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Highlights The bi-phase FeCoNiCr0.4Cu0.2/(FeCoNiCrCu)3O4 high-entropy composites are innovatively constructed for the first time by low-temperature oxygen bath strategy. The bi-phase high-entropy composites (BPHEC) can precisely regulate the electromagnetic genes, realizing the ideal ultra-broadband and temperature-stable electromagnetic wave absorption. Simultaneously, the formation mechanism of BPHEC during low-temperature oxygen bath and the regulation mechanism of electromagnetic genes are elucidated.

Abstract Caving mining in extra-thick coal seams induces large-scale overburden movement, leading to more intense fracture processes in key strata, more significant surface subsidence, and frequent dynamic disasters in mines. This study, using the N34-2 caving face of the 17th coal seam at Junde Mine as a case study, aims to investigate the time-varying linkage mechanism between surface subsidence, microseismic characteristics, and fracture scales of the overburden’s key strata under such mining conditions. Based on Timoshenko’s theory, a bearing fracture mode for the overburden’s key strata is proposed, and corresponding fracture criteria are established. The fracture modes and step distances of the N34-2 working face were calculated theoretically and verified using microseismic localization data, showing that higher key strata are more prone to bearing failure, leading to a significant increase in fracture step distances. Numerical simulations and surface monitoring techniques were employed to comprehensively analyze the main controlling factors for surface subsidence. To further clarify the linkage mechanism between the fracture of high-position key strata and surface subsidence, the full fracture cycle under extra-thick coal seam caving mining is divided into four sub-processes: short-term fracture, rapid movement, compaction stability, and energy accumulation. The dynamic relationship between overburden movement, microseismic data, and surface subsidence responses is analyzed for each sub-process, establishing a time-varying linkage system. This approach offers a more systematic and accurate method to predict and assess the overburden movement and fracture processes, providing new insights for the prevention and control of rock burst disasters in extra-thick coal seams.

Abstract Honeycomb and kagome lattices can host propagating excitations with non-trivial topology as defined by their evolution along closed paths in momentum space. Excitations on such lattices can also be momentum-independent, and the associated flat bands are of interest due to strong interactions between heavy quasiparticles. Here, we report the discovery — using circularly polarized X-rays for the unambiguous isolation of magnetic signals — of a nearly flat spin-wave band and large (compared to elemental iron) orbital moment in the metallic ferromagnet Fe3Sn2 with compact AB-stacked kagome bilayers. As a function of out-of-plane momentum, the nearly flat optical mode and the global rotation symmetry-restoring acoustic mode are out of phase, consistent with a bilayer exchange coupling that is larger than the already large in-plane couplings. The defining units of this topological metal are therefore triangular lattices of octahedral iron clusters rather than weakly coupled kagome planes. The spin waves are strongly damped when compared to elemental iron, opening the topic of topological boson–fermion interactions for deeper exploration within this material platform.

We study linearizability of actions of finite groups on singular cubic threefolds, using cohomological tools, intermediate Jacobians, Burnside invariants, and the equivariant Minimal Model Program.

Marine biofouling seriously affects human marine exploitation and transportation activities, to which marine antifouling (AF) coatings are considered to be the most cost-effective solution. Since the mid-20th century, human beings have dedicated their efforts on developing AF coatings with long cycle and high performance, leading to a large number of non-target organisms' distortion, death and marine environmental pollution. Polydimethylsiloxane (PDMS), is considered as one of the representative environment-friendly AF materials thanks to its non-toxic, hydrophobic, low surface energy and AF properties. However, PDMS AF coatings are prone to mechanical damage, weak adhesion strength to substrate, and poor static AF effect, which seriously restrict their use in the ocean. The rapid development of various nanomaterials provides an opportunity to enhance and improve the mechanical properties and antifouling properties of PDMS coating by embedding nanomaterials. Based on our research background and the problems faced in our laboratory, this article presents an overview of the current progress in the fields of PDMS composite coatings enhanced by different nanomaterials, with the discussion focused on the advantages and main bottlenecks currently encountered in this field. Finally, we propose an outlook, hoping to provide fundamental guidance for the development of marine AF field.

Glutathione S-transferases (GSTs) play crucial roles in crop stress tolerance through protection against oxidative damage. In this study, we conducted genome-wide identification and expression analysis of the GST gene family in the autotetraploid potato cultivar Cooperative-88 (C88) using bioinformatic approaches. We identified 366 GST genes in the potato genome, which were classified into 10 subfamilies. Chromosomal mapping revealed that StGSTs were distributed across all 12 chromosomes, with 13 tandem duplication events observed in three subfamilies. Analysis of protein sequences identified 10 conserved motifs, with motif 1 potentially representing the GST domain. Analysis of cis-acting elements in the StGSTs promoter regions suggested their involvement in stress response pathways. RNA-seq analysis revealed that most StGSTs responded to both drought stress and DNA demethylation treatments. Quantitative PCR validation of 16 selected StGSTs identified four members that showed strong responses to both treatments, with distinct expression patterns between drought-tolerant (QS9) and drought-sensitive (ATL) varieties. Transient expression assays in tobacco demonstrated that these four StGSTs enhanced drought tolerance and may be regulated through DNA methylation pathways, though the precise mechanisms require further investigation. These findings provide a theoretical foundation for understanding the response and epigenetic regulation of potato GST genes under drought stress.

Abstract The text in the natural scene can express rich semantic information, which helps people understand and analyse daily things. This paper focuses on the problems of discrete text spatial distribution and variable text geometric size in natural scenes with complex backgrounds and proposes an end‐to‐end natural scene text detection method based on DBNet. The authors first use IResNet as the backbone network, which does not increase network parameters while retaining more text features. Furthermore, a module with Transformer is introduced in the feature extraction stage to strengthen the correlation between high‐level feature pixels. Then, the authors add a spatial pyramid pooling structure in the end of feature extraction, which realises the combination of local and global features, enriches the expressive ability of feature maps, and alleviates the detection limitations caused by the geometric size of features. Finally, to better integrate the features of each level, a dual attention module is embedded after multi‐scale feature fusion. Extensive experiments on the MSRA‐TD500, CTW1500, ICDAR2015, and MLT2017 data set are conducted. The results showed that IDBNet can improve the average precision, recall, and F‐measure of a text compared with the state of art text detection methods and has higher predictive ability and practicability.

Abstract The effect of snowfall on an image is not only the interference of snow particles but also snow streaks and masking effects (similar to haze). Snowy weather severely reduces the accuracy of computer vision systems. There is a lot of interest in how to effectively remove snow while preserving as much of the original image information as possible. Based on this, the authors propose an effective Generative Adversarial Network (GAN) snow removal algorithm for single images to solve the snow removal failure problem caused by irregular snow particles and snow streaks. Specifically, the authors improve the original GAN network as follows: A novel Transformer module, the Contextual Transformer (CoT) module, is adopted in the residual modules based generator. It effectively uses the contextual information of the snow streaks neighbourhood to restore the texture and information in the noisy image as much as possible based on the focus on snow streaks features. Also, using learnable Regionalized Normalization (RN‐L), potentially corrupted and undamaged regions are automatically detected for separate normalization, and global affine transformations are performed to enhance their fusion. In addition, a multi‐scale discriminator is used in the discriminator to make the discrimination more adequate and retain more details. Extensive experiments have shown that the authors’ GAN network snow removal algorithm outperforms various current networks on snow removal studies in terms of evaluation metrics on both synthetic and real datasets.

Abstract Fundamental to all living organisms and living soft matter are emergent processes in which the reorganization of individual constituents at the nanoscale drives group-level movements and shape changes at the macroscale over time. However, light-induced degradation of fluorophores, photobleaching, is a significant problem in extended bioimaging in life science. Here, we report opening a long-time investigation window by nonbleaching phase intensity nanoscope: PINE. We accomplish phase-intensity separation such that nanoprobe distributions are distinguished by an integrated phase-intensity multilayer thin film (polyvinyl alcohol/liquid crystal). We overcame a physical limit to resolve sub-10 nm cellular architectures, and achieve the first dynamic imaging of nanoscopic reorganization over 250 h using PINE. We discover nanoscopic rearrangements synchronized with the emergence of group-level movements and shape changes at the macroscale according to a set of interaction rules with importance in cellular and soft matter reorganization, self-organization, and pattern formation.

Abstract Microseismic monitoring is an important tool for predicting and preventing rock burst incidents in mines, as it provides precursor information on rock burst. To improve the prediction accuracy of microseismic events in rock burst mines, the working face of the Hegang Junde coal mine is selected as the research object, and the research data will consist of the microseismic monitoring data from this working face over the past 4 years, adopts expert system and temporal energy data mining method to fuse and analyze the mine pressure manifestation regularity and microseismic data, and the "noise reduction" data model is established. By comparing the MEA-BP and traditional BP neural network models, the results of the study show that the prediction accuracy of the MEA-BP neural network model was higher than that of the BP neural network. The absolute and relative errors of the MEA-BP neural network were reduced by 247.24 J and 46.6%, respectively. Combined with the online monitoring data of the KJ550 rock burst, the MEA-BP neural network proved to be more effective in microseismic energy prediction and improved the accuracy of microseismic event prediction in rock burst mines.

Abstract Single image deraining work has attracted a lot of attention. So an effective single image deraining network model, RFCTNet, is designed. Specifically, the residual Fast Fourier Transform convolution module is used as a baseline for the deraining network. The advantage is its ability to capture both long and short‐term information interactions and to integrate high and low‐frequency background information for delivery. And a novel Transformer module, the Contextual Transformer module, is introduced. Contextual knowledge of the rain streaks neighbourhood is learned to improve the recovery of textures and information in the image background based on focusing on the rain pattern features. Because of the overlap between rain streaks, removing them in one stage is difficult, so a multi‐stage progressive rain removal method is used. Considering the catastrophic forgetting problem of deep learning, a continuous learning method, PIGWM, is adopted, which is c and enables the network model to memorize of the previous data set. Also, the rain removal method RFCTNet has been proven through extensive experiments to outperform other advanced methods' evaluation metrics on both synthetic and real datasets. The source code can be found on https://github.com/SUTwu/RFCTNet

The attainment of carbon neutrality requires the development of aqueous energy conversion and storage devices. However, these devices exhibit limited performance due to the permeability–selectivity trade-off of permselective membranes as core components. Herein, we report the application of a synergistic approach utilizing two-dimensional nanoribbons-entangled nanosheets to rationally balance the permeability and selectivity in permselective membranes. The nanoribbons and nanosheets can be self-assembled into a nanofluidic membrane with a distinctive “island-bridge” configuration, where the nanosheets serve as isolated islands offering adequate ionic selectivity owing to their high surface charge density, meanwhile bridge-like nanoribbons with low surface charge density but high aspect ratio remarkably enhance the membrane’s permeability and water stability, as verified by molecular simulations and experimental investigations. Using this approach, we developed a high-performance graphene oxide (GO) nanosheet/GO nanoribbon (GONR) nanofluidic membrane and achieved an ultrahigh power density of 18.1 W m–2 in a natural seawater|river water osmotic power generator, along with a high Coulombic efficiency and an extended lifespan in zinc metal batteries. The validity of our island-bridge structural design is also demonstrated for other nanosheet/nanoribbon composite membranes, providing a promising path for developing reliable aqueous energy conversion and storage devices.

As an emerging new type of battery chemistry, the anion shuttle battery (ASB), based on the shuttling and storage of anions, is considered a sustainable alternative to gigawatt-scale energy storage due to the associated resource abundance, low cost, high safety, and high energy density. Although significant progress has been achieved, practical applications of ASBs are still hindered by tough challenges, such as short lifetime, limited reversible capacity, and low Coulombic efficiency. Therefore, it is very necessary to design and explore new electrolyte systems with high electrochemical/chemical stability, sufficient compatibility towards electrodes, and excellent kinetics/reversibility for anion electrochemical reactions. Here, we review the recent achievements and main challenges in developing electrolytes for ASBs, which include solid, non-aqueous, and aqueous electrolytes. We mainly focus on the unique properties and basic principles of designing these electrolytes, and their various performance parameters. Perspectives on design strategies for ASB electrolytes are also presented, which could facilitate the development of advanced ASBs for grid-scale energy storage.

Lane detection plays a pivotal role in the successful implementation of Advanced Driver Assistance Systems (ADASs), which are essential for detecting the road’s lane markings and determining the vehicle’s position, thereby influencing subsequent decision making. However, current deep learning-based lane detection methods encounter challenges. Firstly, the on-board hardware limitations necessitate an exceptionally fast prediction speed for the lane detection method. Secondly, improvements are required for effective lane detection in complex scenarios. This paper addresses these issues by enhancing the row-anchor-based lane detection method. The Transformer encoder–decoder structure is leveraged as the row classification enhances the model’s capability to extract global features and detect lane lines in intricate environments. The Feature-aligned Pyramid Network (FaPN) structure serves as an auxiliary branch, complemented by a novel structural loss with expectation loss, further refining the method’s accuracy. The experimental results demonstrate our method’s commendable accuracy and real-time performance, achieving a rapid prediction speed of 129 FPS (the single prediction time of the model on RTX3080 is 15.72 ms) and a 96.16% accuracy on the Tusimple dataset—a 3.32% improvement compared to the baseline method.

The formation and later evolution of coal-bearing basins in eastern Heilongjiang are controlled by multi-phase tectonic movements, and the Shuangyashan Basin is tectonically located at the southern end of the Sanjiang Basin in the northeast. The paper focuses on the regional geological and tectonic evolution of the Shuangyashan Basin and its influence on the gas occurrence law and extraction difficulty of the Jixian Coal Mine. The study determined that the gas occurrence of the mine in the Suibin-Jixian depression basin has regional aggregation and caprock sealing characteristics. The gas pressure and content of the 9# Coal Seam were measured in the underground test, and the results showed that the 9# coal seam is a hard-to-extract coal seam with low permeability. Aiming at the issue of hard-to-extract gas in 904 Working Face of 9# Coal Seam which is affected by depression basin and derived secondary tectonic conditions, numerical calculation and analysis of gas extraction effect of working face with different extraction parameters were carried out by COMSOL software, the results showed that: negative extraction pressure has less influence on gas extraction effect under basin conditions; when 113 mm diameter borehole is used for gas extraction, gas pressure decreases to 0.72 MPa; when the spacing of extraction borehole is 2 m, the gas pressure is reduced by 20%; when the coal seam permeability is increased by 10 times to more than 0.015 mD, the gas pressure is reduced by more than 50%. The optimized gas extraction scheme with 113 m diameter, 2 m borehole spacing, and 15 kPa negative pressure was proposed for the test working face, and combined with supercritical CO2 fracturing and permeability enhancement technology. Under underground measurement, the coal seam gas content was reduced by 39.7% compared to the original gas extraction scheme. It can be seen that the reasonable gas extraction scheme and coal seam pressure relief and permeability enhancement technology can significantly improve the gas extraction rate, and the extraction effect is remarkable.

Abstract Separator is a critical component of lithium–sulfur (Li–S) battery, and the property of separator influences the battery performance significantly. Cellulose‐based separator is emerging as a promising alternative to the traditional polyolefin separator used in Li–S battery. Although the excellent battery performance of various cellulose‐based separators is shown, a comprehensive understanding of the advantageous features of bacterial cellulose (BC)‐based separator in Li–S battery still is lacking. In this work, models of BC separators with different thicknesses are prepared and compared with polypropylene separators in terms of their electrochemical performance. The results show that the BC separator exhibits favorable electrolyte affinity, improved lithium‐ion transport, suppressed shuttling of soluble polysulfides, and inhibited the formation of lithium dendrites. The combination of these unique characters of BC separator endows it with excellent battery performance. These results provide insight into the use and design of functional cellulose‐based separators in advanced secondary batteries.

In this work, the impact of temperature on the crushing performance of multi-walled tube (MWT) were investigated using a combined experimental, theoretical and numerical method. The MWT was fabricated using extrusion technology, and the temperature-dependent axial crushing experiment was performed on a hydraulic testing machine. The results show that the peak crushing force (PCF), the mean force (Pm) and the specific energy absorption (SEA) decreased near-linearly by 21.7%, 30.7% and 30.7% as the temperature increased from 25 °C to 250 °C, while the crushing load efficiency (CLE) was insensitive to temperature. The average forces obtained via numerical prediction, theoretical analysis and experimental testing were basically consistent. The numerical results indicate that varied temperature alters the number of dominant wavelets and the relative lateral deflections of MWT. In addition, compared with the competitive structures, the energy absorption property of MWT is excellent at high temperatures.

Abstract The cancer burden in the oldest old has increased rapidly. This study aimed to investigate the epidemiology of second primary malignancy (SPM) in malignant solid tumor survivors aged 85 years and older utilizing the Surveillance, Epidemiology, and End Results (SEER) database. A total of 128,466 malignant solid tumor patients had been identified between 2000 and 2011, including 6774 patients who developed a SPM. The overall crude incidence of developing a SPM was 5.3%. Considering death as a competing event, the 3, 5, and 10-year cumulative incidence was 1.9%, 3.2%, and 5.4%, respectively. Relative younger age, male gender, surgery history, local stage and first primary malignancy (FPM) site located in the urinary system were related to higher cumulative incidence. A median time interval of 24.0 months was found between diagnosis of FPM and SPM. The most common SPM site was digestive system, whereas the least common was oral cavity and pharynx. The median overall survival (OS) was 49.0 months, and the median survival after SPM was 13.0 months. Relative older age, male gender and black race were associated with worse OS and survival after SPM, as well as higher hazard ratios of death. In conclusions, this study performed a comprehensive analysis of SPM among malignant solid tumor survivors aged 85 years and older. Additional studies are needed to characterize the specific cancer type of interest.

The crowded intracellular environment of biomolecules, including organelles, solutes, proteins, and membranes, presents distinct biomolecular dynamics crucial for the functions of biomolecules within living cells. However, background suppression is critical to uncover nanoscale dynamics in living cells. Herein, a new method for enabling rapid, nanoscale background elimination of cellular metallic nanoprobes is presented. By employing integrated nanoscopic correction (iNC) designed to eliminate depolarization effects, which compromise background elimination, a real‐time algorithm to subtract and increment orthogonal pairs of polarizations for real‐time nanoscale background elimination is introduced. The ability to analyze orthogonal pairs at high speed over the entire polarization range is currently difficult to achieve using conventional methods. By processing orthogonal pairs in real time, this method minimizes movement artifacts during the background elimination process. Nanometer spatial stability which enables two orders of magnitude increase in signal‐to‐noise ratio of cellular metallic nanoprobes is shown. Nanoscale background elimination aiding the ability to accurately track biomolecules and their dynamics in living cells is anticipated.

Abstract Background The novel coronavirus disease 2019 (COVID-19) spreads rapidly among people and causes a pandemic. It is of great clinical significance to identify COVID-19 patients with high risk of death. Methods A total of 2169 adult COVID-19 patients were enrolled from Wuhan, China, from February 10th to April 15th, 2020. Difference analyses of medical records were performed between severe and non-severe groups, as well as between survivors and non-survivors. In addition, we developed a decision tree model to predict death outcome in severe patients. Results Of the 2169 COVID-19 patients, the median age was 61 years and male patients accounted for 48%. A total of 646 patients were diagnosed as severe illness, and 75 patients died. An older median age and a higher proportion of male patients were found in severe group or non-survivors compared to their counterparts. Significant differences in clinical characteristics and laboratory examinations were found between severe and non-severe groups, as well as between survivors and non-survivors. A decision tree, including three biomarkers, neutrophil-to-lymphocyte ratio, C-reactive protein and lactic dehydrogenase, was developed to predict death outcome in severe patients. This model performed well both in training and test datasets. The accuracy of this model were 0.98 in both datasets. Conclusion We performed a comprehensive analysis of COVID-19 patients from the outbreak in Wuhan, China, and proposed a simple and clinically operable decision tree to help clinicians rapidly identify COVID-19 patients at high risk of death, to whom priority treatment and intensive care should be given.

Rockburst is a complex dynamic disaster in coal mining and affected by many factors. To accurately predict the rockburst hazard among complex influencing factors, a prediction model of rockburst hazard based on the Gaussian process for binary classification (GPC) was proposed after the identification of the intrinsic relationship between multiple factors of coal mines and rockburst. Through computerized machine learning and integrated intelligent analysis, the non-linear mapping of rockburst hazard and its influencing factors was established. The multi-factor pattern recognition model was constructed using artificial intelligence. The prediction criteria of the rockburst hazard probability and the hazard probability value of the prediction area unit were determined by applying neural network and fuzzy inference methods. In addition, the rockburst hazardous zone was classified, and the corresponding technical scheme for the prevention was put forward. The validity and feasibility of the regional prediction of rockburst hazard based on GPC were verified in the engineering practice. This method is highly targeted and can improve the accuracy and precision of rockburst prediction, thus contributing to the safe and efficient production of coal mines.

Abstract Carbonaceous materials are considered strong candidates as anode materials for sodium‐ion batteries (SIBs), which are expected to play an indispensable role in the carbon‐neutral era. Herein, novel braided porous carbon fibres (BPCFs) are prepared using the chemical vapour deposition (CVD) method. The BPCFs possess interwoven porous structures and abundant vacancies. The growth mechanism of the BPCFs can be attributed to the polycrystalline transformation of the nanoporous copper catalyst in the early stage of CVD process. Density functional theory calculations suggest that the Na+ adsorption energies of the mono‐vacancy edges of the BPCFs (−1.22 and −1.09 eV) are lower than that of an ideal graphene layer (−0.68 eV), clarifying in detail the adsorption‐dominated sodium storage mechanism. Hence, the BPCFs as an anode material present an outstanding discharge capacity of 401 mAh g−1 at 0.1 A g−1 after 500 cycles. Remarkably, this BPCFs anode, under high‐mass‐loading of 5 mg cm−2, shows excellent long‐term cycling ability with a reversible capacity of 201 mAh g−1 at 10 A g−1 over 1000 cycles. This study provided a novel strategy for the development of high‐performance carbonaceous materials for SIBs.

Soft rot Pectobacteriaceae (SRP), typical of Pectobacterium and Dickeya, are a class of Gram-negative bacterial pathogens that cause devastating diseases on a wide range of crops and ornamental plants worldwide. Quorum sensing (QS) is a cell-cell communication mechanism regulating the expression of specific genes by releasing QS signal molecules associated with cell density, in most cases, involving in the vital process of virulence and infection. In recent years, several types of QS systems have been uncovered in Dickeya pathogens to control diverse biological behaviors, especially bacterial pathogenicity and transkingdom interactions. This review depicts an integral QS regulation network of Dickeya, elaborates in detail the regulation of specific QS system on different biological functions of the pathogens and hosts, aiming at providing a systematic overview of Dickeya pathogenicity and interactions with hosts, and, finally, expects the future prospective of effectively controlling the bacterial soft rot disease caused by Dickeya by quenching the key QS signal.

Rational design and construction of self-supporting anodes with high energy density is an essential part of research in the field of lithium-ion batteries. Tin oxide (SnO _2 ) is restricted in application as a prospective high energy density anode due to inherent low conductivity and huge volume expansion of the charge/discharge process. A new strategy that combines high energy ball milling and nonsolvent induced phase separation (NIPS) method was employed to synthesize self-supporting electrodes in which porous SnO _2 was encapsulated in a three-dimensional hierarchical porous copper (Cu) shell structure (3DHPSnO _2 @Cu). This unique structure was constructed due to the different binding energy of the alloy with oxygen, which are −0.91 eV for Cu _41 Sn _11 and −1.17 eV for Cu _5.6 Sn according to the density functional theory calculation. 3DHPSnO _2 @Cu electrodes exhibited excellent discharge capacity with an initial reversible capacity of 4.35 mAh cm ^−2 and a reversible capacity of 3.13 mAh cm ^−2 after 300 cycles at a current density of 1.4 mA cm ^−2 . It is attributed that the porous Cu shell encapsulated with porous SnO _2 provides buffer volume. Among them, the SnO _2 -Cu-SnO _2 interface increases the electrical conductivity and the porous structure provides ion transport channels. This strategy opens a new pathway in the development of self-supporting electrode materials with high energy density.

Abstract Constructing the heterostructures is considered to be one of the most effective methods to improve the poor electrical conductivity and insufficient electrocatalytic properties of metal sulfide catalysts. In this work, MnCo2S4‐CoS1.097 nanotubes are successfully prepared via a reflux‐ hydrothermal process. This novel cathode catalyst delivers high discharge/charge specific capacities of 21 765/21 746 mAh g−1 at 200 mA g−1 and good rate capability. In addition, a favorable cycling stability with a fixed specific capacity of 1000 mAh g−1 at high current density of 1000 mA g−1 (167 cycles) and 2000 mA g−1 (57 cycles) are delivered. It is proposed that fast transmission of ions and electrons accelerated by the built‐in electric field, multiple active sites from the heterostructure, and nanotube architecture with large specific surface area are responsible for the superior electrochemical performance. To some extent, the rational design of this heterostructured metal sulfide catalyst provides guidance for the development of the stable and efficient cathode catalysts for Li‐O2 batteries that can be employed under high current conditions.

Objective: Our study aimed to evaluate the correlation of circular RNA SMARCA5 (circ-SMARCA5) and microRNA 432 (miR-432) with clinical characteristics and survival in bladder cancer patients. Methods: Preoperative clinicopathologic features and survival data of 156 bladder cancer patients were retrospectively reviewed. A total of 156 cases of tumor tissues, whereas 71 cases out of 156 available adjacent tissues were obtained from the Pathology Department for circ-SMARCA5 and miR-432 detections using real-time quantitative polymerase chain reaction. Results: Circ-SMARCA5 was upregulated but miR-432 was downregulated in tumor tissues compared with adjacent tissues; meanwhile, circ-SMARCA5 expression was negatively correlated with miR-432 in bladder cancer tissues. Circ-SMARCA5 high expression was correlated with larger tumor size, higher tumor stage, and lymph node (LYN) metastasis. However, miR-432 high expression was correlated with single multiplicity, smaller tumor size, lower tumor stage, less LYN metastasis in bladder cancer patients. Regarding survival, circ-SMARCA5 high expression was correlated with shorter disease-free survival (DFS) and overall survival (OS); whereas, miR-432 high expression was correlated with longer DFS and OS in bladder cancer patients. Further multivariate Cox's regression analysis displayed that circ-SMARCA5 high expression was an independent predictive factor for both worse DFS and OS in bladder cancer patients. Conclusion: Circ-SMARCA5 high expression but miR-432 low expression is correlated with advanced tumor features and poor survival of bladder cancer patients, which present as potential prognostic markers in bladder cancer.

As one of the most serious shock dynamic disasters in coal mining, rock burst only occurs under the certain geodynamic environment. Geodynamic is the necessary requirement for the occurrence of rock burst, and the disturbance of mining engineering is the sufficient requirement. In terms of the fault structure, the method of geodynamic zoning is used to classify fault structure forms of rock burst in mines, and a model of geological structure is established to reveal the connection between fault structure and mine engineering. Besides, the influence of fault structure on rock burst is analyzed, and the controlling mechanism of the fault structure on the tectonic evolution of the mine area and the occurrence of rock burst is revealed. This research provides a treatment plan for the prediction and prevention of rock burst and guides the safe production in the coal mining engineering.

Ultra-high twinning-induced plasticity (TWIP) steel is receiving increasing attention in the automobile industry. Self-designed Fe–19Mn–0.6C TWIP steel was subjected to reveal the relationship between microstructures, which were related to recrystallization starting/ending temperature and cold rolling. The results indicated that initial deformation twins, secondary deformation twins, and nano-twins were successively generated in rolled TWIP steel with the increase of cold rolling, deformation twins, and dislocations, as well as with the elongation of grains. The elements remained uniformly dispersed rather than agglomerated in the twin crystals and grain boundaries. The recrystallization starting temperature changes of TWIP steel were 500–525, 400–425, 400–415, and 400–410 °C at cold rolling deformations of 25%, 50%, 75%, and 88%, respectively. Furthermore, the obtained corresponding recrystallization ending temperature changes were 580–600, 530–550, 520–540, and 500–520 °C, respectively. The linear relationship between cold deformation and hardness suggests that cold rolling can increase dislocation density and thus facilitate improving the hardness of TWIP steel.

The concept of combining metallic honeycomb with folded thin metallic sheets (corrugation) to construct a novel core type for lightweight sandwich structures is proposed. The honeycomb–corrugation hybrid core is manufactured by filling the interstices of aluminum corrugations with precision-cut trapezoidal aluminum honeycomb blocks, bonded together using epoxy glue. The performance of such hybrid-cored sandwich panels subjected to out-of-plane compression, transverse shear, and three-point bending is investigated, both experimentally and numerically. The strength and energy absorption of the sandwich are dramatically enhanced, compared to those of a sandwich with either empty corrugation or honeycomb core. The enhancement is induced by the beneficial interaction effects of honeycomb blocks and folded panels on improved buckling resistance as well as altered crushing modes at large plastic deformation. The present approach provides an effective method to further improve the mechanical properties of conventional honeycomb-cored sandwich constructions with low relative densities.

Ground-penetrating radar (GPR) is a close-range remote-sensing tool applied in a great many near-surface projects for engineering or environmental purposes. In GPR B-scans, there may exist a variety of reflections and diffractions that corresponds to different structures and targets in the subsurface media, and the noise is always embedded. To assist in the interpretation, GPR B-scans can be generally divided into two parts according to the dip attribute of the reflections, where the sub-horizontal layers and dipping structures are properly separated. In this work, we extend the f - x empirical mode decomposition (f - x EMD) to form a semi-adaptive dip filter for GPR data. In f - x domain, each frequency slice is decomposed by EMD and reconstructed to form a dipping profile and a horizontal profile respectively, where the reflections at different dips are separated adaptively. Then the noises mixed in the dipping profile are further separated by rank-deduction methods in f - x domain. The above two-step scheme constitutes the hybrid scheme, which can separate the dipping structures, sub-horizontal layers, and most of the random noise in GPR B-scans. We briefly review the basics of the f - x EMD, and then introduce the derived hybrid scheme in f - x domain. The proposed method is tested by the synthetic data, the forward simulation data, and the field data, respectively.

Using traditional time-frequency analysis methods, it is possible to delineate the time-frequency structures of ground-penetrating radar (GPR) data. A series of applications based on time-frequency analysis were proposed for the GPR data processing and imaging. With respect to signal processing, GPR data are typically non-stationary, which limits the applications of these methods moving forward. Empirical mode decomposition (EMD) provides alternative solutions with a fresh perspective. With EMD, GPR data are decomposed into a set of sub-components, i.e., the intrinsic mode functions (IMFs). However, the mode-mixing effect may also bring some negatives. To utilize the IMFs’ benefits, and avoid the negatives of the EMD, we introduce a new decomposition scheme termed variational mode decomposition (VMD) for GPR data processing for imaging. Based on the decomposition results of the VMD, we propose a new method which we refer as “the IMF-slice”. In the proposed method, the IMFs are generated by the VMD trace by trace, and then each IMF is sorted and recorded into different profiles (i.e., the IMF-slices) according to its center frequency. Using IMF-slices, the GPR data can be divided into several IMF-slices, each of which delineates a main vibration mode, and some subsurface layers and geophysical events can be identified more clearly. The effectiveness of the proposed method is tested using synthetic benchmark signals, laboratory data and the field dataset.

Self‐healing research based on commercial polymeric materials (such as polyurethane) is beneficial to sustainable development by prolonging the life of materials. However, developing polymeric materials that integrate robust mechanical properties with self‐healing ability at ambient temperature remains a formidable challenge. The formation of polymeric materials by physically and chemically dual crosslinking structures is a powerful method to improve mechanical properties. Herein, a series of dual crosslinking self‐healing polyurethane have been designed and successfully synthesized by incorporating 2‐ureido‐4[1H]‐pyrimidinone (UPy) units and triethanolamine (TEOA) into the polymer networks. Relying on the reinforcement of chemical crosslinking which is induced by TEOA, the resulting polyurethane exhibited robust strength of 10.3 MPa and elongation at break of 569.4%, which are quite prominent compared with previous reports. At the same time, the recombination of hydrogen bonds makes the polyurethane with UPy structure achieve rapid self‐healing after 24 h at 40°C and the strength recovered to 4.98 MPa. This work provided a novel way to fabricate sustainable polyurethane with robust mechanical properties. [ABSTRACT FROM AUTHOR]

Bacterial infections tend to cause a series of cytopathic reactions and have become a major threat to human life. Among them, phenolic compounds are widely used as a natural antibacterial derivative for antifouling and antibacterial applications. In this study, four phenolic hydroxyacrylamide monomers have been successfully prepared using capsaicinoid derivatives as inspiration (named as OHABA, PHABA, AHMA, and AMTHBA, respectively) and the chemical structures were confirmed by FT‐IR, 1H‐NMR, 13C‐NMR. The minimum inhibitory concentration (MIC) assay and plate antibacterial assay were measured to explore the antibacterial properties of the monomer. The results showed that four capsaicin derivatives exhibited antibacterial activity, and the antibacterial properties of the four monomers from strong to weak were PHABA, OHABA, AHMA and AMTHBA. The best antibacterial activity was PHABA (MIC for E. coli: 1.6 mg/mL, bacteriostasis rate: 82.46 %, MIC for S. aureus: 1.6 mg/mL, bacteriostasis rate: 69.58 %). Both the cluster effect of monomers and the spatial distribution of phenolic hydroxyl groups in the structure of derivatives affect the antibacterial properties. [ABSTRACT FROM AUTHOR]

In this paper, we study linear actions of finite groups in small dimensions, up to equivariant birationality. [ABSTRACT FROM AUTHOR]

The interaction mechanism of the multi-element oxide electrodes remains a challenge, despite the fact that their synergy can not only improve the electronic structure, but also broaden the working potential window to some extent. Herein, the simple NiMn alloy system was taken up as a model to investigate the origin of the wide voltage window. Compared with conventional electrodes, this sandwich-type nanoporous-NiO(MnOx)@Ni electrode derived from a NiMn alloy could exhibit a wide working potential window of 1.5 V in aqueous electrolyte. The facilitated successive redox reactions between NiO and MnOx throughout the entire potential window strongly promote the capacitance extension without water decomposition, despite the fact that the cycling lifespan was limited by chemical dissolution of MnOx. The assembled quasi-solid-state supercapacitor can overcome the irreversible conversion and exhibit a remarkable lifespan of 5000 cycles at 10 A cm-3 (91% retention) and high energy density (37.67 mW h cm-3 at 0.2 A cm-3). This work provides new perceptions for the design of multi-element collaborative energy storage electrodes. [ABSTRACT FROM AUTHOR]