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This article develops an efficient fully discrete scheme for a stochastic strongly damped wave equation (SSDWE) driven by an additive noise and presents its error estimates in the strong sense. We use the truncated spectral expansion of the noise to get an approximate equation and prove its regularity. Then we establish a spatio‐temporal discretization of the approximate equation by a finite element method in space and an exponential trapezoidal scheme in time. We prove that the combination can derive higher strong convergence order in time than the use of the piecewise approximation of the noise and the exponential Euler scheme or the implicit Euler scheme in time. Particularly, the temporal strong convergence order of the fully discrete scheme reaches 5/4−ε$$ 5/4-\varepsilon $$ for the one‐dimensional space‐time white noise, which overcomes the order barrier one. Moreover, we allow the covariance operator of the noise to be noncommutative with the Dirichlet Laplacian, which weakens the common assumptions on the noise in the literature. Finally, some numerical experiments in different spatial dimensions are presented to support our theoretical findings. By means of the piecewise spectral approximation of the noise, a piecewise version of the fully discrete scheme is constructed to fulfill a long‐time simulation. [ABSTRACT FROM AUTHOR]

This article presents a vibration model of neighboring rolling parts that takes into account non-smooth symmetric collisions. This model was used to examine the motion state of the rolling element and the collision force between nearby rolling elements. It also determined the motion posture and overall collision form of the rolling element after setting the functional slot. Afterwards, the level of disorderly movement and the structure of the moving object were examined and confirmed through the use of a phase diagram of the motion system in relation to zero symmetry, the Lyapunov exponent, and a platform for measuring irregular vibrations in the bearing. This work aims to clarify the factors that contribute to the persistent chaotic state of rolling elements in bearing vibration. [ABSTRACT FROM AUTHOR]

Multiple regulatory mechanisms are in place to ensure the normal processes of bone metabolism, encompassing both bone formation and absorption. This study has identified chaperone‐mediated autophagy (CMA) as a critical regulator that safeguards bone formation from the detrimental effects of excessive inflammation. By silencing LAMP2A or HSCA8, we observed a hindrance in the osteoblast differentiation of human bone marrow mesenchymal stem cells (hBMSCs) in vitro. To further elucidate the role of LAMP2A, we generated LAMP2A gene knockdown and overexpression of mouse BMSCs (mBMSCs) using adenovirus. Our results showed that LAMP2A knockdown led to a decrease in osteogenic‐specific proteins, while LAMP2A overexpression favored the osteogenesis of mBMSCs. Notably, active‐β‐catenin levels were upregulated by LAMP2A overexpression. Furthermore, we found that LAMP2A overexpression effectively protected the osteogenesis of mBMSCs from TNF‐α, through the PI3K/AKT/GSK3β/β‐catenin pathway. Additionally, LAMP2A overexpression significantly inhibited osteoclast hyperactivity induced by TNF‐α. Finally, in a murine bone defect model, we demonstrated that controlled release of LAMP2A overexpression adenovirus by alginate sodium capsule efficiently protected bone healing from inflammation, as confirmed by imaging and histological analyses. Collectively, our findings suggest that enhancing CMA has the potential to safeguard bone formation while mitigating hyperactivity in bone absorption. [ABSTRACT FROM AUTHOR]

Geothermal resources have been recognized as important sources of clean renewable energy. The exploration, development, and utilization of geothermal resources, especially hot dry rock (HDR) resources, are highly important for achieving peak carbon and carbon neutrality. However, there is no comprehensive evaluation method for determining HDR target areas, and the evaluation scale and application disciplines are relatively simplistic. In this paper, we sought to optimize the identification of HDR target areas through a multiscale and multidisciplinary method and formed a set of generalized and demonstrative processes to guide the exploration of HDR resources. Through practical application to the Gonghe Basin and the Zhangzhou Basin, it was found that the comprehensive geothermal conditions of the Gonghe Basin are superior to those of the Zhangzhou Basin, and the geothermal reservoir depth, geothermal reservoir temperature, geothermal gradient, and heat flow are the four most important factors affecting hot dry rock geothermal resources. Using this method, the prioritization of target areas changes from a qualitative study to a quantitative and semiquantitative study, increasing the specificity and reliability of the decision-making process. [ABSTRACT FROM AUTHOR]

In this paper, we explored the different performances of the evolution of polarization control parameters under algorithm optimization in one‐dimensional, two‐dimensional, and three‐dimensional parameter space. We found that the genetic algorithm (GA) operation has a typical converging trend as the epoch increasing of groups in ultra‐fast pulse generation. The corresponding deviations were calculated to be 10.8%, 11.2%, and 5.0%, respectively, which is different from the traversal algorithm operation. The typical noise‐like pulse state was effectively automatically searched at different length cavities, with center wavelengths of 1973, 1988.7, and 2002.7 nm, repetition rate of 9.4, 10.4, and 5.4 MHz, and typical spike duration of ~224 fs. Our research shows the effectiveness of the GA in searching and controlling the ultrashort pulse output of a 2‐µm thulium‐doped fiber laser. [ABSTRACT FROM AUTHOR]

The epidemic of stripe rust, caused by the pathogen Puccinia striiformis f. sp. tritici (Pst), would reduce wheat (Triticum aestivum) yields seriously. Traditional experimental methods are difficult to discover the interaction between wheat and Pst. Multi-omics data analysis provides a new idea for efficiently mining the interactions between host and pathogen. We used 140 wheat-Pst RNA-Seq data to screen for differentially expressed genes (DEGs) between low susceptibility and high susceptibility samples, and carried out Gene Ontology (GO) enrichment analysis. Based on this, we constructed a gene co-expression network, identified the core genes and interacted gene pairs from the conservative modules. Finally, we checked the distribution of Nucleotide-binding and leucine-rich repeat (NLR) genes in the co-expression network and drew the wheat NLR gene co-expression network. In order to provide accessible information for related researchers, we built a web-based visualization platform to display the data. Based on the analysis, we found that resistance-related genes such as TaPR1, TaWRKY18 and HSP70 were highly expressed in the network. They were likely to be involved in the biological processes of Pst infecting wheat. This study can assist scholars in conducting studies on the pathogenesis and help to advance the investigation of wheat-Pst interaction patterns. [ABSTRACT FROM AUTHOR]

Cultivated grasslands are an important part of grassland ecosystems and have been proven to be major carbon sinks, then playing an important role in the global carbon balance. The effect of cultivated grassland type (Medicago sativa, Triticum aestivum, Secale cereale, and Vicia villosa grasslands) on carbon flux (including net ecosystem CO2 exchange (NEE), ecosystem respiration (ER), and gross ecosystem productivity (GEP)) downstream of the Yellow River was studied via the static chamber technique and a portable photosynthetic system. Bare land was used as a control. The results showed that the four cultivated grassland types were mainly carbon sinks, and bare land was a carbon source. The cultivated grassland types significantly affected carbon flux. The average NEE and GEP of the grassland types were in the following order from high to low: Medicago sativa, Secale cereale, Triticum aestivum, and Vicia villosa grassland. Stepwise regression analysis showed that among all measured environmental factors, soil pH, soil bulk density (BD), soil organic carbon (SOC), and soil microbial carbon (MBC) were the main factors affecting CO2 flux. The combined influence of soil BD, SOC, and pH accounted for 77.6% of the variations in NEE, while soil BD, SOC, and MBC collectively explained 79.8% of changes in ER and 72.9% of the changes in GEP. This finding indicates that Medicago sativa grassland is a cultivated grassland with a high carbon sink level. The changes in carbon flux were dominated by the effects of soil physicochemical properties. [ABSTRACT FROM AUTHOR]

Large-scale wind farms incorporating doubly-fed induction generators (DFIGs) are considered a promising direction for modern energy supply systems due to their role in reducing dependence on fossil energy sources. However, the dynamic interactions between DFIGs and AC grids sometimes lead to sub-synchronous oscillation (SSO) that threatens the safe and stable operation of wind power systems. Therefore, it is essential to develop a mathematical model and design an algorithm to quantitatively design the control parameters. Such algorithms are helpful in preventing or mitigating system stability problems coming from wind power connected to the grid and reducing damage to power equipment. The traditional state-space model is mainly established to determine the stable operating point and analyze the influence of parameters on the system operating mode. However, this method does not provide the selection area for the system parameters. To address this shortcoming, this paper introduces a modular state-space model for DFIGs containing series compensation lines and proposes an algorithm for calculating the parameter selection area based on the Guardian map method. First, a detailed modular state-space model based on the virtual synchronous generator (VSG) control is established. The modular model helps to reflect the relationship between state variables and focuses on describing the operating state of DFIGs in wind farms. Second, this paper focuses on the influence of VSG control parameters and compensation capacitance on SSO. It aims to clarify the role of the series compensation level and control parameters on SSO based on VSG control. Then, an algorithm for the parameter selection area based on the Guardian map is proposed and the area of the VSG-controlled DFIG is obtained. Finally, the accuracy and validity of the algorithm are verified by time domain simulation in MATLAB/Simulink and HIL experiment. [ABSTRACT FROM AUTHOR]

The thermal structure of the lithosphere is key to understanding its thickness, properties, evolution, and geothermal resources. Cratons are known for their low heat flow and deep lithospheric roots. However, present-day cratons in East China have geothermal characteristics that are highly complex, with variable heat flow values, diverging from the typical thermal state of cratons. In this study, we conducted a detailed analysis of the geothermal geological background of the cratons in East China, summarizing the thermal state and tectono-thermal processes of different tectonic units, calculating the temperature at various depths, and discussing differences in temperature and thermal reservoirs at different depths. The observed lithospheric thermal thickness within the North Jiangsu Basin and the Bohai Bay Basin is notably reduced in comparison to that of the Jianghan Basin and the Southern North China Basin. The phenomenon of craton destruction during the Late Mesozoic emerges as a pivotal determinant, enhancing the geothermal resource prospects of both the Bohai Bay Basin and the North Jiangsu Basin. Our findings contribute significantly to the augmentation of theoretical frameworks concerning the origins of heat sources in global cratons. Furthermore, they offer invaluable insights for the methodical exploration, evaluation, advancement, and exploitation of geothermal resources. [ABSTRACT FROM AUTHOR]

Depression is a major cause of suicide and mortality worldwide. This study aims to conduct a systematic review to identify metabolic biomarkers and pathways for major depressive disorder (MDD), a prevalent subtype of clinical depression. We searched for metabolomics studies on depression published between January 2000 and January 2023 in the PubMed and Web of Science databases. The reported metabolic biomarkers were systematically evaluated and compared. Pathway analysis was implemented using MetaboAnalyst 5.0. We included 26 clinical studies on MDD and 78 metabolomics studies on depressive-like animal models. A total of 55 and 77 high-frequency metabolites were reported consistently in two-thirds of clinical and murine studies, respectively. In the comparison between murine and clinical studies, we identified 9 consistently changed metabolites (tryptophan, tyrosine, phenylalanine, methionine, fumarate, valine, deoxycholic acid, pyruvate, kynurenic acid) in the blood, 1 consistently altered metabolite (indoxyl sulfate) in the urine and 14 disturbed metabolic pathways in both types of studies. These metabolic dysregulations and pathways are mainly implicated in enhanced inflammation, impaired neuroprotection, reduced energy metabolism, increased oxidative stress damage and disturbed apoptosis, laying solid molecular foundations for MDD. Due to unavailability of original data like effect-size results in many metabolomics studies, a meta-analysis cannot be conducted, and confounding factors cannot be fully ruled out. This systematic review delineated metabolic biomarkers and pathways related to depression in the murine and clinical samples, providing opportunities for early diagnosis of MDD and the development of novel diagnostic targets. • 78 murine and 26 clinical metabolomics studies were analyzed and compared. • Ten potential markers were consistently altered in both clinical and murine studies. • Fourteen metabolic pathways were enriched and shared in both types of studies. • The findings offer diagnostic clues and potential therapeutic targets for depression. [ABSTRACT FROM AUTHOR]

Stereospecific recognition of chiral molecules plays a crucial role in biological systems. The μ-opioid receptor (MOR) exhibits binding affinity towards (−)-morphine, a well-established gold standard in pain management, while it shows minimal binding affinity for the (+)-morphine enantiomer, resulting in a lack of analgesic activity. Understanding how MOR stereoselectively recognizes morphine enantiomers has remained a puzzle in neuroscience and pharmacology for over half-a-century due to the lack of direct observation techniques. To unravel this mystery, we constructed the binding and unbinding processes of morphine enantiomers with MOR via molecular dynamics simulations to investigate the thermodynamics and kinetics governing MOR's stereoselective recognition of morphine enantiomers. Our findings reveal that the binding of (−)-morphine stabilizes MOR in its activated state, exhibiting a deep energy well and a prolonged residence time. In contrast, (+)-morphine fails to sustain the activation state of MOR. Furthermore, the results suggest that specific residues, namely D1142.50 and D1473.32, are deprotonated in the active state of MOR bound to (−)-morphine. This work highlights that the selectivity in molecular recognition goes beyond binding affinities, extending into the realm of residence time. [ABSTRACT FROM AUTHOR]

With the promotion of the dual carbon target, the scale of the wind power grid connection will significantly increase. However, wind power has characteristics such as randomness and volatility, and its grid connection challenges the pressure of system peak shaving, making it increasingly difficult to regulate the power system. To solve the problem of wind power abandonment, the positive and negative peak shaving characteristics of wind power were first analyzed. Based on this, it is proposed that demand response resources and energy storage with adjustable characteristics are used as the new means of wind power consumption. Together with the thermal power units, they participate in the optimization and scheduling of the power grid, forming a coordinated and optimized operation mode of source load storage. With the goal of minimizing system operating costs, a two-stage economic scheduling model was formed for the day-ahead and intra-day periods. Finally, optimization software was used to solve the problem, and the simulation results showed the effectiveness of the proposed economic scheduling model, which can improve the system's new energy consumption and reduce the system's operating costs. [ABSTRACT FROM AUTHOR]

In this paper, the three-dimensional fully compact high-order gas-kinetic scheme (HGKS) is proposed for the direct numerical simulation of compressible turbulent flows. Because of the high-order gas evolution model, the numerical fluxes as well as the point-wise conservative variables can be evaluated from the time-accurate gas distribution function at the cell interface. As a result, both the cell-averaged variables and their cell-averaged gradients can be updated inside each cell. Based on the cell averaged values and their gradients, the compact Hermite weighted essentially non-oscillatory (HWENO) scheme is developed, in which the dimension-by-dimension reconstruction is used for three-dimensional turbulences. In both normal and tangential directions, the fifth-order HWENO reconstruction is adopted. Compared with the classical WENO scheme, the stencil for the HWENO scheme only contains 33 cells for each cell. To achieve the temporal accuracy, the two-stage fourth-order temporal discretization is used. For the evaluation of point-wise variables, the simplified third-order gas-kinetic solver is used. Several classical benchmark problems are simulated, which validate the accuracy, resolution, and robustness of compact HGKS. As a comparison, the numerical results of HGKS using non-compact WENO reconstruction are also provided. Due to the compact stencil, the compact HGKS has a favorable performance for turbulence simulation in resolving the multi-scale structures. [ABSTRACT FROM AUTHOR]

The pursuit of effective therapeutic strategies for tissue damage has prompted extensive scholarly investigations worldwide. Tissue engineering has emerged as a prominent approach, particularly through the utilization of artificial scaffolds that closely resemble the natural extracellular matrix (ECM). These scaffolds exhibit multi‐scale topological structures and surface physicochemical properties, which significantly influence cellular behavior, thereby attracting considerable attention from numerous researchers. This comprehensive review is concentrated on the primary techniques employed in the fabrication of biodegradable polymer scaffolds possessing oriented porous structures, and the most recent advancements in tissue engineering research are presented. Significantly, the profound influence of scaffold surface characteristics is underscored on cellular behavior, elucidating the superiority of oriented pore structures over disordered ones in mimicking the distinctive attributes of the ECM. Enhanced cell adhesion, proliferation, and tissue differentiation represent notable advantages associated with oriented porous scaffolds. Additionally, the critical interplay between scaffold structure, performance, and functionalization is emphasized, highlighting the imperative to optimize the clinical application of tissue engineering scaffolds. [ABSTRACT FROM AUTHOR]

A full-discrete scheme is presented for a Langevin equation involving Caputo fractional derivative and additive white noise. Based on a spectral truncation of white noise, the fractional Langevin equation is converted to an approximate equation with random parameters and a finite difference scheme is constructed. Consistency of the approximate equation as well as error estimate of the finite difference scheme are obtained. It is proved that when spectral truncation level and the step size are inversely proportional, the convergence order of the finite difference scheme is 1.5 in mean-square sense and independent of the value of fractional derivative order. Numerical examples verify the theoretical analysis. Moreover, to fulfill long-time simulation, a scheme based on piecewise spectral approximation of white noise is further developed. [ABSTRACT FROM AUTHOR]

With the development of digital creative industry and the use of more emerging digital technologies, the forms of digital cultural and creative design products are also increasingly diversified. Unlike traditional cultural and creative design products, digital cultural and creative design products are no longer limited to physical products, but appear more in the field of exhibition, virtual reality and product visualization. At the initial stage of the combination of digital information technology and cultural and creative content, digital cultural and creative design products, unlike ordinary cultural and creative design products, opened a new vision for users. The design quality evaluation of digital cultural and creative design products is viewed as a multi-criteria group decision-making (MCGDM). The single-value neutrosophic sets (SVNSs) concept and its interval-valued version (Interval-valued neutrosophic sets, IVNSs) are within the recent rapid developments for managing the uncertain representation problem in MCGDM. In SVNSs, decision makers (DMs) could portray membership, non-membership and hesitancy. IVNSs expands this useful feature through portraying intervals to these three information decision degrees. In this manner, the uncertainty, ambiguity and vagueness hidden in human judgements could be quantified more efficiently. IVNSs have been widely employed and researched in MCGDM. The main purpose of this paper is to proposed the Interval-valued neutrosophic number MABAC (IVNN-MABAC) technique based on prospect theory (PT) to address the MCGDM. Eventually, an example for design quality evaluation of digital cultural and creative design products and some comparative analysis was employed to demonstrate the superiority of the designed technique. [ABSTRACT FROM AUTHOR]

Regional climates have changed as a result of global warming, which has sped up cirrus circulation and altered the temporal and spatial distribution of precipitation. As climate change intensifies, the pattern of precipitation in the Hoh Xil (HX) region has changed. The dislocation of rain and heat in summer hinders ecological restoration and brings great ecological threat. And it is important to clarify the causes and scopes of the midsummer drought (MSD). In this study we highlight the causes of MSD in terms of water vapour transport, circulation structure and the related influencing factors. We found that (1) the HX region gradually entered a drying‐warming process as MSD developed after 2005. (2) The change in the water vapour balance is the direct cause of MSD in the HX. (3) As a typical climate key zone, the HX is located in the transition region between the westerlies and the Indian monsoon. (4) Regional evaporation capacity is the main factor affecting the occurrence of MSD. The dominant factor shifted from being energy to water with the occurrence and enhancement of MSD. This study complements the scarce research on precipitation anomalies in the HX, provides support for clarifying the impact of climate change on the Qinghai–Tibet Plateau (TP) and contributes to understanding the trends and mechanisms of climate change over the TP under global warming. [ABSTRACT FROM AUTHOR]

The underground pressure disaster caused by the exploitation of deep mineral resources has become a major hidden danger restricting the safe production of mines. Microseismic monitoring technology is a universally recognized means of underground pressure monitoring and early warning. In this paper, the wavelet coefficient threshold denoising method in the time–frequency domain, STA/LTA method, AIC method, and skew and kurtosis method are studied, and the automatic P-phase-onset-time-picking model based on noise reduction and multiple detection indexes is established. Through the effect analysis of microseismic signals collected by microseismic monitoring system of coral Tungsten Mine in Guangxi, automatic P-phase onset time picking is realized, the reliability of the P-phase-onset-time-picking method proposed in this paper based on noise reduction and multiple detection indexes is verified. The picking accuracy can still be guaranteed under the severe signal interference of background noise, power frequency interference and manual activity in the underground mine, which is of great significance to the data processing and analysis of microseismic monitoring. [ABSTRACT FROM AUTHOR]

Ground‐penetrating radar full‐waveform inversion is a high‐resolution method for inverting permittivity and conductivity; however, the issue of multi‐parameter crosstalk during the inversion process, in which perturbations of permittivity and conductivity can produce nearly identical observed data, poses a challenge. Additionally, full‐waveform inversion is highly nonlinear and computationally expensive. In this study, we conducted a sensitivity analysis based on permittivity and conductivity perturbations, which demonstrates that their sensitivities vary with frequency. Specifically, conductivity perturbation has a larger impact on low‐frequency data, whereas permittivity perturbation increasingly affects high‐frequency data. Based on the sensitivity analysis, we propose a modified stepped inversion strategy to mitigate multi‐parameter crosstalk. We also employed wavefield reconstruction inversion, which relaxes the wave‐equation constraint as a penalty term and, thus, can help us avoid local minima of the objective function. In contrast, full‐waveform inversion is more prone to get stuck owing to mismatches between modelled and measured data during the inversion process. Finally, we tested the proposed approach on crosshole synthetic data, which achieved significant computational savings and higher inversion efficiency for fewer forward simulations. Our results demonstrate that the proposed approach is a promising method for inverting subsurface structures and has the potential for practical applications in the future. [ABSTRACT FROM AUTHOR]

Reservoirs play important roles in hydropower generation, flood control, water supply and navigation. However, the regulation of reservoirs is challenged due to their adverse influences on river ecosystems. In this study, 'Ecoflow' was used as an ecological indicator for reservoir operation to indicate the extent of natural flow alteration. Three reservoir optimisation models were established to derive ecological operating rule curves (ORCs). Model 1 only considers maximisation of average annual hydropower generation (AAHG) and the assurance rate (AR) of hydropower generation. Model 2 incorporates ecological objectives and constraints. Model 3 not only considers the hydropower objectives but also simulates runoff and calculates the ecological indicator values of multiple downstream stations. The three models were optimised using a simulation–optimisation framework. Reservoir ecological ORCs were derived for a case study of China's Three Gorges reservoir. The results provided feasible schemes for reservoir operation by considering both hydropower and ecological demands. The AAHG and AR of the preferred optimised scheme for model 3 were increased by 1.06% and 2.50%, respectively. Furthermore, the ecological benefits of three hydrologic stations were also improved. In summary, the ecological indicator Ecoflow and optimisation models could be helpful for reservoir ecological operations. [ABSTRACT FROM AUTHOR]

Autonomous Underwater Vehicle (AUV) is an important tool for intelligent ocean applications, which can be applied to detect underwater environment and search target. Path planning is the key technology to realize AUV intelligence, which has important research significance. Aiming at the dynamic path planning problem, the Regional Ocean Modeling System (ROMS) was first applied to the AUV three‐dimensional (3D) dynamic path planning, and a Gate Recurrent Unit Proximal Policy Optimization with Local Vision (GPPO‐LV) model based on local vision is proposed. The 3D ocean current environment is constructed based on the ROMS simulation data. The local vision matrix is constructed based on underwater images, and the features of local vision are extracted using convolutional neural network. Furthermore, Gate Recurrent Unit (GRU) network is used to mine the hidden information between observation states. Finally, the Actor network for strategy output and the Critical network for action value evaluation are constructed, and strategies are optimized in the process of interaction with the environment. The experiment shows that under various unknown environments, AUV can carry out real‐time path planning under real ocean current data, and has good obstacle avoidance ability. [ABSTRACT FROM AUTHOR]

We consider the problem of estimating the fraction of nonzero means in a sparse normal mixture model in the region where variable selection is possible. The focus is on the situation in which the proportion of nonzero means is very small. The proposed estimator is shown to be nearly rate optimal in the asymptotically minimax sense. Using this estimator, one can also consistently estimate the sparsity parameter in sparse normal mixtures, whose knowledge, in particular, is required to carry out the so-called almost full variable selection procedure. The advantage of using the new estimator is illustrated analytically and numerically. The obtained results can be extended to some nonnormal mixtures. [ABSTRACT FROM AUTHOR]

Highly‐active and low‐cost bifunctional electrocatalysts for oxygen reduction and evolution are essential in rechargeable metal‐air batteries, and single atom catalysts with Fe−N−C are promising candidates. However, the activity still needs to be boosted, and the origination of spin‐related oxygen catalytic performance is still uncertain. Herein, an effective strategy to regulate local spin state of Fe−N−C through manipulating crystal field and magnetic field is proposed. The spin state of atomic Fe can be regulated from low spin to intermediate spin and to high spin. The cavitation of dxz and dyz orbitals of high spin FeIII can optimize the O2 adsorption and promote the rate‐determining step (*O2 to *OOH). Benefiting from these merits, the high spin Fe−N−C electrocatalyst displays the highest oxygen electrocatalytic activities. Furthermore, the high spin Fe−N−C‐based rechargeable zinc‐air battery displays a high power density of 170 mW cm−2 and good stability. [ABSTRACT FROM AUTHOR]

Highly‐active and low‐cost bifunctional electrocatalysts for oxygen reduction and evolution are essential in rechargeable metal‐air batteries, and single atom catalysts with Fe−N−C are promising candidates. However, the activity still needs to be boosted, and the origination of spin‐related oxygen catalytic performance is still uncertain. Herein, an effective strategy to regulate local spin state of Fe−N−C through manipulating crystal field and magnetic field is proposed. The spin state of atomic Fe can be regulated from low spin to intermediate spin and to high spin. The cavitation of dxz and dyz orbitals of high spin FeIII can optimize the O2 adsorption and promote the rate‐determining step (*O2 to *OOH). Benefiting from these merits, the high spin Fe−N−C electrocatalyst displays the highest oxygen electrocatalytic activities. Furthermore, the high spin Fe−N−C‐based rechargeable zinc‐air battery displays a high power density of 170 mW cm−2 and good stability. [ABSTRACT FROM AUTHOR]

Ground-penetrating radar (GPR) has been extensively utilized in deep-space exploration. However, GPR modeling commonly employs simplified antenna models and carrier-free impulse signals, resulting in reduced accuracy and interpretability. In this paper, we addressed these limitations by combining a tilted monopole antenna and linear frequency modulation continuous wave (LFMCW) to simulate real conditions. Additionally, a radiation-pattern-compensation back-propagation (RPC-BP) algorithm was developed to improve the illumination of the right-inclined structure. We first introduced the LFMCW used by the Mars Rover Penetrating Radar (RoPeR) onboard the Zhurong rover, where frequencies range from 15 to 95 MHz. Although the LFMCW signal improves radiation efficiency, it increases data processing complexity. Then, the radiation patterns and response of the tilted monopole antenna were analyzed, where the radiated signal amplitude varies with frequency. Finally, a series of numerical and laboratory experiments were conducted to interpret the real RoPeR data. The results indicate that hyperbolic echoes tilt in the opposite direction of the survey direction. This study demonstrates that forward modeling considering real transmit signals and complex antenna models can improve modeling accuracy and prevent misleading interpretations on deep-space exploration missions. Moreover, the migration process can improve imaging quality by considering radiation pattern compensation. [ABSTRACT FROM AUTHOR]

Near-surface structure investigation plays an important role in studying shallow active faults and has various engineering applications. Therefore, we developed a near-surface structure investigation method using ambient noise in a water environment. This newly developed seismic acquisition technology, fiber-optic distributed acoustic sensing (DAS), was used to acquire ambient noise from the Yangtze River. The recorded data were processed to reconstruct surface waves based on the theory of seismic interferometry. The fundamental-mode dispersion curves were extracted and inverted to obtain a shear-wave velocity model below the DAS line. We compared the inverted velocity model with the subsurface geological information from near the study area. The results from the inverted model were consistent with the prior geological information. Therefore, ambient noise in the water environment can be combined with DAS technology to effectively investigate near-surface structures. [ABSTRACT FROM AUTHOR]

Satellite hyperspectral imagery is an important data source for large-scale refined land cover classification and mapping, but the high spatial heterogeneity and spectral variability at low spatial resolution and the high computation cost for massive data remain challenges in the research community. In recent years, convolutional neural network (CNN) models with the capability for feature extraction have been widely used in hyperspectral image classification. However, incomplete feature extraction, inappropriate feature fusion, and high time consumption are still the major problems for CNN applications in large-scale fine land cover mapping. In this study, a Spatial-Convolution Spectral-Transformer Interactive Network (SCSTIN) was proposed to integrate 2D-CNN and Transformer into a dual-branch network to enhance feature extraction capabilities by exploring spatial context information and spectral sequence signatures in a targeted manner. In addition, spatial-spectral interactive fusion (SSIF) units and category-adaptive weighting (CAW) as two feature fusion modules were also adopted between and after the two feature extraction branches to improve efficiency in feature fusion. The ZY1-02D hyperspectral imagery was collected to conduct the experiments in the study area of the eastern foothills of the Helan Mountains (EFHLM), covering an area of about 8800 km2, which is the largest hyperspectral dataset as far as we know. To explore the potential of the proposed network in terms of accuracy and efficiency, SCSTIN models with different depths (SCSTIN-4 and SCSTIN-2) were performed. The results suggest that compared with the previous eight advanced hyperspectral image classifiers, both SCSTIN models achieved satisfactory performance in accuracy and efficiency aspects with low complexity, where SCSTIN-4 achieved the highest accuracy and SCSTIN-2 obtained higher efficiency. Accordingly, the SCSTIN models are reliable for large-scale fast refined land cover classification and mapping. In addition, the spatial distribution pattern of diverse ground objects in EFHLM is also analyzed. [ABSTRACT FROM AUTHOR]

Chaperone-mediated autophagy (CMA) plays multiple roles in cell metabolism. We found that lysosome-associated membrane protein type 2A (LAMP2A), a crucial protein of CMA, plays a key role in the control of mesenchymal stem cell (MSC) adipo-osteogenesis. We identified a differentially expressed CMA gene (LAMP2) in GEO datasets (GSE4911 and GSE494). Further, we performed co-expression analyses to define the relationships between CMA components genes and other relevant genes including Col1a1, Runx2, Wnt3 and Gsk3β. Mouse BMSCs (mMSCs) exhibiting Lamp2a gene knockdown (LA-KD) and overexpression (LA-OE) were created using an adenovirus system; then we investigated LAMP2A function in vitro by Western blot, Oil Red staining, ALP staining, ARS staining and Immunofluorescence analysis. Next, we used a modified mouse model of tibial fracture to investigate LAMP2A function in vivo. LAMP2A knockdown in mMSCs decreased the levels of osteogenic-specific proteins (COL1A1 and RUNX2) and increased those of the adipogenesis markers PPARγ and C/EBPα; LAMP2A overexpression had the opposite effects. The active-β-catenin and phospho-GSK3β (Ser9) levels were upregulated by LAMP2A overexpression and downregulated by LAMP2A knockdown. In the mouse model of tibial fracture, mMSC-overexpressing LAMP2A improved bone healing, as demonstrated by microcomputed tomography and histological analyses. In summary, LAMP2A positively regulates mMSC osteogenesis and suppresses adipo-osteogenesis, probably via Wnt/β-catenin/GSK3β signaling. LAMP2A promoted fracture-healing in the mouse model of tibial fracture. Key messages: • LAMP2 positively regulates the mBMSCs osteogenic differentiation. • LAMP2 negatively regulates the mBMSCs adipogenic differentiation. • LAMP2 regulates mBMSCs osteogenesis via Wnt/β-catenin/GSK3β signaling pathway. • LAMP2 overexpression mBMSCs promote the fracture healing. [ABSTRACT FROM AUTHOR]

This paper is concerned with the problem of state estimation for nonlinear multi-sensor systems with cross-correlated noise and packet loss compensation. In this case, the cross-correlated noise is modeled by the synchronous correlation of the observation noise of each sensor, and the observation noise of each sensor is correlated with the process noise at the previous moment. Meanwhile, in the process of state estimation, since the measurement data may be transmitted in an unreliable network, data packet dropout will inevitably occur, leading to a reduction in estimation accuracy. To address this undesirable situation, this paper proposes a state estimation method for nonlinear multi-sensor systems with cross-correlated noise and packet dropout compensation based on a sequential fusion framework. Firstly, a prediction compensation mechanism and a strategy based on observation noise estimation are used to update the measurement data while avoiding the noise decorrelation step. Secondly, a design step for a sequential fusion state estimation filter is derived based on an innovation analysis method. Then, a numerical implementation of the sequential fusion state estimator is given based on the third-degree spherical-radial cubature rule. Finally, the univariate nonstationary growth model (UNGM) is combined with simulation to verify the effectiveness and feasibility of the proposed algorithm. [ABSTRACT FROM AUTHOR]

We report the modification of a gas phase ultrafast electron diffraction (UED) instrument that enables experiments with both gas and condensed matter targets, where a time-resolved experiment with sub-picosecond resolution is demonstrated with solid state samples. The instrument relies on a hybrid DC-RF acceleration structure to deliver femtosecond electron pulses on the target, which is synchronized with femtosecond laser pulses. The laser pulses and electron pulses are used to excite the sample and to probe the structural dynamics, respectively. The new system is added with capabilities to perform transmission UED on thin solid samples. It allows for cooling samples to cryogenic temperatures and to carry out time-resolved measurements. We tested the cooling capability by recording diffraction patterns of temperature dependent charge density waves in 1T-TaS2. The time-resolved capability is experimentally verified by capturing the dynamics in photoexcited single-crystal gold. [ABSTRACT FROM AUTHOR]

Surface Heat flow (HF) can be calculated from the accumulation of radiogenic heat production (RHP) of arbitrarily subdivided thin layers of the crust and the residual HF. However, geothermal studies of scientific drilling projects around the world do not have clear vertical correspondence between HF and RHP, which has created a great controversy for the relationship between the two. For the first time, continuous temperature data, thermal conductivity and RHP measurements from the 3,008‐m‐deep Lujiang‐Zongyang Scientific Drilling in the northeastern Yangtze Craton, demonstrate that the abnormal HF is determined by high RHP rock (mean value, 10 μW/m3). The detailed spatial‐temporal study of magmatic activity in the Lujiang‐Zongyang basin shows the high RHP rock are concentrated in the early syenite‐monzonite period (133–131 Ma) in the northern basin. Two enrichment processes caused by late Neoproterozoic and Mesozoic subduction contribute to the formation. Plain Language Summary: Heat flow (HF) is the most important parameter to characterize the thermal state of the Earth's interior. The surface HF can be calculated from the accumulation of heat production of subdivided thin layers of the crust and residual HF. However, no direct evidence of HF and heat production vertical variation has been found in the present continental scientific drilling wells. In this study, the contribution of the vertical variation of heat production to the surface HF is confirmed for the first time, and the HF values significantly higher than the regional background are determined by the high heat production rock. The study of the genesis of the high heat production rock concluded that they likely underwent two enrichment processes in the Late Neoproterozoic and Mesozoic, respectively, with the Late Mesozoic enrichment process being completed in a very short period of time. Key Points: First direct evidence was found to confirm that surface heat flow is determined by the heat productionThe relationship between natural gamma‐ray and heat production is reconstructedThe formation of rocks with high heat production result from two enrichment processes [ABSTRACT FROM AUTHOR]

Aiming at the problems of power flow fluctuation and voltage exceeding standard caused by high permeability distributed power supply access, this paper proposes a load state perception early warning method for distribution networks. Firstly, the random behavior characteristics and voltage early warning mechanisms of power supply and load in distribution networks are analyzed, the dynamic model of distribution networks based on complex network theory is established, and the risk index of voltage exceeding limits under the conditions of high permeability distributed power supply access is put forward. Secondly, the random power flow of distribution networks based on the Monte Carlo method is studied by sampling and analyzing the dynamic model of distribution networks. Then, the risk calculation and safety assessment of voltage exceeding limits are carried out on the currently extracted model, and the risk control strategy of distribution network operation is put forward. Finally, an improved IEEE30-node distribution network topology is proposed. Through simulation analysis, it is proven that the load situation awareness early warning method of distribution networks can effectively predict, improve the security of distribution networks, and provide timely early warning information for maintenance personnel. [ABSTRACT FROM AUTHOR]

Ordered porous polyimide films were fabricated from (AB)m type of diblock copolymer polyimide-b-polystyrene (PI-b-PS). An increase in PS volume fraction (f VPS) is beneficial to decrease the relative dielectric constants and water contact angles of the obtained porous PI films: the relative dielectric constant decreases to 1.89 and water contact angle decreases to 43° when f VPS is 0.36, indicating porous PI films can be used as low-κ material and have good wettability. The solvent uptake of the porous PI films increases with increasing f VPS. A net-like morphology appears when f VPS reaches 0.36. The net-like porous PI film reaches equilibrium uptake of water within approximately 2.5 h, with a final equilibrium uptake ratio of 17.5%, and reaches equilibrium uptake of toluene within approximately 8 h, with a final equilibrium uptake ratio of 15.4%, displaying the highest and fastest solvent uptake compared with other microstructured porous PI films, which is ascribed to the specific characteristic of the interconnecting porous channels derived from the self-assembly of PI-b-PS with f VPS 0.36. Introducing thermally degradable segments to PI-based block copolymer is an effective method to prepare porous PI films and can enhance some of their properties. [ABSTRACT FROM AUTHOR]

The ideal wind turbine power curve provided by the manufacturer cannot monitor the practical performance of wind turbines accurately in the engineering stage; in this paper, a modified approach of the wind turbine power curve is proposed based on improved Bins and K-means++ clustering. By analyzing the wind speed-power data collected by the supervisory control and data acquisition system (SCADA), the relationship between wind speed and output is compared and elaborated on. On the basis of data preprocessing, an improved Bins method for equal frequency division of data is proposed, and the results are clustered through K-means++. Then, the wind turbine power curve correction is realized by data weighting and regression analysis. Finally, an example is given to show that the power curve of the same type of wind turbines, which, installed in different locations, are discrepant and different from the MPC, and the wind turbine power curve obtained by using this method can reflect the output characteristics of the wind turbine operating more effectively in a complex environment. [ABSTRACT FROM AUTHOR]

The high-resolution seismic characterization of gas hydrate reservoirs plays an important role in the detection and exploration of gas hydrate. The conventional AVO (amplitude variation with offset) method is based on a linearized Zoeppritz equation and utilizes only the reflected wave for inversion. This reduces the accuracy and resolution of the inversion properties and results in incorrect reservoir interpretation. We have studied a high-resolution wave-equation-based inversion method for gas hydrate reservoirs. The inversion depends on the scattering integral wave equation that describes a nonlinear relationship between the seismic wavefield and the elastic properties of the subsurface medium. In addition to the reflected wave, it considers more wavefields including the multiple scattering and transmission during inversion to improve the subsurface illumination, so as to enhance the accuracy and resolution of the inversion properties. The results of synthetic data from Pearl River Mouth Basin, South China Sea, demonstrate the validity and advantages of the wave-equation-based inversion method. It can effectively improve the resolution of inversion results compared to the conventional AVO method. In addition, it has good performance in the presence of noise, which makes it a promising method for field data. [ABSTRACT FROM AUTHOR]

Semantic segmentation based on deep learning has undergone remarkable advancements in recent years. However, due to the neglect of the shallow features, the problems of inaccurate segmentation have persisted. To address this issue, a semantic segmentation network-attention-based auxiliary extraction and hybrid subsampled network (AAEHS-Net) is suggested in this study. To extract more deep information and the shallow features, the complementary and enhanced extraction module (CEEM) is utilized by the network. As a result, the edge segmentation of the model is improved. Moreover, to reduce the loss of features, a hybrid subsampled module (HSM) is introduced. Meanwhile, global max pool and global avg pool module (GAGM) is designed as an attention module to enhance the features with global and important information and maintain feature continuity. The proposed AAEHS-Net is evaluated on three datasets: the aerial drone image dataset, the Massachusetts roads dataset, and the Massachusetts buildings dataset. On the three datasets, AAEHS-Net achieves 1.15%, 0.88%, and 2.1% higher accuracy than U-Net, reaching 90.12%, 96.23%, and 95.15%, respectively. At the same time, our proposed network has obtained the best values for all evaluation metrics in three datasets compared to the currently popular algorithms. [ABSTRACT FROM AUTHOR]

Solar‐driven evaporation is a promising strategy to relieve fresh water stress in the world. For an evaporator, it is necessary to be equiped with novel photothermal conversion materials and regulate heat energy loss in the solar‐driven generation process for evaporation efficiency. Herein, a novel eutectic gallium‐indium (EGaIn)/polyaniline (PANI) complex (EP) and cellulose nanocrystals (CNCs) are explored as the light absorber for broadband light absorbing and the dispersant for particles uniformity. Based on the Bénard–Marangoni effect, a dual‐network poly(vinyl alcohol)/poly(acrylamide) (PM) hydrogel as the evaporator and water/ethylene glycol as the solvent to regulate heat transfer. Specifically, with CNCs and EP incorporated, the hydrogel is endowed with excellent mechanical properties, photothermal conversion performance, and electrical characteristics. Surface temperature of the hydrogel can reach to ≈38.7 °C in water under 1 sun illumination for 1 h. Based on combination of broadband light absorption and the Bénard–Marangoni effect, its evaporation rate is higher than 1.50 kg m–2 h–1. The engineered synergy also gives the hydrogels with multiple sensory capabilities, skin‐like function, and power generation. This work demonstrates novel EGaIn‐based photothermal conversion particles and a new approach to regulate the heat transfer for highly solar‐driven evaporation, with a focus on the integration of multifunctional solar evaporation systems. [ABSTRACT FROM AUTHOR]

The propagation of microseismicity in subsurface media is complex. We developed an anisotropic petrophysical model based on an empirical formula, linear slip theory and the bond transform method considering real underground conditions. Using Biot's equations, the seismic response to a general dislocation source in fracture‐induced anisotropic two‐phased media was solved using a staggered grid high‐order finite‐difference algorithm. To understand the relationship between the microseismic wave and fracture parameters, we then designed several different models to calculate the wavefield snapshots and analyse the effect of the fracture volume ratio and orientation. The modelling results indicate that the shear faulting source generates three types of waves in two‐phase media. Fractures can render homogeneous media anisotropic, and anisotropy becomes more noticeable with an increase in the fracture volume ratio. This decreases the velocity of the fast longitudinal and transverse waves in the vertical direction and increases the velocity of the slow longitudinal wave in a certain range. The fracture orientation mainly influences the moment tensor and then affects the wavefronts. These simulations lay the foundation for further studies on microseismic wave propagation in fracture‐induced anisotropic media. [ABSTRACT FROM AUTHOR]

In order to mitigate the negative effects of global climate change, the Chinese government has committed to achieving peak carbon emissions by 2030 and carbon neutrality by 2060. Since municipal cities are the bottom administrative level for drawing up development plans, it is necessary and important to conduct decarbonization pathway research on municipal energy systems (MESs). However, there is little research on decarbonization at the municipal level, and the impact of development paths in each forecast scenario is mostly based on expert evaluation and qualitative assessment. Therefore, this study established a complete decarbonization framework for MESs, including general research procedures, models, and a sustainable evaluation method. The models of energy consumption and carbon emission were adapted and improved for MESs. In order to quantitatively evaluate the energy system development for each scenario, we proposed an energy–economy–environment–security (3E–S) evaluation method, in which principal component analysis (PCA) was adopted for multi-criterion decision making. According to the analysis results of the case city in Guangdong, this evaluation method was proved to be an effective way to identify the factors that may influence coordinated development. By adjusting the relevant parameters and factors in the model, the optimal decarbonization pathway can be found to promote sustainable and coordinated development, thus helping government decision makers to quantitatively evaluate planning paths. [ABSTRACT FROM AUTHOR]

A selective harmonic elimination method of modified packed u-cells (MPUC) inverter fed induction motor built on modified multiverse optimizer (MMVO) algorithm is put forward. The proposed method adopts the MMVO algorithm to search the optimal solution in the SHEPWM equations through the two processes of exploring the optimal solution distribution and exploiting the optimal solution within it. On this basis, the influence of the different orders of power supply harmonics eliminated selectively on the motor's torque ripple is compared and analyzed by using the Simulink and MAXWELL. From the results of simulation and experiments, it can be proved that the method can achieve the required fundamental voltage and selectively suppress the harmonic with particular order. At the same time, it is verified by ANSYS MAXWELL that the working quality of the motor can be improved by selectively eliminating the 5th, 7th, 11th, and 13th harmonics in the power source to effectively suppress the 6th and 12th periodic torque ripples that arise from these harmonics. [ABSTRACT FROM AUTHOR]

Background: The available therapeutic options for large bone defects remain extremely limited, requiring new strategies to accelerate bone healing. Genetically modified bone mesenchymal stem cells (BMSCs) with enhanced osteogenic capacity are recognised as one of the most promising treatments for bone defects. Methods: We performed differential expression analysis of miRNAs between human BMSCs (hBMSCs) and human dental pulp stem cells (hDPSCs) to identify osteogenic differentiation-related microRNAs (miRNAs). Furthermore, we identified shared osteogenic differentiation-related miRNAs and constructed an miRNA-transcription network. The Forkhead box protein A1 (FOXA1) knockdown strategy with a lentiviral vector was used to explore the role of FOXA1 in the osteogenic differentiation of MSCs. Cell Counting Kit-8 was used to determine the effect of the knockdown of FOXA1 on hBMSC proliferation; real-time quantitative reverse transcription PCR (qRT-PCR) and western blotting were used to investigate target genes and proteins; and alkaline phosphatase (ALP) staining and Alizarin Red staining (ARS) were used to assess ALP activity and mineral deposition, respectively. Finally, a mouse model of femoral defects was established in vivo, and histological evaluation and radiographic analysis were performed to verify the therapeutic effects of FOXA1 knockdown on bone healing. Results: We identified 22 shared and differentially expressed miRNAs between hDPSC and hBMSC, 19 of which were downregulated in osteogenically induced samples. The miRNA-transcription factor interaction network showed that FOXA1 is the most significant and novel osteogenic differentiation biomarker among more than 300 transcription factors that is directly targeted by 12 miRNAs. FOXA1 knockdown significantly promoted hBMSC osteo-specific genes and increased mineral deposits in vitro. In addition, p-ERK1/2 levels were upregulated by FOXA1 silencing. Moreover, the increased osteogenic differentiation of FOXA1 knockdown hBMSCs was partially rescued by the addition of ERK1/2 signalling inhibitors. In a mouse model of femoral defects, a sheet of FOXA1-silencing BMSCs improved bone healing, as detected by microcomputed tomography and histological evaluation. Conclusion: These findings collectively demonstrate that FOXA1 silencing promotes the osteogenic differentiation of BMSCs via the ERK1/2 signalling pathway, and silencing FOXA1 in vivo effectively promotes bone healing, suggesting that FOXA1 may be a novel target for bone healing. [ABSTRACT FROM AUTHOR]

ESK reverses LPS-induced depression-like behavior by activating mTOR to inhibit autophagic impairments, while the mTOR inhibitor rapamycin opposes ESK. [Display omitted] • ESK reverses LPS-induced depression-like behavior and alleviates both neuroinflammation and apoptosis. • The inhibition of autophagy by activating the mTOR-BDNF pathway is an essential mechanism for the antidepressant effect of ESK. • The combination of ESK with 3-MA did not enhance the antidepressant effect. Depression is a serious physical and mental disease, with major depressive disorder (MDD) being a hard-to-treat, life-threatening form of the condition. Currently, esketamine (ESK) is used in the clinical treatment of MDD, but the drug mechanisms continue to be unclear. In this study, we explored the therapeutic efficacy of ESK against lipopolysaccharide (LPS)-induced neuroinflammatory, autophagic, and depressive symptoms and the possible mechanisms behind them. Our study demonstrated that LPS increased cytokine levels (TNF-α, IL-1β, IL-6), induced neuroinflammation, led to increased levels of autophagy markers, and enhanced autophagy activation, which ultimately caused depressive symptoms in mouse models. ESK inhibited autophagy via the mTOR-BDNF signaling pathway and significantly alleviated the adverse effects induced by LPS, mainly in the form of reduced levels of cytokines, apoptotic factors, and autophagic markers; elevated BDNF levels; and improved depression-like behavior. Furthermore, we were interested to know if ESK in combination with other autophagy inhibitors would have a better antidepressant effect, and we chose the autophagy inhibitor 3-MA for this attempt. Interestingly, the use of 3-MA did not attenuate or even enhance the therapeutic effect of ESK. The results suggest that, in the LPS-induced depression models, ESK conveyed an antidepressant effect via the inhibition of autophagy through the mTOR-BDNF pathway. [ABSTRACT FROM AUTHOR]

The roles of plateau pika (Ochotona coronae) in the Tibetan Plateau are often controversial, because it is often regarded as a destructive pest or an ecosystem engineer. Here a meta-analysis using 72 paired observations was conducted to examine whether the impacts of plateau pika on environmental quality (i.e., plant and soil properties) depend on population density in the Tibetan Plateau. Pika population density was used as a proxy for disturbance intensity. The pika disturbance intensity was divided into five groups based on the number of burrows, including low disturbance intensity (LD) (9–30 burrows per ha), medium disturbance intensity (MD) (31–100 burrows per ha), high disturbance intensity (HD) (101–170 burrows per ha), extreme disturbance intensity (ED) (171–240 burrows per ha) and uncontrolled (or excessive) disturbance intensity (UD) (>241 burrows per ha). Given that sample sizes in some of the groups are small (especially for the HD), we further pooled the disturbance groups including the LD–MD and HD–UD. Overall, relative to control (i.e., no disturbing), there was a great increase (80.3%) in aboveground biomass under the LD–MD, whereas a decrease of 41.1% occurred under the HD–UD. At the same time, plant coverage, species richness, height, and belowground biomass greatly decreased only in the HD–UD. Furthermore, the effect size of plant coverage, species richness, and aboveground biomass also declined with pika burrow density significantly. With regard to soil properties, there was a significant increase in soil organic carbon, ammonium nitrogen, and soil organic carbon stock under the LD–MD, whereas a decrease under the HD–UD. In addition, soil total nitrogen, total potassium, and nitrate nitrogen increased at the LD–MD and HD–UD. Nevertheless, the effect size of these soil properties (with >20 observations) was not related to pika burrow density. In summary, there is an implication that the low and moderate disturbance of pikas is beneficial to maintain and promote ecosystem functioning in the Tibetan grasslands. In the future pikas' eradication policy should be reconsidered in alpine grassland management. • Low and medium pika disturbance increased aboveground mass and soil organic carbon. • Species richness and aboveground mass reduced if pika disturbance was above medium. • The pika eradication policy should be reconsidered. [ABSTRACT FROM AUTHOR]

Rolling contact fatigue (RCF) is significantly influenced by retained austenite (RA). To study the impact of the RA on fatigue life and pit formation, a high carbon steel was tested with three different RA levels ranging from 5 % to 23 % (volume fraction). The variations of the RA with respect to the number of cycles and along the depth were inspected by X-ray diffraction (XRD) technique. The microstructures before and after RCF were characterized by scanning electron microscopy (SEM) and electron backscatter diffraction (EBSD). The majority of RA was transformed into martensite at an early stage (before 3 × 104 cycles) in both surface and subsurface. And the remaining small fraction of RA was transformed during the rest of the testing life, with a final content lower than 5 %. As the depth increased, the rate of RA transformation decreased. The specimen with the highest RA level of 23 % showed the shortest life. The longest RCF life was seen in the specimen with a medium RA level of 15 % due to the formation of the well-developed hardened layer, which helps resisting the pit formation. Based on these observations, it was suggested that a medium level of RA is beneficial for the improvement of the RCF life of the present high carbon steel. The combined effect of the hardness and the RA acts together on resistance to pit formation. • The specimen with the highest RA level shows the shortest life. • A well-developed hardened layer is formed in the specimen with medium RA level. • A medium RA level of 15 % is beneficial for improving RCF life of present steel. [ABSTRACT FROM AUTHOR]

Aerogel possesses the advantages of high specific surface area, low density, and high porosity, which have shown great application in thermal regulation due to its efficient light scattering capability. However, traditional polymer-based aerogels have poor mechanical properties and lack ductility in outdoor applications, the cooling efficiency of the material is easily affected by damage during transportation, installation, and environmental factors. In this work, combining the porous nature of aerogels and the high ductility of membranes, a polylactic acid-based porous membrane cooler was developed by combining a regular honeycomb surface porous structure design and physical/chemical modification to enhance flexibility, using a simple non-solvent induced phase separation method. This porous membrane exhibits both super-flexibility (116 % elongation at break) and porous characteristics. It achieves a sub-ambient temperature decrease of 4–6 °C under direct sunlight. The optimized porous membrane demonstrates high solar reflectance (94 % of peak reflectivity, 90 % of average reflectivity) and strong infrared emissivity (96 % of peak emissivity, 91 % of average emissivity), it also maintains a solar peak reflectivity of 91 % under 100 % tensile strain and 1000 bending cycles, the cooler still maintains a cooling effect of 2–5 °C below ambient temperature. This work paves the way for developing mechanical flexible and strong radiative coolers for thermal regulation. [ABSTRACT FROM AUTHOR]

Robot-assisted prostate biopsy is a new technology to diagnose prostate cancer, but its safety is influenced by the inability of robots to sense the tool-tissue interaction force accurately during biopsy. Recently, vision based force sensing (VFS) provides a potential solution to this issue by utilizing image sequences to infer the interaction force. However, the existing mainstream VFS methods cannot realize the accurate force sensing due to the adoption of convolutional or recurrent neural network to learn deformation from the optical images and some of these methods are not efficient especially when the recurrent convolutional operations are involved. This paper has presented a Transformer based VFS (TransVFS) method by leveraging ultrasound volume sequences acquired during prostate biopsy. The TransVFS method uses a spatio-temporal local–global Transformer to capture the local image details and the global dependency simultaneously to learn prostate deformations for force estimation. Distinctively, our method explores both the spatial and temporal attention mechanisms for image feature learning, thereby addressing the influence of the low ultrasound image resolution and the unclear prostate boundary on the accurate force estimation. Meanwhile, the two efficient local–global attention modules are introduced to reduce 4D spatio-temporal computation burden by utilizing the factorized spatio-temporal processing strategy, thereby facilitating the fast force estimation. Experiments on prostate phantom and beagle dogs show that our method significantly outperforms existing VFS methods and other spatio-temporal Transformer models. The TransVFS method surpasses the most competitive compared method ResNet3dGRU by providing the mean absolute errors of force estimation, i.e., 70.4 ± 60.0 millinewton (mN) vs 123.7 ± 95.6 mN, on the transabdominal ultrasound dataset of dogs. • A 4D ultrasound based deep learning method for sensing force during prostate biopsy. • A spatio-temporal local–global Transformer for prostate deformation learning. • Spatio-temporal attention modules for feature extraction from ultrasound volumes. • A factorized spatio-temporal scheme for reducing computation cost of 4D Transformer. • The outperforming force sensing performance of our method on four in-house datasets. [ABSTRACT FROM AUTHOR]

In this study, polyvinyl alcohol (PVA), granular active carbon (AC), and Ca2+/polyacrylamide (PAM) were used to enhance granulation in three upflow anaerobic sludge blanket (UASB) reactors, UASB-PVA, UASB-AC, and UASB-PAM. The experimental results showed that the start-up of the UASB-PVA reactor was the fastest, UASB-PVA, UASB-AC, and UASB-PAM took 44, 48 and 54 d, respectively, and the performance of UASB-PVA was relatively stable and less fluctuating. When organic load was up to ∼13 kg chemical oxygen demand (COD)/(m3·d), biogas production of PVA sludge, AC sludge, and PAM sludge were 19.10, 12.32, and 15.13 L/d, respectively, and the biogas production of the three reactors was: UASB-PVA>UASB-PAM>UASB-AC. After 128 days of operation, the granulation effect of the sludge from the three reactors was ranked from high to low in the following order: UASB-PVA>UASB-AC>UASB-PAM. In the process of load shock, the COD removal efficiency (CODRE) and N H 4 + -N removal efficiency ( N H 4 + -NRE) of the UASB-PVA was the most stable under different load impacts, the standard deviation of CODRE and N H 4 + -NRE were 2.7% and 8.7%, respectively. The total fluorescence intensity of dissolved organic matter in the effluent of UASB-PVA, AC, and PAM were 2.5 × 105 – 5.5 × 105, 1.8 × 105 – 13.2 × 105, and 1.5 × 105 – 11.5 × 105, respectively. The change range of the total fluorescence intensity of UASB-PVA was the minimal under load impact. The UASB-PVA can play an important role in the upgrading of sewage treatment plants. [ABSTRACT FROM AUTHOR]

In this paper, a spectral Petrov-Galerkin method is investigated for an optimal control problem with a fractional ordinary differential equation constraint. With the study of its well-posedness and the optimality condition in standard Sobolev space, the regularity for the optimal control problem is established in the framework of weighted Sobolev space, which is superior to the counterpart analyzed in standard Sobolev space. Based on the obtained regularity results, the error estimate of the spectral Petrov-Galerkin method is presented, and optimal convergence orders in L ω − α , 0 2 -norm or L ω 0 , − α 2 -norm are determined. Finally, numerical examples with both smooth inputs and rough inputs are given to verify the theoretical prediction. [ABSTRACT FROM AUTHOR]