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To explore the penetration resistance of calcareous sand media, penetration tests have been conducted in the velocity range of 200–1000 m/s using conical-nosed projectiles with a diameter of 14.5 mm. Further, a pseudo fluid penetration model applicable to the penetration of rigid projectiles in sand media is established according to the approximate flow of compacted sand in the adjacent zone of penetration. The correlation between the impedance function of projectile-target interaction and the internal friction features of pseudo fluid is clarified, and the effects of sand density, cone angle of nose-shaped projectile, and dynamic hardness on the penetration depth are investigated. The results verify the feasibility, wide applicability, and much lower error (with respect to the experimental data) of the proposed model as compared to the Slepyan hydrodynamic model.

Abstract Despite the significant potential of generative models, low synthesizability of many generated molecules limits their real-world applications. In response to this issue, we develop ClickGen, a deep learning model that utilizes modular reactions like click chemistry to assemble molecules and incorporates reinforcement learning along with inpainting technique to ensure that the proposed molecules display high diversity, novelty and strong binding tendency. ClickGen demonstrates superior performance over the other reaction-based generative models in terms of novelty, synthesizability, and docking conformation similarity for existing binders targeting the three proteins. We then proceeded to conduct wet-lab validation on the ClickGen’s proposed molecules for poly adenosine diphosphate-ribose polymerase 1. Due to the guaranteed high synthesizability and model-generated synthetic routes for reference, we successfully produced and tested the bioactivity of these novel compounds in just 20 days, much faster than typically expected time frame when handling sufficiently novel molecules. In bioactivity assays, two lead compounds demonstrated superior anti-proliferative efficacy against cancer cell lines, low toxicity, and nanomolar-level inhibitory activity to PARP1. We demonstrate that ClickGen and related models may represent a new paradigm in molecular generation, bringing AI-driven, automated experimentation and closed-loop molecular design closer to realization.

The topological attributes of fracture networks in limestone, subject to intense hydrodynamics and intricate geological discontinuities, substantially influence the mechanical and hydraulic characteristics of the rock mass. The dynamical evolution of fracture networks under stress is crucial for unveiling the interaction patterns among fractures. However, existing models are undirected graphs focused on stationary topology, which need optimization to depict fractures' dynamic development and rupture process. To compensate for the time and destruction terms, we propose the damage network model, which defines the physical interpretation of fractures through the ternary motif. We focus primarily on the evolution of node types, topological attributes, and motifs of the fracture network in limestone under uniaxial stress. Observations expose the varying behavior of the nodes' self-dynamics and neighbors' adjacent dynamics in the fracture network. This approach elucidates the impact of micro-crack behaviors on large brittle shear fractures from a topological perspective and further subdivides the progressive failure stage into four distinct phases (isolated crack growth phase, crack splay phase, damage coalescence phase, and mechanical failure phase) based on the significance profile of the motif. Regression analysis reveals a positive linear and negative power correlation between fracture network density and branch number to the rock damage resistance, respectively. The damage network model introduces a novel methodology for depicting the interaction of two-dimensional (2D) projected fractures, considering the dynamic spatiotemporal development characteristics and fracture geometric variation. It helps dynamically characterize properties such as connectivity, permeability, and damage factors while comprehensively assessing damage in rock mass fracture networks.

Coral reef limestone at different depositional depths and facies differ remarkably on the textural and mineralogical characteristics, owing to the complex sedimentary diagenesis. To explore the effects of pore structure and mineral composition associated with diagenetic variation on the mechanical behavior of reef limestone, a series of quasi-static and dynamic compression tests along with microscopic examinations were performed on the reef limestone at shallow and deep burial depths. It is revealed that the shallow reef limestone (SRL) is classified as a porous aragonite-type carbonate rock with high porosity (55.3±3.2)% and pore connectivity. In comparison, the deep reef limestone (DRL) is mainly composed of dense calcite-type calcium carbonate with low porosity (4.9±1.6)% and pore connectivity. The DRL strengthened and stiffened by the tight grain framework consistently displays much higher values of the dynamic compressive strength, elastic modulus, brittleness index, and specific energy absorption than those of the SRL. The gap between two types of limestone further increases with an increase in strain rate. It appears that the failure pattern of SRL is dominated by the inherent defects like weak bonding interfaces and growth lines, revealed by the intricate fracturing network and mixed failure. Likewise, although the preexisting megapores in DRL may affect the crack propagation on pore tips to a certain distance, it hardly alters the axial splitting failure of DRL under impacts. The stress wave propagation and attenuation in SRL is primarily controlled by the reflection and diffusion caused by plenty mesopores, as well as an energy dissipation in layer-wise pore collapse and adjacent grain crushing, while the stress wave in DRL is highly hinged on the insulation and diffraction induced by the isolated megapores. This process is accompanied by the energy dissipation behavior of inelastic deformation resulted from the pore-emanated microcracking.

Objectives:: Sequential recommendation aims to recommend items that are relevant to users’ interests based on their existing interaction sequences. Current models lack in capturing users’ latent intentions and do not sufficiently consider sequence information during the modeling of users and items. Additionally, noise in user interaction sequences can affect the model’s optimization process. Methods:: This paper introduces an intent perceived sequential recommendation model (IPSRM). IPSRM employs the generalized expectation–maximization (EM) framework, alternating between learning sequence representations and optimizing the model to better capture the underlying intentions of user interactions. Specifically, IPSRM maps unlabeled behavioral sequences into frequency domain filtering and random Gaussian distribution space. These mappings reduce the impact of noise and improve the learning of user behavior representations. Through clustering process, IPSRM captures users’ potential interaction intentions and incorporates them as one of the supervisions into the contrastive self-supervised learning process to guide the optimization process. Results:: Experimental results on four standard datasets demonstrate the superiority of IPSRM. Comparative experiments also verify that IPSRM exhibits strong robustness under cold start and noisy interaction conditions. Conclusions:: Capturing latent user intentions, integrating intention-based supervision into model optimization, and mitigating noise in sequential modeling significantly enhance the performance of sequential recommendation systems.

Blasting operations, which are crucial to open-pit mine production due to their simplicity and efficiency, require precise control through accurate vibration velocity calculations. The conventional Sadowski formula mainly focuses on blast center distance but neglects the amplification effect of blasting vibration waves by terraced terrain, from which the calculated blasting vibration velocities are smaller than the actual values, affecting the safety of the project. To address this issue, our model introduces the influences of slope and time into Sadowski formula to measure safety through blast vibration displacement. In the northern section of the open-pit quartz mine in Jinchang City, Gansu Province, China, the data of a continuous blasting slope project are referred to. Our findings reveal a noticeable vibration amplification effect during blasting when a multi-stage slope platform undergoes a sudden cross-sectional change near the upper overhanging surface. The amplification vibration coefficient increases with height, while vibration waves within rocks decrease from bottom to top. Conversely, platforms without distinct cross-sectional changes exhibit no pronounced amplification during blasting. In addition, the vibration intensity decreases with distance as the rock height difference change propagates. The results obtained by the proposed blast vibration displacement equation incorporating slope shape influence closely agree with real-world scenarios. According to Pearson correlation coefficient (PPMCC) analysis, the average accuracy rate of our model is 88.84%, which exceeds the conventional Sadowski formula (46.92%).

Introduction: Neuroinflammation and autophagy are implicated in stress-related major depressive disorder (MDD), but the underlying molecular mechanisms remain largely unknown. Objectives: Here, we identified that MDD regulated by HMGB1/STAT3/p65 axis mediated microglial activation and autophagy for the first time. Further investigations were performed to uncover the effects of this axis on MDD in vivo and in vitro. Methods: Bioinformatics analyses were used to re-analysis the transcriptome data from the dorsolateral prefrontal cortex (dlPFC) of post-mortem male MDD patients. The expression level of HMGB1 and its correlation with depression symptoms were explored in MDD clinical patients and chronic social defeat stress (CSDS)-induced depression model mice. Specific adeno-associated virus and recombinant (r)HMGB1 injection into the medial PFC (mPFC) of mice, and pharmacological inhibitors with rHMGB1 in two microglial cell lines exposed to lipopolysaccharide were used to analyze the effects of HMGB1/STAT3/p65 axis on MDD. Results: The differential expression of genes from MDD patients implicated in microglial activation and autophagy regulated by HMGB1/STAT3/p65 axis. Serum HMGB1 level was elevated in MDD patients and positively correlated with symptom severity. CSDS not only induced depression-like states in mice, but also enhanced microglial reactivity, autophagy as well as activation of the HMGB1/STAT3/p65 axis in mPFC. The expression level of HMGB1 was mainly increased in the microglial cells of CSDS-susceptible mice, which also correlated with depressive-like behaviors. Specific HMGB1 knockdown produced a depression-resilient phenotype and suppressed the associated microglial activation and autophagy effects of CSDS-induced. The effects induced by CSDS were mimicked by exogenous administration of rHMGB1 or specific overexpression of HMGB1, while blocked by STAT3 inhibitor or p65 knockdown. In vitro, inhibition of HMGB1/STAT3/p65 axis prevented lipopolysaccharide-induced microglial activation and autophagy, while rHMGB1 reversed these changes. Conclusion: Our study established the role of microglial HMGB1/STAT3/p65 axis in mPFC in mediating microglial activation and autophagy in MDD.

Abstract We aimed to investigate the expression and clinic significance of Rac GTPase Activating Protein 1 (RACGAP1) in human lung adenocarcinoma (LUAD). Online database analysis revealed a significant increase in RACGAP1 mRNA expression among 26 types of tumor tissues, including LUAD tissues. Online database and tissue microarray analyses indicated that RACGAP1 expression was significantly upregulated in LUAD tissues. Genetic variation analysis identified four different genetic variations of RACGAPs in LUAD. Moreover, online database analysis showed that RACGAP1 upregulation was correlated with shorter survival in patients with LUAD. After silencing RACGAP1 expression in A549 cells using siRNA and assessing its protein levels via Western blotting, we found that RACGAP1 knockdown inhibited cell growth and induced apoptosis determined using the Cell Counting Kit-8 assay, colony formation assay, and flow cytometry. Mechanistically, western blot analysis indicated that Bax expression increased, whereas Bcl-2 expression decreased. Moreover, RACGAP1 knockdown attenuated PI3K/AKT pathway activation in lung cancer cells. Taken together, our findings showed that RACGAP1 was overexpressed in LUAD tissues and played an important role in lung cancer by increasing cell growth through the PI3K/AKT signaling pathway. This study suggests recommends evaluating RACGAP1 in clinical settings as a novel biomarker and potential therapeutic target for lung cancer.

Abstract Background In lung transplantation (LTx) surgery, veno-arterial extracorporeal membrane oxygenation (VA-ECMO) can provide mechanical circulatory support to patients with cardiopulmonary failure. However, the use of heparin in the administration of ECMO can increase blood loss during LTx. This study aimed to evaluate the safety of heparin-free V-A ECMO strategies. Methods From September 2019 to April 2022, patients who underwent lung transplantation at the First Affiliated Hospital of Guangzhou Medical University were retrospectively reviewed. A total of 229 patients were included, including 117 patients in the ECMO group and 112 in the non-ECMO group. Result There was no significant difference in the incidence of thrombus events and bleeding requiring reoperation between the two groups. The in-hospital survival rate after single lung transplantation (SLTx) was 81.08%in the ECMO group and 85.14% in the Non-ECMO group, (P = 0.585). The in-hospital survival rate after double lung transplantation (DLTx) was 80.00% in the ECMO group and 92.11% in the Non-ECMO groups (P = 0.095). Conclusions In conclusion, the findings of this study suggest that the heparin-free V-A ECMO strategy in lung transplantation is a safe approach that does not increase the incidence of perioperative thrombotic events or bleeding requiring reoperation.

Geological discontinuity (GD) plays a pivotal role in determining the catastrophic mechanical failure of jointed rock masses. Accurate and efficient acquisition of GD networks is essential for characterizing and understanding the progressive damage mechanisms of slopes based on monitoring image data. Inspired by recent advances in computer vision, deep learning (DL) models have been widely utilized for image-based fracture identification. The multi-scale characteristics, image resolution and annotation quality of images will cause a scale-space effect (SSE) that makes features indistinguishable from noise, directly affecting the accuracy. However, this effect has not received adequate attention. Herein, we try to address this gap by collecting slope images at various proportional scales and constructing multi-scale datasets using image processing techniques. Next, we quantify the intensity of feature signals using metrics such as peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). Combining these metrics with the scale-space theory, we investigate the influence of the SSE on the differentiation of multi-scale features and the accuracy of recognition. It is found that augmenting the image's detail capacity does not always yield benefits for vision-based recognition models. In light of these observations, we propose a scale hybridization approach based on the diffusion mechanism of scale-space representation. The results show that scale hybridization strengthens the tolerance of multi-scale feature recognition under complex environmental noise interference and significantly enhances the recognition accuracy of GD. It also facilitates the objective understanding, description and analysis of the rock behavior and stability of slopes from the perspective of image data.

The basic helix-loop-helix (bHLH) transcription factors play crucial roles in various processes, such as plant development, secondary metabolism, and response to biotic/abiotic stresses. Sophora flavescens is a widely used traditional herbal medicine in clinical practice, known for its abundant flavonoids as the main active compounds. However, there has been no comprehensive analysis of S. flavescens bHLH (SfbHLH) gene family reported currently. In this study, we identified 167 SfbHLH genes and classified them into 23 subfamilies based on comparative genomics and phylogenetic analysis. Furthermore, widespread duplications significantly contributed to the expansion of SfbHLH family. Notably, SfbHLH042 was found to occupy a central position in the bHLH protein-protein interaction network. Transcriptome analysis of four tissues (leaf, stem, root and flower) revealed that most SfbHLH genes exhibited high expression levels exclusively in specific tissues of S. flavescens. The integrated analysis of transcriptomics and metabolomics during pod development stages revealed that SfbHLH042 may play a central role in connecting SfbHLH genes, flavonoids, and key enzymes involved in the biosynthesis pathway. Moreover, we also checked the expression of 8 SfbHLH genes using RT-qPCR analysis to realize the expression profiles of these genes among various tissues at different cultivated periods and root development. Our study would aid to understand the phylogeny and expression profile of SfbHLH family genes, and provide a promising candidate gene, SfbHLH042, for regulating the biosynthesis of flavonoids in S. flavescens.

IntroductionDespite rapid advances in molecular biology, personalized molecular therapy remains a clinical challenge for endometrial cancer due to its complex and heterogeneous tumor microenvironment.Based on clinical findings, AIB1 is a marker molecule for poor prognosis in endometrial cancer and may serve as a potential therapeutic target. Moreover, it is well known that aerobic glycolysis plays an important role in tumour energy metabolism. It has been previously reported in various hormone-related tumour studies that AIB1 affects glycolysis and promotes tumour development. However, the link between AIB1 and aerobic glycolysis in estrogen-dependent endometrial cancer remains unclear.MethodsWe used two endometrial cancer cell lines to validate the high expression of target genes and the effect on the proliferative and invasive capacity of the tumours and verified the pattern of interactions and epigenetic modifications by CHIP and CO-IP techniques. Finally, the conclusions were validated on homozygous miceResultsIn this study, we investigated the transcriptional co-activation functions of AIB1, including its acetylation by PCAF, binding to the c-myc transcription factor, and recruitment of glycolysis-related gene promoters.DiscussionOur findings provide new clues that perturbation of normal homeostatic levels of AIB1 is linked with endometrial cancer. These findings suggest that targeting AIB1-mediated regulation of aerobic glycolysis may offer a novel therapeutic approach for endometrial cancer with high AIB1 expression, opening new avenues for personalized diagnostics and treatment strategies in this disease.

Developing high‐performance, high‐stability, and low‐cost nonprecious metal catalysts to enhance the performance of zinc–air batteries (ZABs) holds significant importance. A bifunctional catalyst consisting of cobalt oxide (CoO) nanocrystals on nitrogen‐doped reduced graphene oxide nanoribbons (N‐rGONR) as a novel substrate is successfully synthesized in this work. This synthesized bifunctional catalyst exhibits mesoporous structure, and remarkable synergistic effects between CoO nanocrystals and N‐rGONR, demonstrating excellent activity and durability in both oxygen reduction reactions and oxygen evolution reactions. Notably, the resulting aqueous electrolyte ZABs show a high discharge peak power density of 196 mW cm−2, a high specific capacity of 615.9 mAh g−1, and long‐time stability for 648 h. Furthermore, the assembly of 1D and 2D flexible solid‐state ZABs fabricated using this bifunctional catalyst exhibits stable electrochemical performance, even under severe deformation. These results underscore the considerable promise of implementing the CoO@N‐rGONR catalyst structure in next‐generation advanced energy storage and conversion devices.

Sea sand exhibits typical features of loose structure, large compressibility and poor consolidation, causing severe challenges for the construction and emergency repair of coastal engineering. A new Hybrid Non-Isocyanate Polyurethane (HNIPU) was utilized as a curing agent to prepare HNIPU-sea sand mixtures (HSM) in this study. A series of uniaxial compression and scanning electron microscopy (SEM) tests were conducted to explore the strength property and microscopic curing mechanism of HSM. As the mass ratio of polyurethane to sea sand increased from 0.1 to 0.7, the uniaxial compressive strength of HSM first increased from 8.75 MPa to 20.09 MPa then decreased to 17.90 MPa. The maximum strength was achieved at a mass ratio of 0.5. The uniaxial compressive strength increased by 79.46% and 58.41% within a temperature range of −10–60 °C and a curing time range of 10–90 min, respectively. Nevertheless, it decreased by 31.06% with an increase from nil to 10% in moisture content. The prediction formula for the uniaxial compressive strength of HSM can be expressed as a function of multiple influencing factors using regression analysis. The main factors affecting the uniaxial compressive strength of HSM are mass ratio, moisture content, curing time, temperature and gradation in sequence. Furthermore, the progressive failure of HSM were identified based on the complete stress-strain curves in conjunction with the failure mode (X-shaped conjugated shear). It is well documented that HNIPU can rapidly fill, encapsulate and cement sea sand and remarkably enhance its strength, ductility and toughness. These research results may provide an effective method for the rapid reinforcement of the beach sand foundation.

To study the anti-explosion protection effect of polyurea coating on reinforced concrete box girder, two segmental girder specimens were made at a scale of 1:3, numbered as G (without polyurea coating) and PCG (with polyurea coating). The failure characteristics and dynamic responses of the specimens were compared through conducting explosion tests. The reliability of the numerical simulation using LS-DYNA software was verified by the test results. The effects of different scaled distances, reinforcement ratios, concrete strengths, coating thicknesses and ranges of polyurea were studied. The results show that the polyurea coating can effectively enhance the anti-explosion performance of the girder. The top plate of middle chamber in specimen G forms an elliptical penetrating hole, while that in specimen PCG only shows a very slight local dent. The peak vertical displacement and residual displacement of PCG decrease by 74.8% and 73.7%, respectively, compared with those of specimen G. For the TNT explosion with small equivalent, the polyurea coating has a more significant protective effect on reducing the size of fracture. With the increase of TNT equivalent, the protective effect of polyurea on reducing girder displacement becomes more significant. The optimal reinforcement ratio, concrete strength, thickness and range of polyurea coating were also drawn.

Abstract Earthquakes triggered by dynamic disturbances have been confirmed by numerous observations and experiments. In the past several decades, earthquake triggering has attracted increasing attention of scholars in relation to exploring the mechanism of earthquake triggering, earthquake prediction, and the desire to use the mechanism of earthquake triggering to reduce, prevent, or trigger earthquakes. Natural earthquakes and large‐scale explosions are the most common sources of dynamic disturbances that trigger earthquakes. In the past several decades, some models have been developed, including static, dynamic, quasi‐static, and other models. Some reviews have been published, but explosion‐triggered seismicity was not included. In recent years, some new results on earthquake triggering have emerged. Therefore, this paper presents a new review to reflect the new results and include the content of explosion‐triggered earthquakes for the reference of scholars in this area. Instead of a complete review of the relevant literature, this paper primarily focuses on the main aspects of dynamic earthquake triggering on a tectonic scale and makes some suggestions on issues that need to be resolved in this area in the future.

Abstract When testing earthquake simulation shaking tables, it is commonly assumed that the test load, table, and actuator are integrated, which differs significantly from the actual situation and negatively impacts the accuracy of system waveform reproduction. This paper simplifies the connection between the three as a spring-damping model for simulation modeling. The effects of different load mass, different connection intrinsic frequency, different connection damping ratios, and other factors on the control performance of the system are analyzed, and based on the results of the analysis, a method to improve the effects of the connection characteristics on the performance of the system, called flexible connection reaction force compensation algorithm, is proposed. Resonance peaks caused by flexible connections reduce the effective bandwidth. To broaden the bandwidth and enhance system stability, the paper introduces a flexible connection force compensation algorithm based on a multi-parameter control algorithm to compensate for the interaction force caused by the connection characteristics. This compensation strategy expands the effective bandwidth, eliminates resonance peaks, improves the waveform correlation coefficient (CC), and reduces the root-mean-square error (RMSE).

Abstract Bisphenol F epoxy resin (EP) is often used in terminal current lead insulation of superconducting equipment because of its good insulation performance, high mechanical strength, good toughness at cryogenic temperatures, and resistance to cold shock and heat shock. However, due to the wide temperature range of 80–300 K and the strong electric field, the EP‐N2 interface is prone to surface flashover, resulting in terminal insulation failure. To improve the reliability of the current lead insulation, non‐linear conductive EP/strontium titanate (SrTiO3) composites were prepared by modification with nano filling. The changes of dielectric, surface discharge, flashover, and trap distribution characteristics of composite materials were studied, and the mechanism of SrTiO3 on the surface flashover of composite materials was analysed. The results show that the conductivity of the composite increases with the rise of SrTiO3 filling content, and the amplitude of improvement is greater under the strong electric field, showing a more significant non‐linearity. The composite has a lower trap energy level and a greater number of shallow traps compared to pure EP, which accelerates surface charge de‐trapping and reduces charge accumulation, effectively enhancing the discharge and surface flashover voltage of the composite.

In many military and civilian areas, there exists a scenario in which multiple intruders from an adversary attempt to enter important region of our own to carry out intentional malign activity. Adversarial Risk (AR) estimation is used to assess and predict the expected damage to our valuable assets from the actions of online adversaries based on measurements performed by sensors. To evaluate random and time-varying AR, this study proposes a stochastic AR estimation approach based on a Labeled Multi-Bernoulli (LMB) tracker. First, in the formulation of LMB filtering, expressions of the minimum mean squared error estimation of the stochastic AR are derived for the additive and multiplying model. Second, by combining the Gaussian mixture and sampling approximations, we devise a numerical calculation approach for the proposed AR estimations. Third, we achieve an online evaluation of the expected damage to our valuable assets from the adversary by embedding the proposed AR estimation and LMB filtering. The effectiveness and performance advantage of the proposed estimation algorithms are verified using measurements from radars, considering a simulated scenario wherein multiple lethal targets hit the radar positions.

Self-powered photodetectors which operate without external power sources hold immense promise in future photodetection systems. To achieve high-performance self-powered optoelectronic devices, efficient electron-hole pair separation is critical to generate high photocurrents. In this work, we successfully synthesized semiconducting graphene nanoribbons (GNRs) with a direct bandgap of 1.80 eV and employed them to construct a high-performance GNR/Al2O3/IGZO heterostructure photodetector. The built-in electric field in the heterojunctions enables this photodetector to exhibit remarkable performance, showing a responsivity of up to 68 mA/W, a detectivity of 8.34 × 1010 Jones, and rapid response times of 21/20 ms at zero bias. Furthermore, the photodetector features a wide spectral detection range of 405 to 1550 nm. These results highlight the promising potential of GNR/IGZO p-n heterojunction-based self-powered photodetectors in optoelectronic applications.

Semantic segmentation is an important issue in intelligent interpretation of remote sensing, playing an important role in applications such as Earth observation and land data update. However, remote sensing images often contain complex ground objects and the boundaries between them are blurred, which poses a huge challenge to the semantic segmentation task of remote sensing images. This article proposes a dual stream hybrid network (DSHNet) model, which focuses on parallel extraction of semantic and boundary features in remote sensing images, and improves the performance of semantic segmentation by fully integrating dual stream information. In the semantic stream, the ViT model pretrained on remote sensing images is used as the backbone network for feature extraction. In the boundary stream, the boundary detection operator Sobel is used to capture the boundaries of different ground objects in the image, and a boundary enhancement mechanism is taken to optimize and enhance the feature representation of ground object boundaries. In addition, DSHNet designs a feature fusion module to cross-aggregate features from both semantic and boundary streams. Compared with the state-to-art semantic segmentation methods, DSHNet model has achieved the best performance on two datasets of Yellow River Estuary Wetland and Gaofen image dataset.

The AlCoCrFeNi2.1 eutectic high-entropy alloy (Ni2.1 EHEA), as an exemplary representative of the high-entropy alloy family, has garnered significant research attention owing to its exceptional comprehensive properties. In this study, we investigated the influence of various growth velocities on the microstructure, lamellar spacing, and mechanical properties of the Ni2.1 EHEA. We observed that at lower growth velocities, the structure consisted of an alternating face-centered-cubic (FCC) phase and B2 phase lamellae aligned in a single direction, with the lamellae orientation parallel to the direction of the heat flow. The yield strength increased with the growth rate, while the ultimate tensile strength decreased with increasing the growth velocity. Ductility remained relatively consistent, and a double yield phenomenon was observed in the elastic-plastic deformation region. Under conditions of high growth velocities, the microstructure transitioned from a single-directional full lamellar structure to a multi-stage lamellar arrangement. The most favorable comprehensive mechanical properties were achieved at a growth rate of 200 μm/s, resulting in a yield strength of 450 MPa, an ultimate tensile strength of 1092 MPa, and a remarkable ductility of ∼32% in the directionally solidified samples—double that of the arc-melted sample. The evolution law of directional solidification structures under the coupling effect of different magnetic fields and different growth rates was studied. The interaction of the thermoelectric-magnetic force and thermoelectric-magnetic convection and the potential mechanism of microstructure evolution under the effect of magnetic field were deeply analyzed. The results reveal that at a growth rate of 2 μm/s, the spacing between eutectic layers decreases as the magnetic induction intensity increases, leading to the transformation of some regular layers into spherical layers. Similarly, at a growth velocity of 10 μm/s, the eutectic structure exhibited a Columnar-to-equiaxed transition (CET). However, as the growth rate further increases, the limited exposure time to the magnetic field prevented significant structural changes.

Background: Ischemic stroke is a severe disorder with high incidence, disability rate and mortality. Multiple pathogenesis mechanisms are involved in ischemic stroke, such as inflammation and neuronal cell apoptosis. Protein inhibitor of activated signal transducer and activators of transcription 1 (PIAS1) plays a crucial role in various biological processes, including inflammation. PIAS1 is also downregulated in ischemia-reperfusion injury and involved in the disease processes. However, the role of PIAS1 in cerebral ischemia is unclear. Methods: Sprague-Dawley (SD) rats were induced with middle cerebral artery occlusion (MCAO). The role and mechanisms of PIAS1 in ischemic cerebral infarction were explored by Longa test, 2,3,5-triphenyltetrazolium chloride (TTC) staining, Morris water maze (MWM) test, hematoxylin-eosin (HE) staining, quantification of brain water content, reverse transcription-quantitative polymerase chain reaction (RT-qPCR), enzyme-linked immunosorbent assay (ELISA), terminal deoxynucleotidyl transferase deoxyuridine triphosphate (dUTP) nick end labeling (TUNEL), Western blot and immunofluorescence assays. Results: The expression of PIAS1 in MCAO-induced rat was declined compared to sham rats. Overexpression of PIAS1 reduced the Longa neurological scores, the percent of infarction area, the pathological abnormality, the escape latency of swimming and the percent of brain water content, and increased the number of platform crossings and time in the target quadrant in the MCAO-induced rats. Besides, overexpression of PIAS1 decreased the MCAO-induced the contents of IL-1β, IL-6 and TNF-α, but further elevated the concentrations of IL-10 in both sera and brain tissues. Moreover, overexpression of PIAS1 reversed the MCAO-induced apoptosis rate and the relative protein level of Bax, cleaved caspase3 and Bcl-2. Overexpression of PIAS1 also reversed the level of proteins involved in NF-κB pathway. Conclusion: PIAS1 reduced inflammation and apoptosis, thereby alleviating ischemic cerebral infarction in MCAO-induced rats through regulation NF-κB pathway.

ABSTRACTThis study is to explore the proportion of significant liver histopathology in hepatitis B e antigen (HBeAg)-negative chronic hepatitis B virus (HBV)-infected patients with normal alanine aminotransferase (ALT) and investigate noninvasive indicators for predicting significant liver histopathology. A total of 201 HBeAg-negative chronic HBV-infected patients with normal ALT who underwent liver biopsy were involved in this study. Significant liver histological changes were defined as necroinflammation grade ≥2 (G ≥ 2) and/or fibrosis stage ≥2 (S ≥ 2). The results showed that 42.3% (85/201) and 45.8% (92/201) of the HBeAg-negative patients with normal ALT have significant liver necroinflammation (G ≥ 2) and fibrosis (S ≥ 2), respectively. High normal ALT (>22 U/L), high level of serum HBV DNA (>3.42 log IU/mL), and low level of prealbumin (PA) (24 U/L) and high level of FIB-4 (>1.53) were independent predictors for significant liver fibrosis, and the predictive value of the combined indicators was 0.740 (P < 0.001). In conclusion, more than 40% of HBeAg-negative patients with normal ALT have significant liver histopathology and require immediate antiviral treatment. ALT, PA, HBV DNA, and FIB-4 can independently predict significant liver inflammation and fibrosis for HBeAg-negative patients with normal ALT. Lowering the treatment threshold of ALT may benefit the HBeAg-negative chronic HBV-infected patients.IMPORTANCEHepatitis B e antigen (HBeAg)-negative chronic hepatitis B virus (HBV)-infected patients with normal alanine aminotransferase (ALT) were supposed to have a low risk of progression to cirrhosis or hepatocellular carcinoma, and it was recommended to regularly follow up or undergo liver biopsy to assess liver histopathology according to the major international guidelines. However, this study indicates that a considerable number of HBeAg-negative chronic HBV-infected patients with normal ALT have significant liver histopathology and require immediate antiviral treatment. Besides, several clinical commonly used noninvasive indicators were found that can be used to predict significant liver histopathology; thereby liver biopsy might be avoided for HBeAg-negative chronic HBV-infected patients with normal ALT.

Abstract This paper presents a numerical modeling method that integrates a grain-growth model and Voronoi polygon configuration to investigate the thermal damage characteristics and fracture mechanism of granite under three distinct thermal conditions: rapid heating, slow heating, and cycle heating. The proposed method accurately simulates the intra-grain damage modes of mineral particles and the mechanical responses of granite. Through the simulation, it was observed that slow heating induces more significant deterioration compared to rapid heating, while cycle heating leads to wider crack openings and apparent brittle damage during the cooling phase. Furthermore, the peak strength and elastic modulus of granite demonstrate a significant decrease with increasing temperature under all three heating conditions. Notably, slow heating exhibits ductility characteristics in its post-peak residual strength. This study also analyzes the effects of different thermal conditions on the damage evolution pattern and cracking mechanism of rocks. It is found that slow heating generates a higher number of cracks with a broader distribution and intra-grain damage, whereas cycle heating results in severe cracks and fractures. The findings of this study have practical implications for preventing and controlling thermal disasters in deep rock engineering.

Abstract Background Phospholipases As (PLAs) are acyl hydrolases that catalyze the release of free fatty acids in phospholipids and play multiple functions in plant growth and development. The three families of PLAs are: PLA1, PLA2 (sPLA), and patatin-related PLA (pPLA). The diverse functions that pPLAs play in the growth and development of a broad range of plants have been demonstrated by prior studies. Methods Genome-wide analysis of the pPLA gene family and screening of genes for expression verification and gene silencing verification were conducted. Additionally, pollen vitality testing, analysis of the pollen expression pattern, and the detection of POD, SOD, CAT, MDA, and H2O2 were performed. Result In this study, 294 pPLAs were identified from 13 plant species, including 46 GhpPLAs that were divided into three subfamilies (I-III). Expression patterns showed that the majority of GhpPLAs were preferentially expressed in the petal, pistil, anther, and ovule, among other reproductive organs. Particularly, GhpPLA23 and GhpPLA44, were found to be potentially important for the reproductive development of G. hirsutum. Functional validation was demonstrated by VIGS which showed that reduced expression levels of GhpPLA23 and GhpPLA44 in the silenced plants were associated with a decrease in pollen activity. Moreover, a substantial shift in ROS and ROS scavengers and a considerable increase in POD, CAT, SOD, and other physiological parameters was found out in these silenced plants. Our results provide plausibility to the hypothesis that GhpPLA23 and GhpPLA44 had a major developmental impact on cotton reproductive systems. These results also suggest that pPLAs are important for G. hirsutum’s reproductive development and suggest that they could be employed as potential genes for haploid induction. Conclusions The findings of the present research indicate that pPLA genes are essential for the development of floral organs and sperm cells in cotton. Consequently, this family might be important for the reproductive development of cotton and possibly for inducing the plant develop haploid progeny.

This study examined the thermal reflective properties of composite inorganic coatings applied to various wall types. It evaluated the influence of these coatings on the thermal insulation and reflectivity of the walls. The findings indicate that coating application markedly enhances a wall’s thermal insulation capabilities and increases its heat flux reflection ratio. These results offer crucial theoretical backing and practical guidance for the future use of coating technologies in construction. By refining the coating formulations and application processes, the thermal insulation properties of walls can be further enhanced, thus making a significant contribution to building energy efficiency and environmental protection. Consequently, this research provides essential references and insights for advancing coating technology in the construction industry.

Coloration is a crucial trait that allows species to adapt and survive in different environments. Wild boars exhibit alternating black (dark) and yellow (light) longitudinal stripes on their back during their infancy (juvenile stripes), and as adults, they transform into uniform wild-type coat color. Aiming to record the procedure of juvenile stripes disappearing, piglets (WD) with juvenile stripes were produced by crossing a wild boar with Duroc sows, and photos of their coat color were taken from 20 d to 220 d. The pigments in the hairs from the black and yellow stripes were determined. Furthermore, the differentially expressed genes between the black and yellow stripes were investigated in 5 WD with the age of 30 d using whole-transcriptome sequencing to explore the genetic mechanism of the juvenile stripes. The juvenile stripes started to disappear at about 70 d, and stripes were not distinguished with the naked eye at about 160 d; that is, the juvenile stripe completely disappeared. A hotspot of a differentially expressing (DE) region was found on chromosome 13, containing/covering 2 of 13 DE genes and 8 of 10 DE lncRNAs in this region. A network among ZIC4, ssc-miR-532-3p, and ENSSSCG00000056225 might regulate the formation of juvenile stripes. Altogether, this study provides new insights into spatiotemporal coat color pattern.

Abstract Background Cytokinin oxidase/dehydrogenase (CKX) plays a vital role in response to abiotic stress through modulating the antioxidant enzyme activities. Nevertheless, the biological function of the CKX gene family has yet to be reported in cotton. Result In this study, a total of 27 GhCKXs were identified by the genome-wide investigation and distributed across 18 chromosomes. Phylogenetic tree analysis revealed that CKX genes were clustered into four clades, and most gene expansions originated from segmental duplications. The CKXs gene structure and motif analysis displayed remarkably well conserved among the four groups. Moreover, the cis-acting elements related to the abiotic stress, hormones, and light response were identified within the promoter regions of GhCKXs. Transcriptome data and RT-qPCR showed that GhCKX genes demonstrated higher expression levels in various tissues and were involved in cotton’s abiotic stress and phytohormone response. The protein-protein interaction network indicates that the CKX family probably participated in redox regulation, including oxidoreduction or ATP levels, to mediate plant growth and development. Functionally identified via virus-induced gene silencing (VIGS) found that the GhCKX14 gene improved drought resistance by modulating the antioxidant-related activitie. Conclusions In this study, the CKX gene family members were analyzed by bioinformatics, and validates the response of GhCKX gene to various phytohormone treatment and abiotic stresses. Our findings established the foundation of GhCKXs in responding to abiotic stress and GhCKX14 in regulating drought resistance in cotton.

The providers of butyric acid, Clostridium butyricum (CB), sodium butyrate (SB), and tributyrin (TB), have been extensively studied as aquafeed additives in recent years. However, no comparative study has been reported on the probiotic effects of CB, SB, and TB as feed additives on sea cucumber (Apostichopus japonicus). A 63-day feeding trial was performed to assess the effects of dietary live cells of C. butyricum (CB group, the basal diet supplemented with 1% CB), sodium butyrate (SB group, the basal diet supplemented with 1% SB), and tributyrin (TB group, the basal diet supplemented with 1% TB) on the growth, non-specific immunity, and intestinal microbiota of A. japonicus with a basal diet group as the control. Results indicated that all three additives considerably increased A. japonicus growth, with dietary CB having the optimal growth-promoting effect. Of the seven non-specific enzyme parameters measured in coelomocytes of A. japonicus (i.e., the activities of phagocytosis, respiratory burst, superoxide dismutase, alkaline phosphatase, acid phosphatase, catalase, and lysozyme), dietary CB, SB, and TB considerably increased the activities of six, five, and six of them, respectively. The immune genes (Aj-p105, Aj-p50, Aj-rel, and Aj-lys) expression in the mid-intestine tissues of A. japonicus was significantly increased by all three additives. The CB group had the highest expression of all four genes. Additionally, the relative expression of Aj-p105, Aj-p50, and Aj-lys genes was significantly up-regulated in the three additive groups after stimulation with inactivated Vibrio splendidus. Dietary CB enhanced the intestinal microbial diversity and richness in A. japonicus while dietary TB decreased them. Meanwhile, dietary CB, SB, and TB significantly enhanced the abundance of Firmicutes, unclassified_f_Rhodobacteraceae, and Proteobacteria, respectively, while dietary CB and SB reduced the abundance of Vibrio. Dietary CB and SB improved the stability of microbial ecosystem in the intestine of A. japonicus. In contrast, dietary TB appeared to have a negative effect on the stability of intestinal microbial ecosystem. All three additives improved the intestinal microbial functions associated with energy production and immunity regulation pathways, which may contribute directly to growth promotion and non-specific immunity enhancement in A. japonicus. Collectively, in terms of enhancing growth and non-specific immunity, as well as improving intestinal microbiota, dietary live cells of C. butyricum exhibited the most effective effects in A. japonicus.

Abstract Acoustic cardiography is a completely new technology, it has great advantages in the rapid diagnosis of cardiovascular diseases. The purpose of this study was to investigate the clinical value of the fourth heart sound (S4), cardiac systolic dysfunction index (SDI), and the cardiac cycle time-corrected electromechanical activation time (EMATc) in the prediction of post-percutaneous coronary intervention (PCI) early ventricular remodeling (EVR) in patients with acute myocardial infarction (AMI). We recruited 161 patients with AMI of 72-h post-PCI, including 44 EVR patients with left ventricular ejection fraction (LVEF)

With the growing energy crisis and environmental problems, distributed photovoltaic (PV), as a clean and renewable form of energy, is receiving more and more attention. However, the large-scale access to distributed PV brings a series of challenges to the distribution network, such as voltage fluctuation, frequency deviation, protection coordination, and other problems. In order to solve these problems, this paper provides a research overview of distribution network consumption strategies containing distributed PV. Firstly, this paper introduces the characteristics of distributed PV and its impact on the distribution grid. Then, the difficulties and challenges of distributed PV consumption are analyzed from the technical and economic levels. On this basis, a comprehensive consumption strategy is proposed, including the following aspects: firstly, it is mentioned to optimize the access method of distributed PV and to reduce the impact on the distribution grid by reasonably choosing the access point and access capacity of distributed PV. Secondly, it summarizes the ways to improve the regulation capacity of distribution networks and improve the consumption capacity of distribution networks for distributed PV through the introduction of energy storage equipment, flexible loads, and other means. Finally, advanced control strategies are summarized to improve the stability and reliability of the distribution network by implementing measures such as power prediction, voltage control, and protection coordination for distributed PV. Overall, this paper synthesizes the research on distribution network consumption strategies containing distributed PV from various aspects, which provides certain theoretical guidance and practical reference for solving distributed PV consumption problems.

Bend sections are ubiquitous in natural sandy river systems. This study employs Computational Fluid Dynamics–Discrete Phase Model (CFD-DPM) methodology to analyze particle transport dynamics in U-bend channel flows, focusing on the distinctions between partially vegetated (Case No.1) and non-vegetated (Case No.2) scenarios. The research aims to unravel the intricate relationships among bending channel-induced secondary flow, vegetation blockage, and particle aggregation, employing both quantitative and qualitative approaches. (I) The key findings reveal that vegetation near the inner walls of curved channels markedly diminishes the intensity of secondary circulation. This reduction in circulation intensity is observed not only within vegetated areas but also extends to adjacent non-vegetated zones. Additionally, the study identifies a close correlation between vertical vortices and particle distribution near the channel bed. While particle distribution generally aligns with the vortices’ margin, dynamic patch-scale eddies near vegetation patches induce deviations, creating wave-like patterns in particle distribution. (II) The application of the Probability Density Function (PDF) provides insights into the radius-wise particle distribution. In non-vegetated channels, particle distribution is primarily influenced by secondary flow and boundary layers. In contrast, the presence of vegetation leads to a complex mixing layer, altering the particle distribution pattern and maximizing PDF values in non-vegetated free flow subzones. (III) Furthermore, the research quantifies spatial–temporal sediment heterogeneity through PDF variance. The findings demonstrate that variance in non-vegetated channels increases towards the outer wall in bending regions. Vegetation-induced turbulence causes higher variance, particularly in the mixing layer subzone, underscoring the significance of eddy size in sediment redistribution. (IV) The study of vertical concentration profiles in vegetated U-bend channels offers additional insights, while secondary flow in non-vegetated channels facilitates upward sediment transport and vegetation presence, although increasing the Turbulent Kinetic Energy (TKE), restricts channel space, and impedes secondary flow, thereby reducing vertical particle suspension. Sediment concentrations are found to be higher in the lower layers of vegetated bends, contrary to the pattern in non-vegetated bends. These findings highlight the complex interplay between vegetation, secondary flow, and sediment transport, illustrating the reduced effectiveness of secondary flow in promoting vertical particle transportation in bending channels due to the vegetation obstruction.

Binary tropical cyclones (BTCs) typically refer to the coexistence of two tropical cyclones (TCs) within a specific distance range, often resulting in disastrous rainstorms in coastal areas of China. However, the differences in rainfall and underlying causes between BTC-influenced typhoons and general typhoons remain unclear. In this article, the TC closer to the rainfall center in the BTC is referred to as the target typhoon (tTC), while the other is termed the accompanying typhoon (cmp_TC). This study compares and analyzes the rainfall differences and potential causes of tTCs and similar typhoons (sim_TC) with a comparable track but which are unaffected by BTCs from 1981 to 2020. The results show that: (1) On average, tTCs and cmp_TCs experience 18.79% heavier maximum daily rainfall compared to general TCs, with a significantly increased likelihood of rainfall ≥250 mm. (2) Given similar tracks, the average rainfall for tTCs (212.62 mm) is 30.2% heavier than that for sim_TCs (163.30 mm). (3) The analysis of potential impact factors on rainfall (translation speed, intensity, direction change) reveals that sim_TCs move at an average of 21.38 km/h, which is about 19.66% faster than the 17.87 km/h of tTCs, potentially accounting for the observed differences in rainfall. (4) Further investigation into the causes of west–east oriented BTC rainfall in the Northern Fujian (N_Fujian) region suggests that water vapor transport and slowing down of the translation speed are the possible mechanisms of BTC influence. Specifically, 80% of tTCs receive water vapor from the direction of their cmp_TC, and the steering flow for tTC is only 59.88% of that for sim_TC.

In recent years, the frequency and intensity of global extreme weather events have gradually increased, leading to significant changes in urban rainfall patterns. The uneven distribution of rainfall has caused varying degrees of water security issues in different regions. Accurately grasping the spatiotemporal distribution patterns of rainfall is crucial for understanding the hydrological cycle and predicting the availability of water resources. This study collected rainfall data every five minutes from 62 rain gauge stations in the main urban area of Kunming City from 2019 to 2021, constructing an unsupervised hybrid dimensionality reduction-clustering (HDRC) model. The model employs the Locally Linear Embedding (LLE) algorithm from manifold learning for dimensionality reduction of the data samples and uses the dynamic clustering K-Means algorithm for cluster analysis. The results show that the model categorizes the rainfall in the Kunming area into three types: The first type has its rainfall center distributed on the north shore of Dian Lake and the southern part of Kunming’s main urban area, with spatial dynamics showing the rainfall distribution gradually developing from the Dian Lake water body towards the land. The second type’s rainfall center is located in the northern mountainous area of Kunming, with a smaller spatial dynamic change trend. The water vapor has a relatively fixed and concentrated rainfall center due to the orographic uplift effect of the mountains. The third type’s rainfall center is located in the main urban area of Kunming, with this type of rainfall showing smaller variations in all indicators, mainly occurring in May and September when the temperature is lower, related to the urban heat island effect. This research provides a general workflow for spatial rainfall classification, capable of mining the spatiotemporal distribution patterns of regional rainfall based on extensive data and generating typical samples of rainfall types.

Summary: Chiral 1,2,3,4-tetrahydroquinoxalines are ubiquitous in natural products and bioactive molecules. Herein, we disclose a protocol for stereodivergent asymmetric hydrogenation of disubstituted quinoxalines for the preparation of both cis- and trans-enantioenriched disubstituted tetrahydroquinoxalines (up to >20:1 d.r. and 99% ee). We describe steps for synthesis of ligands and substrate, setup of hydrogenation of disubstituted quinoxalines, and purification of products. Additionally, we provide detailed diagrams of the hydrogenation installation.For complete details on the use and execution of this protocol, please refer to Liu et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

ABSTRACTObjectives To determine the impact of pretransplant measurable residual disease (pre-MRD) and the efficacy of maintenance therapy in t(8;21) acute myeloid leukemia (AML) patients after allogeneic hematopoietic cell transplantation (allo-HCT).Methods We retrospectively analyzed 100 t(8;21) AML patients who underwent allo-HCT between 2013 and 2022. 40 patients received pre-emptive therapy including immunosuppressant adjustment, azacitidine, and donor lymphocyte infusion (DLI) combined with chemotherapy. 23 patients received prophylactic therapy, including azacitidine or chidamide.Results Patients with a positive pre-MRD (pre-MRDpos) had a higher 3-year cumulative incidence of relapse (CIR) (25.90% [95% CI, 13.87%–39.70%] vs 5.00% [95% CI, 0.88%–15.01%]; P = 0.008). Pre-MRDpos patients were less likely to have a superior 3-year disease-free survival (DFS) (40.83% [95% CI, 20.80%–80.16%]) if their MRD was still positive at 28 days after transplantation (post-MRD28pos). The 3-year DFS and CIR were 53.17% (95% CI, 38.31% – 73.80%) and 34.87% (95% CI, 18.84% – 51.44%), respectively, for patients receiving pre-emptive interventions after molecular relapse. The 3-year DFS and CIR were 90.00% (95%CI, 77.77% – 100%) and 5.00% (95%CI, 0.31% – 21.10%), respectively, for high-risk patients receiving prophylactic therapy. In most patients, epigenetic-drug-induced adverse events were reversible with dose adjustment or temporary discontinuation.Conclusion Patients with pre-MRDpos and post-MRD28pos were more likely to have higher rates of relapse and inferior DFS, even after receiving pre-emptive interventions. Prophylactic therapy may be a better option for high-risk t(8;21) AML patients; however, this warrants further investigation.

Photo-mediated ultrasound therapy (PUT) is a cavitation-based, highly selective antivascular technique. In this study, the effectiveness and safety of PUT on cutaneous vascular malformation was examined through in vivo experiments in a clinically relevant chicken wattle model, whose microanatomy is similar to that of port-wine stain and other hypervascular dermal diseases in humans. Assessed by optical coherence tomography angiography, the blood vessel density in the chicken wattle decreased by 73.23% after one session of PUT treatment in which 0.707 J/cm2 fluence laser pulses were applied concurrently with ultrasound bursts (n = 7, P < .01). The effectiveness of removing blood vessels in the skin at depth up to 1 mm was further assessed by H&E-stained histology at multiple time points, which included days 1, 3, 7, 14, and 21 after treatment. Additional immunohistochemical analyses with CD31, caspase-3, and Masson’s trichrome stains were performed on day 3 after treatment. The results show that the PUT-induced therapeutic effect was confined and specific to blood vessels only, whereas unwanted collateral damage in other skin tissues such as collagen was avoided. The findings from this study demonstrate that PUT can efficiently and safely remove hypervascular dermal capillaries using laser fluence at a level that is orders of magnitude smaller than that used in conventional laser treatment of vascular lesions, thus offering a safer alternative technique for clinical management of cutaneous vascular malformations.

In this paper, six major cities in the Beijing-Tianjin-Hebei region of China are classified into two groups, namely core city (Beijing) and industrial cities. The objective is to analyze the moderating effect of urban endowments in different urban contexts on the environmental regulation-productivity relationship using an econometric model. The results are: As environmental regulation intensifies, production in Beijing's high-polluting industries rises after falling, showing “innovation compensation” and “inefficient exit” effects. In contrast, the high-polluting industries in the industrial cities exhibit a “compliance cost” effect. In Beijing, four urban endowment factors, including economic development, technological innovation, human capital, and government intervention, can provide supportive conditions for business development under environmental regulatory pressure, primarily by reducing the “compliance cost” effect and enhancing the “innovation compensation” effect. In industrial cities, on the other hand, urban endowment factors have not had a positive moderating effect, and government intervention has even had a negative effect. We argue that government intervention may be the more fundamental urban endowment factor, which may affect the moderating outcomes of other endowment factors. Based on these findings, we propose that governments should make greater use of guiding and incentive-based environmental policy instruments, while reducing administrative interventions. Appropriate policy instruments can activate the positive moderating role of urban endowments and thus provide a better supportive environment for firms' technological innovation.

Summary: Drought can adversely influence the crop growth and production. Accordingly, sunflowers have strong adaptability to drought; hence, we conducted analyses for sunflower seedlings with drought stress and rehydration drought acclimation through physiological measurements and transcriptomics. It showed that drought can cause the accumulation of ROS and enhance the activity of antioxidant enzymes and the content of osmolytes. After rehydration, the contents of ROS and MDA were significantly reduced concomitant with increased antioxidant activity and osmotic adjustment. Totally, 2,589 DEGs were identified among treatments. Functional enrichment analysis showed that DEGs were mainly involved in plant hormone signal transduction, MAPK signaling, and biosynthesis of secondary metabolites. Comparison between differentially spliced genes and DEGs indicated that bHLH025, NAC53, and SINAT3 may be pivotal genes involved in sunflower drought resistance. Our results not only highlight the underlying mechanism of drought stress and rehydration in sunflower but also provide a theoretical basis for crop genetic breeding.

Abstract To investigate the disturbance‐induced shear instability mechanism of structural catastrophe in the deep rock mass, MTS 815 material testing machine was used to carry out quasi‐static loading tests and disturbance shear tests on symmetrical regular dentate joints of two materials at three undulation angles under specific initial static stress, disturbance frequency, and peak value. The test results indicate that: (i) the total ultimate instability displacement is only related to the intrinsic properties of the joints but not to the initial static stress and disturbance parameters; (ii) the cumulative irreversible displacement required for the disturbance instability conforms to the logistic inverse function relationship with the number of disturbances, displaying the variation trend of “rapid increase in the front, stable in the middle, and sudden increase in the rear”; (iii) the accumulation of plastic deformation energy is consistent with the evolution law of irreversible displacement of joints and the overall proportion of hysteretic energy is not large; (iv) the dissipated energy required for the instability of each group of joints is basically the same under various disturbance conditions, and this energy is mainly controlled by the initial shear stress and has no connection with the disturbance parameters. The stability of the total disturbance deformation and the disturbance energy law of the joints revealed in the tests provide data support for reasonably determining the disturbance instability criterion of joints.

Cheese production produces a large amount of organic wastewater, and untreated discharge is extremely harmful to the environment, which also wastes many resources. Based on introducing the main components of cheese whey wastewater, this paper reviews the treatment methods and resource utilization of cheese whey wastewater at home and abroad that have been used in recent years. The paramount manners of whey wastewater treatment and use are the membrane recovery technology of the main components of the cheese whey wastewater, the treatment technology of cheese whey wastewater, and the physical, chemical, and biological conversion of whey wastewater into biofuels (hydrogen, methane, and ethanol), electrical energy, and chemical commodities (lactic acid, propionic acid, and biopolymers). In view of the above research status, the prospect of the implementation of cheese whey wastewater treatment method is prospected, which aims to integrate different recycling routes more reasonably to determine the best treatment method for cheese whey wastewater.

This paper investigates the effects of high magnetic field on electrical treeing of silicone rubber (SiR). Experimental results show that electrical trees are more easily to be initiated and spread further along the direction of electric field under the effects of high magnetic field. When the direction of high magnetic field is perpendicular to that of electric field, magnetic field with higher magnetic flux density also results in larger accumulated damage area. Splitting of energy band structure and changes in polarization characteristics result in a lower interface barrier and more serious partial discharge, thus causing the weakened resistance to electrical treeing in high magnetic field. Based on the insulation degradation mechanism, SiR was modified by adding ferroferric oxide (Fe3O4) nanoparticles to improve its insulation performance in high magnetic field. Moderate addition amount of Fe3O4 nanoparticles is proved to be able to suppress electrical treeing in high magnetic field by forming quantum dots, modifying polarization properties and partial discharge behavior. Excessive addition of Fe3O4 nanoparticles has negative effects on suppressing electrical treeing due to the magnetization of the nanocomposites.

High magnetic field causes premature failure of insulation. In order to improve the breakdown strength of silicone rubber (SiR), different filler contents of ferroferric oxide (Fe3O4) nanoparticles were added. Experimental results show that 1 wt% addition amount of ferromagnetic nanoparticles is beneficial to improve the AC breakdown strength of SiR by 5.40% in 12 T magnetic field due to their ability to regulate dielectric polarization and partial discharge (PD) behavior, resulting from the relative higher permittivity and permeability of Fe3O4. Magnetization of Fe3O4 nanoparticles results in 3.33% decrease of DC breakdown strength with 2 wt% filler content in 12 T magnetic field. Fluorination treatment was carried out and proved to be able to improve the DC breakdown strength of SiR/Fe3O4 nanocomposites by 8.84% in 12 T magnetic field with the treatment time being 5 minutes, resulting from the regulation of surface traps. Fluorination treatment weakened the magnetism of nanoparticles, weakening their regulation on insulation polarization and PD. Adding an appropriate amount of ferromagnetic nanoparticles before the fluorination of SiR/Fe3O4 nanocomposites can improve the AC and DC breakdown strength by 0.64% and 8.81% respectively at the same time in high magnetic field.

Multimodal biometric system has received increasing interest as it offers a more secure and accurate authentication solution than unimodal systems. However, existing biometric fusion methods are still inadequate in dealing with correlations and redundancy of multimodal features simultaneously, causing bottlenecks in performance improvement. To overcome the above problem, this paper proposes an end-to-end multimodal finger recognition model that incorporates attention mechanisms into a similarity-aware encoder for accurate recognition results. Firstly, due to the different distribution of fingerprint and finger vein images, we propose a finger asymmetric backbone network (FAB-Net) for extracting discriminative intra-modal features, which reduces the network width by efficient utilization of feature maps. Then, a novel attention-based encoder fusion network (AEF-Net) with fused similarity performs dimensionality reduction-based fusion on multimodal multilevel features to alleviate performance degradation due to information redundancy. We also introduce channel attention in AEF-Net, which differs from the traditional attention mechanism by considering interdependencies between modalities to further improve performance. Extensive recognition experiments are conducted on three multimodal finger databases to verify the effectiveness of our method compared to state-of-the-art methods. Detailed ablation studies have also been carried out, which demonstrated that encoder-based reconstruction of redundant information can improve recognition performance.

Abstract Major depressive disorder (MDD) involves changes in lipid metabolism, but previous findings are contradictory. Mesencephalic astrocyte-derived neurotrophic factor (MANF) is considered to be a regulator of lipid metabolism. To date, the function of MANF has been studied in many brain disorders, but not in MDD. Therefore, to better understand the role of lipids in MDD, this study was conducted to examine lipid levels in the serum of MDD patients and to investigate the potential function of MANF in MDD. First, the data on total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglyceride (TG) in serum from 354 MDD patients and 360 healthy controls (HCs) were collected and analyzed. The results showed that there were significantly lower concentrations of TC and LDL-C in MDD patients compared with HCs, and TC levels were positively correlated with LDL-C levels. Bioinformatics analysis indicated that MANF/EWSR1/ANXA6 pathway might serve as the connecting bridge through which hypolipidemia played a functional role in MDD. Second, to verify this hypothesis, serum samples were collected from 143 MDD patients, and 67 HCs to measure the levels of MANF, EWSR1, and ANXA6 using ELISA kits. The results showed that compared to HCs, MDD patients had a significantly lower level of MANF and higher levels of ANXA6 and EWSR1, and these molecules were significantly correlated with both TC level and Hamilton Depression Rating Scales (HDRS) score. In addition, a discriminative model consisting of MANF, EWSR1, and ANXA6 was identified. This model was capable of distinguishing MDD subjects from HCs, yielded an area under curve of 0.9994 in the training set and 0.9569 in the testing set. Taken together, our results suggested that MANF/EWSR1/ANXA6 pathway might act as the bridge between hypolipidemia and MDD, and these molecules held promise as potential biomarkers for MDD.

Abstract Deep learning (DL) and machine learning contribute significantly to basic biology research and drug discovery in the past few decades. Recent advances in DL-based generative models have led to superior developments in de novo drug design. However, data availability, deep data processing, and the lack of user-friendly DL tools and interfaces make it difficult to apply these DL techniques to drug design. We hereby present ReMODE (Receptor-based MOlecular DEsign), a new web server based on DL algorithm for target-specific ligand design, which integrates different functional modules to enable users to develop customizable drug design tasks. As designed, the ReMODE sever can construct the target-specific tasks toward the protein targets selected by users. Meanwhile, the server also provides some extensions: users can optimize the drug-likeness or synthetic accessibility of the generated molecules, and control other physicochemical properties; users can also choose a sub-structure/scaffold as a starting point for fragment-based drug design. The ReMODE server also enables users to optimize the pharmacophore matching and docking conformations of the generated molecules. We believe that the ReMODE server will benefit researchers for drug discovery. ReMODE is publicly available at http://cadd.zju.edu.cn/relation/remode/ . Graphical Abstract