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With the widespread adoption of next-generation sequencing technologies, the speed and convenience of genome sequencing have significantly improved, and many biological genomes have been sequenced. However, during the assembly of small genomes, we still face a series of challenges, including repetitive fragments, inverted repeats, low sequencing coverage, and the limitations of sequencing technologies. These challenges lead to unknown gaps in small genomes, hindering complete genome assembly. Although there are many existing assembly software options, they do not fully utilize the potential of artificial intelligence technologies, resulting in limited improvement in gap filling. Here, we propose a novel method, DLGapCloser, based on deep learning, aimed at assisting traditional tools in further filling gaps in small genomes. Firstly, we created four datasets based on the original genomes of Saccharomyces cerevisiae, Schizosaccharomyces pombe, Neurospora crassa, and Micromonas pusilla. To further extract effective information from the gene sequences, we also added homologous genomes to enrich the datasets. Secondly, we proposed the DGCNet model, which effectively extracts features and learns context from sequences flanking gaps. Addressing issues with early pruning and high memory usage in the Beam Search algorithm, we developed a new prediction algorithm, Wave-Beam Search. This algorithm alternates between expansion and contraction phases, enhancing efficiency and accuracy. Experimental results showed that the Wave-Beam Search algorithm improved the gap-filling performance of assembly tools by 7.35%, 28.57%, 42.85%, and 8.33% on the original results. Finally, we established new gap-filling standards and created and implemented a novel evaluation method. Validation on the genomes of Saccharomyces cerevisiae, Schizosaccharomyces pombe, Neurospora crassa, and Micromonas pusilla showed that DLGapCloser increased the number of filled gaps by 8.05%, 15.3%, 1.4%, and 7% compared to traditional assembly tools.

Watermelon is one of the most important edible plants worldwide. Owing to its special cultivation conditions, watermelon is exposed to many biological and abiotic stresses during its development. Lectin receptor-like kinases (LecRLKs) are plant-specific membrane proteins that play important roles in sensing and responding to environmental stimuli. Although the LecRLK gene family has been identified in a variety of plants, a comprehensive analysis has not yet been undertaken in watermelon. In this study, 61 putative LecRLK genes were identified in watermelon, consisting of 36 G-type, 24 L-type, and 1 C-type LecRLK genes. They were distributed in clusters on chromosomes, and members from the same subfamily were mostly clustered together. The analysis of the phylogenetic tree and conserved motif indicated that there were obvious differences among three ClaLecRLK subfamilies, and there was also rich diversity in the C-terminal within subfamilies. A collinear analysis revealed that the evolution of the ClaLecRLK gene family in different Cucurbitaceae crops was asynchronous. Furthermore, the analysis of the ClaLecRLK protein structure showed that not all proteins contained signal peptides and a single transmembrane domain. A subcellular localization assay confirmed that the number and position of transmembrane domains did not affect ClaLecRLK protein localization in cells. Transcriptome data revealed distinct expression patterns of LecRLK genes of watermelon in various tissues, and their responses to different fungi infection were also significantly different. Finally, the potential binding sites of the ClaLecRLK genes targeted by miRNA were predicted. This study enhances the understanding of the characteristics and functions of the LecRLK gene family in watermelon and opens up the possibility of exploring the roles that LecRLK genes may play in the life cycle of Cucurbitaceae plants.

Surface‐enhanced Raman scattering (SERS) is a versatile spectroscopic technique, which plays a crucial role in enhancing analytical sensitivity, investigating interfacial reaction mechanisms, enabling biosensing, and fostering efficient catalysis. Currently, the common SERS substrates are primarily metal nanostructures, which entail high manufacturing costs, complex processes, and the metal surface undergo change over time and with environmental conditions. These issues limit the development of SERS technology. In this work, a nitrogen‐doped graphene (N‐graphene) hydrangea was synthesized on a silicon (Si) substrate using plasma‐assisted chemical vapor deposition (PACVD), forming an N‐graphene hydrangea/Si hybrid structure as a SERS substrate. This substrate offers the advantages of high stability, ultra‐sensitivity, and reusability. The three‐dimensional nano‐cavity structure of graphene can increase the interaction between light and graphene, resulting in an increased localized electric field. Combining theoretical simulation analysis, the introduction of nitrogen (N) elements adjusts the Fermi level of graphene, promoting efficient charge transfer. In practical scenarios, Di(2‐ethylhexyl) phthalate (DEHP), a commonly used plasticizer, has raised concerns due to its potential as an endocrine disruptor and carcinogen. The as‐prepared SERS substrate achieves a remarkable detection limit of as low as 10−8 m for DEHP, providing significant support for environmental conservation and human health.

Zirconia (ZrO2) nanoparticles were synthesized using a solvothermal method under varying synthesis conditions, namely acidic, neutral, and alkaline. X-ray diffraction (XRD) and field emission scanning electron microscopy (FESEM) were leveraged to investigate the phase evolution and topographical features in detail. The resulting crystal phase structures and grain sizes exhibited substantial variation based on these conditions. Notably, the acidic condition fostered a monoclinic phase in ZrO2, while the alkaline condition yielded a combination of tetragonal and monoclinic phases. In contrast, ZrO2 obtained under neutral conditions demonstrated a refinement in grain sizes, constrained within a 1 nm scale upon an 800 °C thermal treatment. This was accompanied by an important transformation from a monoclinic phase to tetragonal phase in the ZrO2. Furthermore, a rigorous examination of XPS data and a UV-visible spectrometer (UV-vis) analysis revealed the significant role of oxygen vacancies in phase stabilization. The notable emergence of new energy bands in ZrO2, in stark contrast to the intrinsic bands observed in a pure monoclinic sample, are attributed to these oxygen vacancies. This research offers valuable insights into the novel energy bands, phase stability, and optical absorption properties influenced by oxygen vacancies in ZrO2. Moreover, it proposes an innovative energy level model for zirconia, underpinning its applicability in diverse technological areas.

This study aimed to develop and validate an improved sparrow search algorithm (ISSA)-optimized Least Squares Support Vector Machine (LSSVM) model for accurately predicting the tooth profile deviation of rigid gears produced by wire electrical discharge machining (WEDM). The ISSA was obtained by optimizing the sparrow search algorithm (SSA) using Tent chaotic mapping, adaptive adjustment strategy, dynamic inertia weights, and grey wolf hierarchy strategy. The effectiveness of the ISSA was verified using four different classes of benchmark test functions. Four main process parameters (peak current, pulse width, pulse interval, and tracking) were taken as inputs and the tooth profile deviations of rigid gears were considered as outputs to develop an ISSA-LSSVM-based profile deviation prediction model. The prediction performance of the ISSA-LSSVM model was evaluated by comparing it with the LSSVM model optimized by three standard algorithms. The prediction results of the ISSA-LSSVM model were R2 = 0.9828, RMSE = 0.0029, and MAPE = 0.0156. The results showed that the established model exhibits high prediction accuracy and can provide reliable theoretical guidance for predicting the tooth profile deviation of rigid gears.

In complex environments, users frequently need to manage multiple tasks simultaneously, which poses significant challenges for user interface design. For instance, when driving, users must maintain continuous visual attention on the road ahead while also monitoring rearview mirrors and performing shoulder checks. These multitasking scenarios present substantial design challenges in effectively guiding users. To address these challenges, we focus on investigating and designing visual and haptic guidance systems to augment users’ performance. We initially propose the use of visual guidance, specifically employing a dynamic arrow as a guidance technique. Our evaluation shows that dynamic arrows significantly expedite both reaction and selection times. We further introduce and evaluate haptic feedback, which users perceive as more salient than visual guidance, leading to quicker responses when switching from primary to secondary tasks. This allows users to maintain visual attention on the primary task while simultaneously responding effectively to haptic cues. Our findings suggest that multimodal guidance, especially haptic guidance, can enhance both reaction time and user experience in dual-task environments, offering promising practical implications and guidelines for designing more user-friendly interfaces and systems.

The Shouyang Block was selected as the research subject. Comprehensive analysis was conducted using coalbed methane (CBM) well production data, geochemical test data on water produced from the coalbed methane well, and fundamental geological information. The findings reveal the water dynamics in the Shouyang Block are characterized by weak groundwater runoff or retention in most areas. The groundwater head height exhibits a gradual decrease from the north to south, which is closely associated with the monoclinic structure of the Shouyang Block. Overall, water production is relatively high. As the average water production increases, the average gas production gradually decreases. A concentration of high water production wells is observed in the northern part of the Shouyang Block, which gradually increases towards the southeast direction. A comprehensive analysis was conducted on the factors influencing water production, including total water content of coal seams, coal seam porosity, groundwater stability index, groundwater sealing coefficient, D value of the fracture fractal dimension, fault fractal dimension, and sand–mud ratio. The correlation degree was calculated and ranked in order of magnitude through grey correlation analysis. The order of factors that influence water production, from strongest to weakest, is as follows: sand–mud ratio > porosity > fractal dimension of fault > fracture fractal dimension D value > groundwater sealing coefficient > groundwater stability index > total water content of coal seams. The dissolution amounts of carbonate and sulfate are both small, and the water source may mainly come from the sandstone aquifer. Attention should be paid to the distribution and lithological combination of sandstone aquifers in coal-bearing strata in the future exploration and development process of the Shouyang Block. This will help to avoid the potential influence of fault structures and enable the identification of favorable areas for low water and high gas production.

Abstract Three-dimensional (3D) conformations of a small molecule profoundly affect its binding to the target of interest, the resulting biological effects, and its disposition in living organisms, but it is challenging to accurately characterize the conformational ensemble experimentally. Here, we proposed an autoregressive torsion angle prediction model Tora3D for molecular 3D conformer generation. Rather than directly predicting the conformations in an end-to-end way, Tora3D predicts a set of torsion angles of rotatable bonds by an interpretable autoregressive method and reconstructs the 3D conformations from them, which keeps structural validity during reconstruction. Another advancement of our method over other conformational generation methods is the ability to use energy to guide the conformation generation. In addition, we propose a new message-passing mechanism that applies the Transformer to the graph to solve the difficulty of remote message passing. Tora3D shows superior performance to prior computational models in the trade-off between accuracy and efficiency, and ensures conformational validity, accuracy, and diversity in an interpretable way. Overall, Tora3D can be used for the quick generation of diverse molecular conformations and 3D-based molecular representation, contributing to a wide range of downstream drug design tasks. Graphical Abstract

The LD oilfield is one of the representative offshore oilfields. After weak gel flooding, the recovery rate is significantly improved. However, the oilfield is then in a medium- to high-water content stage, presenting a complex distribution of the remaining oil. The measures for further enhanced oil recovery (EOR) are uncertain. As a result, it is necessary to clarify the distribution pattern and development potential of the remaining oil during the high-water content period after weak gel flooding. In this study, an online nuclear magnetic resonance (NMR) oil displacement experiment and microscopic oil displacement experiment were conducted, and the mechanisms of weak gel flooding and the distribution pattern of the remaining oil were clarified in the LD oilfield. Additionally, high-multiple water flooding and numerical simulation experiments were conducted to analyze the development potential after weak gel flooding. The results show that the effect of weak gel flooding was more significant in the core of 1500 mD, with an increase in oil recovery of 9% compared to 500 mD. At a permeability of 500 mD, the degree of crude oil mobilization in micropores and small pores caused by weak gel flooding was improved by 29.64% and 23.48%, respectively, compared with water flooding. At 1500 mD, the degree of crude oil mobilization in small pores caused by weak gel flooding was increased by 37.79% compared to water flooding. After weak gel flooding, the remaining oil was primarily distributed in medium and large pores. Microscopically, the remaining oil was dominated by cluster residual oil, accounting for 16.49%, followed by columnar, membranous, and blind-end residual oil. High multiple water flooding experiments demonstrated that weak gel flooding could significantly reduce development time. The ultimate oil recovery efficiency of 500 mD and 1500 mD reached 71.85% and 80.69%, respectively. Numerical simulation results show that the ultimate oil recovery efficiency increased from 62.04% to 71.3% after weak gel flooding. This indicated that the LD oilfield still had certain development potential after weak gel flooding. The subsequent direction for enhanced oil recovery focuses mainly on mobilizing oil in medium pores or clustered remaining oil. This will play a crucial role in further exploring methods for utilizing the remaining oil and increasing the recovery rate.

The niobium oxide dihalides have recently been identified as a new class of van der Waals materials exhibiting exceptionally large second-order nonlinear optical responses and robust in-plane ferroelectricity. In contrast to second-order nonlinear processes, third-order optical nonlinearities can arise irrespective of whether a crystal lattice is centrosymmetric. Here, we report third harmonic generation (THG) in two-dimensional (2D) transition metal oxide iodides, namely NbOI2 and TaOI2. We observe a comparable THG intensity from both materials. By benchmarking against THG from monolayer WS2, we deduce that the third-order susceptibility is approximately on the same order. THG resonances are revealed at different excitation wavelengths, likely due to enhancement by excitonic states and band edge resonances. The THG intensity increases for material thicknesses up to 30 nm, owing to weak interlayer coupling. After this threshold, it shows saturation or a decrease, due to optical interference effects. Our results establish niobium and tantalum oxide iodides as promising 2D materials for third-order nonlinear optics, with intrinsic in-plane ferroelectricity and thickness-tunable nonlinear efficiency.

Kiwifruit bacterial canker caused by Pseudomonas syringae pv. actinidiae (Psa) is the most serious disease threatening kiwifruit production. Our previous study found genes encoding the U-box containing proteins were significantly regulated by Psa infection. Here, we report a U-box type E3 ubiquitin ligase PUB23 in kiwifruit which acts as a negative regulator of immune responses against Psa. PUB23 was found to physically interact with GT1, a trihelix transcription factor, in vitro and in vivo. The expression of GT1 was up-regulated in PUB23-silenced plants, indicating that interacting with PUB23 may directly or indirectly suppress GT1 expression. The silencing of PUB23 led to enhanced immune responses of PAMP-triggered immunity (PTI), including a higher expression level of defense marker genes PR1 and RIN4, and increased accumulation of hydrogen peroxide and superoxide anion. Our results reveal a negative role PUB23 plays in kiwifruit immune responses against Psa and may regulate gene expression by interacting with GT1.

Tensile, compressive-shear, and tensile-shear failure are three typical failure modes of rock- and lining-support structural materials in underground engineering. Comparative studies of the acoustic emission (AE) evolution characteristics of specimens of the same shape and size under different stress states are of great significance in determining universal disaster warning guidelines. Based on a self-developed multi-functional test system, direct tensile, compressive-shear, and tensile-shear tests were conducted on intact and jointed rock-like specimens, comparing AE amplitude and peak frequency parameters under different failure modes from the perspectives of crack scale and crack type evolution. All failure tests were monitored with microcrack propagation at an early stage until ultimate rupture occurred at the peak-load moment. As a result, the “quiet-period” could only be observed from the compressive-shear test. The AE signals distributed in three bands can be used as an indicator of failure identifications. Tensile and shear cracks can be identified by strong and weak amplitudes of low- and high-frequency signals. These results enhance the knowledge of the failure modes of rock mechanics for more applications in monitoring disasters in rock engineering.

The root residual stress during gear machining has a significant impact on the bending fatigue performance of the gear. The process parameters of gear hobbing (hob speed, axial feed speed, and radial cutting depth) directly affect the residual stress of the tooth root. To investigate the relationship between the process parameters of hobbing and the residual stress of the tooth root respectively, an analysis of an orthogonal and single factor was conducted in the hobbing experiment, taking into account the interactions among factors, which revealed the influence rule and primary–secondary relationship of the process parameters on the residual stress of the tooth root. The importance coefficients of the process parameters on the residual stress of the tooth root were calculated using the Least Absolute Shrinkage and Selection Operator (LASSO) method. The results indicate that the residual tensile stress at the tooth root increases with an increase in the hob speed and axial feed speed within the selected range but decreases with an increase in the radial cutting depth. The influence of the process parameters on the residual stress of the tooth root can be ranked as follows: hob speed (importance coefficient 0.460), axial feed speed (importance coefficient 0.278), and radial cutting depth (importance coefficient 0.262). This research provides a basis for improving the residual stress of the tooth root and enhancing the anti-fatigue manufacturing of gears, thus holding significant research value.

This paper presents an analytical method based on the shear flow distribution law to study the shear lag effect of thin-walled single- and double-cell box girders. The first step in this method is to determine the box girder’s shear flow distribution. Subsequently, a series of novel improved longitudinal displacement functions mathematically expressed as cubic parabolas are established. The parabolic origin of these functions is located at the zero point of the shear flow corresponding to each plate; the unknown parameters used to describe the function form can be determined according to the shear flow distribution, the continuity conditions, and the axial force balance condition. Then, the variational energy method is adopted to derive the governing differential equations. The shear lag effect in thin-walled single- and double-cell box girders under several boundary conditions and load cases is studied and analytical expressions for the shear lag coefficient are derived. Finally, results obtained using the proposed method are validated via comparison with numerical results. The results show that the proposed method can provide reasonable predictions for the shear lag effect of single- and double-cell box girders, and that this method is more straightforward and practical. In addition, the shear lag coefficients at different webs are not entirely equal, which is related to the distance from the web to the zero point of the shear flow.

Optimize the ultrasonic extraction process of polysaccharides from Dendrobium denneanum by Response surface design (RSM). The main polysaccharide (DP40) from was separated by anion exchange chromatography, and its structure was modified by low-temperature plasma. The results showed that the polysaccharide extraction rate of ultrasonic was 22.98 ± 0.97%, which was significantly higher than water extraction method(P

In this study, the deep eutectic solvent based ultrasound-assisted extraction (DES-UAE) was investigated for the efficient and environmentally friendly extraction of Selaginella chaetoloma total biflavonoids (SCTB). As an extractant for optimization, tetrapropylaminium bromide-1,4-butanediol (Tpr-But) was employed for the first time. 36 DESs were created, with Tpr-But producing the most effective results. Based on response surface methodology (RSM), the greatest extraction rate of SCTB was determined to be 21.68 ± 0.78 mg/g, the molar ratio of HBD to HBA was 3.70:1, the extraction temperature was 57 °C, and the water content of DES was 22 %. In accordance with Fick's second rule, a kinetic model for the extraction of SCTB by DES-UAE has been derived. With correlation coefficients 0.91, the kinetic model of the extraction process was significantly correlated with the general and exponential equations of kinetics, and some important kinetic parameters such as rate constants, energy of activation and raffinate rate were determined. In addition, molecular dynamics simulations were used to study the extraction mechanisms generated by different solvents. Comparing the effect of several extraction methods on S.chaetoloma using ultrasound-assisted extraction and conventional methods, together with SEM examination, revealed that DES-UAE not only saved time but also enhanced SCTB extraction rate by 1.5–3 folds. SCTB demonstrated superior antioxidant activity in three studies in vitro. Furthermore, the extract could suppress the growth of A549, HCT-116, HepG2, and HT-29 cancer cells. Alpha-Glucosidase (AG) inhibition experiment and molecular docking studies suggested that SCTB exhibited strong inhibitory activity against AG and potential hypoglycemic effects. The results of this study indicated that a Tpr-But-based UAE method was suitable for the efficient and environmentally friendly extraction of SCTB, and also shed light on the mechanisms responsible for the increased extraction efficiency, which could aid in the application of S.chaetoloma and provide insight into the extraction mechanism of DES.

Cybersecurity faces constant challenges from increasingly sophisticated network attacks. Recent research shows machine learning can improve attack detection by training models on large labeled datasets. However, obtaining sufficient labeled data is difficult for internal networks. We propose a deep transfer learning model to learn common knowledge from domains with different features and distributions. The model has two feature projection networks to transform heterogeneous features into a common space, and a classification network then predicts transformed features into labels. To align probability distributions for two domains, maximum mean discrepancy (MMD) is used to compute distribution distance alongside classification loss. Though the target domain only has a few labeled samples, unlabeled samples are adequate for computing MMD to align unconditional distributions. In addition, we apply a soft classification scheme on unlabeled data to compute MMD over classes to further align conditional distributions. Experiments between NSL-KDD, UNSW-NB15, and CICIDS2017 validate that the method substantially improves cross-domain network attack detection accuracy.

Strategically upcycling industrial wastes such as petroleum coke and dye wastewater into value-added materials through scalable and economic processes is an effective way to simultaneously tackle energy and environmental issues. Doping carbon electrodes with heteroatoms proves effective in significantly enhancing electrochemical performance through alterations in electrode wettability and electrical conductivity. This work reports the use of dye wastewater as the sole dopant source to synthesize N and S co-doped petroleum coke-based activated carbon (NS-AC) by the one-step pyrolysis method. More importantly, our wastewater and petroleum coke-derived activated carbon produced on a large scale (20 kg/batch) shows a specific surface area of 2582 m2 g−1 and an energy density of about 95 Wh kg−1 in a soft-packaged full cell with 1 M TEATFB/PC as the electrolyte. The scalable production method, together with the green and sustainable process, can be easily adopted and scaled by industry without the need for complex processes and/or units, which offers a convenient and green route to produce functionalized carbons from wastes at a low cost.

The coal mine in deep mining can easily form a compound dynamic disaster with the characteristics of rock burst and gas outburst. In this paper, the analytic hierarchy process (AHP) and the entropy weight method (EWM) are combined, and the fuzzy comprehensive evaluation (FCE) secondary evaluation model of compound dynamic disaster is proposed to evaluate the risk of compound dynamic disaster, which avoids the problems of the imperfect evaluation index system and strong subjectivity of index weight. Based on the statistical analysis of typical compound dynamic disaster cases in China, three first-level indicators were established, and sixteen second-level indicators were developed. The verification results show that the accuracy and weight are better than the traditional evaluation methods. Combined with geological and mining data, the compound dynamic disaster risk assessment was carried out on the second mining area of mine B, in the Pingdingshan mining area, and the result was grade II (weak risk). Corresponding prevention measures and parameters were implemented, and no compound dynamic disaster occurred during the working face excavation.

For biological groups, the behaviors of individuals will have an impact on the alignment efficiency of the collective movement. Motivated by Vicsek’s pioneering research on self-organized particles and other related works about flocking behaviors, we propose two mathematical models based on the local information of individuals to include more realistic details in the interaction mechanism between individuals and the rest of the group during the flocking process. The local information of the individual refers to the local consistency, representing the degree of alignment with its neighbors. These two models are the self-introspection model, where the process of orientation adjustment of one individual is ruled by the degree of local consistency with the neighborhood, and the credit evaluation model, where the average orientation of the neighborhoods is weighed using the local consistency of the interacting individuals. Different metrics are calculated to analyze the effects of the model parameters and flocking parameters on groups. Simulation calculations indicate that the two improved models have certain advantages in terms of alignment efficiency for the group. Finally, the optimal model parameters are determined, and the effects of random noise on groups with a single behavior and mixed behaviors are analyzed. The results confirm that individuals with mixed behaviors still possess robustness against noise. This research would contribute to the further interdisciplinary cooperation that involves biology, ethology, and multi-agent complex systems.

In order to reduce the silique shattering loss of the rapeseed mechanical harvesting process, based on the state of force on the silique during the rapeseed harvesting reel branch stage, Ningza 1810, Zhenyou 8, and Fengyou 306 were used as research objects, and the experimental research on the factors affecting rapeseed silique shattering was carried out using the swing impact method. The experimental analysis showed that rapeseed varieties, silique moisture content, silique growth position, collision material, impact speed, force position, and other factors had significant effects on silique shattering. The impact velocity was less than 1.5 m·s−1, the difference in the effect of each factor on pod shattering was not significant, and it was not easy to shatter when the moisture content of the rapeseed silique was higher. The impact resistance of the front side of rapeseed was two to four times that of the bonding surface of rapeseed petals, the shattering rate of the top rapeseed silique was twice that of the bottom siliques, and when siliques were supported, they were more likely to shatter under external forces than when they were unsupported. The experimental study of the mechanical properties of rapeseed siliques was carried out using the impending fracture method; the experimental analyses showed that the support position and force position of the silique, the loading speed, and the growth position of the silique had a significant effect on the mechanical properties of the silique. The maximum cracking force was higher and the bending strength was stronger when the body of the silique was supported; the range of the maximum cracking force was 3.05 N to 4.16 N, and the bending strength range was 8.48 MPa to 11.57 MPa. The maximum cracking force and bending strength of the silique were stronger when the front side of the silique petal was pressurized than when the bonding surface of the petal was pressurized. Based on Pearson’s correlation and grey correlation analysis, the morphological characteristics of rapeseed siliques were ranked in order of their influence on the performance of siliques in terms of the angle between the silique and stalk, stalk diameter, petal thickness, beak length, silique thickness, silique width, and silique length. This study can be used as a reference for the design and optimization of the rapeseed harvesting reel branch mechanism and the selection of machine-harvestable rapeseed varieties.

Unsupervised domain adaptation for object detectors addresses the problem of improving the cross-domain robustness of object detection from label-rich to label-poor domains, which has been explored in many studies. However, one important issue in terms of when to apply the domain adaptation algorithm for geospatial object detectors has not been fully considered in the literature. In this paper, we tackle the problem of detecting the moment or change-point when the domain of geospatial images changes based on conformal test martingale. Beyond the simple introduction of this martingale-based process, we also propose a novel transformation approach to the original conformal test martingale to make change-point detection more efficient. The experiments are conducted with two partitions of our released large-scale remote sensing dataset and the experimental results empirically demonstrate the promising effectiveness and efficiency of our proposed algorithms for change-point detection.

Abstract In fuel cells, the generally low oxygen reduction reactions (ORR) rate at the cathode is a major factor limiting the overall performance of fuel cell, so the development of high‐performance, stable and inexpensive ORR electrocatalysts is a major researching direction. Nano‐electrocatalysts, especially one‐dimensional (1D) electrocatalysts, exhibit good catalytic behavior in fuel cell reactions due to their unique anisotropic structure, large specific surface area, high elasticity and excellent stability. To date, many advanced 1D electrocatalysts have been reported for optimizing the cathode ORR of fuel cells. Therefore, a comprehensive review of the structural design of 1D nano‐electrocatalysts and a systematic analysis of their enhanced performance still need further summarized and concluded. In this review, we firstly introduce the main synthetic methods of 1D electrocatalysts, and then discuss the recent advances and advantages of different structured 1D electrocatalysts involving nanofibers, nanotubes, nanorods, nanochains, nanowires, nanobelts, nanoneedles, nanowhiskers, and coaxial nanocables. In addition, we also introduce 1D electrocatalysts while highlighting advanced strategies and preparation methods for these different structured 1D electrocatalysts to improve ORR performance. Finally, we prospect the future development of 1D ORR electrocatalysts.

Aspergillus ochraceus, generally known as a food spoilage fungus, is the representative species in Aspergillus section Circumdati. A. ochraceus strains are widely distributed in nature, and usually isolated from cereal, coffee, fruit, and beverage. Increasing cases suggest A. ochraceus acts as human and animal pathogens due to producing the mycotoxins. However, in terms of benefits to mankind, A. ochraceus is the potential source of industrial enzymes, and has excellent capability to produce diverse structural products, including polyketides, nonribosomal peptides, diketopiperazine alkaloids, benzodiazepine alkaloids, pyrazines, bis-indolyl benzenoids, nitrobenzoyl sesquiterpenoids, and steroids. This review outlines recent discovery, chemical structure, biosynthetic pathway, and bio-activity of the natural compounds from A. ochraceus.

Heat stress is an increasingly significant abiotic stress factor affecting crop yield and quality. This study aims to uncover the regulatory mechanism of sweet corn response to heat stress by integrating transcriptome and metabolome analyses of seedlings exposed to normal (25 °C) or high temperature (42 °C). The transcriptome results revealed numerous pathways affected by heat stress, especially those related to phenylpropanoid processes and photosynthesis, with 102 and 107 differentially expressed genes (DEGs) identified, respectively, and mostly down-regulated in expression. The metabolome results showed that 12 or 24 h of heat stress significantly affected the abundance of metabolites, with 61 metabolites detected after 12 h and 111 after 24 h, of which 42 metabolites were detected at both time points, including various alkaloids and flavonoids. Scopoletin-7-o-glucoside (scopolin), 3-indolepropionic acid, acetryptine, 5,7-dihydroxy-3′,4′,5′-trimethoxyflavone, and 5,6,7,4′-tetramethoxyflavanone expression levels were mostly up-regulated. A regulatory network was built by analyzing the correlations between gene modules and metabolites, and four hub genes in sweet corn seedlings under heat stress were identified: RNA-dependent RNA polymerase 2 (RDR2), UDP-glucosyltransferase 73C5 (UGT73C5), LOC103633555, and CTC-interacting domain 7 (CID7). These results provide a foundation for improving sweet corn development through biological intervention or genome-level modulation.

Ultra-reliable low-latency communication (URLLC) is an important application scenario in fifth generation (5G) communication. With the increasing deployment of 5G, spectrum resources are becoming increasingly scarce, and millimeter wave (mmWave) operating in a high frequency has garnered significant attention. However, the short wavelength of the mmWave makes the signals susceptible to fading. Precoding has emerged as a promising solution for mitigating the severe path loss in mmWave, which can enhance the system capacity and communication performance. In our system, an achievable rate maximization problem is established by jointly optimizing the analog and digital precoders at the base station, subject to the constraint of the total power and the constant modulus constraint of the subarrays. The simulation results demonstrate that the algorithm employed in our system can successfully solve the optimization problem in this new scenario. Furthermore, the subarray-structure hybrid precoder has a higher energy efficiency than that of a fully connected hybrid precoder or all-digital precoder. The proposed algorithm also outperforms the MM (Majorization–Minimization) algorithm.

Despite the many strategies employed to slow the spread of cancer, the development of new anti-tumor drugs and the minimization of side effects have been major research hotspots in the anti-tumor field. Natural drugs are a huge treasure trove of drug development, and they have been widely used in the clinic as anti-tumor drugs. Selaginella species in the family Selaginellaceae are widely distributed worldwide, and they have been well-documented in clinical practice for the prevention and treatment of cancer. Biflavonoids are the main active ingredients in Selaginella, and they have good biological and anti-tumor activities, which warrant extensive research. The promise of biflavonoids from Selaginella (SFB) in the field of cancer therapy is being realized thanks to new research that offers insights into the multi-targeting therapeutic mechanisms and key signaling pathways. The pharmacological effects of SFB against various cancers in vitro and in vivo are reviewed in this review. In addition, the types and characteristics of biflavonoid structures are described in detail; we also provide a brief summary of the efforts to develop drug delivery systems or combinations to enhance the bioavailability of SFB monomers. In conclusion, SFB species have great potential to be developed as adjuvant or even primary therapeutic agents for cancer, with promising applications.

Coal fire remains one of the main hazards of underground work. Spontaneous coal fires cause serious casualties and property losses. At present, most of the studies on coal spontaneous combustion have been conducted on working faces shorter than 200 m. However, the ultra-long working face gob of shallow buried coal seam is much larger, the distribution of its flow field is more complex, and, thus, risk of spontaneous combustion in the gob is higher. Exploring the evolution law of the gob flow field of ultra-long working face to quickly determine the range of the coal spontaneous combustion hazardous zone is of great significance to the safe production of similar mines. In this study, the gas flow field distribution in the gob of an ultra-long working face was measured by buried pipeline method and oxygen concentration was used as the index. It is found that the oxygen concentration decreases with the advance of the working face. Based on the flow field distribution, the oxidation zone of the gob was determined. Meanwhile, a three-dimensional (3D) numerical model of the working face was established, and the overlying stratum collapse and porosity evolution in the gob were simulated using the particle flow software, PFC3D discrete element software, for the porosity distribution law of the gob. The obtained porosity data were then imported into FLUENT using the custom function UDF to construct a 3D grid model. The flow field distribution in the gob was then numerically simulated for the seepage and migration law of the wind flow in the gob. The results reveal an arch-shaped wind flow field distribution with a swirl shape on the intake airway side. In the strike direction, the wind flow gradually becomes weaker with the advance of the working face. In the dip direction, the wind flow seepage range on the return airway side is obviously higher than that on the intake airway side. In the vertical direction, the wind flow range in the upper gob is larger than that in the middle and lower gob. The spontaneous combustion and oxidation zone of the gob is determined to be at 140.4–313.3 m on the intake airway side, 201.2–351.6 m in the middle of the gob, and 153.2–328.1 m on the return airway side. Finally, the residual coal distribution was superimposed onto the oxygen concentration distribution to obtain the spontaneous residual coal combustion hazardous zone in the gob.

Abstract A new kind of photolabile protecting group (PLPG) for carboxyl moieties was designed and synthesized as the linker between resin and peptide. This group can be used for the protection of amino acid carboxyl groups. The peptide was synthesized on Nph (2‐hydroxy‐3‐(2‐nitrophenyl)‐heptanoic acid)‐derivatized resins and could be cleaved under UV exposure, thus avoiding the necessity for harsh acid‐mediated resin cleavage. The PLPG has been successfully used for solid‐phase synthesis of peptides.

β-Glucosidase (β-Glc) is an enzyme capable of the selective hydrolysis of the β-glycosidic bond of glycosides and glycans containing glucose. β-Glc expressed by intestinal microbiota has attracted increasing levels of interest, due to their important roles for the metabolism of exogenous substances in the gut. Using the 2-((6-hydroxy-2,3-dihydro-1H-xanthen-4-yl)methylene)malononitrile fluorophore (DXM-OH, λem 636 nm) and the recognition group β-Glucose, an enzymatic activatable turn-on fluorescent probe (DXM-Glc) was developed for the selective and sensitive sensing of β-Glc. In addition, DXM-Glc could be used to sense endogenous β-Glc in living fungal cells. Using DXM-Glc, Pichia terricola M2 was identified as a functional intestinal fungus with β-Glc expression. P. terricola M2 could transform the flavone glycoside Icariin to Icariside Ⅱ efficiently, which confirmed the metabolism of glycosides in the gut mediated by fungi. Furthermore, Icariside Ⅱ could inhibit the proliferation of human endometrial cancer cells (RL 95-2 and ishikawa) significantly, suggesting the metabolic activation of Icariin by intestinal fungi in vivo. Therefore, DXM-Glc as a probe for β-Glc provided a novel technique for the investigation of the metabolism of bioactive substances by intestinal microbiota.

The rock deformation and failure characteristics and mechanisms are very important for stability evaluation and hazard control in rock engineering. The process of rock deformation and failure is often accompanied by temperature changes. It is of great significance to study the characteristics and mechanism of temperature variation in rock under deformation and fracturing for a better understanding of rock failure and to obtain some probable precursor information for guiding the prediction of the mechanical behavior of rock. However, most of the studies are based on observations in the field and laboratory tests, while it is still required to develop an effective method for modeling and calculating the temperature variation of rock during the deformation and failure processes. In this paper, a particle flow modeling method based on energy analyses is proposed for simulating the temperature variation of rocks, considering four temperature effects, including the thermoelastic effect, friction effect, damping effect, and heat conduction effect. The four effects are analyzed, and the theoretical equations have been provided. On this basis, the numerical model is built and calibrated according to the laboratory uniaxial compressive experiment on a marble specimen, and a comparison study has been conducted between the laboratory and numerical experiment results. It is found that the numerical model can well simulate the average value and distribution of the temperature variation of rock specimens, so this method can be applied for studying the mechanism of temperature variation more comprehensively during the whole process of rock deformation and fracturing compared with the continuous modeling methods. With this method, it is shown that the temperature change has three different stages with different characteristics during the uniaxial compression experiments. In the different stages, the different effects play different roles in temperature variation, and stress distribution and crack propagation have obvious influences on the local distribution of temperature. Further investigations have also been conducted in a series of sensitive analyses on the influences of four factors, including the thermal conductivity, friction coefficient, thermal expansion coefficient, and particle size ratio. The results show that they have different influences on the thermal and mechanical behaviors of the rock specimens during the deformation and failure process, while the thermal expansion coefficient and the particle size ratio have more significant impacts than the other two factors. These findings increase our knowledge on the characteristics and mechanism of temperature variation in rock during the deformation and fracturing process, and the proposed modeling method can be used in more studies for deformation and fracturing analyses in rock experiments and engineering.

In the economically developed Beijing–Tianjin–Hebei region, magnetotelluric data are susceptible to contamination from cultural noise, which can be caused, for example, by urban stray currents, high-speed railways, or high-voltage lines. The multiple remote references method is an effective tool that can be used to suppress interference and improve signal-to-noise ratios. Therefore, this paper first introduces the basic principles of multiple remote references and then takes high-speed railway noise as an example. The characteristics of the time domain and frequency domain of the high-speed railway noise signals are analyzed. Then, we use two remote reference stations (with a single remote reference and multiple remote references) to process the data interfering with the high-speed railway and compare the results. Finally, the multiple remote references method is used to process the data for the entire section. Coupled with the known geological and seismic data, the inversion results well-reflect the deep underground geological structure.

Nitrogen is one of the most important mineral elements for plant growth and development. Excessive nitrogen application not only pollutes the environment, but also reduces the quality of crops. However, are few studies on the mechanism of barley tolerance to low nitrogen at both the transcriptome and metabolomics levels. In this study, the nitrogen-efficient genotype (W26) and the nitrogen-sensitive genotype (W20) of barley were treated with low nitrogen (LN) for 3 days and 18 days, then treated with resupplied nitrogen (RN) from 18 to 21 days. Later, the biomass and the nitrogen content were measured, and RNA-seq and metabolites were analyzed. The nitrogen use efficiency (NUE) of W26 and W20 treated with LN for 21 days was estimated by nitrogen content and dry weight, and the values were 87.54% and 61.74%, respectively. It turned out to have a significant difference in the two genotypes under the LN condition. According to the transcriptome analysis, 7926 differentially expressed genes (DEGs) and 7537 DEGs were identified in the leaves of W26 and W20, respectively, and 6579 DEGs and 7128 DEGs were found in the roots of W26 and W20, respectively. After analysis of the metabolites, 458 differentially expressed metabolites (DAMs) and 425 DAMs were found in the leaves of W26 and W20, respectively, and 486 DAMs and 368 DAMs were found in the roots of W26 and W20, respectively. According to the KEGG joint analysis of DEGs and DAMs, it was discovered that glutathione (GSH) metabolism was the pathway of significant enrichment in the leaves of both W26 and W20. In this study, the metabolic pathways of nitrogen metabolism and GSH metabolism of barley under nitrogen were constructed based on the related DAMs and DEGs. In leaves, GSH, amino acids, and amides were the main identified DAMs, while in roots, GSH, amino acids, and phenylpropanes were mainly found DAMs. Finally, some nitrogen-efficient candidate genes and metabolites were selected based on the results of this study. The responses of W26 and W20 to low nitrogen stress were significantly different at the transcriptional and metabolic levels. The candidate genes that have been screened will be verified in future. These data not only provide new insights into how barley responds to LN, but also provide new directions for studying the molecular mechanisms of barley under abiotic stress.

The presence of diatoms in diatomaceous soil gives it geotechnical properties that are unusual compared with common clays. The most typical physical property of diatomaceous soil is its abnormally high Atterberg limits compared to fine-grained soil without diatoms. For diatomaceous soil, the Atterberg limits are associated with many factors, such as diatom content, diatom crushing degree, etc. In the study reported here, it was ascertained that more diatoms lead to higher plastic and liquid limits. Once the diatoms are crushed, the plastic and liquid limits decrease. The pore fluid salt concentration barely influenced the Atterberg limits of diatomaceous soil. Additionally, the porous diatom microstructure and trimodal pore size distribution of diatomaceous soil were investigated via scanning electron microscopy, transmission electron microscopy, and mercury intrusion porosimetry. The underlying mechanism of abnormally high liquid and plastic limits of diatomaceous soil is revealed as the water stored in the special diatom microstructure. However, water in diatoms has no contribution to plasticity. Also discussed is the applicability of the current soil classification systems for diatomaceous soil. The findings of this study can help for a better understanding of Atterberg limits of diatomaceous soil and provide suggestions for the classification of diatomaceous soil.

Understanding the asperity damage behaviors of joints during shearing is critical for evaluating the stability of deep underground engineering structures. In this paper, we prepared plaster joints and used them for direct shear tests under different normal stiffness (0–7 MPa/mm) and various shear rate (0.5–20 mm/min) conditions. The effects of normal stiffness and shear rate on mechanical behavior and AE characteristics were studied. With the increase of normal stiffness, the damaged area of the surface of the joint and the weight of the damaged, rough body basically show a linear increase. With the increase of the shear rate, the peak shear stress and the final shear stress of the joint are non-linearly decreased (the decrease rate at the shear rate of 0.5–5 mm/min is much larger than that at the shear rate of 5–20 mm/min), more local cracks appear on the surface of the joint, and the dilatancy of the joint slightly decreases. More than 60% of the acoustic emission signals in the shearing process of the joint are concentrated in the post-peak phase. With the increase of normal stiffness, the cumulative number of acoustic emission impacts and cumulative energy both increase. With the increase in shear rate, the accumulated acoustic emission impact number decreases, and the accumulated AE energy tends to increase when the shear rate is 0.5–5 mm/min and decreases when the shear rate increases to 5–20 mm/min.

Dendrobium denneanum is an important medicinal and ornamental plant. Its ornamental and medicinal values are affected by its vegetative growth conditions and chemical composition accumulation. This study adopted an orthogonal experimental design to treat D. denneanum with nine different levels of nitrogen (N), potassium (K), and phosphorus (P). The morphological indicators of the plant were positively correlated with the nitrogen concentration. The polysaccharide content was the highest at 1500 mg·L−1 nitrogen and 3000 mg·L−1 phosphorous and was 26.84% greater than the control. The flavonoid content increased by 36.2% at 500 mg·L−1 nitrogen, 2000 mg·L−1 phosphorous, and 300 mg·L−1 potassium. Principal component score analysis showed that nitrogen had the most significant impact on the various indicators of D. denneanum, followed by phosphorus and potassium. The comprehensive score showed that the T9 treatment (N: 1500 mg·L−1, P: 3000 mg·L−1, K: 500 mg·L−1) had the strongest effect on D. denneanum. Transcriptional analysis showed that compared with the control, the T9 treatment led to 2277 differentially expressed genes (1230 upregulated and 1047 downregulated). This includes fifteen genes enriched in the MAPK signaling pathway, five genes in phenylpropanoid biosynthesis, and two genes in flavonoid biosynthesis. These genes may be involved in regulating plant growth and the biosynthesis of polysaccharides and flavonoids. This study provides guidance for the optimal use of N, P, and K in the cultivation of D. denneanum.

Abstract As an important category of porous crystalline materials, metal‐organic frameworks (MOFs) have attracted extensive research interests owing to their unique structural features such as tunable pore structure and enormous surface area. Besides controlling the size, dimensionality, and composition of MOFs, further exploring the crystal‐phase‐dependent physicochemical properties is essential to improve their performances in various applications. Recently, great progress has been achieved in the phase engineering of nanomaterials (PEN), which provides an effective strategy to tune the functional properties of nanomaterials by modulating the arrangement of atoms. In this review, we adopt “phase” instead of “topology” to describe the crystal structure of MOFs and summarize the recent advances in phase engineering of MOFs. The two main strategies used to control the phase of MOFs, that is, phase‐controlled synthesis and phase transformation of MOFs, will be highlighted. The roles of various reaction parameters in controlling the crystal phase of MOFs are discussed. Then, the phase dependence of MOFs in various applications including luminescence, adsorption, and catalysis are introduced. Finally, some personal perspectives about the challenges and opportunities in this emerging field are presented.

Entecavir (ETV), a guanosine analogue, can be rapidly phosphorylated to the active intracellular triphosphate form that inhibits replication of the hepatitis B virus (HBV). This work aims to develop useful methods to quantify the content of ETV-A in ETV-H and ETV-A binary mixtures. The integral enthalpy value of the phase transformation in the DSC thermogram was selected to quantify the content of ETV-A in binary mixture. Different ranges (full spectrum and partial spectrum) of the PXRD and ATR-FTIR data versus ETV-A content were used to develop partial least squares (PLS) calibration curves with different pre-processing algorithms including multiplicative scatter correction (MSC), standard normal variate (SNV), wavelet transform (WT) or their combinations. The standard curve obtained for the DSC technique is Y = 100.455 + 7.255X, R2 = 0.997, in the ETV-A contents range of 0–100% w/w% in binary mixtures. Limit of detection (LOD) of ETV-A was 0.909% and limit of quantitation (LOQ) is 2.755%. The best correction models for PXRD and ATR-FTIR techniques, in the ETV-A contents range of 0–100% w/w% in binary mixtures, were Y = 0.346 + 0.999X, R2 = 0.999 in the 2θ range of 4-6° with 14-34° and Y = 0.767 + 0.991X, R2 = 0.991 in the range of 3500–2500 cm−1 with 2000–400 cm−1 pretreated by MSC + WT, respectively. Limit of detection (LOD) of ETV-A was 1.394% and limit of quantitation (LOQ) was 4.224% for PXRD technique. LOD and LOQ for ATR-FTIR technique were 9.124% and 27.648%. The results show that DSC, PXRD and ATR-FTIR techniques are precise and accurate, and could be used for the measurement of ETV-A content in the binary mixtures.

Castor (Ricinus communis L.) seed oil is the commercial source of ricinoleate, a valuable raw material used in many industries. Oleoyl-12-hydroxylase (RcFAH12) is a key enzyme in the biosynthesis of ricinoleate, accumulating nearly 90% of the triacylglycerol in castor seeds. Little is known about the transcriptional regulation of RcFAH12. We used rapid amplification of cDNA 5′ ends (5′RACE) to locate the transcription start site (TSS) of RcFAH12, and the sequence of a 2605 bp region, −2506~+99, surrounding the TSS was cloned. We then investigated these regions to promote β-glucuronidase (GUS) expression in transgenic Arabidopsis by the progressive 5′ and 3′ deletions strategies. The GUS staining showed that the GUS accumulation varied in tissues under the control of different deleted fragments of RcFAH12. In addition, the GUS expression driven by the RcFAH12 promoter markedly accumulated in transgenic seeds, which indicated that RcFAH12 might play an important role in the biosynthesis of ricinoleic acid. This study will lay a potential foundation for developing a tissue-specific promoter in oil-seed crops.