The aim of this paper is to use the elementary method and the properties of the second kind Stirling numbers to study the congruence properties of a new sequence, which is closely related to Fubini polynomials and Euler numbers, and give some interesting congruences for it. This solves a problem proposed by the first author at an unpublished paper.

This study empirically examines the spatial spillover effect of various environmental regulations on green technology innovation using panel data from 284 county-level cities in China between 2007 and 2019. A geographical-economic spatial weight matrix is constructed, and the spatial Durbin model is employed to identify the specific characteristics of this spillover effect. The findings indicate that the spatial spillover effect of green technology innovation primarily occurs through geographical transmission. However, there is no significant spatial autocorrelation when using the economic distance weight matrix. Various types of environmental regulations influence the spatial spillover effect of green technology innovation in distinct ways. Specifically, Market-motivated environmental regulation exhibits a U-shaped relationship with the spatial spillover effect, while Command-controlled environmental regulation demonstrates an inverted U-shaped relationship, suggesting a complementary effect. Additional research shows that the upgrading of industrial structure acts as a mediator between command environmental regulation and the spatial spillover effect of green technology innovation. Government departments should comprehensively coordinate Market-motivated environmental regulation and Command-controlled environmental regulation, accurately assess the intensity of Command-controlled measures, and prevent the migration of green technology innovation elements caused by excessive regulatory measures within enterprises.

The 3D reconstruction of vermiculite-based sealing material was carried out based on CT scanning experiments and Avizo software. The precision and representation of the reconstructed digital core were tested by calculating the pore structure parameters and comparing them with the experimental results of mercury compression. Avizo is a perfect interface with Fluent software to perform micro-scale seepage simulation to explore the distribution of pressure and velocity fields during fluid transport. In this paper, a new approach is proposed to study the penetration leakage of non-metallic gaskets by using equivalent pore networks.

We propose a computer-generated hologram method for near-eye virtual reality and augmented reality 3D display. A 3D object located near the holographic plane is projected onto a projection plane to obtain a plurality of projected images with different angles. The hologram is calculated by superposition of projected image convolution with a specific PSF through the interference of reference wave with object wave. Holographic 3D display systems with LED as illumination, 4f optical filtering system and lens as eyepiece for near-eye VR display and HOE as combiner for near-eye AR display are designed. The results show that the proposed method is about 38 times faster than the conventional point cloud method. The proposed method is flexible to produce speckle noise free high-quality VR and AR images with efficient focus and defocus capabilities.

MCrAlX (M: Ni or Co or both, X: minor elements) coatings have been widely used to protect hot components in gas turbines against oxidation and hot corrosion at high temperatures. Understanding the influence of the X-elements on oxidation behaviour is important in the design of durable MCrAlX coatings. In this study, NiCoCrAlX coatings doped with Y+Ru and Ce, respectively, were deposited on Inconel-792 substrate by HVOF. The samples were subjected to isothermal oxidation test in laboratory air at 9000, 1000, 1100 ºC and cyclic oxidation test between 100 ºC and 1100 ºC with 1 hour dwell time at 1100 ºC. It was observed that the coating with Ce shows a much higher oxidation rate than the coating with Y+Ru under both isothermal and cyclic oxidation tests. Besides, β-depletion due to interdiffusion between coating and substrate was significantly lower with Ru addition. Simulations results using both a moving phase boundary model and an established oxidation-diffusion model show that Ru stabilize β grains which reduces β-depletion of coating due to substrate interdiffusion. This paper presents a comprehensive study of the influence of Ce and Ru on oxidation behaviour including investigation of the microstructure evolution influenced by oxidation time at coating surface and coating-substrate interface combining experiment and simulation results.

For personalized recommender systems,matrix factorization and its variants have become mainstream in collaborative filtering.However,the dot product in matrix factorization does not satisfy the triangle inequality and therefore fails to capture fine-grained information. Metric learning-based models have been shown to be better at capturing fine-grained information than matrix factorization. Nevertheless,most of these models only focus on rating data and social information, which are not sufficient for dealing with the challenges of data sparsity. In this paper,we propose a metric learning-based social recommendation model called SRMC.SRMC exploits users' co-occurrence pattern to discover their potentially similar or dissimilar users with symmetric relationships and change their relative positions to achieve better recommendations.Experiments on three public datasets show that our model is more effective than the compared models.

Abstract: Image aesthetic assessment (IAA) with neural attention has made significant progress due to its effectiveness in object recognition. Current studies have shown that the features learned by convolutional neural networks (CNN) at different learning stages indicate meaningful information. The shallow feature contains the low-level information of images and the deep feature perceives the image semantics and themes. Inspired by this, we propose a visual enhancement network with feature fusion (FF-VEN). It consists of two sub-modules, the visual enhancement module (VE module) and the shallow and deep feature fusion module (SDFF module). The former uses an adaptive filter in the spatial domain to simulate human eyes according to the region of interest (ROI) extracted by neural feedback. The latter not only takes out the shallow feature and the deep feature by transverse connection, but also uses a feature fusion unit (FFU) to fuse the pooled features together with the aim of information contribution maximization. Experiments on standard AVA dataset and Photo.net dataset show the effectiveness of FF-VEN.

Insulator defect detection is of great significance to compromise the stability of the power transmission line. The state-of-the-art network of object detection, YOLOv5, has been widely used on insulator and defect detection. However, YOLOv5 network has some limitations like poor detection rate and high computational loads in detecting small insulator defects. To solve these problems, we proposed a light-weight network for insulator and defect detection. In this network, we introduced Ghost module into YOLOv5 backbone and neck to reduce the parameters and model size to enhance the performance in unmanned aerial vehicles (UAVs). Besides, we added small object detection anchors and layers for small defect detection. In addition, we optimized the backbone of YOLOv5 by applying convolutional block attention module (CBAM) to focus on critical information for insulator and defect detection and suppress uncritical information. The experiment result shows the mean average precision (mAP) 0.5 and the mAP0.5:0.95 of our model can reach 99.4% and 91.7%, the parameters and model weight are reduced to 3807372 and 8.79M, which can easily deploy to embedded devices like UAVs. And the speed of detection can reach 10.9ms/image, which can meet the real-time detection requirement.

Understanding of the correlation between the magnetomechancial coupling factors (k) and damping factors (Q^-1) is a key pathway to enhance the magnetomechanical power conversion ef-ficiency in laminated magnetoelectric (ME) composites by engineeringly manipulating the magnetic and mechanical properties of Fe-based amorphous metals. The k and Q^-1 factors of FeSiB amorphous ribbons annealed in air at different temperatures are investigated. It is found that k and Q^-1 factors are affected by both magnetic and elastic properties. The magnetic and elastic properties are equalized in terms of the magnetomechanical power efficiency for the low temperature annealing. The k and Q^-1 of FeSiB-based epoxied laminates with different stacking numbers show that the -3 dB bandwidth and Young’s modulus are equalized in terms of the magnetomechanical power efficiency for the high lamination stacking.

Seismic travel time tomography using surface waves is an effective tool for three-dimensional crustal imaging. Historically, these surface waves are the result of active seismic sources or earthquakes. More recently, however, also surface waves retrieved through the application of seismic interferometry are exploited. Conventionally, two-step inversion algorithms are employed to solve the tomographic inverse problem. That is, a first inversion results in frequency-dependent, two-dimensional maps of phase velocity, which then serve as input for a series of independent, one-dimensional frequency-to-depth inversions. As such, a two-dimensional grid of localized depth-dependent velocity profiles are obtained. Stitching these separate profiles together subsequently yields a three-dimensional velocity model. Relatively recently, a one-step three-dimensional non-linear tomographic algorithm has been proposed. The algorithm is rooted in a Bayesian framework using Markov chains with reversible jumps, and is referred to as transdimensional tomography. Specifically, the three-dimensional velocity field is parameterized by means of a polyhedral Voronoi tessellation. In this study, we investigate the potential of this algorithm for the purpose of recovering the three-dimensional surface-wave-velocity structure from ambient noise recorded on and around the Reykjanes Peninsula, southwest Iceland. To that end, we design a number of synthetic tests that take into account the station configuration of the Reykjanes seismic network. We find that the algorithm is able to recover the 3D velocity structure at various scales in areas where station density is high. In addition, we find that the standard deviation on the recovered velocities is low in those regions. At the same time, the velocity structure is less well recovered in parts of the peninsula sampled by fewer stations. This implies that the algorithm successfully adapts model resolution to the density of rays. Also, it adapts model resolution to the amount of noise on the travel times. Because the algorithm is computationally demanding, we modify the algorithm such that computational costs are reduced while sufficiently preserving non-linearity. We conclude that the algorithm can now be applied adequately to travel times extracted from (time-averaged) station-station cross correlations by the Reykjanes seismic network.

In recent years, intelligent identification and prediction of ore deposits based on deep learning algorithm and image processing technology has gradually become one of the research frontiers in the field of geological and metallogenic prediction. However, this method also has many problems that need to be solved. For example, (1) very few trainable image samples containing mineral point labels; (2) The geological image features are small and irregular, and the image similarity is high; (3) It is difficult to calculate the influence of different geological prospecting factors on ore mineralization. Based on this, this paper constructs a deep learning network model Multiscale Feature Attention Framework (MFAF) based on geo-image data. The results show that MFCA-Net module in MFAF model can solve the problem of scarce mine label images to a certain extent. In addition, the channel attention mechanism SE-Net module can quantify the difference of influence of different source factors on mineralization. The prediction map is obtained by applying the MFAF model in the study of deposit identification and prediction in the research area of the southern section of Qin-hang metallogenic Belt. In the forecast map, many regions have high metallogenic potential. Through observation, it is found that the above predicted area covers 100% of the known ore deposits at present, which has a good prediction effect. Later, we can find out the specific reasons through field verification. The multi-scale feature fusion and attention mechanism MFA Framework in this paper can provide a new way of thinking for geologists in mineral exploration. The research of this paper also provides resource guarantee and technical support for the sustainable exploitation of mineral resources and the sustainable growth of society and economy.

The aim of this study was to examine and understand the physiological and biochemical components of the blood and vitreous humor of goldfish (Carassius auratus). Blood was drawn from the arterial (static) line and vitreous humour was extracted using a syringe from healthy goldfish. An automatic haematology analyzer was used to detect 17 physiological indicators, including white blood cells and red blood cells. At the same time, 20 biochemical indexes, including albumin, calcium, and glutamic pyruvic transaminase, were found in the automatic biochemical analyzer. Experiments were also conducted on the effect of blood and vitreous fluid collection on the subsequent survival rate of the celestial goldfish. The findings demonstrated that there were values for 17 physiological indicators in the blood of the goldfish, including red blood cells (2.19 × 1012), white blood cells (62.21 × 109), hemoglobin (138.25g/L), and no eosinophils or basophils. However, no data for 17 physiological indications of vitreous humor were discovered. The quantities of total protein, glutamic oxaloacetic transaminase, and potassium in the vitreous humor were substantially lower than those in the serum (P < 0.01) according to the results of 20 biochemical indexes in the serum and vitreous humor of goldfish. Alkaline phosphatase, chlorine, and creatinine between vitreous humor and serum did not differ significantly(P > 0.05). The levels of glutamic pyruvic transaminase and γ-glutamyl transpeptide in vitreous humor were significantly higher than those in serum (P < 0.01). This experiment provides basic datas for the healthy culture of goldfish and the perfection of hematology in goldfish, and the results will be convenient for the further study of development and formation of celestial eye traits.

In view of the problem that the hot and cold loads of mushroom houses are affected by multiple factors such as environment, mushrooms, and equipment, which are difficult to accurately model, this paper proposes a short-term load prediction method based on empirical wavelet transform (EWT) and mixed autoregressive integrated moving average (ARIMA) and convolutional bi-directional short- and long-term attention mechanism (CNN-BiLSTM-Attention). The method first uses the Boruta algorithm to filter the input characteristics, and then uses the EWT method to decompose the mushroom house load data into 4 modal components. Then the Lempel-Ziv method is introduced to divide the modal components into two categories of high and low frequencies, and the CNN-BiLSTM-Attention and ARIMA prediction models are constructed separately. Finally, the two types of prediction results are superimposed and reconstructed to obtain the final load prediction value. The test results show that the Boruta algorithm can effectively filter out the characteristics of key influencing factors. Compared with the Spearman and Pearson correlation coefficient methods, the mean absolute error (MAE) of the prediction results is reduced by 14.72% and 3.75%, respectively; compared with the ensemble empirical mode decomposition (EEMD) method, the EWT method can increase the decomposition and reconstruction error by 103 orders of magnitude, which can effectively improve the prediction accuracy of the model; compared with the individual neural network model, the prediction effect of the model proposed in this paper has obvious advantages, and the MAE, root mean square error (RMSE) and mean absolute percentage error (MAPE) of the prediction results are reduced respectively. 31.06%, 26.52% and 39.27%.

An approach to estimate the dynamic characteristic of multilayered three-dimensional cubic quasicrystal cylindrical shells, annular plates, and truncated conical shells with different boundary conditions is presented. These investigated structures can be in a vacuum, totally filled with quiescent fluid, and subjected to internal flowing fluid, in which the fluid is incompressible and inviscid. The velocity potential, Bernoulli’s equation, and impermeability condition have been applied to the shell-fluid interface to obtain an explicit expression, from which the fluid pressure can be converted into the coupled differential equations in terms of displacement functions. The state-space method is formulated to quasicrystal linear elastic theory to derive the state equations for three structures along the radial direction. The mixed supported boundary conditions are represented by means of the differential quadrature technique and Fourier series expansions, respectively. A global propagator matrix, which connects the field variables at the internal interface to those at the external interface for the whole structure, is further completed by joint coupling matrices to overcome the numerical instabilities. Numerical examples show the correctness of the proposed method and the influence of the semi-vertical angle, different boundary conditions, and the fluid debit on the natural frequencies and mode shapes for various geometries and boundary conditions.

Understanding the thermal cracks of rock caused by high temperature is of great help to the development of underground engineering, such as geothermal mining, underground coal gasification. Although there has been many study on thermal cracking, it is not systematic and in-depth enough. In order to deeply study the thermal crack mechanism of rock, this paper conducted thermal cracking experiments on granite at different temperatures and heating/cooling paths, and qualitative and quantitative analysis was conducted on the crack initiation characteristics, propagation paths, and crack network morphology of rock thermal crack under different test conditions. The thermal crack mechanism was also analyzed from the perspectives of mineral petrology, fracture mechanics, thermodynamics, and other aspects. The research results show that there are two obvious mutation points in the study temperature range for samples with fast cooling paths (SF path: slow heating and fast cooling; FF path: fast heating and fast cooling), around 200-300 ℃ and 600 ℃, respectively, while for samples with slow cooling paths (SS path: slow heating and slow cooling; FS path: fast heating and slow cooling), there is only one mutation point around 600 ℃. The initiation positions of thermal cracking under all temperature paths are relatively similar, with intergranular crack located between particles at the edge of the sample or intercrystalline crack in the middle of feldspar or quartz aggregates. The initiation temperature of SF and FF path specimens is relatively low compared to SS and FS path specimens, and the number and size of cracks is small. The crack network structure formed by the SF path is the most complex, with the largest crack ratio and cumulative crack length; The crack network structure formed by the FF path is relatively complex, with a larger main crack size but relatively fewer secondary cracks; The FS and SS paths do not form a complex network with good connectivity. The process of thermal crack development can be divided into three stages: the development of small cracks, the joint development of main cracks and small cracks, and the connection of cracks into a network structure. The mechanism of thermal crack propagation is that the expansion and thermal conductivity between different crystals are different. The thermal stress caused by temperature gradient and the tension or shear stress caused by the inconsistent deformation of crystals form stress concentration in weak areas such as particles boundary, cleavage, and original cracks. Firstly, it causes some crystals with smaller strength or less rounded shape to crack, and when the combined stress is large, the cracks will gradually expand along the existing fine cracks. This also explains that the most main cracks of the SF and FF path specimens mainly surround some large mineral aggregates or between particles.

Fabrication of durable materials with excellent oil adsorption capacity and separation performance for the treatment of oily wastewater is meaningful based on smart responsiveness. Herein, a solvent-responsive melamine sponge (MS) was developed via silanization followed by the in-situ growth of zeolitic imidazolate framework-8 (ZIF-8). Detailed characterization of the resultant composite MS was conducted using scanning electron microscopy (SEM), energy dispersive spectrometer (EDS), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR). The multiscale hierarchical MS substrate exhibited highly hydrophobic property in the pH range of 1-11, along with a satisfactory adsorption capacity in the range of 65.4-134.2 g/g for different oils. The modified surface transformed from superhydrophobicity/superlipophilicity to superhydrophilicity/underwater superoleophobicity upon ethanol wetting, reverting to its original superhydrophobic state upon drying. The separation flux of the MS substrate was above 1.5×104L/m2h for both oil and water removal, along with the separation efficiency more than 98.7%. No obvious changes of the separation performance after 50 successive immiscible oil/water separation indicated the excellent durability and robustness of the anchored ZIF-8 nanoparticles on the surface of modified MS substrate. More importantly, oil-in-water emulsion separation was successfully carried out via the ZIF-8 MS composite with a high separation efficiency over 99.1%. The developed smart sponge with high oil absorption capacity, excellent chemical stability and fire resistance exhibited a wide range of potential practical applications in the convenient treatment of oily wastewater.

Fosmidomycin (FOS) is a naturally occurring compound active against the enzyme DXR in the MEP pathway, and using it as a template for lead structure design is an effective strategy in developing new active compounds. In this work, by replacing the hydroxamate unit of FOS with pyrazole, isoxazole and the related heterocycles that also have the metal ion binding affinity, while retaining the monophosphonic acid in FOS or replacing it with a bisphosphonic acid group, heterocycle-containing mono- and bisphosphonic acid compounds as FOS analogs were designed. The key steps involved in the facile synthesis of these FOS analogs include the Michael addition of diethyl vinylphosphonate or tetraethyl vinylidenebisphosphonate to β-dicarbonyl compounds and the subsequent cyclic condensation with hydrazine or hydroxylamine. Two additional isoxazolinone-bearing FOS analogs were synthesized by the Michaelis-Becker reaction with diethyl phosphite as a key step. The bioactivity evaluation on model plants demonstrated that several compounds have better herbicidal activities compared to FOS, with the most active compound showing a 3.7-fold inhibitory activity on Arabidopsis thaliana, while on the root and stalk of Brassica napus L. and Echinochloa crus-galli in pre-emergence inhibitory activity test, the activities of this compound were found to be 3.2- and 14.3-, 5.4- and 9.4-fold, respectively, and in post-emergency activity test on Amaranthus retroflexus and Echinochloa crus-galli, 2.2- and 2.0-fold inhibition activities were displayed. Despite the significant herbicidal activity, this compound exhibited a DXR inhibitory activity lower than that of FOS but comparable to that of other non-hydroxamate DXR inhibitors, and the dimethylallyl pyrophosphate rescue assay gave no statistical significance, suggesting a different target might be involved in the inhibiting process. This work demonstrates that using bioisosteric replacement can be considered a valuable strategy for discovering new FOS analogs that may have high herbicidal activity.

Event detection provides a crucial foundation for intelligent text analysis and supports numerous downstream applications. However, existing detection models often fail to meet the high accuracy requirements and typically require a human–machine collaborative detection mode involving “machine detection followed by manual audit and correction.” Analysis reveals that the recall rate of machine detection is a major factor limiting the efficiency of human–machine collaboration. To address this at its root and ensure high recall, an event trigger recommendation task is introduced, and a span-based recommendation model for Chinese, SpETR (Span-based Event Trigger Recommender), is developed. This model integrates confidence information from both trigger identification and event classification stages to recommend candidate triggers and their event types for each event. To enhance recall, a semantic boundary smoothing method is proposed, which assigns soft labels to spans around gold triggers based on semantic completeness and part-of-speech, combined with a modified focal loss function to make the model predictions smoother. Experiments on DuEE and a self-built dataset show that SpETR is most effective when the number of recommendations is set to 3, achieving recall rates of 97.76% and 98.70%, respectively, comprising improvements of 4.30% and 5.22% over the optimal baseline models. In terms of human–machine collaborative detection, SpETR saved 30.6% and 25.8% of time compared to traditional detection models on two datasets, and the average F1 score of the annotation results was also improved by 5.35% and 3.48%, respectively.

Single-phase-to-ground fault in non-effectively grounded systems poses serious public safety concern. Along with increasing deployment of low-voltage (LV) sensors, new opportunities and ways are created for solving this traditional problem in distribution systems. A new approach, identifying primary single-phase-to-ground line fault and locating it through measurement data from smart sensors deployed in the secondary side of distribution transformers, is proposed in this paper. When a fault occurs in primary distribution feeder, the transient aerial mode voltage (AMV) of each LV smart sensor is calculated. The fault line can be identified by an abrupt change value of AMV at LV side. Next, by finding the position of the maximum value of this AMV from LV sensors on the fault line, the fault location can be pinpointed to two neighboring distribution transformers. The proposed method has been proven to be efficient and reliable by simulation studies.

As an outstanding information carrier, skyrmion is increasingly widely used in devices based on complex geometries. To achieve the skyrmion-based spintronic devices, a reasonable and feasible nanotrack is essential. In this paper, we conducted a study on the current-driven skyrmion movement in a circular-ring-shaped nanotrack. Our results suggest that the asymmetry of the inside and outside boundary of the circular ring changed the stable position of the skyrmion, causing it to move like the skyrmion Hall effect when driven by currents. Moreover, the asymmetric boundaries have advantages in enhancing or weakening the skyrmion Hall effect. Additionally, we also compared the skyrmion Hall effect from the asymmetric boundary of circular ring nanotracks with that from inhomogeneous DMI. It is found that the skyrmion Hall effect caused by the circular ring is significantly greater than that caused by the inhomogeneous DMI. These results contribute to our understanding of the skyrmion dynamics in confined geometries and offer an alternative method for controlling the skyrmion Hall effect of skyrmion-based devices.

Discrete distribution estimation is a fundamental statistical tool, which is widely used to perform data analysis tasks in various applications involving sensitive personal information. Due to privacy concerns, individuals may not always provide their raw information, which leads to unpredictable biases in the final results of estimated distribution. Local Differential Privacy (LDP) is an advanced technique for privacy protection of discrete distribution estimation. Currently, typical LDP mechanisms provide same protection for all items in the domain, which imposes unnecessary perturbation on less sensitive items and thus degrades the utility of final results. Although, several recent works try to alleviate this problem, the utility can be further improved. In this paper, we propose a novel notion called Item-Oriented Personalized LDP (IPLDP), which independently perturbs different items with different privacy budgets to achieve personalized privacy protection. Furthermore, to satisfy IPLDP, we propose the Item-Oriented Personalized Randomized Response (IPRR) based on the observation that the sensitivity of data shows an inverse relationship with the population size of respective individuals. Theoretical analysis and experimental results demonstrate that our method can provide fine-grained privacy protection and improve data utility simultaneously.

Although neural network architectures are critical for their performance, how the structural characteristics of a neural network affect its performance has still not been fully explored. We here map architectures of neural network to directed acyclic graphs, and find that incoherence, a structural characteristic to measure the order of directed acyclic graphs, is a good indicator for the performance of corresponding neural networks. Therefore we propose a deep isotropic neural network architecture by folding a chain of same blocks then connecting the blocks with skip connections at different distances. Our models, named FoldNet, have two distinguishing features compared with traditional residual neural netowrks. First, the distances between block pairs connected by skip connections increase from always equal to one to specially selected different values, which lead to more incoherent graphs and let the neural network explore larger receptive fields and thus enhance its multi-scale representation ability. Second, the number of direct paths increases from one to multiple, which leads to a larger proportion of shorter paths and thus improve the direct propagation of information throughout the entire network. Image classification results on CIFAR-10 and Tiny ImageNet benchmarks suggested that our new network architecture performs better than traditional residual neural networks.

Near-surface humidity (Qa) is a key parameter that modulates oceanic evaporation and influences the global water cycle. Remote sensing observations act as feasible sources for long-term and large-scale Qa monitoring. However, existing satellite Qa retrieval models are subject to apparent uncertainties due to model errors and insufficient training data. Based on in situ observations collected over the China Seas over the last two decades, a deep learning approach named Ensemble Mean of Target deep neural networks (EMTnet) was proposed to improve the satellite Qa retrieval over the China Seas for the first time. The EMTnet model outperforms five representative existing models by nearly eliminating the mean bias and significantly reducing the root-mean-square error in satellite Qa retrieval. According to its target deep neural networks selection process, the EMTnet model can obtain more objective learning results when the observational data are divergent. The EMTnet model was subsequently applied to produce a 30-year monthly gridded Qa data over the China Seas. It indicates that the climbing rate of Qa over the China Seas under the background of global warming are probably underestimated by current products.

Visual question answering (VQA) is receiving increasing attention from researchers in both the computer vision and natural language processing fields. There are two key components in the VQA task: feature extraction and multi-modal fusion. For feature extraction, we introduce a novel co-attention scheme by combining Sentence-guide Word Attention (SWA) and Question-guide Image Attention (QIA) in a unified framework. To be specific, the textual attention SWA relies on the semantics of the whole question sentence to calculate contributions of different question words for text representation. For the multi-modal fusion, we propose a “Cross-modal Multistep Fusion (CMF)” network to generate multistep features and achieve multiple interactions for two modalities, rather than focusing on modeling complex interactions between two modals like most current feature fusion methods. To avoid the linear increase of the computational cost, we share the parameters for each step in the CMF. Extensive experiments demonstrate that the proposed method can achieve competitive or better performance than the state-of-the-art.

Quantifying the landscape pattern change can effectively demonstrate the ecological progresses and the consequences of urbanization. Based on remotely sensed land cover data in 1994, 2000, 2006 and a gradient analysis with landscape metrics at landscape- and class- level, we attempted to characterize the individual and entire landscape patterns of Shanghai metropolitan during the rapid urbanization. We highlighted that a roadscape transect approach that combined the buffer zone method and the transect-based approach was introduced to describe the urban-rural patterns of agricultural, residential, green, industrial, and public facilities land along the railway route. Our results of landscape metrics showed significant spatiotemporal patterns and gradient variations along the transect. The urban growth pattern in two time spans conform to the hypothesis for diffusion–coalescence processes, implying that the railway is adaptive as a gradient element to analyze the landscape patterns with urbanization. As the natural landscape was replaced by urban landscape gradually, the urban fringe expanded radically. The results also showed that the desakota region expanded its extent widely. Satellite towns witnessed the continual transformation from the predominantly rural landscape to peri-urban landscape. Furthermore, the gap between urban and rural areas remained large especially in public service. More reasonable urban plans and land use policies should push to make more of an effort to transition from the urban-rural separation to coordinated urban-rural development. This study is a meaningful trial in demonstrating a new form of urban–rural transects to study the landscape change of large cities from a strategic viewpoint. By combining gradient analysis with landscape metrics, we addressed the process of urbanization both spatially and temporally, and provided a more quantitative approach to urban studies.

This work investigated the influence of current density, plating solution flow rate, and nozzle outlet-cathode distance on the properties of Ni-diamond composite coatings. A multi-physics field simulation is employed to analyze the interplay between current density, plating solution flow rate, and nozzle outlet-cathode distance on the flow field and electric field distribution. Additionally, particle tracing simulations were incorporated into the model to evaluate the incorporation efficiency of diamond particles during composite electrodeposition. Experimental validation of the findings shows a significant increase in the diamond particle content of the coating. This combined approach provides valuable insights for optimizing the jet electrodeposition process for Ni-diamond composite coatings with superior properties.

Spacecraft recovery technology is crucial in the field of aerospace, in which the parachute plays a key role in slowing down the descent speed of the spacecraft and realizing a smooth landing. In order to construct a dynamically adjustable parachute deployment strategy, it is necessary to measure the parachute dynamic load accurately in real time. However, the existing sensor measurement scheme is difficult to meet the measurement requirements due to its large structure and complex wiring. In order to meet the current demand for real-time measurement of parachute cords dynamic load, a miniature measuring instrument is designed.According to the function and technical requirements of the miniature measuring instrument, the hardware modules of the acquisition system are selected and designed, and the integration debugging and performance optimization of the microcontroller module, A/D sampling module, signal acquisition circuit and power supply module are carried out. The software of the parachute cords tension acquisition system based on the miniature measuring instrument is developed. The elastomer is modeled by using SolidWorks and statically analyzed by using AnsysWorkbench finite element analysis software. Then the final structure of the elastomer and the pasting position of the strain gage are determined through the results analysis as well as experimental verification. The hardware module of the signal acquisition system for the miniature measuring instrument is then encapsulated. The force value of the miniature measuring instrument is calibrated and tested many times by using the microcomputer-controlled electronic universal testing machine. The experimental results show that the designed miniature measuring instrument has accurate data, strong stability and good real-time performance, which meets the demand for real-time accurate measurement of miniature measuring instrument, and can provide reliable data for parachute cords parameter validation and stepless unfolding design.

Photosynthetic function, photoprotection, and the response of related proteomics of mulberry (Morus alba L.) seedling leaves under NaCl and NaHCO3 stress with the same Na+ concentration (100 mmol•L-1) were studied by using photosynthetic gas exchange and chlorophyll fluorescence techniques combined with TMT proteomics. The results showed that NaCl stress had no significant effect on photosystem II (PSII) activity in mulberry seedling leaves, and the expressions of the related proteins, OEE3-1 and PPD4, of the PSII oxygen-evolving complex (OEC) and the antenna proteins, CP24 10A, CP26, and CP29, of LHCII in the leaves also increased to varying degrees. The photosystem I (PSI) activity in the leaves of mulberry seedling also increased, and the expressions of some proteins, PsaF, PsaG, PsaH, PsaL, PsaN, and Ycf4, in PSI increased significantly under NaCl stress. Under NaHCO3 stress, the activity of PSII and PSI and the expression of their protein complexes and the electron transfer-related proteins significantly decreased. NaCl stress had little effect on RuBP regeneration during dark reaction in the leaves and the expressions of glucose synthesis related proteins and net photosynthetic rate (Pn) did not decrease significantly. The leaves could adapt to NaCl stress by reducing stomatal conductance (Gs) to increase water use efficiency (WUE). Under NaHCO3 stress, the expression of dark reaction-related proteins was mostly down-regulated, and Gs was significantly reduced, which indicated that non-stomatal factors were important reasons for the significant inhibition of carbon assimilation. In the photoprotective mechanism under NaCl stress, the expression of cyclic electron flow (CEF) related proteins, ndhH, ndhI, ndhK, and ndhM, involved in NAD(P)H dehydrogenase (NDH) and the key enzyme of the xanthophyll cycle, violaxanthin de-epoxidase (VDE) were up-regulated. In addition, the ratio of xanthophyll cycle components (A+Z)/(V+A+Z) was increased. The expressions of proteins FTR and Fd-NiR, which are related to Fd-dependent ROS metabolism and nitrogen metabolism, were also significant up-regulated under NaCl stress, which can effectively reduce the electronic pressure on Fd. Under NaHCO3 stress, the expressions of CEF-related proteins, VDE, ZE, FTR, Fd-NiR, Fd-GOGAT, SGAT, and GGAT, were significant down-regulated, and the photoprotective mechanism, like the xanthophyll cycle, CEF, and photorespiration, might be damaged, resulting in the inhibition of PSII activity and carbon assimilation in leaves of mulberry seedling under NaHCO3 stress.

In order to reveal the impact of boundary-spanning activities of cooperative innovation teams on team innovation performance, this paper takes the panel data of 71 cooperative innovation teams from January to November 2022 as the research sample. It introduces intermediary variables (teamwork crafting and individual work crafting) to analyze the impact mechanism of boundary-spanning activities of teams on innovation performance, 71 teams were divided into 41 experimental groups and 30 control groups, and a quasi-natural experiment was conducted on the innovation performance of team boundary-spanning activities using the Double Difference Model (DID).Research has shown that boundary-spanning activities of collaborative innovation teams can promote team innovation performance. Team job crafting has a mediating effect on team innovation performance in boundary-spanning activities of collaborative innovation teams. Team job crafting and individual job crafting mediate between the boundary-spanning activities of collaborative innovation teams and team innovation performance. Further analysis using the double difference model found that compared to teams without boundary-spanning activities, teams with boundary-spanning activities can directly improve team innovation performance. When team reflection is vital, and task interdependence is high, it will promote team innovation performance. This research enriches the research on the effects of boundary-spanning activities of collaborative innovation teams, explores solutions based on quasi-nature, and provides a reference for improving the team innovation performance of collaborative innovation teams.

Nanosystems-based antifungal agents have emerged as an effective strategy to address issues related to drug resistance, drug release, and toxicity. Among the different materials used for drug delivery, multifunctional polymers have proven to be ideal due to their versatility. This review provides an overview of the various types of nanoparticles used in antifungal drug delivery systems, with a particular emphasis on the types of polymers used. The review focuses on the application of drug delivery systems and the release behavior of these systems. Furthermore, the review summa-rizes the critical physical properties and relevant information utilized in antifungal polymer nanomedicine delivery systems, and briefly discusses the application prospects of these systems.

The interaction between different regions normally is reflected by the form of the stream. For example, the interaction of the flow of people and flow of information between different regions can reflect the structure of cities’ network, and also can reflect how the cities function and connect to each other. Since big data has become increasingly popular, it is much easier to acquire flow data for various types of individuals. Currently, it is a hot research topic to apply the regional interaction model, which is based on the summary level of individual flow data mining. So far, previous research on spatial interaction methods focused on point-to-point and area-to-area interaction patterns. However, there are a few scholars who study the hotspot interaction pattern between two regional groups with some predefined neighborhood relationship by starting with two regions. In this paper, a method for identifying a similar hotspot interaction pattern between two regional groups has been proposed, and the Geo-Information-Tupu methods are applied to visualize the interaction patterns. For an example of an empirical analysis, we discuss China’s air traffic flow data, so this method can be used to find and analyze any hotspot interaction patterns between regional groups with adjoining relationships across China. Our research results indicate that this method is efficient in identifying hotspot interaction flow patterns between regional groups. Moreover, it can be applied to any analysis of flow space that is used to excavate regional group hotspot interaction patterns.

This paper studies the impact of agricultural subsidies and product certification on the use rate of green pesticides based on experimental economics. We found that agricultural subsidies effectively increased the utilization rate of green pesticides. If the agricultural subsidies raised from 20% to 100%, the green pesticides’ using rate increased by 438.51%. We also found that product certification increased the utilization rate of green pesticides by 376.16%%.The increase of agricultural subsidies is more effective than the product certification. Under a higher proportion of agricultural subsidies, farmers’ behavior will maintain “status bias”. Therefore, there are three suggestions proposed. Firstly, because of high price of green pesticides and lower production, the subsidies for agricultural materials should raise greatly to effectively improve the utilization rate of green pesticides. It is recommended that green pesticide provided free of charge in some wealthy areas. Secondly, both subsidies and product certification can improve the use rate of green pesticides. However, since the effect of agricultural subsidies is better than product certification, and farmers may have status bias. Therefore, it is recommended to give priority to the substantial increase on the proportion of agricultural subsidies, and then to product certification.

The unique characteristics of frescoes on overseas Chinese buildings can attest to the integration and historical background of Chinese and Western cultures. Reasonable analysis and preservation of overseas Chinese frescoes can provide sustainable development for culture and history. This research adopts the image analysis technology based on artificial intelligence, and proposes a ResNet-34 model and method integrating transfer learning. This deep learning model can identify and classify the source of the frescoes of the emigrants, and can effectively deal with the problems such as the small number of fresco images on the emigrants' buildings, poor quality, difficulty in feature extraction, and similar pattern text and style. The experimental results show that the training process of the model proposed in this article is stable. On the constructed Jiangmen and Haikou fresco JHD datasets, the final accuracy is 98.41%, and the recall rate is 98.53%. The above evaluation indicators are superior to classic models such as AlexNet, GoogLeNet, and VGGNet. It can be seen that the model in this article has strong generalization ability and is not prone to overfitting. It can effectively identify and classify the cultural connotations and regions of frescoes.

Concrete cracks have a detrimental effect on the strength properties and durability of the structures. So, repairing of concrete cracks to recover their strength parameters is more important task in civil engineering. To repair concrete cracks, MICP has been widely analysed in recent times; but, zero research is conducted to deeply investigate the repair effects of MICP on concrete cracks with rough surface by using the theoretic model. In current research, MICP with a novel mathematical model was attained by taking the precipitation of calcium carbonate (CaCO3), ureolysis, suspended biomass, geochemistry, transport of solute and biofilm growth. Furthermore, crack repair experiments were performed to check the workability of the new mathematical method. The outcomes revealed that the designed suspended biomass concentrations in cracks diminished step by step. The comparison in between the experimental results and calculated results verified the precision of migration behaviour of the suspended biomass. At the inlet, the solute concentrations and biofilm volume fractions was higher, causing in rise of yield amounts for calcium carbonate. The consumed solutes concentrations were higher for cracks of less rough surface, ultimately causing in smaller sonic time; and the values of sonic time for upper portions of cracks was smaller, showing good repair impacts. The recommended mathematical model provides a better tool that controls repair time and microbial metabolism process to report a new adjustive, bioremediation and biomineralization to concrete, which could provide a firm base for remediation of material in civil engineering field.

Pluripotent stem cells (PSCs) can differentiate into three germ layers and diverse autolo-gous cell lines. Being among the most commonly used large domesticated hoofed animals and serving as a vital source of food and bioreactors, cattle are among the many species in which PSCs have been developed. Bovine PSCs (bPSCs) are the "seed cells" of regenerative science and have immense potential to advance species propagation, genetic engineering, and disease treatment. Moreover, they can aid in screening new drugs for efficacy and toxicity, model human diseases, and establish a sustainable agricultural system that can cater to the needs of the growing global population. Establishing stable bPSCs in vitro has been a critical scientific challenge, and researchers have made numerous attempts to address this issue. This review primarily delves into the current research progress of bPSCs, the challenges faced, and their potential applications.

We present the generation and nonlinear frequency conversion of nanosecond cylindrical vector beams (CVBs) in two-mode fiber (TMF). Based on the polarized dependence vector mode coupling characteristic and the precise wavelength tunability of an acoustically-induced fiber grating (AIFG), the nanosecond cylindrical vector beams (CVBs, 1064 nm, 10 ns) is directly generated in a TMF with convenient switching characteristics between the radial and azimuthal vector beams. Furthermore, the stimulated Raman scattering (SRS) is produced based on the transmission of the nanosecond CVBs in the 100-meters long TMF, and the spatial intensity and polarization distributions characteristics the 1st-order Stokes shifted component is consistent with the nanosecond CVBs pump pulse. This work provides a method for achieving wavelength conversion of the CVBs in optical fiber.

Ti and its alloys are the most commonly used materials for biomedical applications. However, bacterial infection after implant placement is still one of the significant rising complications. Therefore, the application of the antimicrobial agents into implant surfaces to prevent implant-associated infection has attracted lots of attention. Scientific papers have shown that inorganic antibacterial metal element (e.g. Ag, Cu, Zn) can be introduced to implant surfaces with the addition of metal nanoparticles or metallic compounds into electrolyte via micro-arc oxidation (MAO) technology. In this review, the effects of the composition and concentration of electrolyte and process parameters (e.g. voltage, current density, oxidation time) on morphological characteristics (e.g. surface morphology, bonding strength), antibacterial ability and biocompatibility of MAO antimicrobial coating were discussed in detail. Anti-infection and osseo-integration can be simultaneously accomplished with the selection of the proper antibacterial elements and operating parameters. Besides, MAO assisted by magnetron sputtering (MS) to endow Ti-based implant materials with superior antibacterial ability and biocompatibility was also discussed. Finally, the development trend of MAO technology in the future was forecasted.

The need for cross-modal retrieval (CMR) among users is growing because of the swift advancements in computer vision and natural language processing. Promoting home operating systems is greatly aided by the openKylin home operating system. It is focused on enhancing the functionality of the operating system with safe and dependable operating technologies. Practical implications abound for integrating computer vision research into home operating systems. A multimodal retrieval approach based on openKylin is presented to improve the usability of text search graphs, audio, and video. The overview of pertinent domestic and international research is the main topic of this article. This technological advancement. It then offers details on the design, implementation procedure, and final implementation outcomes for demonstration. The works of natural operations show that this strategy has excellent accuracy and performance.

Tryptanthrin has not been widely applied in clinical practice due to its poor solubility and low bioavailability in spite of possessing several biological and pharmacological activities. Here, to improve the solubility of tryptanthrin, two types of novel tryptanthrin-loaded micelles were prepared. One was tryptanthrin physically encapsulated by distearoyl phosphatidylethanolamine polyethylene glycol (DSPE-PEG) and the other was pegylated tryptanthrin synthesized by acid-sensitive hydrazone bond and further prepared as micelles. Molecular imprinting technology was used to separate pegylated tryptanthrin and free mPEG-COOH in the preparation of PEGylated tryptanthrin micelles with considerably high separation efficiency. The solubility of tryptanthrin-loaded DSPE-PEG micelles (TDMs) and PEGylated tryptanthrin micelles (PTMs) was increased by 300 and 1493 fold compared with that of tryptanthrin, respectively. The PTMs increased the solubility of tryptanthrin more effectively and 95% of tryptanthrin was released from PTMs at pH 5.5 in 12 h. The cytotoxicity of PTMs decreased under physiological conditions compared with that of tryptanthrin, whereas at pH 5.5, the PTMs showed comparable cytotoxicity with that of tryptanthrin, indicating successful drug release from the carrier in response to tumor cell pH. Overall, we elucidated an efficient method to improve water solubility of tryptanthrin and indicated pegylated tryptanthrin is a promising prodrug.

With the rapid advancements in remote sensing technology, the spectral information from hyperspectral remote sensing images has become increasingly rich, facilitating detailed spectral analysis of the Earth's surface objects. However, this abundance of spectral data poses significant challenges in data processing, such as the curse of dimensionality leading to the “Hughes” phenomenon, "strong correlation" due to high resolution, and "non-linear characteristics" caused by varied surface reflectance rates. Therefore, dimensionality reduction of hyperspectral data has become a crucial task. This paper, grounded in manifold theory and manifold learning techniques, and considering the non-linear structures and features in hyperspectral remote sensing data, elucidates the principles and processes of dimensionality reduction in hyperspectral remote sensing images using manifold learning, with a formalized expression of the process. This article introduces spectral information divergence (SID) into the nearest neighbor graph computation of manifold learning algorithms. The principles and computational processes of nearest neighbor graph algorithms based on Euclidean distance (ED), spectral angle mapping (SAM), and SID are studied, and a comparative analysis of the dimensionality reduction effects under these three metrics in hyperspectral data is conducted. Experiments on feature extraction under different metrics were performed using the publicly available Indian Pines hyperspectral dataset. The intrinsic features obtained post-dimensionality reduction were used as inputs for classification algorithms in ground objects classification experiments, with algorithm runtime, overall accuracy, and Kappa coefficient as evaluation metrics for dimensionality reduction quality. The results demonstrate that nearest neighbor graph computation based on SAM and SID outperforms traditional ED methods; SAM-based computation has the lowest time complexity, while SID-based manifold learning yields the highest accuracy in ground objects classification. Thus, manifold learning based on SAM and SID metrics proves to be an effective method for feature extraction in hyperspectral remote sensing data, underscoring the potential of manifold learning techniques in the dimensionality reduction of hyperspectral remote sensing images.

Spider silk has excellent strength and elasticity in natural, researchers have been working for decades try to achieve natural spider silk outstanding mechanical properties using recombinant spider silk protein (spidroin) through artificial spinning. In this work, we chose wet spinning method to explore the relationship between concentration of coagulation bath and fiber performance. It was found that the concentration of methanol has important effect on fiber continuity, diameter and mechanical properties. Lower concentration favors spinning continuous thinner, fibers with high strain. Secondary stretching benefits spinning silk fibers with stable mechanical properties, and thermal stability. Through applying different methanol concentration and additional stretching, we obtained silk fibers with Young’s modulus of 3.052± 2.626 GPa, stress of 25.3944 ± 17.48 MPa, and strain of 140 ± 95.4%.

A fast calculation method for the full parallax high-resolution hologram is proposed based on the elemental light field image (EI) rendering. A 3D object located near the holographic plane is firstly rendered as multiple EIs with a pinhole array. Each EI is interpolated and multiplied by a divergent sphere wave and interfered with a reference wave to form a hogel. Parallel acceleration is used to calculate the high-resolution hologram because calculation of each hogel is independent. A high-resolution hologram with the resolution of 20,0000×20,0000 pixels is calculated only within 8 minutes. Full parallax high-resolution 3D displays are realized by optical reconstructions.

Hepatic carboxylesterase 1(CES1) metabolizes many prodrugs into active ingredients or direct-acting drugs into inactive metabolites. We aim to develop a semi-physiologically based pharmacokinetic model(Semi-PBPK model) to simultaneously predict pharmacokinetics of CES1 substrates and their active metabolites in liver cirrhosis(LC) patients. Six prodrugs(enalapril, benazepril, cilazapril, temocapril, perindopril and oseltamivir) and three direct-acting drugs (flumazenil, pethidine and remimazolam) were selected. The parameters including organ blood flows, plasma binding protein concentrations, functional liver volume, hepatic enzymatic activity, glomerular filtration rate(GFR) and gastrointestinal transit rate were introduced into the simulation. Pharmacokinetic profiles of these drugs and their active metabolites were simulated in 100 virtual subjects. The developed semi-PBPK model, following validation in healthy subjects, was extrapolated to LC patients. Most of the observations are within the 5% and 95% quantile of simulations from 100 virtual patients. The estimated AUC and Cmax are within 0.5-2-fold of observation. The sensitivity analysis showed that the decreased plasma exposure of active metabolite due to the decreased CES1 was partly attenuated by the decreased GFR. Conclusion: The developed PBPK model has successfully predicted pharmacokinetics of CES1 substrates and their metabolites in healthy subjects and LC patients, which assists in tailoring dosages of CES1 substrates in LC patients.

The impacts of inflation on international finance are generally reflected in the decline of buying power, risks of investment and deposit loss from currency devaluation. For the purpose of optimized allocation and management of asset values, i.e., annual income or research grants, a framework of a three-level model for static financial management is presented to maximize banking interests, bonuses, and the remaining balance after spending necessary expenditures. Meanwhile, in retrospect to higher-level financial inflation, strategies of dynamic investment, i.e., posing regular tests of flipping coins, exploiting variations of the currency exchange rate, as well as applying the theory of broad money, are presented to increase the appreciation rate of net assets in and post the era of COVID-19. Quantitative evaluations in case studies verify the feasibility of improving the financial situation, indicating broader applications for budgeting and investing when US inflation rate is below 3.0%. Besides, combining approaches of static and dynamic strategies, the expected annual growth rate of individual zero-risk asset investment is predicted as within the range of 8.30~9.62% according to budgeted appreciation on net assets in 12 months, which is capable of overcoming negative impacts from higher level annual inflation, i.e., those as highest as 8.01% in the Year 2022.

The greatly diversified flowering plants (angiosperms) are the dominating and defining group in the current earth ecosystem. However, from which group by what way the flowers, especially their gynoecia (key characteristics of angiosperms), are derived have been the questions in botany unanswered over centuries. Such an embarrassing situation can be attributed to the lack of plants with partially enclosed ovules, which are supposed to be a post between gymnosperms and angi-osperms. Here we report a fossil plant that has an apparent coniferous vegetative and reproduc-tive morphologies but has a single seed partially wrapped by the subtending bract. Such a mor-phology suggests that the carpels in angiosperms may be equivalent to bracts enclosing their axil-lary seed(s). Such a non-traditional interpretation of the homology of angiosperm carpels is com-patible with various new progresses made in botany and is in line with Tomlinson’s recent hy-pothesis. Together with other fossil evidence reported recently, it appears that gynoecia in angio-sperms are derived in multiple ways.

Soil organic matter (SOM) is important for the global carbon cycle, and hyperspectral remote sensing has proven a promising method for fast SOM content estimation. However, soil physical properties significantly affect the sensitivity of satellite hyperspectral imaging to SOM, leading to poor generalization ability of the estimation model. This study aims to improve the spatiotemporal transferability of the SOM prediction model by alleviating the coupling effect of soil physical properties on the spectra. Based on satellite hyperspectral images and soil physical variables, including soil moisture (SM), soil surface roughness (root mean squared height, RMSH), and soil bulk weight (SBW), a soil spectral correction strategy was established based on the information unmixing method. Two important grain-producing areas in Northeast China were selected as study areas to verify the performance and transferability of the spectral correction model and SOM content prediction model. The results showed that soil spectral corrections based on fourth-order polynomials and the XG-Boost algorithm had excellent accuracy and generalization ability, with residual predictive deviations (RPD) exceeding 1.4 in almost all bands. In addition, when the soil spectral correction strategy was adopted, the accuracy of the SOM prediction model and the generalization ability after model migration were significantly improved. The SOM prediction accuracy based on the XG-Boost corrected spectrum was the highest, with a coefficient of determination (R2) of 0.76, root mean square error (RMSE) of 5.74 g/kg, and RPD of 1.68. The prediction accuracy, R2, RMSE, and RPD of the model after migration were 0.72, 6.71 g/kg, and 1.53, respectively. Compared with the direct migration prediction of the model, adopting the soil spectral correction strategy based on fourth-order polynomials and XG-Boost reduced the RMSE of the SOM prediction results by 57.90% and 60.27%, respectively. The performance comparison highlighted the advantages of considering soil physical properties in regional-scale SOM prediction.

Tilapia lake virus (TiLV) is the main tilapia-infecting virus worldwide, causing serious economic losses. However, there is no vaccine for this viral disease. Here, TiLV ORF10 (TiLV-ORF10) encoding a protein with abundant epitopes was constructed into the eukaryotic expression vector pcDNA3.1, and used to evaluate the immune protective effects in Nile tilapia (Oreochromis niloticus). RT-PCR and western blot analyses confirmed vaccine plasmid expression in tilapia muscle tissues. Moreover, the transcription levels of immunoglobulin M, toll-like receptor 2, myeloid differentiation factor 88, interleukin 8, tumor necrosis factor alpha, gamma-IFN, and nuclear factor κB immune-related genes were statistically significantly upregulated in the spleen, liver, and kidney of vaccinated tilapias (P < 0.05). TiLV challenge experiments showed that relative percent survival (RPS) was significantly enhanced in fish by this DNA vaccine. Moreover, RPS was enhanced further when using a higher amount of the DNA vaccine (85.72% RPS at a DNA dose of 45 μg pcDNA3.1–ORF10). Vaccination with pcDNA3.1–ORF10 significantly reduced virus replication, as evidenced by the low amount of virus in the spleen, liver, and kidney of vaccinated tilapias after TiLV challenge. Thus, pcDNA3.1–ORF10 could induce protective immunity in tilapia and may be a potential vaccine candidate for controlling diseases caused by TiLV.

A plasmonic refractive index (RI) sensor based on metal-insulator-metal (MIM) waveguide coupled with concentric double rings resonator (CDRR) is proposed and investigated numerically. Utilizing the novel supermodes of the CDRR, the FWHM of the resonant wavelength can be modulated, and a sensitivity of 1060 nm/RIU with high figure of merit (FOM) 203.8 is realized in the near-infrared region. The unordinary modes as well as the influence of structure parameters on the sensing performance are also discussed. Such plasmonic sensor with simple framework and high optical resolution could be applied to on-chip sensing systems and integrated optical circuits. Besides, the special cases of bio- sensing and triple rings are also discussed.

Under the influence of various factors, the bronze ware unearthed by archaeology has various diseases of different degrees, and the mineralization problem is more prominent. The physical properties of mineralized bronzes have been destroyed, and the whole is loose and fragile, which is in urgent need of reinforcement and protection. Common reinforcement and protection materials mainly consider surface sealing, matrix bonding reinforcement and penetration reinforcement. Considering the low matrix strength and complex disease types of fragile bronzeware, it is difficult to achieve targeted protection with commonly used reinforcement and protection materials. In view of the problems such as poor permeability and easy discoloration of commonly used protection materials, this paper uses self-developed reinforcement and protection material AMC to compare its reinforcement and protection performance with B72, which has a high comprehensive evaluation on the performance of commonly used reinforcement and protection materials. The matrix strength was increased, and the appearance intervention degree was less than B72.

A series of defective ZSM-5 zeolites (~300 nm, SiO₂/Al₂O₃ ratio of 55, 100, 400 and 950) were intentionally prepared and systematically studied by XRD, SEM, ²⁹Si MAS NMR, argon physisorption, NH₃-TPD and FT-IR technologies. The nature, the amount and the accessibility of the acid sites of defective ZSM-5 zeolites are greatly different from reported ZSM-5 zeolites with perfect crystal structure. The co-existed strong Brønsted acid sites (Si(OH)Al) and weak Brønsted acid sites (hydroxyl nests) over defective ZSM-5 zeolites might lead to unique catalytic function. Zn(C₂H₅)₂ was grafted onto defective ZSM-5 zeolites through chemical liquid deposition (CLD) method. Interestingly, FT-IR spectroscopy studies find that Zn(C₂H₅)₂ was preferentially grafted on the hydroxyl nests with weak acidity rather than the Si(OH)Al groups with strong acidity over different defective ZSM-5 zeolites. Particularly, home-built operando dual beam FTIR-MS was applied to study the catalytic performance of Zn species locating at different sites of defective ZSM-5 zeolites under n-hexane transformation. Results show that Zn species grafted over hydroxyl nests obtain better dehydrogenation performance than Zn species over framework aluminum. This study provides guidance for the rational design of highly efficient alkane dehydrogenative aromatization catalysts.

High-precision displacement sensing has been widely used across from both scientific researches and industrial applications. The recent interests in developing micro-opto-electro-mechanical systems (MOEMS) have given rise to an excellent platform for miniaturized displacement sensors. Advancement in this field during past years is now yielding integrated high-precision sensors which show great potential in applications ranging from photoacoustic spectroscopy to high-precision positioning and automation. In this review, we briefly summarize different techniques for high-precision displacement sensing based on MOEMS, and discuss the challenges for future improvement.

This letter presents a dual-frequency terahertz amplitude modulator based on a cross-shaped structure and U-shaped metal patches. Its structural unit is a typical metal-substrate structure. The top metal consists of a cross-shaped structure and U-shaped metal patches, and the bottom substrate layer is made of quartz. Amplitude modulation is achieved by adjusting the temperature of the vanadium dioxide (VO2) patches. The modulation depth can be approximately 75%. The mechanism of the resonance frequency is explained by the equivalent circuit model. The proposed structure shows good amplitude modulation capability at different incidence and azimuth angles by changing the location of the VO2 patches. The dual-frequency terahertz amplitude modulator can be used in terahertz communication, imaging, etc.

In this paper, an ultracompact combined sensor for displacement and angle synchronous measurement is proposed based on self-imaging effect of optical microgratings. Using a two-grating structure, linear and angular displacement can be measured by detecting the change of phase and amplitude of the optical transmission respectively within one single structure in meantime. The optical transmitted properties of the two-grating structure are investigated in both theory and simulation. Simulated results indicate that, the optical transmission changes in a sinusoidal relationship to the input linear displacement. Meanwhile, the amplitude of the curve decreases with an input pitch angle, indicating the ability for synchronous measurement within one single compact structure. The synchronous measurement of the linear displacement and the angle is also demonstrated experimentally. The results show a resolution down to 4nm for linear displacement measurement, and a sensitivity of 0.26mV/arcsec within a range of ±1° for angle measurement. Benefitting from a simple common-path structure without using optical components including reflectors and polarizers, the sensor shows an ultrahigh compactness for multiple-degrees-of-freedom measuring, indicating the great potential for this sensor in the fields such as integrated mechanical positioning and semiconductor fabrication.

The spectra and global distributions of the X-ray emissions generated by the solar wind charge-exchange (SWCX) process in the terrestrial magnetosheath are investigated based on a global hybrid model and a global geocoronal hydrogen model. The solar wind O6+ ions which are the primary charge state for oxygen ions in solar wind are considered. The line emissivity of the charge-exchange born O5+ ions are calculated by Spectral Analysis System for Astrophysical and Lab oratory (SASAL). It is found that the emission lines from the O5+ ranges from 105.607 to 118.291 eV with the strong line at 107.047 eV. We then simulated the magnetosheath X-ray emission intensity distributions with a virtual camera at two positions of north pole and dusk at six stages during the passing of a perpendicular interplanetary shock combined with a tangential discontinuity structure through the Earth’s magnetosphere. During this process, the X-ray emission intensity increases with time, and the maximum value is 27.11 keV cm-2 s-1 sr-1 on the dayside, which is 4.5 times that before the solar wind structure reaches the Earth. A clear shock structure can be seen in the magnetosheath and moves earthward. The maximum emission intensity seen at dusk is always higher than that seen at north pole.

Nowadays, it is highly desired to develop highly active and humidity resistive ozone decomposition catalyst to eliminate the ozone contaminant, one of the primary pollutants in air. In this work, a series of Cu2S hollow structured materials are rapidly synthesized using different structured Cu2O templates. The Cu2S from porous Cu2O shows the highest ozone catalytic decomposition efficiency of >95% to 400 ppm ozone with a weight hourly space velocity of 480,000 cm3g-1h-1 in dry air. Importantly, the conversion still keeps >85% in a high relative humidity of 90%. The mechanism is explored by diffusive reflectance infrared spectroscopy which shows the decomposition intermediate of O22-, and the X-ray photoelectron spectroscopy reveals the dual active site of both Cu and S. All these results show the effective decomposition of ozone by Cu2S especially in harsh environments, promising for active ozone elimination.

Product innovation is a crucial factor in enterprise survival. Even though there are sources from strategic theory that guides the clear comprehension towards appreciating the nexus between these two variables (product innovation and enterprise survival), there are still many lacunas that should be addressed and filled. Consequently, the need for additional empirical corroboration or support is pertinent. This study aimed at verifying the nexus between product innovation and enterprise survival, and how they are affected by the existence of antecedent variables such as competitive intensity and competitive advantage. In the methodology, this study adopts the conduct of explanatory and cross-sectional investigations through the use of structural equation modelling (SEM) to a sample of selected food and beverages enterprises in Lagos, Nigeria. Regarding the food and beverage enterprises in Lagos, Nigeria, this study discovered that competitive intensity has huge positive implication on product innovation at (0.39; t = 5.69, p < 0.05). This gives numerical evidence that, in the face of more market competition, enterprises will be pressured to adopt the model of costs reduction on products which will enhance the reduction of product prices, and will have significant impact on profit. However, the findings reveal that there is no significance between competitive advantage and product innovation at (0.002; t = 0.203, p > 0.05), and there is no significance between product innovation and enterprise survival at (-0.035; t = -1.583, p > .05). As a result, the food and beverage enterprises should concentrate more on product innovation so that they will be able to stand the intensity of competition. The results emanated from the study is germane as it make significant contribution to literature and the body of knowledge and on strategic management by enlightening that competitive intensity is a necessary inducement for product innovation.

With the increasing demand for security surveillance, assisted driving, and remote sensing, target detection networks with rich environmental perception capabilities and high detection accuracy have become a research hotspot. However, detection techniques based on single-modality images face limitations in environmental adaptability, as they are easily affected by lighting conditions, as well as obstacles such as smoke, rain, and vegetation, leading to information loss and failing to meet the required accuracy. To address these issues, we propose a target detection network—IV-YOLO, which integrates features from both visible and infrared images. We built a dual-branch fusion network based on YOLOv8 (You Only Look Once v8) that combines infrared and visible images for target detection. On this foundation, we designed a Bidirectional Pyramid Feature Fusion structure (Bi-Fusion) to fully integrate complementary features from different modalities, reducing detection errors caused by feature redundancy and extracting fine-grained features of small targets through dual-modal fusion. Additionally, we developed the Shuffle-SPP structure, which combines channel and spatial attention mechanisms to enhance focus on deep features and further aggregate upsampling, extracting richer features. To improve the model’s expressive power, we designed a loss function tailored for multi-scale target detection boxes, accelerating the network’s convergence during training. Experimental results show that the proposed IV-YOLO network achieves an average precision (mAP) of 74.6% on the UAV remote sensing dataset, 75.4% on the KAIST pedestrian dataset, and 84.8% on the FLIR dataset. While ensuring detection accuracy, our model significantly reduces computational load, making it well-suited to meet real-time requirements. This architecture is expected to find broad application in fields such as autonomous driving, public safety, and others.

Coal mining has caused a significant loss of nitrogen content of soil in mining areas. This article studies the effects of organic fertilizer, inorganic fertilizer, and combined application of Pseudomonas fluorescens with the ability of nitrogen fixation on soil nitrogen accumulation and composition in the reclamation area of Tunlan Coal Mine from 2016 to 2022 under the condition of equal nitrogen application, providing scientific basis for microbial fertilization and rapid increase of nitrogen content in the reclaimed soil of mining areas. The results showed that as the reclamation time increased, the nitrogen content and its composition structure of the soil treated with fertilization rapidly evolved towards normal farmland soil. The soil nitrogen content increased the fastest in the treatment of Pseudomonas fluorescens + organic fertilizer (MB), compared with inorganic fertilizer (CF), organic fertilizer (M), and Pseudomonas fluorescens + inorganic fertilizer (CFB) treatments, the treatment of Pseudomonas fluorescens + organic fertilizer (MB) can bring the total nitrogen (TN) content of the soil to normal farmland soil levels 1-3 years earlier. The comprehensive scores of Pseudomonas fluorescens + organic fertilizer (MB) and Pseudomonas fluorescens + inorganic fertilizer (CFB) on the two principal components were increased 1.58 and 0.79 than those of organic fertilizer (M) and inorganic fertilizer (CF) treatments, respectively. This further indicates that the combination of Pseudomonas fluorescens and organic fertilizer has a better effect on improving soil nitrogen accumulation than the combination of Pseudomonas fluorescens and inorganic fertilizer. At the same time, the application of Pseudomonas fluorescens will increase the content of unknown nitrogen (UN) in acid-hydrolysable nitrogen (AHN), and decrease the content of amino acid nitrogen (AAN) and ammonia nitrogen (AN), relatively. However, there was no significant effect on the content of ammonium nitrogen (NH4+-N) and nitrate nitrogen (NO3--N) in soil inorganic nitrogen (SMN). When combined with inorganic fertilizer, the contribution of soil mineralized nitrogen (SMN) to total nitrogen (TN) increased by 14.78%, while when combined with organic fertilizer, the contribution of acid-hydrolysable nitrogen (AHN) to total nitrogen (TN) increased by 44.77%. In summary, the use of Pseudomonas fluorescens is beneficial for nitrogen recovery in the reclaimed soil of coal mining areas. The optimal fertilization method under the experimental conditions is the combination of Pseudomonas fluorescens and organic fertilizer.

Background: Esophageal cancer was hardly diagnosed in early stage, and more potential biomarkers should be found. Methods: 252 patients and normal controls which recruited in Renmin Hospital of Wuhan University, were divided into esophageal carcinoma group (105 cases), disease control group (75 cases) and the control group of healthy people (72 cases). Moreover, TISIDB and GEPIA databases were used to investigate the different expression of EC and normal tissues, and explore the roles of C1q in tumor-immune system interactions in EC. Results: The concentration of serum C1q in EC group is 196.8(180~219.4) mg/L, which is higher than the level of DC [178.10(153.70~200.85) mg/L]and HC [183.00(167.75~201.00) mg/L] (P<0.05). A higher expression level of C1q was observed in Ⅲ and Ⅳ grades [214(192~237.3) mg/ml] than grades Ⅰ and Ⅱ [180.95(172.03~193.85) mg/L] (P<0.05). C1q was positively correlated with eosinophils, active CD8 T cells, myeloid derived suppressor cells, natural killer cells, monocytes and macrophages (r = 0.373; r = 0.659; r = 0.846; r = 0.760; r = 0.499; r = 0.757; P<0.05). Conclusion: The concentrations of C1q increased in EC and related to the severity of EC, which had potential value of diagnosis of EC. There were correlations in C1q and tumor-infiltrating lymphocytes.

In the era of massive construction, damaged and aging infrastructure are becoming more common. Defects, such as cracking, spalling, etc., are main types of structural damage that widely occur. Hence, ensuring the safe operation existing infrastructure through health monitoring has emerged as an important challenge facing structural engineers. In recent years, intelligent approaches, such as data driven machine and deep learning crack detection, gradually dominate over traditional methods. Among them, the semantic segmentation using deep learning models is a process of characterization of accurate location and portrait of cracks using pixel level classification. Most available studies rely on single model knowledge to perform this task. However, it is well-known that the single model might suffer from low variance and low ability to generalize in case of data alteration. By leveraging the ensemble deep learning philosophy, a novel corporative semantic segmentation of concrete cracks method called Co-CrackSegment is proposed. Firstly, five models, namely the U-net, SegNet, DeepCrack19, DeepLabV3-ResNet50, and DeepLabV3-ResNet101 are trained to serve as core models for the ensemble model Co-CrackSegment. To build the ensemble model Co-CrackSegment, a new iterative approach based on the best evaluation metrics, namely the dice score, IoU, pixel accuracy, precision, and recall metrics is developed. Results show that the Co-CrackSegment exhibits a prominent performance compared to core models and weighted average ensemble by means of the considered best statistical metrics.

Objectives: To investigate the value of early lactate dynamic monitoring index in predicting prognosis of patients with sepsis and septic shock. Methods: We performed our test on 50 patients. Out of 50 patients, 28 are male, and 22 are female. Prospectively studied pediatric patients with septic shock were performed. Vital signs, Lactate clearance, were obtained at presentation 6 h, 12 h, 24 h over the first 48 h of hospitalization. The therapy received, outcome parameters of mortality and duration of hospitalization were recorded. Results: The statistical data and comparative analysis showed that an average of 16.88 days after admission, 5 patients have died, 17 patients are poorly prognosis leaves the hospital, and the remaining 28 are recovered and discharged. The primary outcome variable of mean 16 days hospitalization mortality rate was 10%. Poor prognosis 34% and fully recovery 56 % were observed. In this retrospective cohort study, a lactate level of more than 2.5mmol/L was the best threshold to predict 28-day mortality among severe sepsis and septic shock patients. In our research, we found mean LC 6 h 3.08mmol/L, and after 48 h mean it is 1.79mmol/L. Significant LC 6 h found, which is 8.08mmol/L in the death group patient where 48 h mmol/L shows significant high. Poor prognosis also presents a clinical increase of lactate level high in the LC 6 h analysis, which is 3.32mmol/L. Recovered patients showed a significant improvement after administering treatment depending on the patient organ involvement and good decrease of lactate reports achieved, which is 1.20mmol/L, where admission reports show it was 1.91mmol/L in LC 6 h. Mean Heart rate 94/51mmhg, pulse 119, temperature 39℃, respiratory rate 32.26, and urine output 456 ml recorded during our study. Death patient shows a remarkable detonation of those reports but has a significant clinical report with the recovered patients. Conclusion: The early lactate dynamic monitoring index has a high value in predicting sepsis and septic shock patients' prognosis, thus worth popularizing.

The morbidity and mortality caused by invasive fungal infections is increasing across the globe due to developments in transplant surgery, the use of immunosuppressive agents, and the emergence of drug-resistant fungal strains, which has led to a challenge in terms of treatment due to the limitations of three classes of drugs. Hence, it is imperative to establish effective strategies to identify and design new antifungal drugs. Drug repurposing is an effective way of expanding the application of existing drugs. In the last years, various existing drugs have been shown to be useful in the prevention and treatment of the invasive fungi. In this review, we summarize the currently used antifungal agents. In addition, the most up to date information on the effectiveness of existing drugs with antifungal activity is discussed. Moreover, the antifungal mechanisms of existing drugs are highlighted. These data will provide valuable knowledge to stimulate further investigation and clinical application in this field.

Japanese encephalitis is a zoonotic disease caused by Japanese encephalitis virus (JEV). It is mainly epidemic in Asia with an estimated 69,000 cases occurring per year. However, no approved agents are available for the treatment of JEV infection, and existing vaccines cannot resist various types of JEV strains. Drug repurposing is a new concept for finding new indication of existing drugs, and recently, it has been used to discover new antiviral agents. Identifying host proteins involved in the progress of JEV infection and using these proteins as targets are the center of drug repurposing for JEV infection. In this study, based on the gene expression data of JEV infection and the phenome-wide association study (PheWAS) data, we identified 286 genes participating in the progress of JEV infection using the systems biology methods. The enrichment analysis of these genes suggested that the genes identified by our methods were predominantly related to viral infection pathways and immune response-related pathways. We found that bortezomib which can target these genes may have potential effect on the treatment of JEV infection. Subsequently, we evaluated the antiviral activity of bortezomib using the JEV-infected mice model. The results showed that bortezomib can lower JEV-induced lethality in mice, alleviate suffering in JEV-infected mice and reduce the damage in brains caused by JEV infection. This work provides a new method for the development of antiviral agents.

Spermatogonial stem cells (SSCs) are the only primitive spermatogonial cells in males that can naturally transmit genetic information to their offspring and replicate throughout their lives. Phospholipase D family member 6 (PLD6) has recently been found to be a surface marker for SSCs in mice and boars; however, it has not been validated in cattle. The results of RT-PCR and qRT-PCR found that the relative expression of PLD6 gene in the testicular tissues of 2-year-old Simmental calves was significantly higher than that of 6-month-old calves. Immunofluorescent staining further verified the expression of PLD6 protein in bovine spermatogenic cells like germ cell marker VASA. Based on multiple bioinformatic databases, PLD6 is a conservative protein which has high homology with mouse Q5SWZ9 protein. It is closely involved in the normal functioning of the reproductive system. Molecular dynamics simulation analyzed the binding of PLD6 as a phospholipase to cardiolipin (CL), and PLD6-CL complex showed high stability. The protein interaction network analysis showed that there is a significant relationship between PLD6 and piRNA binding protein. PLD6 acts as an endonuclease and participates in piRNA production. In addition, PLD6 in bovine and mouse testes has a similar expression pattern with the spermatogonium-related genes VASA and PIWIL2. In conclusion, these analyses imply that PLD6 has a relatively high expression in bovine testes and could be used as a biomarker for spermatogenic cells including SSCs.

In our article in Genome Biology Ecology six years ago, one complete plastid genome of Belian was assembled for comparative analyses of the plastomes in Lauraceae. However, Ariati et al. (2023) concluded that our sequenced Belian individual could be located in the clade of Myristicaceae instead of that of Lauraceae. Here, we performed re-analyses of additional two Belian plastomes, along with 42 plastomes from plants spanning ten families of the Magnoliids. The plastomes of the three Belian individuals range from 157,535 to 157,577 bp in length. Comparative genomic analysis revealed 170 mutation sites in their plastomes, which include 111 substitutions, 53 indels, and six microinversions. Phylogeny was reconstructed using maximum likelihood and Bayesian approaches for 44 magnoliids species indicated that our three Belian individuals are nested among the species in the family Lauraceae rather than Myristicaceae.

Malaria, as a major global health problem, continues to affect a large number of people each year, especially those in the developing countries. Effective drug discovery is still one of the main efforts to control malaria. As natural products are still considered as a key source for discovery and development of therapeutic agents, we have evaluated more than 2000 plant extracts against Plasmodium falciparum. As a result, we discovered dozens of plant leads that displayed antimalarial activity. Our phytochemical study of some of these plant extracts led to identification of several potent antimalarial compounds. The prior comprehensive review article entitled “Antimalarial activity of plant metabolites” by Schwikkard and Van Heerden (2002) reported structures of plant-derived compounds with antiplasmodial activity and covered literature up to the year 2000. As a continuation of this effort, the present review covers the antimalarial compounds isolated from plants, including marine plants, reported in the literatures from 2001 to the end of 2017. During the span of the last 17 years, 175 antiplasmodial compounds were discovered from plants. These active compounds are organized in our review article according to their plant families. In addition, we also include ethnobotanical information of the antimalarial plants discussed.

After long years of development, the technology of analyzing the working condition of power units based on vibration signals has had relatively stable applications, but the accuracy and the degree of automation and intelligence for fault diagnosis are still inadequate due to the limitations of the current development of key technologies. With the development of big data and artificial intelligence technology, the involvement of new technologies will be an important boost to the development of this field. To support the subsequent research, bibliometrics is used as a tool to sort out the development of the technology in this field at the macro level; at the micro level, the classical and key literature is studied to grasp the development status at the technical level and prepare for the selection of entry points to continue in-depth innovation afterwards.

The emergence of non-canonical amino acids (ncAAs) has enriched the functional pool inherent in canonical amino acids (cAAs). ncAAs are important building blocks in the production of various pharmaceuticals. The biosynthesis of ncAAs has emerged as an alternative to traditional chemical synthesis because of its environmental friendliness and high efficiency. The breakthrough genetic code expansion (GCE) technique developed in recent years has allowed for the incorporation of ncAAs into target proteins, giving them special functions and biological activities. Biosynthesis of ncAAs and their incorporation into target proteins within a single microbe has become an enticing application of such molecules. Based on that, in this study we first review the biosynthesis methods for ncAAs and analyze the difficulties in biosynthesis. We then summarize the GCE methods and analyze their advantages and disadvantages. Further, we review the application progress of ncAAs and anticipate the challenges and future development directions of ncAAs.

Natural cellulose hydrogels have been widely used to enhance mechanical properties. However, existing natural fiber composite hydrogels are not reusable, limiting their potential applications. To address this issue, we designed and prepared a polyvinyl alcohol/glycerol /bamboo microfibril double network tough hydrogel using a simple method. The bamboo microfibril and polyvinyl alcohol form a tight and rigid network through hydrogen bonding, improving mechanical properties. The prepared polyvinyl alcohol/glycerol/bamboo microfibril double network tough hydrogel has the advantages of reusability and fatigue resistance. Furthermore, both the elastic modulus and toughness of the hydrogel increase with increasing bamboo microfibril content. We also demonstrated that the hydrogel can be recast after cyclic compression, maintaining its recyclability, stability, and certain stiffness and toughness. Our study highlights the potential of hydrogels for controllable mechanical properties, fatigue resistance and shows that polyvinyl alcohol/glycerol/bamboo microfibril hydrogel has broad value for plasticity and reuse.

: This work introduces the instrument design of the medium energy proton detector (MEPD, detection range: 30keV-5MeV) mounted on the Chinese Fengyun-4B (FY-4B) satellite. Compared with the similar detector on the Fengyun-3E (FY-3E) satellite, the instrument has undergone significant changes due to the different orbital radiation environment and solar lighting conditions. Based on the calculation of radiation model AP8, the geometry factor is reduced to 0.002 cm2sr, while the MEPD on FY-3E satellite is 0.005 cm2sr. Another difference is that sensors in some directions is exposed to direct sunlight for 80 minutes every day on this orbit, depending on the attitude angle of the satellite, which is much worse than that on FY-3E satellite. According to the calculation results of permeability of photons through different materials, a 100 nm thickness nickel film is added in front of sensors in order to eliminate light pollution completely. The experiment on the solar simulator shows that the measure is effective and the detector has no error counts when the solar irradiance coefficient is 1.0. In addition, Geant4 software is applied to simulate particle transportation process under complete machine condition so that to check the contamination of electrons on sensors among all directions after magnetic deflection. Data obtained in orbit shows that the instrument works properly, and the data is in good agreement with the AP8 model. The observations of the MEPD on board the FY-4B satellite can provide important support for the safety of the spacecraft and the theoretical research related to space weather.

Lyme disease (LD) is a tick-transmitted infection caused by Borrelia burgdorferi sensu lato species which includes B. burgdorferi, B. afzelii, and B. garinii. The majority of patients with early LD can be cured by standard treatment, yet some still suffer from post-treatment Lyme disease syndrome (PTLDS). The presence of Borrelia persisters has been proposed as a contributing factor, which cannnot be completely killed by the currently used antibiotics for Lyme disease. Finding new pharmaceuticals targeting Borrelia persisters is crucial in developing more effective treatment. Here, we first confirmed the existence of persisters in cultures of B. garinii and B. afzelii and then conducted high-throughput screening of a custom drug library against persister-rich stationary-phase cultures of B. garinii and B. afzelii. Among 2427 compounds screened, hypocrellin A (HA), anthracycline class of drugs, and topical antibiotics along with some other natural compounds were identified to have strong potential in killing persisters of B. garinii and B. afzelii. HA was the most active anti-Borrelia compound, capable of eradicating stationary-phase Borrelia persisters, in particular when combined with doxycycline and/or ceftriaxone. Liposoluble antioxidant vitamin E was found to antagonize the activity of HA, indicating HA’s target is the cell membrane where HA-triggered reactive oxygen species (ROS) generation took place in the presence of light. HA was found to have distinct bactericidal activity against Borrelia species but had poor or no activity against Gram-positive and Gram-negative bacteria. Identification of the above-mentioned drug candidates may help to develop more effective therapies for LD.

The Yixian Formation (Lower Cretaceous) of China is famous worldwide for its fossils of early angio-sperms, but there is only one record of flower bud hitherto. A previous fossil record of flower bud just showed the appearance and lacked any internal details. Such a lacuna in knowledge of flower buds hin-ders our understanding of the evolution of flowers. Our new specimen was collected from an outcrop of the Yixian Formation (the Barremian-Aptian, Lower Cretaceous) near Dawangzhangzi, Lingyuan, Liao-ning, China. The specimen was observed and photographed using a Sony ILCE-7 digital camera and a Nikon SMZ1500 stereomicroscope, and details were observed using a TESCAN MAIA3 SEM. Our ob-servations document a fossil flower bud, Archaebuda cretaca sp. nov, from the Lower Cretaceous of China. The occurrence of two species of Archaebuda in the Yixian Formation not only confirms the ex-istence of the expected gynoecium (and possible androecium) in a flower bud, but also underscores the occurrence of typical flowers in the Early Cretaceous.

Yield calculation is an important link in modern precision agriculture, which is an effective means to improve breeding efficiency, and adjust planting and marketing plans. With the continuous progress of artificial intelligence and sensing technology, yield calculation schemes based on image processing technology have many advantages such as high accuracy, low cost, and non-destructive calculation, and have been favored by a large number of researchers. This article reviews the research progress of crop yield calculation based on remote sensing images and visible light images, describes the technical characteristics and applicable objects of different schemes, and focuses on detailed explanations of data acquisition, independent variable screening, algorithm selection and optimization. Common issues are also discussed and summarized. Finally, solutions are proposed for the main problems that have arisen so far, and future research directions are predicted, with the aim of achieving more progress and wider popularization of yield calculation solutions based on image technology.

Contrafreeloading (CFL) refers to animals' tendency to prefer obtaining food through effort rather than free access to food. Researchers have proposed various hypotheses to explain this intriguing phenomenon, but few studies have comprehensively analyzed its influencing factors. In this study, we observed the choice of alternative food containers in budgerigars to investigate their CFL tendencies and the effects of pre-training, food deprivation, and effort required on the CFL levels. The results show that, like most captive animals, budgerigars without food deprivation tend to choose challenging food containers. Additionally, the study finds that pre-trained budgerigars prefer to choose highly challenging food containers, while food-deprived budgerigars tend to choose Easy food containers. Moreover, budgerigars showed more selection time proportion on moderate challenging than high challenging food containers. In conclusion, budgerigars exhibit CFL tendencies, and pre-training enhances their CFL levels, while high challenge and deprivation of food decrease their contrafreeloading level. Studying animal contrafreeloading can help understand why animals choose to expend effort to obtain food rather than accessing it for free, and it also has implications for setting feeding environments to enhance the animal welfare of captive and domesticated animals.

Recently, the phase-sensitive OTDR (Φ-OTDR) based vibration sensor system has gained the focus of many researchers and some efforts have been undertaken to push further the limitations imposed on the performance of the Φ-OTDR sensor system. Then, progress in the different areas of its performance evaluation factors such as: improvement of the signal-to-noise ratio (SNR), spatial resolution (SR) in the sub-meter range, enlargement of the sensing range, frequency response bandwidth over the conventional limit and phase signal demodulation for quantitative measurement have been realized. This paper presents an overview of the recent progress in the Φ-OTDR based vibration sensing system in the different areas mentioned above.

The rapid and accurate detection of parasites is crucial for timely curative intervention in parasitosis and for epidemiological surveillance. To meet the needs of clinical diagnosis, it is imperative to develop a diagnostic tool based on nucleic acid that combines the sensitivity and specificity of established nucleic acid amplifica-tion tests with the speed, cost-effectiveness, and convenience of isothermal amplification methods. A new nu-cleic acid detection method, utilizing the clustered regularly interspaced short palindromic repeats (CRISPR)-associated (Cas) nuclease, holds promise for point-of-care testing. Specifically, the CRISPR-Cas12a system has demonstrated numerous advantages for detecting parasites, with hopeful outcomes for identify-ing malaria, toxoplasmosis, and other parasitic ailments. This review provides an overview of how CRISPR-Cas12a can be utilized for parasite detection, evaluates its advantages and disadvantages, and sug-gests ways to improve the efficiency and sensitivity of CRISPR-Cas12a-based assays.

The use of ARPIs has led to an increase in the proportion of AR-null prostate cancer, including NEPC and DNPC, but the mechanism underlying this lineage transition has not been elucidated. We found that ID2 expression was increased in AR-null prostate cancer. In vitro and in vivo studies confirmed that ID2 promotes PCa malignancy and can confer resistance to enzalutamide in PCa cells. We generated a ID2 UP50 signature, which is capable to determine resistance to enzalutamide and also valuable for predicting patient prognosis. Functional experiments showed that ID2 could activate the stemness-associated JAK/STAT and FGFR signaling while inhibiting the AR signaling pathway. Our study indicates that ID2 promotes the acquisition of a stem-like phenotype in adenocarcinoma cells, leading to resistance to ADT and next-generation ARPIs in prostate cancer.

Land plants have undergone their great diversification and evolution in the past 400 million years. Although appearing complex and hard to grasp, the evolution of plants centers around an invariable core development process, SRC (Sexual Reproductive Cycle). Various modifications have been added sequentially to this core process, and thus creating various novel organs and distinguishing their bearers one from another. Reproductive organs of all land plants, including sporangium, megasporangium, metamegasporangium (= ovule), and various metamegasporangium complexes, are derived from terminal sporangia in the earliest land plants. Throughout the million-year-long evolution, plants sequentially recruit associating accessories to protect their vulnerable core parts (spore and gamete). The occurrence of every single of these novelties is a stair marking land plant reproduction evolution and leads to enhanced offspring development conditioning (ODC).

In the full load operating range, wind turbines typically use pitch control to maintain rotor speed and output power at their rated values to guarantee the whole system’s safety. Blade pitch actuators are subject to physical limitations and safety requirements, which imposes strict constraints on pitch angle’s amplitude and rate of change. These constraints will bring windup problem to the integral part of the pitch controller. It leads to deterioration of the pitch control system’s performance or even the instability problem, especially for large-scale turbines operating in extreme uncertain wind conditions or suffering from cyber attacks. This paper designs an anti-windup robust pitch angle control strategy to deal with pitch rate constraint issue to enhance the security of control system. First, to facilitate controller design, a filtered tracking error technique is employed to transform the nonaffine form into an affine one. Subsequently, a feedback robust controller based on UDE is developed to handle the model’s uncertainty and external disturbances. To address the issue of integral saturation in the pitch system and guarantee its safety, an elliptical bounded constraint is integrated into the designed UDE strategy. This bounded UDE controller can improve the stability of power generation quality, reduces the mechanical loads on components and enhance the whole system’s safety. Finally, the effectiveness of the proposed scheme is verified on the Wind Turbine Blockset platform in Matlab/Simulink. It can achieve better performance than the traditional method.

Flower color is an important ornamental feature, often modulated by the contents of flavonoid. Chalcone synthase is the first key enzyme in the biosynthesis of flavonoid, but little is known about the role of R. delavayi CHS in flavonoid biosynthesis. In this paper, three CHS genes (RdCHS1-3) were successfully cloned from R. delavayi flowers. According to multiple sequence alignment and phylogenetic analysis, only RdCHS1 contained all the highly conserved and important residues, and classified into the cluster of bona fide CHSs. Thus RdCHS1 was then subjected for further functional analysis. Real-Time PCR analysis revealed that transcripts of RdCHS1 was the highest in leaves and lowest in root, did not match the anthocyanin accumulation patterns during flower development. Biochemical characterization displayed that RdCHS1 could catalyze p-coumaroyl-CoA and malonyl-CoA molecules to produce naringenin chalcone. Physiological function of RdCHS1 was checked in Arabidopsis mutant and tobacco, the results showed RdCHS1 transgenes could recover the color phenotypes of tt4 mutant and made tobacco flower color from pink to dark pink through modulating the expression of endogenous structural and regulatory genes in tobacco. All these results demonstrated that RdCHS1 is a bona fide CHS and contribute to flavonoid biosynthesis in R. delavayi.

In this work, a ZIF-67/MWCNTs/Nafion sensor platform was constructed based on the good adsorption capacity of ZIF-67, the electrical conductivity of multiwalled carbon nanotubes (MWCNTs) and the excellent chemical stability of Nafion for the detection of Cu2+ in water. Meanwhile, the modified materials were characterized by scanning electron microscopy (SEM), Transmission electron microscopy (TEM), BET specific surface area test, X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD) and Fourier transform infrared spectrometry (FT-IR). Cyclic voltammetry (CV), electrochemical impedance (EIS), and square wave solvation voltammetry (SWSV) electrochemical methods were used to perform applied test studies on ZIF-67/MWCNTs/Nafion/GCE. The results show that ZIF-67/MWCNTs/Nafion/GCE has high sensitivity (57.5 μA/μM) and a low limit of detection (15.0 nM) for the electrochemical detection of Cu2+ ions in an electrochemical sensing system. It has high adsorption selectivity for Cu2+, and the recovery of Cu2+ in real water reached 98.6%-103%. The modified electrode has good repeatability, reproducibility, anti-interference, and stability, which makes this sensing platform can be practically applied to the detection of domestic water.

Fibroblast activation protein (FAP) is a serine protease characterized by its high expression in cancer-associated fibroblasts (CAFs) and near absence in adult normal tissues and benign lesions. This unique expression pattern positions FAP as a prospective biomarker for targeted tumor radiodiagnosis and therapy. The advent of FAP-based radiotheranostics is anticipated to revolu-tionize cancer management. Among various types of FAP ligands, peptides and antibodies, have shown advantages over small molecules, exemplifying prolonged tumor retention in human volunteers. Within its scope, this review summarizes the recent research progress of the FAP radiopharmaceuticals based on antibodies and peptides, on tumor imaging and therapy. Additionally, it incorporates insights from recent studies, providing valuable perspectives on the clinical utility of FAP-targeted radiopharmaceuticals.

Tunnel-interchange connecting sections pose significant safety challenges on mountainous expressways due to their high incidence of accidents. Improving road safety necessitates a comprehensive understanding of driver behavior in such areas. This study explores the influences of road characteristics, signage information volume, and traffic conditions on drivers' car-following and lane-changing behavior in tunnel-interchange diverging areas. Utilizing driving data from 25 subjects of 72 simulated road models, driving performance is assessed using Friedman rank test and multivariate variance analysis. The results highlight the significant influence of both connection distance and signage information load on driving behavior. In tunnel-interchange scenarios, the reduction of velocity increased by 62.61%, and speed variability surged by 61.11%, indicating potential adverse effects on driving stability due to the environmental transitions. Decreased connection distances are associated with reduced lane-changing durations, larger steering angles, and increased failure rates. Furthermore, every two units increase in signage information leads to a 13.16% rise in maximum deceleration and a 5% increase in time headway. Notably, the signage information volume shows a significant interaction with connection distance (F=1.60, P=0.045) for most car-following indicators. Hence, the study recommends a maximum connection distance of 700 m and signage information not exceeding nine units for optimal safety and stability.

The soybean yield per unit area and soybean acreage are increased to boost overall soybean production as two effective solutions. There is a large area of saline soils in northeast China, where if soybeans could be grown with the help of isolated saline-tolerant rhizobia, the cultivation area of soybeans in China can be effectively expanded. Several rhizobia with different salt-, acid- and alkali-resistant characteristics were obtained in this research by isolating, identifying, and analyzing the nitrogen-fixing activities of indigenous rhizobia from different soybean planting soils, and further analyzed the host compliance between rhizobia and different soybean germplasm concerning 30 representative germplasm resources in the northeast region. Collectively, the results of the resistance study of HLNEAU2 isolated from the Shaanxi region are great references for guiding the application of rhizobia on soybeans.

Lung cancer is a common malignant tumor of the lung and the leading cause of cancer mortality worldwide. Non-small-cell lung cancer (NSCLC) accounts for 80%–85% of lung cancer, 40% of NSCLCs will have spread beyond the lungs by the time it is diagnosed. Long non-coding RNA (LncRNA) prostate androgen-regulated transcript 1 (PART-1) was reported that promote the development of several cancers. In the current study, we conducted experiments to investigate the role of PART-1 in the proliferation, invasion, and migration of NSCLC. The expression level of the PART-1 gene increased significantly in the NSCLC cell lines, including A549, H1229, H1650, H1975, and PC9. Knocking down of PART-1 inhibited the proliferation, invasion, and migration of A549 cells, moreover, decreased the tumor proliferation in nude mice. We confirmed that PART-1 targeted miR-204-3p directly, and miR-204-3p targeted the insulin-like growth factor binding protein 2 (IGFBP-2) directly. Furthermore, we discovered that PART-1 involved the NSCLC progression by regulating the miR-204-3p-targeted IGFBP-2 pathway. LncRNA PART-1 might be a target for treating NSCLC, and a warning sign of diagnosis of early lung cancer.

: AliCPT-1 is the first Cosmic Microwave Background (CMB) experiment in China, dedicated to achieve accurate measurements of B-mode polarization. Situated in Ali of Tibet, China, this telescope is currently undergoing deployment and will operate in two frequency bands centered at 90 and 150 GHz. The Far-Field Flat Mirror（FFF）is a calibration device of AliCPT-1 telescope for far-field beam mapping. The design of FFF is optimized for easy assembly and adjustment. Meteorological station data reveals that the maximum wind speed near FFF is 17.5 m/s, while the maximum wind speed on the windward side is 8 m/s. The wind pressure on FFF was analysed using a maximum wind speed of 17.5m/s as the input condition, based on the fluid-structure coupling method in ANSYS. The results demonstrate that it is safe and reliable when withstanding combined gravity and wind pressure loads. The torque on the mount is within the motor rated torque. The flatness of the FFF reflective surface can be adjusted to an RMS value of 0.05 mm when taken into account the effect of gravity and assembly accuracy. The deformation caused by the maximum wind loads is approximately 0.0587 mm under the protection of wind-proof wall. The combined deformation is 0.077 mm in RMS value combining the two influences, which is less than 1/20 of wavelength. The FFF mirror assembly is stable and precisely for telescope calibration.

Orchids are often a mystery because of their close and complex relationships with various microorganisms in the natural environment. Orchids rely on microorganisms to obtain nutrients, affecting their seed germination, protocorm, and adult plant growth. Currently, the majority of relevant research is concentrated on isolating and identifying environmental microorganisms that support orchid development and growth. With the development of metagenomic technology, our understanding of orchid mycorrhizal fungi (OMF) and root-associated bacteria (RAB) has been expanded. New research results and discoveries have emerged, which require a comprehensive assessment to provide a reference for studying microorganisms related to orchids. Therefore, we present a comprehensive summary, identifying significant inadequacies of present methodologies while providing ideas for further research.

Limited studies have shown that exposure to arsenic is associated with serum vitamin D levels, but the results are still inconsistent. A cross-sectional study of 762 participants was conducted in Wenshui Country, Shanxi Province, which was identified as an area of water-borne arsenicosis. The results showed positive relationship between arsenic species (iAs, MMA, DMA) and serum 25(OH)D. Binary logistic regression analysis showed that the significant increases of 0.4% and 0.6% in the risk of vitamin D excess for every 1-unit increment in the Box-Cox transformed urinary tAs and DMA, respectively. After stratifying populations based on arsenic methylation metabolic capacity, each one-unit increase in the Box-Cox transformed tAs level was associated with increases of 0.064 (95%CI: 0.032 to 0.096) in serum 25(OH)D in the populations with iAs% above the median. In the populations with skin hyperkeratosis, urinary iAs was positively associated with serum 25(OH)D (β=0.592, 95%CI: 0.041 to 1.143). Overall, our findings support the positive relationship between urinary arsenic and serum 25(OH)D.

A switchable and tunable terahertz (THz) metamaterial based on photosensitive silicon and Vanadium dioxide (VO2) was proposed. By using finite-difference time-domain (FDTD) method, the transmission and reflective properties of the metamaterial were investigated theoretically. The results imply that, the metamaterial can realize a dual electromagnetically induced transparency (EIT) or two narrow-band absorption depending on the temperature of the VO2. Additionally, the magnitude of the EIT and two narrow-band absorption can be tuned by varying the conductivity of photosensitive silicon (PSi) via pumping light. Correspondingly, the slow light effect accompanying the EIT can also be adjusted.

There are close dynamic relationships among the livelihood, well-being, and ecological environment of farm households. It is of great significance to scientifically clarify the impact of the grain for green policy on the livelihoods and well-being of farm households in mountainous areas. Based on data from a survey of 392 farm households in Zhangbei County, a system of indicators for farm household livelihood assets and farm household well-being was constructed, drawing on a sustainable livelihood framework (SLF). The livelihood assets and well-being levels of different types of farm households were measured, and a multiple linear regression model was used to analyze the impact of the grain for green policy implementation on the well-being levels of farm households. The three main results are as follows: (1) The level of natural assets among the total average livelihood assets of farm households in Zhangbei County is the highest at 0.374, while the level of physical assets is the lowest at 0.018. The level of livelihood assets of returned farmland households (0.948) is lower than that of nonreturned farmland households (1.117). (2) The level of well-being of all farm households in Zhangbei County is 0.517, with the level of wealth contributing the most to the well-being of farm households at 40.20% and the quality of the ecological environment contributing the least at 11.99%. The level of well-being of returned farmland households (0.518) was slightly higher than that of nonreturned farmland households (0.514). (3) The degree of influence of each influence factor on the level of well-being of farm households varies significantly. Household size was the strongest driver, at 0.366, while educational attainment of household members, household labor capacity, annual household expenditure, livelihood diversity, number of large production tools, and total value of livestock were also important drivers of household well-being, and area of arable land is negatively associated with household well-being. There are also differences in the factors influencing the level of well-being of different types of farming households.

The 2019 novel coronavirus (2019-nCoV) causes novel coronavirus pneumonia (NCP). Given that approved drug repurposing becomes a common strategy to quickly find antiviral treatments, a collection of FDA-approved drugs can be powerful resources for new anti-NCP indication discoveries. In addition to synthetic compounds, Chinese Patent Drugs (CPD), also play a key role in the treatment of virus related infections diseases in China. Here we compiled major components from 38 CPDs that are commonly used in the respiratory diseases and docked them against two drug targets, ACE2 receptor and viral main protease. According to our docking screening, 10 antiviral components, including hesperidin, saikosaponin A, rutin, corosolic acid, verbascoside, baicalin, glycyrrhizin, mulberroside A, cynaroside, and bilirubin, can directly bind to both host cell target ACE2 receptor and viral target main protease. In combination of the docking results, the natural abundance of the substances, and botanical knowledge, we proposed that artemisinin, rutin, glycyrrhizin, cholic acid, hyodeoxycholic acid, puerarin, oleanic acid, andrographolide, matrine, codeine, morphine, chlorogenic acid, and baicalin (or Yinhuang Injection containing chlorogenic acid and baicalin) might be of value for clinical trials during a 2019-nCov outbreak.

Cost-efficient catalyst for hydrogen evolution reaction (HER) and methanol oxidization reaction (MOR) is of great importance for industrial application. The alloying of platinum with cheap transition metal offers a great opportunity to reduce cost and enhance the electro-catalytic performance. Herein, we report a simple and green route to synthesize porous Pt-Cu catalysts, where Pt-Cu solid particles were first produced by using cuprous chloride (CuCl) nanoparticles as the template, followed by a dealloying treatment to obtain final porous product. The porous alloy nanoparticles show higher catalytic activity and superior stability for HER and methanol oxidation reaction, which is beneficial from the porous structure and synergetic effect between Pt and Cu.

In view of the complexity of the pile foundation underpinning structure system and the stringent requirements of the construction process, this paper briefly describes the necessity of introducing epoxy resin reinforcing adhesive of planting rebar in the design of pile foundation underpinning beam structure to im-prove the mechanical properties of the underpinning beam new and old concrete joint surfaces and proposes a new type of pile foundation underpinning beam system construction method by “chiseling + prestressed reinforcement + epoxy resin reinforcing adhesive”. This paper uses an actual pile foundation underpinning project of an urban overpass as a prototype, designs and creates a model structure with a similarity ratio of 1/6, and performs repeated pro-gressive static loading tests to study the load carrying capacity, displacement change, and other properties of the underpinning structure, as well as analyses and distorts the overall working performance and failure mode of them. On this basis, the prototype structure's finite element analysis model was built, and the finite element analysis results were compared with the test results to get the mechanical properties and deformation characters of the actual pile foundation under-pinning structure system corresponding to the actual underpinning beam load. This paper's study can lay the theoretical and experimental foundation for the smooth development of similar projects.

The main idea of this paper is to investigate the exact solutions and dynamic properties in optical nanofibers, which is modeled by space-time fractional perturbed nonlinear schr\"odinger equation involving Kerr law nonlinearity with conformal fractional derivative. Firstly, by the complex fractional traveling wave transformation, the traveling wave system of the original equation is obtained, then a conserved quantity, namely the Hamiltonian is constructed, and the qualitative analysis of this system is conducted via this quantity by classifying the equilibrium points. Moreover, the prior estimate of the existence of the soliton and periodic solution is established via the bifurcation method. Furthermore, all exact traveling wave solutions are constructed to illustrate our results explicitly by the complete discrimination system for polynomial method.

The lower reaches of the Changhua River are located in the northwest of Hainan Island, and the shallow groundwater in this area is the main water source for residents living at both sides of the river. In order to sustain the exploitation and use of water resources in this area, it is essential to clarify the chemical characteristics and the formation mechanism of the groundwater. We collected 100 sets of shallow groundwater samples from the lower reaches of the Changhua River, and analyzed the chemical characteristics of the groundwater in shallow aquifers as well as its controlling factors by means of the methods including descriptive statistical analysis, Piper diagram, Gibbs diagram, and ion ratio. The results show that the overall characteristics of groundwater in the study area are near-neutral to weakly alkaline nature, indicating a generally oxidized environment. The groundwater involves in 56 chemical types, and the most predominant types are Ca•Na-HCO3 and Ca-HCO3, respectively. NO- 3 has become a macro component exceeding SO2- 4in most of the sampling groundwater, suggesting a significant impact of human activities in this area. At the same time, the chemical characteristics of groundwater in the study area are mainly affected by the water-rock interaction, while the water-rock interaction is mostly affected by the dissolution of silicate rocks and less by the dissolution of carbonate rocks and evaporite rocks. According to the ion ratio results, Na+ and K+ in the study area are mainly from the leaching of silicate rocks, Ca2+ and Mg2+ are mainly from the dissolution of carbonate rocks, in addition to a certain degree of cationic exchange. NO- 3 is mainly related to human activities, and the human activities are more affected by agricultural activities and domestic sewage than by industrial and mining activities. This study can provide a reference for the development and protection of shallow groundwater in the lower reaches of the Changhua River.

Digital technology makes energy systems more dynamic, efficient, reliable and sustainable. Promoting the digital governance of renewable energy is not only a key part of energy transformation, but also an important initiative to cope with the global energy crisis, which provides a new impetus for realizing the goal of net-zero emissions. In order to achieve the "dual-carbon" goal, China has been actively promoting energy reform and enhancing the wide application of digital technologies in the development and utilization of renewable energy. The digital governance system and governance capacity of renewable energy is an important support for the modernization of the national governance system and governance capacity. Although the digital governance of renewable energy in China has better policy support and advantages, the dilemmas it faces are still relatively prominent, including unsound laws and policies, insufficient governance capacity, and security loopholes in digital technology, etc. Therefore, this paper proposes a problem-oriented approach to the digital governance of renewable energy. Therefore, this paper puts forward problem-oriented optimization suggestions to innovate the legal system of renewable energy digital governance, promote the digital transformation of China's renewable energy industry, provide development space for renewable energy digital governance in a diversified mode, and enhance the digital governance capacity by improving the renewable energy security system.

Fructan, a fructose polymer, is used as carbohydrate reserve in many plants. The nutritional and therapeutic benefits of fructans have attracted increasing interest by consumers and food industry. In the course of evolution, many plants have developed the ability of regulating plant frunctan metabolism genes to produce different structures and chain length fructans, which are strongly correlated with their survival in harsh environments. De nevo domestication of fructan-rich plants based on genome editing is a viable and promising approach to improve human dietary quality and reduce the risk of chronic disease. These advances will greatly facilitate breeding and production of tailor-made fructans as a healthy food ingredient from wild plants such as polygonati rhizoma. The purpose of this review is to broaden our knowledge on plant fructan biosynthesis, evolution and beneficial applications for human health.

Recent advances in satellite technology have brought enormous potential to ecosystem mapping, which is one of the fundamental components of environmental studies. In this paper, a Random Forest classifier is applied for the strict assessment of the efficiency of ecosystem mapping through a detailed comparative analysis between combined Sentinel-1 and Sentinel-2 data and stand-alone Sentinel-2 imagery over three priority ecosystems, including wetlands, riverine areas, and mangroves in Bangladesh. The collocated images, based on the integration of Sentinel-1 data with Sentinel-2 data, would do better than Sentinel-2 imagery alone over various ecosystems. Particularly, in this study, attention focused on the Hakaluki Haor area for the wetlands, the Padma-Jamuna River confluence for the riverine ecosystem, and the Sundarban forest for mangroves. By leveraging Synthetic Aperture Radar (SAR) data in C-band dual-polarization from Sentinel-1 and four spectral bands (blue, green, red, and near-infrared) from Sentinel-2, the study analyzes imagery from December 2022 to February 2023. A 5% cloud masking filter is applied to optical data to enhance accuracy. In this methodology, 70% of the total signature values are used for training the classification model and the remaining 30% for testing. It can be noticed from the results that with the use of fused data, remarkably high accuracy in classification has been improved, such as overall accuracies of 94.17% for mangroves, 87.30% for riverine, and 85.96% for wetland ecosystems. In contrast, the use of singular Sentinel-2 imagery yields lower accuracies of 91.56%, 85.21%, and 82.51% for the respective ecosystems. The integration of radar data is shown to provide critical information, especially in environments with dense vegetation or cloud cover, where optical data alone may be insufficient. The findings of this study underline the limitations of relying on Sentinel-2 imagery to capture complex details of diverse ecosystems and highlight the need to include Sentinel-1 data for a more holistic analysis. This fusion allows improved accuracy to be achieved, which not only brings in more depth of ecological knowledge but also underpins more effective conservation strategies.

Cell junction that is usually associated with dynamic cytoskeletons is essential for a wide range of cellular activities such as cell migration, cell communication, barrier function and signal transduction. Real-time observation of cell junction facilitates understanding of the mechanisms by which cell junction regulate relevant cellular activities. In this study, we examined the binding capacity of a modified tridecapeptide from Cx43 to cell junction protein ZO-1 and sought to create a fluorescent peptide that could be used to label cell junction. To introduce the fluorescent peptide into the cells, a cell-penetrating peptide was linked to the modified tridecapeptide and synthesized. The binding of the modified tridecapeptide was tested using pull down and immunoprecipitation assay. The ability of the peptide to label cell junction was assessed by adding it to fixed or cultured Caco-2 cells. Testing assay revealed that the Cx43-derived peptide can bind to ZO-1. Besides, the peptide was able to label cell junction of fixed cell, although no obvious cell junction labeling was observed clearly in living cells, probably due to the inadequate affinity. These results indicate that a peptide-based strategy for labeling cell junction may be feasible, and efforts to improve its affinity are warranted in the future.

Genome-scale metabolic models (GEMs) have been widely used for phenotypic prediction of microorganisms. However, the lack of other constraints in the stoichiometric model often leads to a large metabolic solution space inaccessible. Inspired by previous studies that take allocation of macromolecule resources into account, we developed a simplified Python-based workflow for constructing enzymatic constrained metabolic network model (ECMpy) and constructed an enzyme-constrained model for Escherichia coli (eciML1515) by directly adding a total enzyme amount constraint in the latest version of GEM for E. coli (iML1515), considering the protein subunit composition in the reaction, and automated calibration of enzyme kinetic parameters. Using eciML1515, we predicted the overflow metabolism of E. coli and revealed that redox balance was the key reason for the difference between E. coli and Saccharomyces cerevisiae in overflow metabolism. The growth rate predictions on 24 single-carbon sources were improved significantly when compared with other enzyme-constrained models of E. coli. Finally, we revealed the tradeoff between enzyme usage efficiency and biomass yield by exploring the metabolic behaviors under different substrate consumption rates. Enzyme-constrained models can improve simulation accuracy and thus can predict cellular phenotypes under various genetic perturbations more precisely, providing reliable guidance for metabolic engineering.