The 1,000 km‐long Haiyuan fault is the largest strike‐slip fault system in the northeastern Tibetan Plateau, accommodating part of the plateau's eastward extrusion. However, few large earthquakes ...have been instrumentally recorded, hindering our understanding of strain partitioning across the fault system. Here, we use synthetic aperture radar images to investigate fault geometries and slip distributions of the adjacent 2016 Mw5.9 and 2022 Mw6.7 Menyuan earthquakes that occurred 35 km apart along the western Haiyuan fault system. The purely strike and purely thrust slips of the 2022 and 2016 events indicate that strain was released separately on shallow steep fault and low‐angle fault at depth. We propose that such strain partitioning is controlled by the ratio between interseismic shear and normal velocities and the branching fault structure beneath the Lenglongling segment. Seismic hazard due to both focal mechanisms has to be considered along the western Haiyuan fault in northeastern Tibet.
Plain Language Summary
Apart by 35 km, two earthquakes occurred on 20 January 2016 and 7 January 2022 with the moment magnitude of Mw5.9 and Mw6.7 along the western Haiyuan fault system, near Menyuan county, China. They are the largest events on the Lenglongling (LLL) mountain in past decades and also the only ones with clear surface deformation captured by radar imaging geodesy. Here, we use Synthetic aperture radar images to measure the surface deformations caused by these two events and derive their fault geometries and slip distributions. For the 2022 event, our modeling shows that the rupture propagated on both the LLL and the Tuolaishan (TLS) fault, supporting that the Haiyuan fault system may extend westward through LLL to the TLS fault. The purely thrust‐slip and purely strike‐slip mechanisms of the 2016 and 2022 events indicate the strain partitioning that the shear and normal strain can be released by the strike‐slip event and thrust event separately. Such strain partitioning reminds us to consider seismic hazards due to both shallow strike‐slip and deep thrust earthquakes along the western Haiyuan fault system.
Key Points
Slip distributions of the 2016 Mw5.9 and 2022 Mw6.7 Menyuan earthquakes are derived from Sentinel‐1 interferograms and pixel offsets
The 2022 Menyuan earthquake suggests the Tuolaishan fault may as the continuation of the Haiyuan fault west of the Lenglongling fault
Coseismic slip partitioning along the western Haiyuan fault agrees with the interseismic shear‐to‐normal strain ratio and fault geometries
This study investigates the impact of macroprudential policies on CO2 emissions in G7 and BRIC countries using country-level panel data from 11 countries, covering the period from 1992 to 2020. The ...findings indicate that macroprudential policies alleviate CO2 emissions in the sample. Quantile regression results reveal that policies can exacerbate CO2 emissions in countries with high levels of CO2 emissions due to carbon leakage. The positive impact of macroprudential policies on sustainable development can be strengthened by high level of globalisation. Moreover, the influence of macroprudential policies stayed the same based on the basic regression results during the post-global financial crisis (GFC) period, while the impact was positive in the pre-GFC period. Finally, robust tests validated the findings reported in the basic regression model. From this, policymakers should prioritise sustainable economic growth when implementing macroprudential policies and leverage the influence of globalisation to amplify their impact on CO2 emissions. Furthermore, it is crucial to strengthen environmental regulations to prevent carbon leakage that result from industries seeking lenient standards.
This study is a systematic review of 20 years of research on the usage of virtual reality (VR) in K‐12 and higher education settings, which aims to consolidate, evaluate, and communicate evidence ...that can inform both the theory and practice of VR‐based instruction. A total of 149 articles were selected from three major academic databases using search strings and manual screening protocols. The literature analysis emphasized four interrelated aspects of VR‐based instruction: instructional context, instructional design, technological affordances, and research findings. The results revealed evolving trends in the VR literature in terms of publication patterns, pedagogical assumptions, equipment usage, and research methodologies, as well as the contextual factors behind VR adoption in education. Additionally, a meta‐analysis was conducted to examine the efficacy of VR‐based instruction, with results indicating an overall medium effect and several moderating factors. Finally, practical implications and a future research agenda for VR‐based instruction are discussed.
Lay Description
What is currently known about the subject matter
VR is a promising educational technology with several learning benefits.
Research findings on VR‐based education have been conditional and inconclusive.
Contemporary research on VR in K‐12 and higher education settings lacks a comprehensive review and meta‐analysis.
What this paper adds
This paper systematically reviewed 20 years of empirical research on VR application in K‐12 and higher education.
This paper revealed evolving trends in the VR literature in terms of publication patterns, pedagogical assumptions, and equipment usage.
This paper synthesised the key pedagogical and technological features of VR interventions.
This paper reported an overall medium effect size of VR‐based instruction and several moderating factors.
Implications of this study for practitioners
Decision to adopt VR technology should be based on the careful assessment of learning domains and tasks.
Embedded functions for learning assessment, collaboration, and data collection are recommended for future VR interventions.
Research in VR is needed with focus on advanced technology, cross‐disciplinary comparison, holistic instructional process, and cost‐benefit analysis.
This study investigates the impact of geopolitical risk (GPR) on consumption-based carbon (CCO
) emissions as well as the moderating role of environmental policy stringency (EPS) on the above ...relationship. Based on data collected from 27 countries from 1990 to 2020, the basic results from the sample of the study indicate that GPR accelerates CCO
emissions. Quantile regression results reveal that the effect of GPR is more pronounced in countries with higher CCO
emissions. Moreover, EPS weakens the escalating effect of GPR on CCO
emissions. The robust test results validate the findings reported in the basic regression model. The heterogeneity test indicates that the impact of GPR on CCO
emissions is greater in developing countries compared in developed countries. The study also proposes these policy implications based on the findings: (1) countries should ensure a stable political environment, establish a robust legal system and promote energy transition; and (2) the scope of environmental taxes should be expanded where different tax rates should be imposed in order to be useful in reducing CCO
emissions.
Adverse drug reactions (ADRs) are unintended and harmful reactions caused by normal uses of drugs. Predicting and preventing ADRs in the early stage of the drug development pipeline can help to ...enhance drug safety and reduce financial costs.
In this paper, we developed machine learning models including a deep learning framework which can simultaneously predict ADRs and identify the molecular substructures associated with those ADRs without defining the substructures a-priori.
We evaluated the performance of our model with ten different state-of-the-art fingerprint models and found that neural fingerprints from the deep learning model outperformed all other methods in predicting ADRs. Via feature analysis on drug structures, we identified important molecular substructures that are associated with specific ADRs and assessed their associations via statistical analysis.
The deep learning model with feature analysis, substructure identification, and statistical assessment provides a promising solution for identifying risky components within molecular structures and can potentially help to improve drug safety evaluation.
The aim of this study was to explore the influence of cutting parameters on the cutting performance of 7075-T651 aluminum alloy under different processing methods. Using finite element software, ...normal cutting, x-direction ultrasonic vibration cutting, y-direction ultrasonic vibration cutting, and elliptical ultrasonic vibration cutting processes were simulated with various values of the cutting parameters. The results showed that when the cutting speed was between 160 and 280 m/min, with the increase of the cutting speed, the main cutting force value under the four processing methods increases gradually. At 280–320 m/min, the main cutting force value of normal cutting showed a downward trend. The cutting force increased with the increase of feed and cutting depth. At the same time, the increase of cutting speed and feed increased the cutting temperature and the temperature of the blade-to-chip contact area. However, cutting depth had little influence on the temperature during the cutting process. When the cutting parameters changed, the cutting temperatures of the four machining modes were in the following order: elliptical vibration cutting > y-direction vibration cutting > x-direction vibration cutting > normal cutting. When the cutting speed and feed increased, the magnitude and depth of residual stress increased to a certain extent. As the cutting depth increased, the heat generated by the cutting increased, but most of the heat was carried away by the chips, resulting in lower influence of the thermal stress and phase changes on the residual stress.
The purpose of this study was to investigate the effects of the cutting and vibration parameters on the machining performance of 7075-T651 aluminum alloy in an unidirectional ultrasonic vibration ...cutting. Simulation experiments were performed using the AdvantEdge finite element analysis software. The results showed that as the cutting speed and feed rate increased, the cutting force and cutting temperature of the ultrasonic vibrations in the
x-
and
y-
directions increased. As the amplitude and frequency increased, they decreased accordingly. The highest temperatures of the rake and relief of the tool were located 0.01–0.02 mm from the cutting edge. With the change in the cutting and vibration parameters, the residual stress curve had a “spoon-shaped” distribution. When the cutting parameters were increased, the magnitude of the residual stress and the depth of the layer increased to a certain extent. With the increase in the vibration parameters, the change in the residual stress value of the ultrasonic vibration in the
x
direction was small, whereas the residual stress value of the ultrasonic vibration in the
y
direction increased accordingly.
y
-direction ultrasonic vibration and conventional cutting experiments were performed on the workpiece. The simulation values of the
y
-direction ultrasonic vibration cutting agreed well with the experimental values. At the same time, compared with conventional cutting, the ultrasonic vibration cutting exhibited a greatly reduced cutting force and cutting temperature.
Aiming at the problems of high stochasticity and volatility of power loads as well as the difficulty of accurate load forecasting, this paper proposes a power load forecasting method based on CEEMDAN ...(Completely Integrated Empirical Modal Decomposition) and TCN-LSTM (Temporal Convolutional Networks and Long-Short-Term Memory Networks). The method combines the decomposition of raw load data by CEEMDAN and the spatio-temporal modeling capability of TCN-LSTM model, aiming to improve the accuracy and stability of forecasting. First, the raw load data are decomposed into multiple linearly stable subsequences by CEEMDAN, and then the sample entropy is introduced to reorganize each subsequence. Then the reorganized sequences are used as inputs to the TCN-LSTM model to extract sequence features and perform training and prediction. The modeling prediction is carried out by selecting the electricity compliance data of New South Wales, Australia, and compared with the traditional prediction methods. The experimental results show that the algorithm proposed in this paper has higher accuracy and better prediction effect on load forecasting, which can provide a partial reference for electricity load forecasting methods.
As a catenary riser, unbonded flexible pipe (UFP) has the advantages of convenient installation, recyclability, flexibility, anti-corrosion and large design space. To analyze the residual fatigue ...life of in-service unbonded flexible riser (UFR), a global model of riser is established in this paper. By analyzing the distribution of configuration, tension, bending moment and bending curvature along the riser under static and dynamic loads, the most dangerous position and dynamic response are determined. And then, the residual fatigue life of the UFR is calculated. The calculation results show that the fatigue life of the UFR is greatly affected by the pipe annulus condition, and the dry annulus condition is 4.6 times that of the wet annulus condition. It is concluded that when evaluating the remaining fatigue life of an in-service UFR, the S-N curve of the tensile amour layers must be calculated according to different annular conditions, so that the fatigue life can be accurately obtained. Summarily, this paper provides an effective method for calculating the residual fatigue life of in-service UFRs.
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