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Abstract The seismic hazard of a fault system is controlled by the maximum possible earthquake magnitude it can host. However, existing methods to estimate maximum magnitudes can result in large uncertainties or ignore their temporal evolution. Here, we show how the maximum possible earthquake magnitude of a fault system can be assessed by combining high-resolution fault coupling maps with a physics-based model from three-dimensional dynamic fracture mechanics confirmed by dynamic rupture simulations. We demonstrate the method on the Anninghe-Zemuhe fault system in southwestern China, where dense near-fault geodetic data has been acquired. Our results show that this fault system currently has the potential to generate Mw7.0 earthquakes with maximum magnitudes increasing to Mw7.3 by 2200. These results are supported by the observed rupture extents and recurrence times of historical earthquakes and the b values of current seismicity. Our work provides a practical way to assess the earthquake potential of natural faults.

Abstract Although fault locking state has been widely acquired with space geodetic observations, the mechanisms controlling fault locking are poorly known. Here, we infer the locking state of the Xiaojiang fault with a viscoelastic deformation model and integrated GNSS data, based on which we probe the mechanism that may control the locking pattern of the fault. Our results reveal four highly locked asperities along the Xiaojiang fault, which are separated by weak locking zones. Relying on the inferred locking degree and spring water temperature along the fault, we construct a model to connect the fault hydraulic conductivity with the cooling process of upwelling water. Model results suggest that high spring water temperature correlates with high hydraulic conductivity. Further, we use an experimental law to infer that the obtained high hydraulic conductivity may associate with high pore fluid pressure, which in turn weakens the fault frictional strength and leads to weak locking.

Understanding the distribution of species is highly important for optimizing future conservation priorities and strategies at the regional scale. Relatively little attention has been given to multi-taxon aquatic biota in extreme alpine environments. We examined the spatial and temporal patterns of alpha and beta diversity, site-specific contributions to beta diversity and assembly mechanisms of four taxonomic groups (fishes, macroinvertebrates, zooplankton and phytoplankton) from the source to the estuary of the Za'gya Zangbo River above 4500 ​m AMSL (above mean sea level) on the northern Qinghai-Tibetan (Q–T) Plateau. A total of 4 fish species, 45 macroinvertebrate taxa, 17 zooplankton taxa and 56 phytoplankton taxa were found in the study area. No consistent patterns in taxonomic richness were observed across taxa from upstream to estuary. The fish communities had the lowest dissimilarity between communities, the phytoplankton community had the highest dissimilarity in the dry season, and the macroinvertebrate community had the highest dissimilarity in the wet season. The relative importance of the turnover and nestedness components varied considerably across taxa and along spatial gradients. The diversity patterns of macroinvertebrate, zooplankton and phytoplankton communities were significantly correlated with several environmental factors, whereas only the beta diversity of fish was correlated with altitude. Stochastic processes dominated in shaping the macroinvertebrate communities whereas deterministic processes dominated the assembly of the phytoplankton communities. Weak congruence of diversity patterns across taxonomic groups suggested that biological groups cannot serve as reliable surrogates for one another and that multiple biological groups should be included in the biomonitoring of high-altitude rivers on the Q‒T Plateau. The relatively unique species in the upstream area and estuary of the Za'gya Zangbo River harbor should receive more attention in future conservation and management schemes.

Abstract The rheology of materials near fault zones controls the deformation of the fault, thus playing an important role in the rupture propagation of large earthquakes. Here, we model the postseismic deformation in the first 4 years following the 2019 Ridgecrest earthquake, and probe the laterally variable lower‐crustal viscosity and fault afterslip, using a combined model incorporating afterslip and viscoelastic relaxation. Modeling results reveal that laterally variable low‐viscosity zones (1017∼1018 Pa·s) beneath the Coso Volcanic Field are required to explain the observations well. These low‐viscosity materials may reduce the width of the brittle part of the fault, thus affecting the northwestward propagation of the 2019 Ridgecrest earthquake rupture and the spatial pattern of nearby seismicity. Numerical simulations reveal that the postseismic viscoelastic relaxation of the event will cause contractional strain in the upper‐crustal magma reservoirs, which may counteract the extensional strain caused by the coseismic rupture.

In the realm of wireless communications, accurate Radio Signal Received Power (RSRP) prediction serves as the foundation for improving user experience and optimizing network efficiency and reliability. With the deep integration of Artificial Intelligence (AI) technology and the wireless communication network, Federated Learning (FL) is considered as a promising approach for enhancing RSRP prediction while protecting user data privacy in the upcoming of 6G network. However, in practice, the heterogeneity of User Equipment (UE) environments and the limitations of UE communication bandwidth and computational capabilities can lead to poor model performance and inefficient model interactions in FL. To address these challenges, this paper proposes a Multi-head DNN based FL algorithm for RSRP prediction. The experimental results show that the proposed algorithm can enhance both RSRP prediction performance and communication efficiency.

Pine wilt disease is a major biological disaster caused by Bursaphelenchus xylophilus. This study establishes a high-quality and well-annotated genome sequence of B. xylophilus strain TS-1 from Mountain Tai in Shandong province, China. The 75-Mbp assembly containing six chromosomes was established. These genome data represent a valuable new resource for future studies on B. xylophilus and the management of pine wilt disease. [Figure: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

The substitution of ingredients with Salmonidae, particularly Salmo salar, has led to widespread reports of financial losses and health risks globally, emphasizing the urgent need for the development of a rapid and precise method for species identification. The aim of the present study was to develop a novel method for the rapid screening of Salmonidae ingredients and the accurate detection of S. salar simultaneously using multiplex real-time PCR coupled with melting curve analysis. Specifically, primer sets specific for S. salar and Salmonidae were cross-confirmed. Moreover, the reaction system and conditions of a real-time duplex PCR were optimized, and the proposed methodology was verified, proving that the assay has good specificity and sensitivity. Clear and distinguishable melting peaks, with expected Tm values of around 80 °C (S. salar) and 84 °C (Salmonidae), were observed for twelve products, proving the presence of S. salar. However, four products were not derived from S. salar, but they could have belonged to another species within the Salmonidae family due to the presence of only one specific melting peak at a Tm value of about 84 °C. Therefore, the novel assay in the present study allows for the fast and accurate screening of Salmonidae ingredients and the detection of S. salar simultaneously.

BackgroundMotor impairment is the most prevalent consequence following a stroke. Interhemispheric homotopic connectivity, which varies regionally and hierarchically along the axis of the somatomotor-association cortex, plays a critical role in sustaining normal motor functions. However, the impact of strokes occurring in various locations on homotopic connectivity is not fully understood. This study aimed to explore how motor deficits resulting from acute strokes in different locations influence homotopic connectivity.MethodsEighty-four acute ischemic stroke patients with dyskinesia were recruited and divided into four demographically-matched subgroups based on stroke locations: Group 1 (G1; frontoparietal, n = 15), Group 2 (G2; radiation coronal, n = 16), Group 3 (G3; basal ganglia, n = 30), and Group 4 (G4; brain stem, n = 23). An additional 37 demographically-matched healthy controls were also recruited in the study. Multimodal MRI data, motor function assessments, and cognitive tests were gathered for analysis. Interhemispheric homotopic functional and structural connectivity were measured using resting-state functional MRI and diffusion tensor imaging, respectively. These measurements were then correlated with motor function scores to investigate the relationships.ResultsVoxel-mirrored homotopic connectivity (VMHC) analysis showed that strokes in the frontoparietal and basal ganglia regions led to diminished homotopic connectivity in the somatosensory/motor cortex. In contrast, strokes in the radiation coronal and brainstem regions affected subcortical motor circuits. Structural homotopic connectivity analysis using diffusion tensor imaging showed that frontoparietal and basal ganglia strokes predominantly affected association fibers, while radiation coronal and brainstem strokes caused widespread disruption in the integrity of both cortical-cortical and cortical-subcortical white matter fibers. Correlation analyses demonstrated significant associations between the Fugl-Meyer Assessment (FMA), Modified Barthel Index (MBI), and National Institutes of Health Stroke Scale (NIHSS) scores with the VMHC in the inferior temporal gyrus for G1 (G1; r = 0.838, p < 0.001; r = 0.793, p < 0.001; and r = −0.834, p < 0.001, respectively). No statistically significant associations were observed in Groups 2, 3, and 4.ConclusionOur results suggest that motor deficits following strokes in various regions involve distinct pathways from cortical to subcortical areas. Alterations in lesion topography and regional functional homotopy provide new insights into the understanding of neural underpinnings of post-stroke dyskinesia.

Abstract Inspired by the excellent wear resistance and lubrication of articular joints, a novel bionic interfacial system was proposed by combining thixotropic hydrogel with surface porous Ultrahigh Molecular Weight Polyethylene (UHMWPE). Thixotropic hydrogel, synthesised by gelatin, alginate sodium, tannic acid and weak crosslinking by Ca2+ (Gel‐TA‐Alg@Ca2+), was used as a lubricant due to its shear‐thinning when loaded, then the recovery viscosity to be benefitted for reserving in surface pores on UHMWPE when unloaded. Surface porous UHMWPE was fabricated by using hydroxyapatite particles as porogen to control its porosity, pore size, surface roughness and surface energy (PE‐HA). Gel‐TA‐Alg@Ca2+ significantly reduced average coefficients of friction and wear factors compared to those under normal saline and calf serum solution lubricating after reciprocating tribological testing. Notably, Gel‐TA‐Alg@Ca2+ still maintained thixotropy and was stored in surface pores of UHMWPE even after tribological testing for 7200 min. Thus, durable lubrication could be realised due to the synergistic effect of surface porous structure and thixotropy. Stribeck curves showed the characterisations of mixed, elastohydrodynamic and hydrodynamic, but without boundary lubrications for PE‐30HA under three lubricants. The present results might provide the potential application to construct the durable lubrication bionic articular joint interfacial system for artificial joints.

Abstract Two major earthquakes (MW 7.8 and MW 7.7) ruptured left-lateral strike-slip faults of the East Anatolian Fault Zone (EAFZ) on February 6, 2023, causing >59,000 fatalities and ~$119B in damage in southeastern Türkiye and northwestern Syria. Here we derived kinematic rupture models for the two events by inverting extensive seismic and geodetic observations using complex 5-6 segment fault models constrained by satellite observations and relocated aftershocks. The larger event nucleated on a splay fault, and then propagated bilaterally ~350 km along the main EAFZ strand. The rupture speed varied from 2.5-4.5 km/s, and peak slip was ~8.1 m. 9-h later, the second event ruptured ~160 km along the curved northern EAFZ strand, with early bilateral supershear rupture velocity (>4 km/s) followed by a slower rupture speed (~3 km/s). Coulomb Failure stress increase imparted by the first event indicates plausible triggering of the doublet aftershock, along with loading of neighboring faults.

Cement-based materials are the foundation of modern buildings but suffer from intensive energy consumption. Utilizing cement-based materials for efficient energy storage is one of the most promising strategies for realizing zero-energy buildings. However, cement-based materials encounter challenges in achieving excellent electrochemical performance without compromising mechanical properties. Here, we introduce a biomimetic cement-based solid-state electrolyte (labeled as l-CPSSE) with artificially organized layered microstructures by proposing an in situ ice-templating strategy upon the cement hydration, in which the layered micropores are further filled with fast-ion-conducting hydrogels and serve as ion diffusion highways. With these merits, the obtained l-CPSSE not only presents marked specific bending and compressive strength (2.2 and 1.2 times that of traditional cement, respectively) but also exhibits excellent ionic conductivity (27.8 mS·cm−1), overwhelming most previously reported cement-based and hydrogel-based electrolytes. As a proof-of-concept demonstration, we assemble the l-CPSSE electrolytes with cement-based electrodes to achieve all-cement-based solid-state energy storage devices, delivering an outstanding full-cell specific capacity of 72.2 mF·cm−2. More importantly, a 5 × 5 cm2 sized building model is successfully fabricated and operated by connecting 4 l-CPSSE-based full cells in series, showcasing its great potential in self-energy-storage buildings. This work provides a general methodology for preparing revolutionary cement-based electrolytes and may pave the way for achieving zero-carbon buildings.

Filamentous algae blooms (FABs) have been increasing globally in recent years, and their presence can have both harmful and beneficial effects on aquatic ecosystems. As one of the most common FABs, Cladophora blooms have been reported in the lakes of the Qinghai-Tibet Plateau during the past few years. However, there have been few studies focused on how FABs impact other aquatic organisms, especially in alpine lakes since these are at the forefront of responding to global climate change. In this study, the phytoplankton communities in different regions of Qinghai Lake were profiled in different seasons using meta-barcode sequencing. The phytoplankton assemblages in areas with Cladophora blooms were compared to those without Cladophora. The phytoplankton community structure correlated with physicochemical properties including water temperature, electrical conductivity, nitrate, and the presence or absence of Cladophora blooms. The relative abundance of Bacillariophytes was found to be higher in zones with Cladophora blooms than in other regions. Significant seasonal changes in phytoplankton biomass and β diversity were observed in zones with Cladophora blooms. Growth and microbial degradation of Cladophora can change the pH, dissolved oxygen, secchi depth, and nitrate. Together with seasonal temperature and electrical conductivity changes, Cladophora growth can significantly impact the phytoplankton biomass, community dissimilarity and assembly process. These results showed that Cladophora plays a key role in littoral aquatic ecosystem ecology.

BackgroundAs a typical self-paced brain–computer interface (BCI) system, the motor imagery (MI) BCI has been widely applied in fields such as robot control, stroke rehabilitation, and assistance for patients with stroke or spinal cord injury. Many studies have focused on the traditional spatial filters obtained through the common spatial pattern (CSP) method. However, the CSP method can only obtain fixed spatial filters for specific input signals. In addition, the CSP method only focuses on the variance difference of two types of electroencephalogram (EEG) signals, so the decoding ability of EEG signals is limited.MethodsTo make up for these deficiencies, this study introduces a novel spatial filter-solving paradigm named adaptive spatial pattern (ASP), which aims to minimize the energy intra-class matrix and maximize the inter-class matrix of MI-EEG after spatial filtering. The filter bank adaptive and common spatial pattern (FBACSP), our proposed method for MI-EEG decoding, amalgamates ASP spatial filters with CSP features across multiple frequency bands. Through a dual-stage feature selection strategy, it employs the Particle Swarm Optimization algorithm for spatial filter optimization, surpassing traditional CSP approaches in MI classification. To streamline feature sets and enhance recognition efficiency, it first prunes CSP features in each frequency band using mutual information, followed by merging these with ASP features.ResultsComparative experiments are conducted on two public datasets (2a and 2b) from BCI competition IV, which show the outstanding average recognition accuracy of FBACSP. The classification accuracy of the proposed method has reached 74.61 and 81.19% on datasets 2a and 2b, respectively. Compared with the baseline algorithm, filter bank common spatial pattern (FBCSP), the proposed algorithm improves by 11.44 and 7.11% on two datasets, respectively (p

BackgroundIncreasing age is a significant risk factor for atrial fibrillation (AF) recurrence after catheter ablation (CA). We accomplished this study to evaluate the efficacy and safety of the vein of Marshall (VOM) ethanol infusion (VOM-EI) with CA in elderly patients with persistent AF (PsAF).MethodsThis retrospective observational study included 360 consecutive adult patients with PsAF, of which 141 were in the Elder group (age ≥65 years) and 219 were in the Younger group (age

On 19 September 2022, a major earthquake struck the northwestern Michoacán segment along the Mexican subduction zone. A slip model is obtained that satisfactorily explains geodetic, teleseismic, and tsunami observations of the 2022 event. The preferred model has a compact large‐slip patch that extends up‐dip and northwestward from the hypocenter and directly overlaps a 1973 Mw 7.6 rupture. Slip is concentrated offshore and below the coast at depths from 10 to 30 km with a peak value of ∼2.9 m, and there is no detected coseismic slip near the trench. The total seismic moment is 3.1 × 10^20 N·m (Mw 7.6), 72% of which is concentrated in the first 30 s. Most aftershocks are distributed in an up‐dip area of the mainshock that has small coseismic slip, suggesting near‐complete strain release in the large‐slip patch. Teleseismic P waveforms of the 2022 and 1973 earthquakes are similar in duration and complexity with high cross‐correlation coefficients of 0.68–0.98 for long P to PP signal time windows, indicating that the 2022 earthquake is a quasi‐repeat of the 1973 earthquake, possibly indicating persistent frictional properties. Both the events produced more complex P waveforms than comparable size events along Guerrero and Oaxaca, reflecting differences in patchy locking of the Mexican megathrust.

In recent years, the open and standardized interfaces for radio access networks (Open RAN), promoted by the standard organization O-RAN alliance, demonstrate the potential to apply artificial intelligence in 6G networks. Among O-RAN, the newly introduced radio intelligence controller (RIC), including near-real-time RIC and non-real-time RIC, provides intelligent control of the radio network. However, existing research on RIC only focuses on the implementation of interfaces and progress, while ignoring the resource allocation between near-RT RIC and non-RT RIC which is essential for ultra-low latency in 6G networks. In this paper, we propose a reinforcement learning-based resource allocation scheme that minimizes service latency by optimizing requests allocated and processed between near-RT RIC and non-RT RIC. Specifically, we aim at improving the request acceptance and minimum the average service latency, in our policy, we apply the Double DQN to decide whether the requests are processed at near-RT RIC or non-RT RIC and then allocate the near-RT RIC resource to finish the requests. Firstly, we define and formulate the resource allocation problem in RIC by the Markov decision process framework. Then we propose an allocation scheme based on the Double Deep Q network technique (Double DQN), with two variations (Double DQN with cache and Double DQN without cache) for handling different request types. Extensive simulations demonstrate the effectiveness of the proposed method in offering the maximum reward. Additionally, we conduct experiments to analyze the updating of cached AI models and the results show that the performance of the proposed method is always optimal compared to other algorithms in terms of latency and accepted number of requests.

Abstract Active government intervention is a striking characteristic of the Chinese stock market. This study develops a behavioral heterogeneous agent model (HAM) comprising fundamentalists, chartists, and stabilizers to investigate investors’ dynamic switching mechanisms under government intervention. The model introduces a new player, the stabilizer, into the HAM as a proxy for the government. We use the model to examine government programs during the 2015 China stock market crash and find that it can replicate the dynamics of investor sentiment and asset prices. In addition, our analysis of two simulations, specifically the data-generating processes and shock response analysis, further corroborates the key conclusion that our intervention model not only maintains market stability but also promotes the return of risk asset prices to their fundamental values. The study concludes that government interventions guided by the new HAM can alleviate the dilemma between reducing price volatility and improving price efficiency in future intervention programs.

Purpose – The purpose of this paper is to design a unified operational design domain (ODD) monitoring framework for mitigating Safety of the Intended Functionality (SOTIF) risks triggered by vehicles exceeding ODD boundaries in complex traffic scenarios. Design/methodology/approach – A unified model of ODD monitoring is constructed, which consists of three modules: weather condition monitoring for unusual weather conditions, such as rain, snow and fog; vehicle behavior monitoring for abnormal vehicle behavior, such as traffic rule violations; and road condition monitoring for abnormal road conditions, such as road defects, unexpected obstacles and slippery roads. Additionally, the applications of the proposed unified ODD monitoring framework are demonstrated. The practicability and effectiveness of the proposed unified ODD monitoring framework for mitigating SOTIF risk are verified in the applications. Findings – First, the application of weather condition monitoring demonstrates that the autonomous vehicle can make a safe decision based on the performance degradation of Lidar on rainy days using the proposed monitoring framework. Second, the application of vehicle behavior monitoring demonstrates that the autonomous vehicle can properly adhere to traffic rules using the proposed monitoring framework. Third, the application of road condition monitoring demonstrates that the proposed unified ODD monitoring framework enables the ego vehicle to successfully monitor and avoid road defects. Originality/value – The value of this paper is that the proposed unified ODD monitoring framework establishes a new foundation for monitoring and mitigating SOTIF risks in complex traffic environments.

Under the background of insufficient scientific research funding, evaluating the level of scientific research from the perspective of sustainable development is necessary. The study aims to develop an evaluation index system based on the theories for sustainable competitive advantage (SCA), which could be used to evaluate the sustainable development trend of scientific research in universities. In this study, 42 world-class universities in China are used as examples to calculate their SCA performance in scientific research using the entropy and equal weights methods. The scores of scientific research in different universities in the Academic Ranking of World Universities (ARWU) in 2021 are used to verify the effectiveness of the evaluation index system. The results show that the evaluation index system can effectively predict the scientific research performance of universities in the future. It could be deduced from the results that universities with better scientific research performance meet the needs of the external market better and have more valuable, rare, imitable, and ambiguous resources but a lower level of scientific research dynamic ability. The evaluation index system makes up for the lack of emphasis on the potential scientific research capacity of the university in the current evaluation methods. It can help university administrators formulate relevant scientific research management regulations.

Ipomoea batatas polysaccharides (IBPs) have many important physiological functions. The optimal extraction conditions were extraction time of 40 min, solid–liquid ratio of 1:8 and ultrasonic power of 240 W. 1D/2D nuclear magnetic resonance (1D/2D NMR) analysis showed that the main chain of IBP-1A was mainly composed of →4)-α-D-Glcp-(1→ and →3, 6)-β-D-Glcp-(1→ residues. In vivo experiments showed that polysaccharide significantly increased the levels of antioxidation-related enzymes and metabolites in older mice. It could significantly relieve oxidative stress injury and delay aging. Therefore, this study provided a new theoretical basis for the development of IBPs as antioxidant food.

Abstract Sudden and uncertain events often cause cross-contagion of risk among various sectors of the macroeconomy. This paper introduces the stochastic volatility shock that follows a thick-tailed Student’s t-distribution into a high-order approximate dynamic stochastic general equilibrium (DSGE) model with Epstein–Zin preference to better analyze the dynamic effect of uncertainty risk on macroeconomics. Then, the high-dimensional DSGE model (DSGE-SV-t) is developed to examine the impact of uncertainty risk on the transmission mechanism among macroeconomic sectors. The empirical research found that uncertainty risk generates heterogeneous impacts on macroeconomic dynamics under different inflation levels and economic states. Among them, a technological shock has the strongest impact on employment and consumption channels. The crowding-out effect of a fiscal policy stimulus on consumption and private investments is relatively weakened when considering uncertainty risk but is more pronounced during periods of high inflation. Uncertainty risk can partly explain the decline in investments and the increase in interest rates and employment rates, given the impact of an agent’s risk preferences. Compared with external economic conditions, the inflation factor has a stronger impact on the macro transmission mechanism caused by uncertainty risk.

[Introduction] Using nuclear fusion to generate electricity is a promising way for nuclear energy in the future. In order to research the best civil structure design, it is necessary to discuss techniques from fossil fuel power plant and conventional island of other NPPs. [Method] Through comparation analysis, structure system of main building, roof structure, TG foundation and fire protection design were discussed. [Result] Conceptual design for civil structure and engineering advice are also given. [Conclusion] The research in this paper can provide reference for similar project.

Antitumor, antioxidant, hypoglycemic, and immunomodulatory properties are all exhibited by maize polysaccharides. With the increasing sophistication of maize polysaccharide extraction methods, enzymatic method is no longer limited to a single enzyme to extract polysaccharides, and is more often used in combination with ultrasound or microwave, or combination with different enzymes. Ultrasound has a good cell wall-breaking effect, making it easier to dislodge lignin and hemicellulose from the cellulose surface of the maize husk. The “water extraction and alcohol precipitation” method is the simplest but most resource- and time-consuming process. However, the “ultrasound-assisted extraction” and “microwave-assisted extraction” methods not only compensate for the shortcoming, but also increase the extraction rate. Herein, the preparation, structural analysis, and activities of maize polysaccharides were analyzed and discussed.

The maidenhairtree polysaccharides (MTPs) have important application prospects. So, the extraction, purification, structure, derivatization and biological activities of polysaccharides from leaves, fruits, and testae of maidenhairtree were disscussed. Polysaccharides were extracted by collaborative extraction methods such as ultrasound-assisted extraction and microwave-assisted extraction. The ultrasound-assisted extraction had higher content and higher efficiency. The structural characteristics and structure-activity relationship of maidenhairtree polysaccharides were studied in order to provide theoretical basis and technical support for the further development and utilization of maidenhairtree polysaccharides.

For studying the traffic safety of the high-speed railway, this research considers high-quality second-level wind speed data as its basis. However, the quality of second-level wind speed data can be greatly lowered by disturbances during data collection and storage. Therefore, it is crucial to control the data quality during collection and storage. Wind speed data along the high-speed railway are unstable and non-linear. In order to adapt to this characteristic, this study combines a convolutional neural network (CNN), long short-term memory (LSTM), and isolated forest from the time dimension to form a quality control (QC) algorithm for wind speed monitoring data. First, CNN is used to extract the original data features, which are then transferred to the LSTM network for one-step prediction. The prediction residual of the model is obtained and sent to the isolated forest, where the abnormal value position in the original wind speed data is calibrated by detecting the abnormal value position in the prediction residual. Comparative experiments have been conducted to test the performances of the three different QC methods. The results show that the error detection rate of CNN–LSTM–IF in this research method is approximately 0.95. For different terrains and seasons, the method has certain robustness and generalization.

Financial literacy has become increasingly crucial in today’s complex financial markets. This paper explores the impact of financial literacy on the stock market by establishing an artificial financial market that aligns with the characteristics of the Chinese A-share market using agent-based modeling. The study incorporates financial literacy into investors’ mixed beliefs and simulates their behavior in the market. The results show that improving individual investors’ financial literacy can improve market quality and investor performance, as well as reduce the unequal distribution of wealth to some extent. However, the phenomenon of speculative trading and irrational behavior in the market can pose potential risks that require regulatory measures. Thus, policy recommendations to improve individual investors’ financial literacy and establish corresponding regulatory measures are proposed.

This study aims to fabricate zein-based colloidal nanoparticles, which were used to stabilize Pickering emulsions, by conjugation with soybean polysaccharide (SSPS) through the Maillard reaction. The physicochemical properties of the conjugated particles as well as the physical and oxidative stability of the fabricated Pickering emulsion that utilized conjugated colloidal particles with the volumetric ratio of water and oil at 50:50 were investigated. The grafting degree of zein and SSPS was verified through examination of FT-IR and fluorescence. Moreover, the conjugated Zein/SSPS nanoparticles (ZSP) that were prepared after dry heating for 48–72 h exhibit excellent colloidal stability across a range of pH values (4.0–10.0). Further, the wettability of ZSP decreased based on a contact angle analysis of θ~87°. Confocal laser scanning microscopy (CLSM) images indicated that ZSP particles were located around the oil droplets. Additionally, the ZSP effectively improved the oxidative stability of the Pickering emulsions, as demonstrated by a significant decrease in both peroxide value (PV) and thiobarbituric acid reactive substances (TBARS). The results of this study demonstrate that ZSP represents a promising food-grade Pickering emulsifier, capable of not only stabilizing emulsions but also inhibiting their oil oxidation.

Given a pair of bitemporal very high resolution (VHR) remote sensing images, the semantic change detection task aims to locate land surface changes and identify their semantic classes. The existing algorithms use independent branches to locate and identify separately without considering the association between branches. In this article, we propose an end-to-end spatially and semantically enhanced Siamese network (SSESN) for semantic change detection. The SSESN aggregates the rich spatial and semantic information in the VHR image through a designed spatial and semantic feature aggregation module. Additionally, a change-aware module is proposed to decouple the aggregated features. Features in the binary branch are fused to the semantic branches as prior location information. This allows the spatially enhanced features to predict changed regions and the semantically enhanced features to refine the region categorizations. Experimental results show that our method provides comparable results with the state-of-the-art binary change detection and semantic change detection algorithms.

The currency market is one of the most important financial markets in the world. The exchange rate movement has effect on international trade and capital flow. This study presents a forecasting method for exchange rate based on multi-modal combination market trend. The method facilitates the more accurate identification of volatility link between exchange rates, unlike the conventional ones, in which only information related to itself is used as input. We select multiple characteristics of the exchange rate from other countries as input data. Then the Pearson correlation coefficient and random forest model are used to filter these characteristics We integrate the data with higher correlation into the temporal convolutional network model to forecast the exchange rate. For the empirical samples, a nine-year period historical exchange rates of the Euro, Ruble, Australian dollar, and British pound corresponding to the Renminbi are used. The empirical results show the more stable effect using the forecasting method proposed in this study than the traditional models.

Due to the huge economic value of combustible natural gas, the kinetic energy generated by gas flowing from underground to the earth’s surface is often ignored in the production process. Based on the existing oil field production data when integrated with geological, geophysical and geochemical theory, we present initial research on the feasibility of utilizing a significant and hitherto unexploited new energy source — geostress energy. This is the energy associated with the enormous geostress to discharges the natural gas (including combustible gas and non-combustible gas) from the rock pores to the earth’s surface, so that the abundant underground natural gas becomes the geostress energy carrier. Through the analysis of oil field production data, we find that vast geostress energy exists not only in high pressure self-spouting wells, but also in some abandoned wells. Then, we are able to establish that the available geostress energy is enormous in the world from estimation of the top 10 natural gas producing countries. Finally, since the utility of such a new type energy is still under the initial developing stage, we outline the future research tasks and summarize the main challenges to achieve widespread use of the geostress energy and make a sizable great contribution to reducing the exploitation of fossil energy, solving environmental pollution problems and achieving carbon neutrality.

This paper examines how independent directors’ social capital, as measured by their social network, affects corporate fraud. We find that firms with well-connected independent directors are less likely to commit fraud, supporting our monitoring effect hypothesis. This result is robust to a battery of tests. Further analyses show that the effect is stronger for firms with a relatively poor legal environment, for firms whose independent directors face strong reputation incentives and when independent directors are audit committee members. Moreover, we explore a potential economic mechanism of the effect and observe that well-connected independent directors are associated with less absenteeism and more dissension. Overall, our findings suggest that independent directors’ social capital plays an important role in corporate governance.

Abstract We propose an empirical behavioral order-driven (EBOD) model with price limit rules, which consists of an order placement process and an order cancellation process. All the ingredients of the model are determined based on the empirical microscopic regularities in the order flows of stocks traded on the Shenzhen Stock Exchange. The model can reproduce the main stylized facts in real markets. Computational experiments unveil that asymmetric setting of price limits will cause the stock price to diverge exponentially when the up price limit is higher than the down price limit and to vanish vice versa. We also find that asymmetric price limits have little influence on the correlation structure of the return series and the volatility series, but cause remarkable changes in the average returns and the tail exponents of returns. Our EBOD model provides a suitable computational experiment platform for academics, market participants, and policy makers.

Following the 2008 financial crisis, multiple studies have contributed to the research on stock price crashes. However, most of the studies on stock price crashes are from the corporate management perspective, focusing on factors such as the board’s character, the CEO’s power, the brand’s capital, and ESG performance. Few studies have taken external information, such as media coverage, into consideration. Meanwhile, in the era of 5G, internet media has witnessed exponential growth, heavily enhancing the speed of information transmission; this could possibly impact the future risk associated with stock price crashes. From this perspective, our study extends the coverage by investigating the relationship between internet media coverage and the potential risk of stock price crashes. Using a comprehensive dataset of the Chinese stock market from 2008 to 2021, we found that the optimistic (pessimistic) tones of internet media were positively (negatively) correlated with the future risk of crashes. These findings remained firm after accounting for winsorization, corporate governance control, firm fixed effects, and instrumental variable analysis. Further analyses showed that media tone impacts were more pronounced for firms with higher analyst coverage. Our study indicates that investors, especially retail investors, who are more easily influenced by internet media, should be more cautious about the increasingly favorable internet coverage of listed companies, which could result in a heightened future risk of stock price crashes. Moreover, regulators should inform investors when listed companies are experiencing more favorable internet coverage to minimize potential stock market fluctuations and investment losses for investors.

Apple canker disease, caused by Valsa mali, is one of the most serious apple tree diseases in China. VmSom1 is an important transcription factor that acts on the cyclic adenosine signaling pathway (cAMP/PKA), regulating the growth, development, morphological differentiation, and pathogenic forces of the pathogen. We perform transcriptome analysis of the VmSom1 deletion mutant and the wild-type strain 11-175 and identify a significantly differentially expressed gene, VM1G_06867, a zinc finger motif transcription factor in V. mali. In this study, we obtain the VM1G_06867 gene using the single deletion mutant via homologous recombination. To determine the relationship between VmSom1 and VM1G_06867, we also obtain a double deletion mutant ΔVmSom1/06867. Compared to the wild-type strain 11-175, the single deletion mutant VM1G_06867 shows a drastic reduction in growth rate and forms more pycnidia on the PDA medium. Additionally, the growth of the mutant is inhibited by SDS, Congo red, and fluorescent brighteners. In comparison to the single deletion mutant VmSom1, the double deletion mutant ΔVmSom1/06867 shows no significant change in growth or conidiation and is unable to produce conidia. The growth rate is significantly increased in Congo red, NaCl, and Sorbitol mediums. These results demonstrate that VM1G_06867 plays important roles in growth, pathogenicity, asexual development, and maintenance of cell wall integrity. VM1G_06867 can recover osmotic stress and cell wall integrity defects caused by the deletion of VmSom1, as well as restore the loss of pathogenicity caused by the deletion of the VmSom1 gene, but not completely.

Microplastic pollution has become an increasingly important environmental issue worldwide in recent years because of its ubiquitous presence in different environmental media and its potential to affect the health of organisms and ecosystems. Aquaculture contributes significantly to the world's food production and nutritional supply, especially in developing countries. Widespread occurrence of microplastics in aquaculture systems has raised great concern regarding aquaculture production and food safety issues of aquaculture products. China is a world leader in aquaculture production, with freshwater aquaculture accounting for 59.1% of total aquaculture production of the world in 2020. Therefore, this review mainly focuses on recent research progress related to microplastic pollution in freshwater aquaculture systems in China. Results from the literature show that microplastics are present in freshwater aquaculture systems at abundances comparable to natural waterbodies in China. Microplastics can be ingested and remain in the body of aquaculture products. Exposure to microplastics can adversely affect the health of aquatic organisms and aquatic ecosystem functions. However, risks of microplastics in real world environment remain uncertain. Consumption of freshwater aquaculture products is not a major pathway for human exposure to microplastics. To provide scientific guidance for governmental decision-making and pollution control, future work should focus on progress in toxicological methodology and understanding the impacts of microplastics at community and ecosystem levels.

Rapid development of aquaculture industry and increasing demand of various inputs (especially antibiotics), are suspected to promote the occurrence and spread of ARGs in aquaculture related environments. However, the occurrences of ARGs under different freshwater aquaculture practices are rarely known. Here, we investigated the seasonal profiles of the main ARGs, intI1 and bacteria in waters from three kinds of predominant freshwater aquaculture practices around the Honghu Lake (China), as well as their co-occurrences and interrelationships with antibiotics, heavy metals and general water quality. The results indicate that quinolone resistance genes (qnrB), tetracycline resistance genes (tetB and tetX) and sulfonamide resistance genes (sul1 and sul2) were the top five predominant ARGs with seasonal variations of abundance. Fish ponds were of the highest absolute abundances of tested ARGs than the other two modes. Crayfish ponds and their adjacent ditches shared similar ARGs profile. Different subtypes of ARGs belonging to the same class of resistance were varied in abundances. Some bacteria were predicted to carry different ARGs, which indicating multi-antibiotic resistances. Moreover, the combined environmental factors (antibiotics, heavy metals and water quality) partially shaped the profiles of ARGs and bacteria composition. Overall, this study provides new comprehensive understanding on the characterization of ARGs contamination in different freshwater aquaculture practices from the perspectives of environmental chemistry, microbiology and ecology. The results would benefit the optimization of aquaculture practices toward environmental integrity and sustainability.

Loop-mediated isothermal amplification (LAMP) is often confounded by the non-specific amplification arising from primer dimers, off-target priming, and other artifacts. Precipitation of the DNA produced during LAMP with the use of specific fluorescently labeled probe has proved the effectiveness in specific detection. Herein, two fluorophores (ROX and FAM) were attached to the primers S-LB-6 and R-FIP for Atlantic salmon and rainbow trout, respectively, which are self-quenched in unbound state and become de-quenched after binding to the dumbbell-shaped DNA specifically. The DNA precipitation and appearance of small sediment took 10 s of centrifugation at 1000 g, by adding polyethylenimine (PEI) 600. Each target species was specifically amplified with the predicted color of PEI-DNA sediment, namely red for Atlantic salmon, green for rainbow trout, and pale yellow for mixed species. The optimized duplex LAMP system has proved its specificity and can detect as little as 1 ng DNA in visual detection.

Littoral zones in oligotrophic lakes play an essential role in supporting animal consumers and in the exchange of matter between the water body and the terrestrial sources, but are easily altered by changes in water level. We studied Qinghai Lake, a deep oligotrophic lake in northwest China, where lake water level has increased rapidly in recent years, altering the character of the littoral zones. We sampled common organisms and used stable carbon and nitrogen isotope analyses to compare how contributions of different sources (allochthonous and autochthonous) to the diets of consumers differed between sand (original habitat, OH) and submerged grassland (new habitat, NH) substrate habitat conditions. Our results showed that allochthonous resources (i.e., terrestrial detritus) constituted the largest diet proportion of consumers in OH due to poor nutrient conditions, while consumers in NH utilized more autochthonous resources (i.e., Cladophora and phytoplankton). We also found that terrestrial nutrient subsidies from soil and decomposed grass led to increased biomasses of Cladophora, phytoplankton, zooplankton and zoobenthos in NH compared to those in OH, accounting for autochthonous replacement of part of the allochthonous resources in NH. Therefore, hydrological conditions may alter the trophic interactions within littoral food webs, contributing to a more complex and interconnected food web. Overall, our results suggest that the littoral food webs of Qinghai Lake are vulnerable to changes in hydrological conditions, which may be enhanced by climate change.

Abstract Background The outcomes for volar locking plate (VLP) and external fixation (EF) in distal radius fracture cases remain controversial. The current study of randomized controlled trials (RCTs) aimed to assess VLP and EF, which might benefit distal radius fracture cases. Methods RCTs comparing VLP and EF in distal radius fracture cases, until 18 March 2020, were systematically reviewed and summarized. The functional and radiographic outcomes, together with complications, for distal radius fracture cases, were evaluated. Results In total, 12 studies comprising 1205 distal radius fracture cases were included. The VLP group had observed lower disability in the arm shoulder and hand score (DASH) at 3rd, 6th, and 12th -month post-operation, with the mean differences (MDs) of − 10.43 (95 % CI = − 15.77 to − 5.08, P 0.05). The VLP group had a lower complication rate than that in the EF group. Conclusions VLP had a lower DASH score and VAS score but with lower grip strength. No significant differences in radiographic outcomes were observed. VLP had a lower complication rate than that of EF.

Abstract This paper investigates the impact of economic policy uncertainty (EPU) on the crash risk of US stock market during the COVID-19 pandemic. To this end, we use the GARCH-S (GARCH with skewness) model to estimate daily skewness as a proxy for the stock market crash risk. The empirical results show the significantly negative correlation between EPU and stock market crash risk, indicating the aggravation of EPU increase the crash risk. Moreover, the negative correlation gets stronger after the global COVID-19 outbreak, which shows the crash risk of the US stock market will be more affected by EPU during the epidemic.

Carbon catabolite repression (CCR) is a very important mechanism for efficient use of carbon sources in the environment and is necessary for the regulation of fungal growth, development, and pathogenesis. Although there have been extensive studies conducted regarding this mechanism in fungi, little is yet known about the effects of CreA genes on Valsa mali. However, based on the results obtained in this study for the identification of the VmCreA gene in V. mali, it was determined that the gene was expressed at all stages of fungal growth, with self-repression observed at the transcriptional level. Furthermore, the functional analysis results of the gene deletion mutants (ΔVmCreA) and complements (CTΔVmCreA) showed that the VmCreA gene played an important role in the growth, development, pathogenicity, and carbon source utilization of V. mali.

While Cas9 outperforms TALENs in euchromatin, it is less efficient in heterochromatic regions. Here the authors, using single-molecule imaging, show that Cas9 uses a less efficient search strategy compared to TALENs in these regions.

The improvement of wind power prediction accuracy is beneficial to the effective utilization of wind energy. An improved XGBoost algorithm via Bayesian hyperparameter optimization (BH-XGBoost method) was proposed in this article, which is employed to forecast the short-term wind power for wind farms. Compared to the XGBoost, SVM, KELM, and LSTM, the results indicate that BH-XGBoost outperforms other methods in all the cases. The BH-XGBoost method could yield a more minor estimated error than the other methods, especially in the cases of wind ramp events caused by extreme weather conditions and low wind speed range. The comparison results led to the recommendation that the BH-XGBoost method is an effective method to forecast the short-term wind power for wind farms.

Osteochondral defects include the damage of cartilage and subchondral bone, which are still clinical challenges. The general replacements are difficult to simultaneously repair cartilage and subchondral bone due to their various requirements. Moreover, appropriate printable bioactive materials were needed for 3D bioprinting personalized scaffolds for osteochondral repairing. Herein, the novel hydrogel was developed by hybridizing the alginate sodium (SA) and gellan gum (GG) with the inorganic thixotropic magnesium phosphate-based gel (TMP-BG) in the pre-crosslinking of Mg2+ to enhance osteochondral repairing. SA-GG/TMP-BG hybrid hydrogels possessed controllable rheological, injectable, mechanical properties and porosities by tuning their ratio. The shear-thinning of SA-GG/TMP-BG was responsible for its excellent injectability. SA-GG/TMP-BG hybrid hydrogels displayed good cell compatibility, on which MG-63 and BMSCs cells attached and spread well with the high proliferation and up-regulated osteogenic genes. In addition, the inorganic TMP-BG gel hybridized with SA-GG hydrogel released Mg2+ was conducive to recruiting BMSCs and promoting the osteogenic and chondrogenic differentiation of BMSCs. Histological results confirmed that SA-GG/TMP6040 significantly promoted the osteogenesis of subchondral bone and then further facilitated the cartilage repairing after being implanted in osteochondral defects of rabbits for 6 and 12 weeks.Our finding revealed that the inorganic TMP-BG endowed the excellent osteogenic activity of the hybrid hydrogels, which played a key role in successful osteochondral repairing. The newly SA-GG/TMP-BG hybrid hydrogels appeared to be promising materials for osteochondral repairing and the further 3D bioprinting.

Summary: Two-dimensional van der Waals materials offer various possibilities for synaptic devices, matching the requirements of intelligent and energy-efficient computation. However, very few studies on robust flexible synaptic transistors have been reported, which hold great potential for soft robotics and wearable applications. Here a floating gate synaptic device based on ambipolar black phosphorus (BP) on a flexible substrate has been demonstrated with two working modes. The three-terminal mode, where the carriers are injected into the floating gate, shows a nonvolatile memory effect, whereas the two-terminal mode shows a quasi-nonvolatile memory effect. Remarkably, the synaptic device working on the three-terminal mode shows an excellent performance in the energy-efficient computation of sub-fJ/spike with a fast gate voltage response down to ∼10 ns. Furthermore, the flexible synaptic device exhibits good endurance under 5,000 bending cycles with a strain of ∼0.63%, suggesting great potential in flexible neuromorphic applications with low energy consumption.

Abstract With the introduction of many derivatives into the capital market, including stock index futures, the trading strategies in financial markets have been gradually enriched. However, there is still no theoretical model that can determine whether these strategies are effective, what the risks are, and how costly the strategies are. We built an agent-based cross-market platform that includes five stocks and one stock index future, and constructed an evaluation system for stock index futures trading strategies. The evaluation system includes four dimensions: effectiveness, risk, occupation of capital, and impact cost. The results show that the informed strategy performs well in all aspects. The risk of the technical strategy is relatively higher than that of the other strategies. Moreover, occupation of capital and impact cost are both higher for the arbitrage strategy. Finally, the wealth of noise traders is almost lost.

Botryosphaeriaceae, as a major family of the largest class of kingdom fungi Dothideomycetes, encompasses phytopathogens, saprobes, and endophytes. Many members of this family are opportunistic phytopathogens with a wide host range and worldwide geographical distribution, and can infect many economically important plants, including food crops and raw material plants for biofuel production. To date, however, little is known about the family evolutionary characterization, mating strategies, and pathogenicity-related genes variation from a comparative genome perspective. Here, we conducted a large-scale whole-genome comparison of 271 Dothideomycetes, including 19 species in Botryosphaeriaceae. The comparative genome analysis provided a clear classification of Botryosphaeriaceae in Dothideomycetes and indicated that the evolution of lifestyle within Dothideomycetes underwent four major transitions from non-phytopathogenic to phytopathogenic. Mating strategies analysis demonstrated that at least 3 transitions were found within Botryosphaeriaceae from heterothallism to homothallism. Additionally, pathogenicity-related genes contents in different genera varied greatly, indicative of genus-lineage expansion within Botryosphaeriaceae. These findings shed new light on evolutionary traits, mating strategies and pathogenicity-related genes variation of Botryosphaeriaceae.

Since the period of unusual volatility in China’s A-share market in 2015, there has been an ongoing discussion about the role of stock index futures in the A-share market. There is no unified consensus among academics and industry insiders on whether stock index futures affect spot market volatility. Using agent-based modeling, we construct a theoretical model of the order book of the stock index futures market to assess the microbehavior of speculators, arbitrageurs, and hedgers in this market. We then calibrate the link between the futures and spot models to explore the respective influences of heterogeneous investors in the two markets. We find that speculators, arbitrageurs, and hedgers all play different roles and have varying effects on the two markets. While speculators serve as the foundation for other investors to participate in trading activities, both arbitrageurs and hedgers affect the spot market by significantly reducing volatility, enhancing price efficiency, and playing a positive role in the operation of this market. We develop our model from the perspective of investor behavior and explain why the stock index futures market can reduce spot market volatility. In addition, our conclusion may help regulators understand the roles played by different types of investors in the Chinese stock index futures market.

AbstractDue to diverse mineral composition and complex lithology, mixed shale oil reservoir wettability features and the associated controlling factors remain unclear, limiting the evaluation of the oil-bearing property and sweet spot distribution. This paper examined mixed shale oil samples from the Jimusar Sag in the Lucaogou Formation. Casting thin sections, X-ray diffraction, geochemical characteristics, argon ion polishing scanning electron microscope, and high pressure mercury injection were used to analyze lithologic characteristics, mineral compositions, and pore-throat structures within the mixed shale oil reservoir. Using spontaneous imbibition and nuclear magnetic resonance, the wettability characteristics were analyzed. Impacts of organic matter abundance, mineral composition, pore-throat structure, and source-reservoir combination on wettability were discussed. The Lucaogou mixed shale oil reservoir primarily contains intergranular dissolved pores, intragranular dissolved pores, and intercrystalline pores. Three types of mercury intrusion cures were observed, including a weak platform shape (type I), gentle straight line shape (type II), and upward convex shape (type III), corresponding to intergranular, dissolved, and dissolved-intercrystalline dominant pore-throat systems, respectively. Mixed shale oil reservoirs show dual wet properties, containing both oil-wet and water-wet pores. Oil-wet pores (large pores with T2>1 ms) are more common and have better connectivity than water-wet pores (small pores with T2

This article aims to reveal the factors that affecting the impact of international collaboration papers in the field of social sciences and humanities. Based on resource-based theory and transaction cost theory, we analyzed the articles from a sample of 13,331 listed research papers come from the 42 world class universities in China using descriptive statistics, ordinary least square (OLS) regression, and came to the following conclusions: First, it is the quality rather than the quantity of international collaborator that affect the academic influence of the research outputs. Second, researchers from different backgrounds are conducive to improve the impact of research papers and the collaboration leading by Chinese university perform better. Yet, too much collaborators coming from different institutions would have an adverse impact, which may due to the increase cost of cooperation. Finally, collaborating researchers from developed countries or top universities will significantly improve the research performance because of the abundant resources behind them. Findings from this research suggest that setting up international collaboration should pay more attention to the level of the collaborator and consider the cost behind the whole process.