes of the detected events obey a Gutenberg‐Richter distribution with a b‐value close to one. Foreshocks are common among these detected events, increasing in rate before mainshocks following an inverse Omori's law. Plain Language Summary: We show that an array of over 1,000 seismometers located on a small patch of the San Jacinto Fault in southern California can detect many times more earthquakes than those in standard earthquake catalogs. Although accurate locations cannot be obtained for most of these newly identified events, their amplitudes indicate they obey similar scaling with size as larger magnitude earthquakes. Many of the larger events are preceded by foreshocks and the foreshock rate increases in the time leading up to the mainshocks. Our results suggest that future deployments of small‐aperture seismometer arrays could be used to complement existing seismic networks to probe earthquake activity in great detail. Key Points: We detect over 13,000 seismic events during 26 days in 2014 using a dense nodal array on the San Jacinto fault zone in southern CaliforniaMost of the detections are newly discovered earthquakes not in existing catalogsForeshocks are common among these earthquakes, increasing in the rate before their mainshocks following an inverse Omori's law [ABSTRACT FROM AUTHOR]

Corn is an important food crop worldwide, and its yield is directly related to Chinese food security. Accurate remote sensing extraction of corn can realize the rational application of land resources, which is of great significance to the sustainable development of modern agriculture. In the field of large-scale crop remote sensing classification, single-period optical remote sensing images often cannot achieve high-precision classification. To improve classification accuracy, multiple time series image combinations have gradually been adopted. However, due to the influence of cloudy and rainy weather, it is often difficult to obtain complete time series optical images. Synthetic aperture radar (SAR) data are imaged by microwaves, which have strong penetrating power and are not affected by clouds. A critical way to solve this problem is to use SAR images to compensate for the lack of optical images and obtain a complete time series image in the corn-growing season. However, SAR images have limited wavelengths and cannot provide important wavelengths, such as visible light bands and near-infrared information. To solve this problem, this study took Zhaodong City, a vital corn-planting base in China, as the research area; took GF-6/GF-3 and Sentinel-1/Sentinel-2 as remote sensing data sources; designed12 classification scenarios; analyzed the best classification period and the best time series combination of corn classification; studied the influence of SAR images on the classification results of time series images; and compared the classification differences between GF-6/GF-3 and Sentinel-1/Sentinel-2. The results show that the classification accuracy of time series combinations is much higher than that of single-period images. The polarization characteristics of SAR images can improve the classification accuracy with time series images. The classification accuracy of GF series images from China is obviously higher than that of Sentinel series images. The research performed in this paper can provide a reference for agricultural classification by using remote sensing data. [ABSTRACT FROM AUTHOR]

A precise finite‐fault model including the fault geometry and slip distribution is essential to understand the physics of an earthquake. However, the conventional linear inversion of geodetic data for a finite‐fault model cannot fully resolve the fault geometry. In this study, we developed a Bayesian inversion framework that can comprehensively solve a non‐planar fault geometry, the corresponding fault slip distribution with spatially variable directions, and objective weighting for multiple data types. In the proposed framework, the probability distributions of all the model parameters are sampled using the Monte Carlo method. The developed methodology removes the requirement for manual intervention for the fault geometry and data weighting and can provide an ensemble of plausible model parameters. The performance of the developed method is tested and demonstrated through inversions for synthetic oblique‐slip faulting models. The results show that the constant rake assumption can significantly bias the estimates of fault geometry and data weighting, whereas additional consideration of the variability of slip orientations can allow plausible estimates of a non‐planar fault geometry with objective data weighting. We applied the method to the 2013 Mw 6.5 Lushan earthquake in Sichuan province, China. The result reveals dominant thrust slips with left‐lateral components and a curved fault geometry, with the confidence interval of the dip angles being between 20°–25° and 56°–58°. The proposed method provides useful insights into the scope of imaging a non‐planar fault geometry, and could help to interpret more complex earthquake sources in the future. Plain Language Summary: An earthquake originates from a rapid relative movement between two blocks on both sides of a fault. The earthquake can produce ground deformation, which can be measured by geodetic instruments deployed on the ground. Geophysicists can thus utilize the geodetic measurements to invert the earthquake attributes, including the fault geometry and the associated slips (i.e., the zone and amount of the relative movement between two blocks). Simultaneous estimation of the fault geometry parameters and the slip parameters is a nonlinear problem. The conventional inversion of geodetic data uses a linear adjustment method that cannot fully resolve the fault geometry. In addition, geodetic measurements have different precisions in terms of the types of instruments. We developed a nonlinear inversion based Bayesian inference framework to solve both these problems. The proposed method can correctly interpret an earthquake source with a non‐planar fault geometry. We applied the method to the 2013 Mw 6.5 Lushan earthquake in southwest China and determined a statistical estimate of the fault geometry and slips. The results indicate that the proposed method could help to improve our knowledge of complicated earthquake sources in the future. Key Points: We develop a Bayesian finite‐fault inversion for non‐planar fault geometry and spatially variable slip amplitude and rakeAccounting for variable directions of fault slips allows to better constrain non‐planar fault geometry and tune objective data weightingAccounting for the non‐planar fault geometry, the 2013 Lushan earthquake modeling reveals a dominant thrust slip with sinistral component [ABSTRACT FROM AUTHOR]

A comparative study, in aspects of both wavelength dependence and fabrication tolerance, is carried out between silica-based phase shifters designed in two different regime, namely length difference regime and refractive index difference regime. Results show that in the wavelength range of 1500-1600 nm, phase shifter designed in refractive index difference regime has a working wavelength range 2.8~3.1 times wide as that designed in length difference regime; while in the aspect of fabrication tolerance, phase designed in length difference regime is advantageous, with respect to waveguide core dimension error, and waveguide core refractive index error as well.

The white-backed planthopper Sogatella furcifera (Horváth) is an important pest on rice plants throughout Asia. The application of chemical insecticides is still the main approach to suppressing the field population of S. furcifera. However, misuse of chemical insecticides has promoted the development of insecticide resistance in this insect pest. Thus, in the present study, dose responses of 58 field populations of S. furcifera to 7 insecticides were analyzed by rice-stem dipping from 2011 to 2021 in Central China. The results indicated that field populations of S. furcifera showed moderate levels of resistance to nitenpyram (RR = 1.7–17.8-fold), thiamethoxam (RR = 1.4–25.8-fold), dinotefuran (RR = 1.5–25.3-fold), clothianidin (RR = 2.1–12.5-fold), chlorpyrifos (RR = 1.1–56.6-fold), etofenprox (RR = 1.1–14.8-fold) and isoprocarb (RR = 1.4–11.5-fold). The results presented here will be beneficial to improve our ability to identify and predict insecticide resistance, make better control recommendations and prevent further insecticide resistance development. [ABSTRACT FROM AUTHOR]

The 2021 Mw 6.1 Yangbi earthquake in southwest China is preceded by three major foreshocks: 05/18 Mw 4.3, 05/19 Mw 4.6, and 05/21 Mw 5.2. It provides a valuable chance to revisit two end‐member foreshock models: cascade‐up and pre‐slip models. We first determine the fault structure with relocated aftershocks and the focal mechanisms obtained from a multipoint‐source inversion. We find that the mainshock and two smaller foreshocks occur on an unmapped near‐vertical fault, and the largest foreshock occurs on a mapped stepover fault that dips to northeast. Second, for each major foreshock, we estimate and delineate the rupture area based on its aftershock location and a spectral ratio analysis. Based on the inferred rupture model, we finally calculate the evolution of Coulomb stress and examine potential interactions between each major event. Results show that the Yangbi sequence can be explained by the cascade triggering mechanism, while we also find evidence for aseismic slip that contributes to the triggering process: the first foreshock is preceded by a short‐term localized cluster, three repeater sequences are detected in the foreshock period, and the aftershock zones expand logarithmically with time. The Yangbi mainshock is probably triggered by multiple major foreshocks through both seismic and aseismic processes. This detailed seismological characterization of Yangbi sequence lends supports for an improved understanding on the foreshock mechanism: (a) the controlling mechanisms are not limited to cascade‐up and pre‐slip. Instead, multiple mechanisms can operate together; and (b) aseismic slip does not always provide more deterministic information on the mainshock. Plain Language Summary: The 2021 magnitude 6.1 Yangbi earthquake in southwest China is preceded by three magnitude 4–5 earthquakes, which are known as foreshocks. Whether the foreshock sequence can be used to forecast future occurrence of large earthquakes is of great scientific interest. Here, we analyze the interaction between these foreshocks with a high‐resolution seismic catalog and the modeling of stress transfer after each major foreshock. We find that the migration directions of foreshocks are not consistent, and that the stress transfer following each foreshock is large enough to explain the triggering of the Yangbi mainshock. This supports the cascade triggering model for foreshock generation, where the foreshocks are not precursors. However, we also find several lines of evidence for aseismic fault slip. These include: the first foreshock is preceded by a short‐term localized cluster, three repeater sequences are detected in the foreshock sequence, and the aftershock zones of three foreshocks expand logarithmically with time, suggesting that they are driven by afterslip. Our results suggest that multiple mechanisms (e.g., cascade‐triggering and aseismic slip) can act at the same time to drive foreshocks, and it is relatively challenging to use foreshocks to forecast future occurrence of large earthquakes. Key Points: The Yangbi mainshock and two smaller foreshocks occur on an unmapped near‐vertical fault, and the largest foreshock occurs on a mapped stepover fault that dips to NEThe rupture directivity and source parameters of major foreshocks are estimated by aftershock distribution and spectral ratio analysisThe Yangbi sequence can be explained as a cascade sequence, but aseismic processes can also be inferred, including pre‐slip cluster and logarithmic expansion of aftershocks [ABSTRACT FROM AUTHOR]

Parallel phase-shifting digital holography (PPSDH) employing a polarization image sensor can suppress zero-order and twin-image noise through a single exposure, achieve instantaneous measurement of complex-valued dynamic objects, and have broad applications in the areas of biomedicine, etc. To improve the imaging resolution of PPSDH, we propose an oversampled super-pixel image reconstruction method, which can be expressed as the implementation of nearest-neighbor interpolation to replace blank pixels in sparse sub-phase-shift holograms. We found experimentally that the maximum spatial lateral resolution of the reconstructed image based on the existing super-pixel method, B-spline, bicubic, bilinear, and the proposed nearest-neighbor interpolation was 12.4 µm, 11.4 µm, 9.8 µm, 8.8 µm, and 7.8 µm, respectively. The main reason for not reaching the ideal value of 6.9 µm was the inherent residual zero-order and twin-image noise, which needs to be removed in the future. [ABSTRACT FROM AUTHOR]

In the present study, wind tunnel experiments were performed to investigate the power and thrust characteristics of a wind turbine model subjected to a variety of surge and sway motions. The turbine model was mounted on a translational stage to simulate the surge and sway motions at prescribed amplitudes and frequencies. The power output and rotor thrust were measured in each sets of the motion frequencies and amplitudes, respectively; and the measurements were also performed in a base-fixed turbine for comparison. Results show that the surge and sway motions with various amplitudes and frequencies all have slight impact on the mean power output and mean rotor thrust of a wind turbine. However, the rotor thrust fluctuations of the surging turbine, not only appeared significantly higher than those of the swaying turbine and base-fixed turbine at the same sets of amplitudes and frequencies, but also increased with the surge frequency and surge amplitude. Moreover, for both the surging and swaying turbine, the rotor thrust fluctuated with the same period as the surge and sway motions, respectively; and the power spectral density of the rotor thrust both exhibited a peak at the motion frequency and its odd multiple frequencies. • Turbine power and thrust characteristics under surge and sway motions were studied. • Motions had slight effect on mean turbine power and thrust in various conditions. • Thrust fluctuations of surging turbine were higher than swaying and fixed turbine. • Surging turbine thrust fluctuations increased with surge frequency and amplitude. • The PSD of thrust for surging and swaying turbine peaked at motion frequency. [ABSTRACT FROM AUTHOR]

An experimental study was performed in a uniform incoming flow wind tunnel to investigate the effect of surge and sway motions on the wake characteristics of a wind turbine model. The platform surge and sway motions can be simulated at prescribed amplitudes and frequencies through a translation stage mounted on the base of the turbine model. The flow fields of near, intermediate, and far wakes of the turbine model were characterized by a particle image velocimetry system. Results show that the mean velocity profiles during the whole surging and swaying process of the downwind wakes were almost unchanged with that of a base-fixed turbine; however, the maximum mean velocity differences appeared near the blade tips for both motions compared with the base-fixed cases. Little difference was found between the mean velocity profiles of the turbine model while moving in different directions, for both the surge and sway motions. Later, the characteristics of instantaneous velocity profiles were investigated, and the lateral offset of the instantaneous velocity profiles for the swaying turbine at the two ends of the sway motion was observed. The offset distance was very close to sway amplitudes within the near wake, and it gradually decreased until it disappeared as the downstream distance increases. This work may provide an instrumental guide in the further research on the wake of floating offshore wind turbines. [ABSTRACT FROM AUTHOR]

Understanding earthquake foreshocks is essential for deciphering earthquake rupture physics and can aid seismic hazard mitigation. With regional dense seismic arrays, we identify immediate foreshocks of 527 0.9 ≤M≤ 5.4 events of the 2019 Ridgecrest earthquake sequence, including 48 earthquakes with series of immediate foreshocks. These immediate foreshocks are adjacent to the mainshocks occurring within 100 s of the mainshocks, and their P waves share high resemblances with the mainshock P waves. However, attributes of the immediate‐foreshock P waves, including the amplitudes and preceding times, do not clearly scale with the mainshock magnitudes. Our observations suggest that earthquake rupture may initiate in a universal fashion but evolves stochastically. This indicates that earthquake rupture development is likely controlled by fine‐scale fault heterogeneities in the Ridgecrest fault system, and the final magnitude is the only difference between small and large earthquakes. Plain Language Summary: Understanding earthquake foreshocks have both scientific and societal implications regarding earthquake physics and seismic hazards. Using dense arrays in the Ridgecrest region, we find immediate foreshocks of 527 earthquakes that occurred within a month of the 2019 Mw 7.1 Ridgecrest earthquake. These immediate foreshocks are adjacent to their mainshocks and likely near‐instantaneously trigger the following slip within 100 s. Attributes of the P waves of these immediate foreshocks do not seem to correlate with the mainshock magnitudes. Our observations suggest that earthquakes may initiate via similar means and it remains challenging to use such foreshocks to predict the mainshock magnitudes. Key Points: Immediate foreshocks are observed for 527 Ridgecrest earthquakesCharacteristics of their P waves do not scale with the eventual earthquake magnitudesThese Ridgecrest earthquakes may have initiated as a rate‐dependent cascading process [ABSTRACT FROM AUTHOR]

As a new quasi-zero-dimensional nanomaterial, graphene quantum dots (GQDs) can solve the impact of carbon materials that have low specific surface area and few active sites, improving the performance of planar on-chip micro-supercapacitors (POMSs) by reducing the interdigital width. In this article, nitrogen and oxygen co-doped GQDs (N-O-GQDs) as an electrode material and narrow electrode width and gap are both 6 μm make the POMS possess a power density of 28.1 μW cm−2 and an energy density of 15.11 nWh cm−2. Importantly, the capacitance retention rate is as high as 96.1% after 10,000 cycles of charging and discharging. [ABSTRACT FROM AUTHOR]

Proper classification of nontectonic seismic signals is critical for detecting microearthquakes and developing an improved understanding of ongoing weak ground motions. We use unsupervised machine learning to label five classes of nonstationary seismic noise common in continuous waveforms. Temporal and spectral features describing the data are clustered to identify separable types of emergent and impulsive waveforms. The trained clustering model is used to classify every 1 s of continuous seismic records from a dense seismic array with 10–30 m station spacing. We show that dominate noise signals can be highly localized and vary on length scales of hundreds of meters. The methodology demonstrates the complexity of weak ground motions and improves the standard of analyzing seismic waveforms with a low signal‐to‐noise ratio. Application of this technique will improve the ability to detect genuine microseismic events in noisy environments where seismic sensors record earthquake‐like signals originating from nontectonic sources. Plain Language Summary: Improvements in microseismic detection will advance observations of failure processes on faults subjected to slowly accumulating tectonic stress. Continuous seismic waveforms contain copious variations of nontectonic signals that inhibit the detection of genuine microearthquakes. Developing a framework to identify emergent and impulsive signals originating from natural and anthropogenic activity will advance seismic network monitoring capabilities. We apply unsupervised machine learning techniques to classify multiple types of weak ground motions that occur ubiquitously in continuous seismic records. A trained model is used to label every 1 s of a dense geophone array to provide a high‐resolution description of the anatomy of continuous seismic records. Further methodology developments and application in various environments have high potential for improving the ability to monitor earthquakes and other sources of ground motion. Key Points: Emergent and impulsive signals in continuous seismic waveforms are identified using cluster analysis on a dense array dataAn unsupervised learning model is trained to identify multiple classes of noise using temporal and spectral data featuresA more complete understanding of seismic noise signals will improve the ability to detect genuine microseismic events [ABSTRACT FROM AUTHOR]

We develop a semiautomated method for estimating with second seismic moments the directivity, rupture area, duration, and centroid velocity of earthquakes. The method is applied to 41 southern California earthquakes with magnitude in the range 3.5–5.2 and provides stable results for 28 events. Apparent source time functions (ASTFs) of P and S phases are derived using deconvolution with three stacked empirical Green's functions (seGf). The use of seGf suppresses nongeneric source effects, improves the focal mechanism correspondence to the analyzed earthquakes, and typically allows inclusion of 5 to 15 more ASTFs compared with analysis using a single eGf. Most analyzed earthquakes in the Trifurcation area of the San Jacinto Fault have directivities toward the northwest, while events around Cajon Pass and San Gabriel Mountain tend to propagate toward the southeast. These results are generally consistent with predictions for dynamic rupture on bimaterial interfaces associated with the imaged velocity contrasts in the area. The second moment inversions also provide constraints on the upper and lower bounds of rupture areas in our data set. Stress drops and uncertainties are estimated for elliptical ruptures using the derived characteristic rupture length and width. The semiautomated second moment method with seGfs can be used for routine application to moderate earthquakes in locations with good station coverage. Key Points: We develop a semiautomated method for estimating finite fault parameters of earthquakes with second seismic momentsResolved rupture directivities are generally consistent with expectations for dynamic ruptures on the imaged velocity contrastsStress drops and uncertainties are estimated for elliptical ruptures using the derived characteristic rupture length and width [ABSTRACT FROM AUTHOR]

Previous studies on smartphone use motivation (SUM) and problematic smartphone use (PSU) have been limited in the utilization of regional samples of emerging adults (e.g., college students) and also in the foci on the direct association between SUM and PSU. To address such gaps, using data from a large, national representative sample of Chinese young adolescents and their parents this study examined the associations between adolescents' various types of SUM and their PSU, and also tested the potential mediating roles of smartphone use time (SUT) that adolescents spent on various activities in such associations. A nationwide representative sample of 8,261 Chinese adolescents (Mage = 12.86 years old, SD = 1.76; 42.6% females) and their parents (49% mothers) participated in this survey study. Instrumental SUM (i.e., to expand knowledge or acquire information) was associated negatively with PSU via longer SUT spent on learning and shorter SUT spent on entertainment and communication. Self-expression SUM (i.e., to gain acceptance and recognition of others by maintaining or improving self-images) was associated with longer SUT spent on both learning and entertainment, which, in turn, predicted lower and higher levels of PSU, respectively. Last, hedonic SUM (i.e., to gain pleasure) was associated positively with PSU via longer SUT spent on entertainment and communication. These findings contribute to the literature by adding greater specificity in our understanding of the implications of SUM and SUT in the etiology of PSU during the critical life stage of adolescence in a Chinese cultural context. [ABSTRACT FROM AUTHOR]

We develop a methodology to separate continuous seismic waveforms into random noise (RN), not random noise (NRN) produced by earthquakes, wind, traffic and other sources of ground motions, and an undetermined mixture of signals. The analysis is applied to continuous records from a dense seismic array on the San Jacinto fault zone. To detect RN signals, we cut hourly waveforms into non-overlapping 1 s time windows and apply cross-correlations to separate RN candidates from outliers. The cross-correlation coefficients between different RN candidates fall into a tight range (i.e. 0.09–0.35), while cross-correlation coefficients of RN candidates with NRN signals (e.g. seismic or air-traffic events) are lower. The amplitude spectra of RN candidates have a well-defined level, while the amplitude spectra of other signals deviate from that level. Using these properties, we examine the amplitude spectra of moving time windows and cross-correlation coefficients with RN templates in each hour. The hourly RN is quasi-stationary and the results cluster tightly in the parameter space of cross-correlation coefficients and L2 norm deviations from the mean spectra of RN candidates. Time windows with parameters in this tight cluster are identified as RN, windows that deviate significantly from the RN cluster are identified as NRN and windows with values in between are identified as mixed signals. Several iterations on each hourly data are used to update and stabilize the selection of RN templates and mean noise spectra. For the days examined, the relative fractions of RN, NRN and mixed signals in local day (night) times are about 26 (42 per cent), 40 (33 per cent) and 34 per cent (25 per cent), respectively. [ABSTRACT FROM AUTHOR]

Analysis of continuous seismic waveforms from a temporary deployment at Sage Brush Flats on the San Jacinto fault reveals earthquake‐ and tremor‐like signals generated by the interaction of wind with obstacles above the surface. Tremor‐like waveforms are present at the site during wind velocities above 2 m/s, which occur for 70% of the deployment duration. The response to the wind has significant spatial variability with highest ground motions near large surface objects. The wind‐related signals show ground velocities that exceed the average ground motions of M1.0–1.5 earthquakes for 6–31% of the day. Waveform spectra indicate a modulation of amplitude that correlates with wind velocity and distance from local structures. Earthquake‐like signals are found to originate from local structures and vegetation, and are modified on length scales of tens of meters. Transient signals originating beyond the study area are also observed with amplitudes greater than some microseismic events. The wind‐related ground motions contribute to local high‐frequency seismic noise. Some of these signals may be associated with small failures of the subsurface material. During elevated wind conditions a borehole seismometer at a depth of 148 m shows increased energy in the 1–8‐Hz band that is commonly used for earthquake and tremor detection. The wind‐related earthquake‐ and tremor‐like signals should be accounted for in earthquake detection algorithms due to the similar features in both time and frequency domains. Proper recognition of wind‐related ground motions can contribute to understanding the composition of continuous seismic waveforms and characterize mechanical properties of the shallow crust. Plain Language Summary: Seismic recordings contain information on atmospheric and anthropogenic phenomena which can occur over much larger portions of the daily records than tectonic events. We characterize signals with earthquake‐ and tremor‐like waveforms that are generated as wind gusts interact with objects on the surface and modulate the ambient environmental noise. The wind interaction may produce microfailures in the shallow crust generating high‐frequency energy that contributes to the local seismic noise. The classification of nontectonic signals is becoming increasingly important as earthquake detection algorithms employ machine learning techniques that utilize the data to build a detection model. Properly identifying different classes of signals will provide better detection models as the algorithms continue to improve. Key Points: Wind gusts above 2‐m/s shaking surface objects produce earthquake‐ and tremor‐like waveforms that vary spatially over tens of metersWind‐related ground motions exceed the PGV of M1.0–1.5 earthquakes for 6–31% of the day and inhibit detection of small earthquakesRecognition of wind‐related signals can increase the performance of advanced algorithms for detecting small earthquakes and tremor [ABSTRACT FROM AUTHOR]

Abstract In realistic social systems, there exists multiple networks which are influenced by each other with different level of impacts. Inspired by this, we thus study the evolution of public cooperation on two interdependent networks that are connected by means of an asymmetric information sharing updating function, which can construct the interdependent networks in two different classes in order to simulate asymmetric influence of multiple networks which exist in from bacteria to animals as well as human societies. Interestingly, we find that interdependence by means of asymmetric information sharing function can dramatically promote the evolution of cooperation by restraining negative feed-back effect to provide a better environment for cooperators to mushroom. The result shows that the stronger the level of asymmetry, the higher the level of cooperation. And we further inquiry why this asymmetric information sharing updating mechanism can strikingly promote the cooperation in the upper network and find that the value of combined Fermi–Dirac Function of defector in the upper network is relatively larger than the original Fermi–Dirac Function, which can eventually lead to the fraction of cooperation to one in the upper network. Our work can reveal some essential principles in asymmetric interdependent networks that ubiquitously exists in biological and human social systems. [ABSTRACT FROM AUTHOR]

Abstract: We observe frequent air traffic events in continuous seismic waveforms recorded for about 30 days by 1,108 vertical geophones in a tight array on the San Jacinto fault zone. The waveforms of the air traffic events resemble tremor or collections of small earthquakes. However, time‐frequency analysis reveals clear Doppler effects that can be modeled with basic equations and fitted well with parameters corresponding to airplanes and helicopters. The flying traces can be inverted by fitting the parameters at each station across the entire array. About 31 air traffic events are detected per day in the relatively remote study area, with peak activity from about 8:00 to 18:00 and significantly fewer events between 23:00 and 4:00 local time. The average event duration is about 200 s, so they cover together >7% of the day. To estimate the total time covered by earthquakes, we derive a scaling relation logτ(M) = 0.41M + 0.89 between earthquake duration and magnitudes using data of 266 earthquakes in the magnitude range 0 ≤ M ≤ 3. The results indicate that in most places, the duration of air traffic events is likely to exceed considerably the total time covered by earthquakes. [ABSTRACT FROM AUTHOR]

• Porewater Ni isotope composition (δ60Ni) can be heavier than deep seawater. • Dissolution of detrital materials in marine sediments may supply dNi to pore fluids. • In marine sediments, porewater Ni isotopes are fractionated by active Mn cycling. • Continental margin sediments can supply dissolved Ni with heavy δ60Ni to the ocean. • Heavy benthic δ60Ni may help to resolve the global ocean mass balance of Ni. Nickel (Ni) is a bio-essential element for phytoplankton in the modern oceans, and yet, the global ocean mass balance of Ni has puzzled scientists for decades. Many estimates of total Ni output flux are larger than the total Ni input flux to the ocean. The measurement of Ni stable isotopes (δ60Ni) in earth materials may inform our understanding of ocean biogeochemistry and redox conditions in both the modern ocean and the geological past. An ocean Ni stable isotope imbalance has also concerned scientists, with a global ocean δ60Ni of +1.4 ‰ which is notably heavier than the major source of Ni to the oceans from rivers. Recent efforts to resolve Ni and δ60Ni imbalances have focused on the role which manganese (Mn) oxides play in marine Ni cycling, both in the water column and in marine sediments. Manganese oxide rich marine sediments can supply isotopically heavy dissolved Ni to porewater fluids and seawater, but the source of the isotopically heavy porewater Ni remains unclear. Here we present porewater trace metal concentrations and δ60Ni from two sites from the continental margin off southern California. Porewater Ni concentrations are up to roughly 100-fold higher than deep seawater concentrations (∼1 μM compared to 10 nM, respectively). Porewater δ60Ni is near 0 ‰ in the subsurface region where Ni concentrations are highest, suggesting dissolution of lithogenic material from sediments. Porewater δ60Ni increases dramatically towards the sediment-water interface with values of up to +2.66 ‰, which to our knowledge are the heaviest Ni isotope compositions ever reported for natural materials. Measurements of porewater and sediment Ni and Mn concentrations suggest that Ni is released to porewaters in the Mn-reducing zone, and then removed by newly precipitated Mn oxides as Mn and Ni move towards the oxygenated zone of sediments. A simple Rayleigh model suggests a Ni isotope fractionation of factor of -0.61 ‰ for Ni sorption onto Mn oxides, while a diffusion-reaction model suggests a Ni isotope fractionation of -1.80 to -0.96 ‰, always with preferential adsorption of lighter Ni isotopes. This flux of Ni toward the sediment-water interface, coupled with preferential removal of lighter Ni isotopes in marine sediments, provides evidence supporting an isotopically heavy benthic source of new Ni to the oceans, which we estimate has a magnitude of 0.65 × 108 to 1.66 × 108 moles/year. We find that a benthic flux such as measured here over just 0.27-2.70 % of the ocean seafloor could mix with the river δ60Ni of +0.8 ‰ to achieve the observed deep ocean δ60Ni of +1.4 ‰. This study reveals the similarities in how rivers and continental margin sediments supply heavy Ni isotopes to the ocean. In both continental rivers and margin sediments, terrigenous Ni is released with an δ60Ni near 0.1 ‰, but lighter isotopes are captured by precipitation onto oxides so that the dissolved flux to the ocean is isotopically heavier than the terrigenous material from which Ni was released, and in the case of margin sediments may be heavier than even bulk seawater δ60Ni. We thus recognize continental margin sediments with active Mn cycling as a 'new' source of isotopically heavy dissolved Ni to the ocean. [ABSTRACT FROM AUTHOR]

Based on 4 annual waves of data from a large sample of Chinese college students (N = 2,329, Mage = 18.40 years old, SD =.85; 63.10% females), this study examines the within-person and between-person effects in the association between problematic Internet use (PIU) and mental health issues. Results of analyses using the developmental equilibrium model (i.e., an autoregressive, cross-lagged panel model) demonstrate a reciprocal positive association between PIU and mental health issues consistently across waves. In contrast, results of analyses utilizing the random intercept, cross-lagged panel model (i.e., a model that can disaggregate within-person and between-person effects) indicate a unidirectional positive within-person effect from PIU to mental health issues (rather than the reverse) consistently over time, while controlling for the between-person effects that exist when comparing different individuals. Such findings highlight the importance of disaggregating within-person and between-person effects in understanding the nature of the temporal dynamics of the association between PIU and mental health. [ABSTRACT FROM AUTHOR]