Colorectal liver metastases (CRLM) patients combined with hepatic lymph node metastases was a negative prognostic factor associated with outcomes. Up to now, there was still lack of a reliable method to identify the status of hepatic lymph nodes. The aim of this study was to investigate the predictive ability of mono-exponential, bi-exponential, and stretched-exponential diffusion-weighted imaging (DWI) models to distinguish between benign and malignant hepatic lymph nodes in CRLM patients who underwent neoadjuvant chemotherapy prior to surgery. In total, 97 CRLM patients with pathologically proved hepatic lymph node status were included. Various quantitative parameters, including the apparent diffusion coefficient (ADC) from mono-exponential model, D, D*, and f derived from intravoxel incoherent motion (IVIM) model, as well as DDC and α from stretched-exponential model (SEM), were measured. Multivariate analysis revealed that the pre- treatment DDC value and the short diameter of the largest lymph node after treatment were independent predictors of metastatic hepatic lymph nodes. A nomogram combining these two factors demonstrated excellent performance in distinguishing between benign and malignant lymph nodes in CRLM patients, with an area under the curve (AUC) of 0.873. Therefore, the nomogram can serve as a preoperative assessment tool for determining the status of hepatic lymph nodes and aiding in the decision-making process for surgical treatment in CRLM patients.

Mn3O4 /graphene nanosheets (GNS) composites serve as very excellent electrode materials for supercapacitors. They can fully combine the advantages of two materials such as graphene and metal oxide. Meanwhile, they can improve not only the specific energy and specific power of the materials, but also the cyclic stability of the materials. The results of the cyclic voltammetry and constant current charge discharge test on the composite electrode material have shown that the Mn3O4 /GNS powder sample has good capacitive performance. When the scanning rate is 5~50mV, the specific capacity retention rate of the composite electrode is 80.3% and 88% respectively. Mn3O4 nanoparticles, with the highest ratio of network coated GNS, exhibit a specific capacitance value of 957.6 F g−1 at a current density of 2 A g−1 in 1 M Na2SO4 solution. Besides, its network structure demonstrates high specific capacity and multiplying performance.

(1) Background: The imaging energy range of a typical Compton camera is limited due to the fact that scattered gamma photons are seldom fully absorbed when the incident energies are above 3 MeV. Further improving the upper energy limit of gamma-ray imaging has important application significance in active interrogation of special nuclear materials and chemical warfare agents, as well as range verification of proton therapy; (2) Methods: To realize gamma-ray imag-ing in a wide energy range of 0.3~7 MeV, a principle prototype, named a portable three-layer Compton camera, was developed using the scintillation detector that consist of an silicon photo-multiplier array coupled with a Gd3Al2Ga3O12:Ce pixelated scintillator array. Implemented in a list-mode maximum likelihood expectation maximization algorithm, a far-field energy-domain imaging method based on two-interaction and three-interaction events was applied to estimate the initial energy and spatial distribution of gamma-ray sources. The simulation model of detec-tors was established based on Monte Carlo simulation toolkit Geant4. The reconstructed images of a 133Ba, a 137Cs and a 60Co point-like sources were successfully obtained with our prototype in laboratory tests and compared with simulation studies; (3) Results: The proportion of effective imaging events accounted for about 2%, which made our prototype realize reconstructing the distribution of a 0.05 μSv/h 137Cs source in 10 seconds. The angular resolution for resolving two 137Cs point-like sources was 15°. Additional simulated imaging of the 6.13 MeV gamma-rays from 14.1 MeV neutron scattering with water preliminarily demonstrated the imaging capability for high incident energy; (4) Conclusions: We concluded that the prototype had good imaging per-formance in a wide energy range (0.3~7 MeV), which showed potential in several MeV gam-ma-ray imaging applications.

To conduct a precise impact assessment of marine diesel engines, a 200t floating impact platform was utilized to simulate realistic testing conditions. The testing generated the acceleration time curve and the impact response spectrum for the diesel engine. According to the applicable standards, the spectral velocity was chosen as the evaluation index, and an evaluation of the longitudinal, transverse, and vertical impact environment of the diesel engine was conducted. The shock factor interpolation method was corrected using the confidence interval based on normal distribution, and the interpolated confidence interval of the shock factor was determined. The findings reveal that: The 200t-class floating shock platform is capable of providing a reliable shock environment for diesel engine tests. The shock wave serves as the primary external force during the experiment, and the impact of bubble pulsation can be disregarded when assessing using the floating shock platform. To more accurately describe the experimental shock intensity when presented with dispersed data, the confidence interval can be utilized, and the resulting prediction formula provides a higher level of impact safety. The obtained conclusions can serve as a reference for predicting the shock environment of large shipboard equipment using the shock platform.

A enantioselective tandem transformation concerning asymmetric allylic decarboxylative addition and cyclization of N-nosylimines with vinylethylene carbonates (VECs) in the presence of [Rh(C2H4)2Cl]2, chiral sulfoxide-N-olefin tridentate ligand has been developed. The reaction of VECs with various substituted N-nosylimines proceeded smoothly under mild conditions, giving highly functionalized oxazolidine frameworks in good to high yields with good to excellent enantioselectivity.

The fluid seepage in local-saturated zone of subgrade promotes the migration of fine particles in the filler, resulting in the change of pore structure and morphology of the filler and the deformation of solid skeleton, which affects the fluid seepage characteristics. Repeatedly, the muddy interlayer, mud pumping and other diseases are finally formed. Based on the theory of two-phase seepage, the theory of porous media seepage, and the principle of effective stress in porous media, a two-phase fluid-solid coupling mathematical model in local-saturated zone of subgrade considering the effect of fine particles migration is established. The mathematical model is numerically calculated with the software COMSOL Multiphysics○R, the two-phase seepage characteristics and the deformation characteristics of the solid skeleton in local-saturated zone of the subgrade are studied. The research results show that due to the continuous erosion and migration of fine particles in local-saturated zone of the subgrade, the volume fraction of fine particles first increases then decreases and finally becomes stable with the increase of time. And the volume fraction of fine particles for the upper part of the subgrade is larger than that for the lower part of the subgrade. The porosity, the velocity of fluid, the velocity of fine particles, and the permeability show a trend of increasing first and then stabilizing with time; the pore water pressure has no significant changes with time. The vertical displacement increase first and then decrease slightly with the increase of time, and finally tend to be stable. For a filler with a larger initial volume fraction of fine particles, the maximum value of the volume fraction of fine particles caused by fluid seepage is larger, and the time required to reach the maximum value is shorter. It can be concluded that in actual engineering, the volume fraction of fine particles in the subgrade filler should be minimized on the premise that the filler gradation meets the requirements of the specification.

We reported previously that poly (3-hydroxybutyrate) (PHB) oligomer is an effective antimicrobial agent against gram-positive bacteria, gram-negative bacteria, fungi and multi-drug resistant bacteria. In this work, it was further found that polyethylene glycol (PEG) can promote the antimicrobial effect of PHB oligomer synergistically. Three hypothetic mechanisms were proposed, that is, generation of new antimicrobial components, degradation of PHB macromolecules and dissolution/dispersion of PHB oligomer by PEG. With a series of systematic experiments and characterizations of HPLC-MS, it was deducted that dissolution/dispersion of PHB oligomer dominated the synergistic antimicrobial effect between PHB oligomer and PEG. This work demonstrates a way for promoting antimicrobial effect of PHB oligomer and other antimicrobial agents through improving hydrophilicity.

Following our previous success in identifying new steroid-based anticancer agents, we herein disclosed the structural requirements for retaining high potency against cancer cells and associated modes of action. The structurally novel steroidal dimer by001 inhibited growth of different esophageal cancer cells and colony formation at low micromolar levels, elevated cellular ROS levels and caused mitochondrial dysfunction. Mechanistic studies showed that by001 induced cell death through the mitochondria and death receptor-mediated apoptotic pathways and autophagy induction, as well as inhibited migration.

TTF1-NP(5,2′,4′-trihydroxy-6,7,5′-trimethoxyflavone nanoparticles), derived from the traditional Changbai Mountain medicinal plant Sorbaria sorbifolia (SS), has been showedits anti-cancer effect in various liver cancer cell types and tissues. The present study was designed to evaluate the antitumor mechanism of the TTF1-NP against HepG2 hepatoma cells and HepG2 cells-induced hepatocarcinoma (HCC) in nude mouse model. Here we demonstrated that TTF1-NP inhibits tube formation of HUVECs and HepG2 cell migration and invasion, and inhibits tumor growth in nude mice implanted with HepG2 cells through the downregulation of STAT3 protein and activation, along with VEGF, KDR, bFGF, MMP2 and MMP9 levels. We further revealed that TTF1-NP decreased the DNA-binding capacity of STAT3. Together our results provide a mechanism by which TTF1-NP suppresses cancer cell migration, invasion and angiogenesis through the action of STAT3 and suggests TTF1-NP as a potential therapy for hepatocellular cancer treatment.

Due to the long-term deformation settlement of foundations, issues such as damage and functional failure of buildings and structures have long been of concern in the engineering field. The creep of soil is one of the primary causes leading to long-term deformation of foundations. In this paper, the consolidation deformation, creep characteristics, and creep model of reconstituted saturated silty clay were studied by isotropic compression test and triaxial shear creep test. The results show that for the isotropic compression test, although the applied load adopts different stages of loading, as long as the final applied confining pressure is the same, the number of stages applied by the confining pressure has little effect on the final isotropic consolidation deformation of the sample and the triaxial undrained shear strength after creep. However, for the triaxial shear creep test, it is found that under the same final deviatoric stress, the final deviatoric strain of the sample is closely related to the number of loading stages of deviatoric stress. It shows that the more loading stages of the sample loaded with the same deviatoric stress, the smaller the final deviatoric strain, and the triaxial undrained shear strength of the sample after creep will increase. In addition, it is reasonable to determine the pore pressure dissipation of the sample to 95%((u0-u0)/u0=95%) as the main consolidation end time (tEOP) of the sample. The isotropic consolidation creep curves and the triaxial shear creep curves show certain nonlinearity. Then the logarithmic model and the hyperbolic model were used to fit the creep curves of the samples. It is found that the hyperbolic model has a better fitting effect than the logarithmic model, but for the triaxial shear creep test, the creep parameters of the sample change greatly. Therefore, studying the creep characteristics of soil under different pre-loading steps is of significant engineering importance for evaluating the long-term deformation of underground structures.

In view of the problem of cracking easily and partial distortion of images after encryption or decryption, a novel image encryption and decryption algorithm based on Arnod Transform and fractional chaotic is proposed. To begin with, the Arnold transform is used to encrypt. So that the spatial confidence of the original image has been comprehensively disturbed. Secondly, the XOR involving the fractional order chaotic sequence is used to encrypt. The key sequence is dynamically generated to ensure the randomness and difference of key generation. When decryption is required, the first decryption is performed using the key and XOR. Then the second decryption is carried out by using the inverse Arnold transform, and finally the decrypted image is obtained. Experimental results show that the improved algorithm has achieved better performance in encryption and decryption.

Patient value is an important factor in clinical decision-making, but conventionally, it is not incorporated in the decision processes. In this paper, a value-based therapy recommendation comprehensive model is proposed. A literature analysis is conducted to collect value-based evidence. Categorized values and candidate therapies are used in combination as filtering keywords to build this evidence. Then a formalism model is put forward to integrate the value-based evidence with clinical evidence. The relative importance of two evidence can be adjusted dynamically by decision-makers during the decision-making processes. A prototype system was implemented using a case study for breast cancer and validated for feasibility and effectiveness.

In recent years, various optical measurement technologies such as far-infrared spectroscopy, low-frequency Raman spectroscopy, optical Kerr effect spectroscopy, and two-dimensional Raman-terahertz spectroscopy have developed vigorously. By comparing the complementary aspects detected by various linear and nonlinear spectroscopic techniques, a coherent picture emerges from studies of dynamics in water. Numerous molecular dynamics experiments and theoretical investigations have demonstrated low-frequency molecular motions in liquid water. For example, intermolecular hydrogen bond vibration, molecular reorientation motion, and the interaction between molecule/ionic solute and hydrogen bond all occur in the THz region, which are closely related to their physical/chemical properties and structural dynamics. However, precise probing of various modes of motion is difficult due to the complexity of the collective and cooperative motion of molecules and the spectral overlap of related modes. With the development of THz optical technology, current state-of-the-art THz sources can generate pulsed electric fields with peak intensities on the order of ~MV/cm. Such strong fields make it possible to use THz waves as the driving light source for nonlinear polarization of the medium, which in turn leads to the development of the emerging terahertz Kerr effect (TKE) spectroscopy technique. Many low-frequency molecular motion modes, such as the collective directional motion of molecules and the cooperative motion under the constraint of weak intermolecular interactions, are resonantly excited to unprecedentedly strong amplitudes driven by the THz electric field. Thereby the collected responses are increased. The TKE technique thus creates an interesting prospect for investigating low-frequency dynamics in these media. In view of this, this paper firstly summarizes the research work on the measurement mechanism of TKE spectroscopy by taking the solid material without low-frequency molecular dynamics process as an example. Starting from the principle of TKE technology and the exploration of the properties of solid matter using this technology, its application in the exploration of low-frequency molecular dynamics of liquid water and aqueous solutions is introduced. Liquid water is considered the building block of life and possesses many extraordinary physical and biochemical properties. Its hydrogen bonding network plays a crucial role in these properties. It is generally believed that the ability of water to form complex hydrogen-bonding networks is the main reason for its various kinetic and thermodynamic properties that are different from other liquids. However, the exact structure of the hydrogen-bonding network, the spatial extent of its existence, and the associated timescale are not known. And the relevant spectral information of the basic properties of the reaction water is still not known. Therefore, it is of great significance to evaluate the hydrogen bond-related kinetic properties of liquid water by optical means.

Keywords: Deep mining; Drill bit structural parameters; Fidelity coring; Abaqus simulation and analysis.

Abnormal connections in brain networks of healthy people always bring the problems of cognitive impairments and degeneration of specific brain circuits, which may finally result in Alzheimer’s disease (AD). Exploring the development of the brain from normal controls (NC) to AD is an essential part of human research. Although connections changes have been found in the development, the connection mechanism that drives these changes remain incompletely understood. The purpose of this study is to explore the connection changes in brain networks in the process from NC to AD, and uncover the underlying connection mechanism that shapes the topologies of AD brain networks. In particular, we propose a model named MINM from the perspective of topology-based mutual information to achieve our aim. MINM concerns the question of estimating the connection probability between two cortical regions with the consideration of both the mutual information of their observed network topologies and their Euclidean distance in anatomical space. In addition, MINM considers establishing and deleting connections, simultaneously, during the networks modeling from the stage of NC to AD. Experiment results show that MINM is sufficient to capture an impressive range of topological properties of real brain networks such as characteristic path length, network efficiency, and transitivity, and it also provides an excellent fit to the real brain networks in degree distribution compared to experiential models. Thus, we anticipate that MINM may explain the connection mechanism for the formation of the brain network organization in AD patients.

Based on the data of A-share listed companies in Shanghai and Shenzhen of China from 2011 to 2018 and the digital inclusive finance index of Peking University (2011-2018), this paper empirically tests the impact of digital finance development on corporate social responsibility in various provinces of China and its impact mechanism. The results show that: (1) the development of digital finance helps to promote the fulfillment of corporate social responsibility; (2) the influence mechanism of the development of digital finance to promote the fulfillment of corporate social responsibility lies in that it reduces the cost of debt financing and leads to the improvement of corporate social responsibility.(3) Further research shows that the positive relationship between digital finance and corporate social responsibility is more significant in private enterprises. At the same time, the impact is more significant in areas with poor market environment. The above research shows that the development of digital finance has a significant positive effect, which will improve the level of corporate social responsibility.

Compared with liquid crystal clad waveguide, MEMS mirror has some merits, such as high-er-transmissivity, lager-angle of scanning, faster scanning speed and so on. Furthermore, MEMS mirror arrays perform more superior than MEMS mirror when they steer laser beam, which make MEMS arrays much more suitable to be used in devising compact Lidar. Before assembling a Lidar with MEMS arrays, the optical intensity and distributions of the laser diffracted by MEMS arrays should be analyzed, but few published papers about this issue are available so far, this paper will focus on this issue about MEMS arrays. Firstly, the complex amplitudes of laser which is diffracted by 1-D and 2-D arrays are presented, respectively. Then the optical intensity and distributions on the observation plane are presented. Finally, the simulation diagrams of these distributions are shown, and the correctness of the results is indirectly verified by Young’s dou-ble-slit experiment. The results gotten in this letter are essential to design a compacted Lidar based on MEMS arrays.

Objective: To evaluate the effect of propofol combined with psychological intervention on pain and emotional evaluation in painless colonoscopic colonic polypectomy patients undergoing endoscopic mucosal resection (EMR).Methods: A total of 80 patients who underwent painless colonoscopic colonic polypectomy with EMR treatment between June 2020 and June 2022 were selected in order of admission and divided into two groups. The control group received conventional analgesia, while the observation group received propofol combined with psychological intervention. Pain visual analog scale (VAS) and emotional scale were used to evaluate pain and emotions in both groups of patients. Adverse reactions and clinical efficacy were also compared between the two groups.Results: The two groups of patients were generally comparable with no significant differences (P > 0.05). The VAS score in the observation group was significantly lower than that in the control group (P < 0.05), and the emotional scale score was also improved compared to the control group (P < 0.05). The number of patients with adverse reactions in the observation group was less than that in the control group. The clinical effective rate in the observation group was significantly higher than that in the control group (P < 0.05).Conclusion: Propofol combined with psychological intervention can effectively alleviate pain and improve emotional status in painless colonoscopic colonic polypectomy patients undergoing EMR treatment, thereby increasing the comfort and success rate of the surgery. The number of patients with adverse reactions in the observation group was less than that in the control group, and the clinical effective rate in the observation group was significantly higher than that in the control group (P < 0.05).

This paper presents a compact wideband circularly polarized cross dipole antenna with low-pass filter response. It consists of two pairs of folded crossed dipole arms printed separately on both sides of the top substrate, and the two dipole arms on the same surface are connected by an annular phase-shifting delay line to generate circular polarization. A bent metal square ring and four small metal square rings around the cross dipoles are employed to introduce new resonant frequencies, effectively extending the impedance and axial ratio bandwidth. Four square patches printed on the middle substrate are connected to the ground plane by the vertical metal plates, in order to reduce the antenna height. Thus, a compact wideband circularly polarized antenna is realized. In addition, a transmission zero can be introduced at the upper frequency stopband by the bent metal square rings, without using extra filter circuits. For verification, the proposed model is implemented and tested. The overall size of the model is 90mm×90mm×33mm(0.37λ0×0.37λ0×0.14λ0, λ0 denotes the center operating frequency). The measured impedance bandwidth and 3 dB axial ratio bandwidth are 53.3% and 41%, respectively. More than 15 dB upper-band radiation suppression level is realized, indicating a good low-pass filter response.

The composite post insulator composed of a large diameter mandrel and flange pressed by one-time integral pultrusion has high strength and good toughness, widely used in the existing flexible converter valve. For constructing the finite element model of the crimped post insulator, most of the flange surface and the mandrel surface are directly connected, making the simulation model's stiffness deviate from the actual model and the model distortion. Based on this, this study proposes a new finite element simplified model of crimped composite post insulator based on Multi-Point Constraints (MPC), which accurately simulates the crimping area of man-drel and flange in engineering practice. It verifies the model's reliability through static tests and characteristic vibration tests. The results show that the difference between the finite element simulation and test results is within 5 %. The finite element modeling method based on MPC local constraints is very reliable in applying crimped composite post insulators. Based on the proposed model, the influence of flange height and thickness on the mechanical properties of composite post-insulators is further explored. The results show that the influence of flange height on mechanical properties can be ignored when the height of the insulator stiff-ener ( non-press common area ) is constant. Within the allowable thickness range of the flange crimping process, the increase in flange thickness will significantly reduce the maximum bend-ing stress of the insulator and increase its safety margin. It provides a good design idea for the design of crimping composite insulators.

Objectives: The purpose of this study is to determine the association between umbilical venous blood flow (UVBF) to placental pulsatility index (PPI) ratio and gestational age (GA) in women undergoing prenatal assessments and adverse pregnancy outcome (APO) screening Methods: Between January and December 2022, sonographic examinations were conducted to assess the fetal umbilical cord insertion site in singleton fetuses, and hemodynamic indices of the umbilical artery, umbilical vein, and uterine artery were computed. Through regression analysis, we derived the optimal regression equation to elucidate the UVBF/PPI ratio parameters based on GA. Results: Among 492 singleton fetuses between 21+0 and 40+6 weeks of gestation in the final study. The average fetal UVBF/PPI ratio was 180.45±119.32. Correlation analysis revealed a positive relationship between the UVBF/PPI ratio and GA(p = .000). Using regression analysis, the best-fit regression equation was the linear function model, which explains the value of UVBF/PPI ratio parameters based on GA. Lower UVBF/PPI ratio revealed a positive relationship in the low birth weight fetuses (p=0.021) and higher preterm delivery rate (p=0.034). Cerebroplacental ratio (CPR) showed a high correlation with the UVBF/PPI ratio (r=0.471, p=0.000). Conclusions: The findings of our analyses revealed that contribute to our understanding of fetal hemodynamics and highlight the potential of UVBF/PPI ratio as a predictive marker for adverse pregnancy outcomes, such as preterm birth, low birth weight, or potential fetal hypoxemia. It might be useful for prenatal counseling and clinical purposes.

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.

As an irreplaceable ecological barrier, the ecological conservation developing area (ECDA) is vital for the integrated construction of urban and rural areas, and optimization and adjustment of industrial structure. Developing green agriculture is the foundation and guarantee for improving the rural ecological environment and meeting the increasing needs of farmers′ income. Issued by the Chinese government, No. 1 Central Document stated the necessity of promoting agricultural green development (AGD) and the related technologies in dealing with ecological pressure and resource shortages, especially for large cities like Beijing. However, few empirical studies have conducted on spatiotemporal variations of AGD in ECDA of large cities. Based on the green agricultural traits of Beijing and the accessible data, we evaluate AGD and analyze its spatial and temporal heterogeneity of Beijing ECDA by constructiing a framework with 13 indicators. The weight coefficients of AGD indicators were calculated by the projection pursuit method, with the district panel data from 2006 to 2016. The results demonstrated that energy consumption is a vital factor of green agriculture production, and agricultural output value per unit of the arable land area is the key to the green agricultural revenue. From 2006 to 2016, the AGD index of ECDA had an increasing trend till 2012, followed by a decreasing tendency. The AGD index of the northern region is higher than the southern of ECDA. The obstacle degree model was used to verify AGD limiting factors. They were poor infrastructure, slow agritourism, low labor productivity, and low resource utilization efficiency that varied by districts in ECDA. Given these findings, our study is conducive to the AGD evaluation at the district (county) level for ECDA of large cities and also provides important policy implications.

A series of D–π–A diketopyrrolopyrrole (DPP)-based small molecules have been designed for organic light-emitting diodes (OLEDs) and organic solar cells (OSCs) applications. Appling the PBE0/6-31G(d,p) method, the ground state geometry and relevant electronic properties were investigated. The first excited singlet state geometry and the absorption and fluorescent spectra were simulated at the TD-PBE0/6-31G(d,p) level. The calculated results reveal that the photophysical properties are affected through the introduction of different end groups. Furthermore, the electronic transitions corresponding to absorption and emission exhibit intramolecular charge transfer feature. It was disclosed that the designed molecules act not only as luminescent for OLEDs, but also donor materials in OSCs. Moreover, they also can be used as potential electron transfer materials using for OLEDs and OSCs.

A rapid and efficient method using an alkyl functionalized magnetic nanoparticles-based extraction technique combined with Ultra-High Performance Liquid Chromatography was developed for the detection of trace amounts of polycystic aromatic hydrocarbons in tea leaves. As a popular coating for chromatographic column packing materials, C18-alkyl has been demonstrated to be effective in separating polycystic aromatic hydrocarbons. And the magnetism of the nanomaterials accelerates the extraction process while their high surface ratio enables desirable dispersity in the sample matrix. Meanwhile, the adsorbents can be washed and reused 30 times without compromise on recovery, which greatly reduced the budget. The effects of various parameters were investigated and optimized, and the recoveries for five analytes were in the range of 84.8–103.7%. The reproducibility rate of intra-day and inter-day were below 7.1% and 11.3% respectively. The limits of detection and limits of quantification ranged from 1.69–9.97 ng g-1 and 5.12–30.21 ng g-1, indicating satisfactory sensitivity. Thus, the proposed methodology is rapid, highly efficient, and economical, and it expands the application of magnetic cleanup approaches in complex food matrices.

Non-Vitamin K Oral Anticoagulants (NOACs) have revolutionized anticoagulant therapy, offering improved safety and efficacy over traditional agents like warfarin. This review comprehensively examines the dual roles of NOACs—Apixaban, Rivaroxaban, Edoxaban, and Dabigatran—not only as anticoagulants but also as modulators of inflammation via Protease-Activated Receptor (PAR) signaling. We highlight the unique pharmacotherapeutic properties of each NOAC, supported by key clinical trials demonstrating their effectiveness in preventing thromboembolic events. Beyond their established anticoagulant roles, emerging research suggests that NOACs influence inflammation through PAR signaling pathways, implicating factors such as FXa and Thrombin in the modulation of inflammatory responses. This review synthesizes current evidence on the anti-inflammatory potential of NOACs, exploring their impact on inflammatory markers and conditions like atherosclerosis and diabetes. By delineating the mechanisms by which NOACs mediate anti-inflammatory effects, this work aims to expand their therapeutic utility, offering new perspectives for managing inflammatory diseases. Our findings underscore the broader clinical implications of NOACs, advocating for their consideration in therapeutic strategies aimed at addressing inflammation-related pathologies. This comprehensive synthesis not only enhances understanding of NOACs' multifaceted roles but also paves the way for future research and clinical applications in inflammation and cardiovascular health

Most machine learning and deep learning algorithms can only use low-dimensional data as input, but the data that must be processed in practical applications is diverse and irregular. There are two main problems with big dynamic data. (1) The size of the embedding table grows linearly with the vocabulary size, resulting in massive memory consumption. (2) For different newly added vocabularies. To solve these two problems, this paper proposes a novel embedding algorithm that can learn attribute associations with entities based on deep and hash algorithms. Taking movie data as an example, the encoding method and the specific flow of the algorithm are presented in detail, and the effect of dynamic reuse of data models is realized. Compared with the four existing embedding algorithms which can fuse entity attribute information, the deep hash embedding algorithm proposed in this paper has obvious optimization of time and space complexity.

Bartonella henselae is a fastidious Gram-negative intracellular bacterium which can cause cat scratch disease, endocarditis in humans and animals as well as other complications, leading to acute or chronic infections. The current treatment for Bartonella infections is not very effective due to antibiotic resistance and also persistence. To develop better therapies for persistent and chronic Bartonella infections, in this study, with the help of SYBR Green I/PI viability assay, we performed a high-throughput screening of an essential oil library against stationary phase B. henselae. We successfully identified 32 essential oils that had high activity, including four essential oils extracted from Citrus plants, three from Origanum, three from Cinnamomum, two from Pelargonium and two from Melaleuca, as well as frankincense, ylang ylang, fir needle, mountain savory (winter), citronella, spearmint, elemi, vetiver, clove bud, allspice and cedarwood essential oils. The minimal inhibitory concentration (MIC) determination of these 32 top hits indicated they were not only active against stationary phase non-growing B. henselae but also had good activity against log phase growing B. henselae. The time-kill curve by drug exposure assay showed 13 active hits, including essential oils of oregano, cinnamon bark, mountain savory (winter), cinnamon leaf, geranium, clove bud, allspice, geranium bourbon, ylang ylang, citronella, elemi and vetiver, could eradicate all stationary phase B. henselae cells within 7 days at the concentration of 0.032% (v/v). Two active ingredients, carvacrol and cinnamaldehyde, of oregano and cinnamon bark essential oils, respectively, were shown to be very active against stationary phase B. henselae such that they were able to eradicate all the bacterial cells even at the concentration ≤ 0.01% (v/v). Our finding of active essential oils may help to develop more effective treatments for persistent Bartonella infections.

The remediation of dredged marine sediments contaminated by heavy metals has drawn increasing attention worldly. The immobilization was regarded as a promising method to reduce adverse impacts on marine ecosystem. In this study, kaolinite and limestone were used as amendments to immobilize heavy metals (e.g. Zn, Pb and Cu) respectively in dredged marine sediments collected from the coastal zone adjacent to Tianjin Port in Bohai Bay. The sequential extraction procedure was applied to identify the mobility of heavy metals and further to evaluate the immobilization effect of amendments. The physical-chemical properties of sediments, such as pH, electrical conductivity (EC), salinity, and total organic carbon (TOC), were also measured to better understand their influence on heavy metals’ mobility. In addition, the compositions of clay minerals were also analyzed to identify the transformation process of minerals in the sediments. The results of sequential extraction procedure indicated that mobile fractions of heavy metals were converted into relatively stable fractions because of the two amendments. In addition, EC, salinity and TOC decreased moderately while no obvious variations of pH in the sediments were observed with the addition of the the kaolinite and the limestone. The percentage of montmorillonite decreased to minimum value while that of chlorite increased gradually during the experimental periods for 40 days probably due to complexation reaction. It was confirmed that both kaolinite and limestone can effectively reduce the mobility and bioavailability of heavy metals, particularly for Zn, generally, limestone has a better immobilization effect compared with kaolinite.

Infrared and visible image fusion technologies are used to characterize the same scene by diverse modalities. However, most existing deep learning-based fusion methods are designed as symmetric networks, which ignore the differences between modal images and lead to the source image information loss during feature extraction. In this paper, we propose a new fusion framework for the different characteristics of infrared and visible images. Specifically, we design a dual-stream asymmetric network with two different feature extraction networks to extract infrared and visible feature maps respectively. The transformer architecture is introduced in the infrared feature extraction branch, which can force the network to focus on the local features of infrared images while still obtaining their contextual information. And the visible feature extraction branch uses residual dense blocks to fully extract the rich background and texture detail information of visible images. In this way, it can provide better infrared targets and visible details for the fused image. Experimental results on multiple datasets indicate that DSA-Net outperforms state-of-the-art methods in both qualitative and quantitative evaluations. In addition, we also apply the fusion results to the target detection task, which indirectly demonstrates the fusion performances of our method.

The multi-modal data fusion method based on IA-net and CHMM technical proposed is designed to solve the problem that the incompleteness of target behavior information in complex family environment leads to the low accuracy of human behavior recognition.The two improved neural networks(STA-ResNet50、STA-GoogleNet)are combined with LSTM to form two IA-Nets respectively to extract RGB and skeleton modal behavior features in video. The two modal feature sequences are input CHMM to construct the probability fusion model of multi-modal behavior recognition.The experimental results show that the human behavior recognition model proposed in this paper has higher accuracy than the previous fusion methods on HMDB51 and UCF101 datasets. New contributions: attention mechanism is introduced to improve the efficiency of video target feature extraction and utilization. A skeleton based feature extraction framework is proposed, which can be used for human behavior recognition in complex environment. In the field of human behavior recognition, probability theory and neural network are cleverly combined and applied, which provides a new method for multi-modal information fusion.

A full connected world is expected to gain in the 6th generation mobile network (6G). As a typi-cal fully connected scenario, the internet of vehicle (IoV) enables intelligent vehicle operations via artificial intelligence (AI) and edge computing technologies. In the future of vehicular net-works, wide variety of services need powerful computing resources and higher quality of ser-vice (QoS). Existing resources are insufficient to match these requirements. Aim to this problem, An intelligent service offloading framework is provided. Based on the framework, an Algorithm of Improved Gradient Descent (AIGD) is created to accelerate the speed of iteration. So, the con-vergence of convolutional neural network (CNN) based on AIGD is able to be accelerated too. Then, an Algorithm of convolutional long short-term memory (CN_LSTM) Based Traffic Predic-tion (ACLBTP) is designed to gain the predicted number of vehicles belonged to the edge node. At last, an Algorithm of Service Offloading Based on CN_LSTM (ASOBCL) is conducted to of-fload these services to the vehicles belonged to the edge node. In ASOBCL, sorting technique is adopted to speed up the offloading work. Simulation results demonstrate the fact that the pre-diction strategy designed in this paper has high accuracy. The low offloading time and main-taining stable load balance is gained via running ASOBCL. Low offloading time means short response time. And, the QoS is guaranteed. So, these strategies designed in this paper are effec-tive and valuable.

This paper is concerned with the optimal linear quadratic Gaussian (LQG) control problem for discrete time-varying system with multiple input delays and multiplicative noises. The main contributions are two-fold. Firstly, when the state variables can be observed exactly, we obtain a necessary and suffcient condition for the multiple-delays system in terms of the non-homogeneous relationship between the state and costate, which is the solution to the coupled forward and backward stochastic difference equations. Secondly, when the state variables are partially observed, we derive a suboptimal linear output feedback controller for the discrete-time system based on the obtained results of the optimal LQG control. Numerical examples are shown to illustrate the proposed algorithm.

In the manufacturing industry, orders are typically scheduled and delivered through batches, and the probability of machine failure under high-load operation is high. On this basis, we focus on a single machine batch scheduling problem with a maintenance interval (SMBSP-MI). The studied problem is expressed by three-field representation as 1|B,MI|\sum{F_j+\mu}m, and the optimization objective is to minimize total flow time and delivery costs. Firstly, 1|B,MI|\sum{F_j+\mu}m is proved to be NP-hard by Turing reduction. Secondly, shortest processing time (SPT) order is shown the optimal scheduling of SMBSP-MI, and a dynamic programming algorithm based on SPT (DPA-SPT) with the time complexity of O(n^3T_1) is proposed. A small-scale example is designed to verify the feasibility of DPA-SPT. Finally, DPA-SPT is approximated to a fully-polynomial dynamic programming approximation algorithm based on SPT (FDPAA-SPT) by intervals partitioning technique. The proposed FDPAA-SPT runs in O(\frac{n^5}{\varepsilon^2})\ time with the approximation (1+\varepsilon).

In order to help the transportation industry achieve the goal of carbon peak and carbon neutrality, this study is based on the selection of eight variables, such as population size, per ca pita GDP, personal vehicle ownership, passenger and freight turnover, and green space coverage, as the factors influencing the carbon emissions of the transportation industry in Jiangsu Province, and the prediction and analysis of the transportation carbon emission trends from 2000 to 2021, and the prediction and analysis of the carbon emissions of the transportation industry and the time of the peak of the carbon emissions in Jiangsu Province. The trend of transportation carbon emissions from 2000 to 2021 was predicted and analyzed, and the carbon emissions and peak time of carbon emissions in the transportation industry in Jiangsu Province were predicted and analyzed. Comparing the predicted results with other models to verify the accuracy of the results, it was found that the WOA-SVM model had the smallest error among several models. On this basis, targeted measures are proposed to accelerate the process of carbon peak and ensure the smooth achievement of carbon neutrality goals in Jiangsu Province. The results indicate that under the current policy measures, the peak carbon emissions in Jiangsu Province will occur in 2038, with a peak of 48.72 million tons. Jiangsu Province should actively adopt energy-saving and emission-reduction measures, build a green and low-carbon transportation development model, and achieve the carbon peak target ahead of schedule.

The porous structure is an important three-dimensional morphological feature of the peripheral nerve guidance conduit (NGC), which permits infiltration of cells, nutrients, and molecular signals, and the discharge of metabolic waste. Porous structures with precisely customised pore sizes, porosities, and connectivities were used to construct fully permeable, semi-permeable, and asymmetric peripheral NGCs to replace traditional nerve autografts in treatment of long-segment peripheral nerve injury. In this review, the features of porous structures and classification of NGCs based on these characteristics are discussed. Common methods for constructing 3D porous NGCs in current research are described, as well as the pore characteristics and the parameters used to tune the pores. The effects of the porous structure on the physical properties of NGCs including biodegradation, mechanical performance, and permeability were analysed. Pore structure affects the biological behaviour of Schwann cells, macrophages, fibroblasts, and vascular endothelial cells during peripheral nerve regeneration. Construction of ideal porous structures is a significant advancement in the regeneration of peripheral nerve tissue engineering materials. The purpose of this review is to generalise, summarise, and analyse the preparation methods for porous NGCs and their biological functions in promoting peripheral nerve regeneration to guide development of medical nerve repair materials.

In this paper, a study was conducted on the Ramsey interference and spectral line locking techniques based on rubidium-87 cold atoms. Using sequential control technique, the timing design of a three-dimensional magneto-optical trap (MOT), cold atoms’ free fall, Ramsey microwave interference, and two-level fluorescence detection was realized, achieving the state preparation of cold atoms and clock transitions. By designing an automatic peak-finding algorithm, numerical integration was performed on the time-of-flying (TOF) signal, and narrow linewidth cold atom Ramsey interference fringes were obtained. Based on this, a frequency-hopping method was used to lock the frequency of the 10MHz oven-controlled crystal oscillator (OCXO) in a closed loop, achieving a linewidth of 38Hz. This preliminary result verifies the feasibility of the system design.

Foxtail millet (Setaria italica (L.) P. Beauv) is an important food and forage crop that is well adapted to nutrient-poor soils. However, little is known about how foxtail millet adapts to low nitrogen (LN) at the physiological and molecular levels. In the present study, two foxtail millet varieties with contrasting low nitrogen (LN) tolerance properties were investigated through integrative analyses of physiological featureparameters and transcriptomics. The physiological results showed that JG20 (high tolerance to LN) had higher biomass accumulation, nitrogen content and nitrogen use efficiency compared with JG22 (low tolerancesensitive to LN) under LN. JG20 had higher soluble sugar and soluble protein concentration in shoots compared with JG22 under LN, while contcentrations of soluble sugar and soluble protein contents were higher in the roots of JG22. Higher levels of CTK contentzeatin concentration were found in the shoots of JG20 com-pared with JG22, and a higher ABA contcentration was found in both the shoots and roots of JG22 compared with JG20 under LN. In the transcriptomics results, JG20 had more differentially ex-pressed genes (DEGs) than JG22 both in shoots and roots in response to LN. These LN-responsive genes were enriched in glycolysis, starch and sucrose metabolism, photosynthesis, biosynthesis of amino acids, hormone metabolism and nitrogen metabolism. Furthermore, the high-affinity nitrate transporter gene, SiNRT2.1, and glutamine synthetase gene, SiGS5, chlorophyll apoprotein of photosystem II gene, SiPsbQ, ATP synthase subunit gene, b, auxin-responsive protein gene, SiIAA25, and aldose 1-epimerase gene, SiAEP, in shoots, and high-affinity nitrate transporter gene, SiNRT2.3, SiNRT2.4, and glutamate synthase gene, SiGOGAT2, auxin-responsive protein gene, SiIAA4, fructose-bisphosphate aldolase gene, SiAEP5, in root, were important genes in-volved in the LN tolerance of foxtail millet. These results provide a detailed description of the physiological and transcriptome response of foxtail millet under LN condition.

In this paper, we demonstrate a method of measuring the flexural elastic modulus of ceramics at an intermediate (~millimeter) scale, at high temperatures. We used a picosecond laser to precisely cut micro-beams from the location of interest in a bulk ceramic. They had a cross-section of approximately 100 μm × 300 μm, and a length of ~1 cm. They were then tested in a thermal-mechanical analyzer at room temperature, 500°C, 800°C, and 1100°C using the four-point flexural testing method. We compared the elastic moduli of high-purity Al2O3 and AlN measured by our method with the reported values in the literature and found that the difference was less than 5% for both materials. This paper provides a new and accurate method of characterizing the high-temperature elastic modulus of miniature samples extracted from representative/selected areas of bulk materials.

As an important carrier of urban residents' public life, urban public open space plays an indispensable role in improving the quality of life of urban residents. Accessibility is an important indicator to characterize the publicity and service level of a public open space. This study optimized the GIS-based, Gaussian two-part mobile search method to quantitatively calculate and evaluate the accessibility of public open space within a 5-minute walking distance for residents in Nanshan District, Shenzhen. On this basis, social survey methods, including the questionnaire survey method via a field survey and the interview method, were used to conduct field research on residents' accessibility satisfaction. Comparing the results of the survey on residents' accessibility satisfaction to the GIS quantitative evaluation results of accessibility, the results of the field research show that current residents of Nanshan are more satisfied with the accessibility of public open space. In view of the similarities and differences between the two sets of results, the influencing factors of public open space accessibility were analyzed, corresponding countermeasures were proposed for the construction of public open spaces in the future.

The poor water-solubility and instability of Ru(II) carbonyl complex hamper the therapeutic application as CO releasing materials (CO-RMs). To enhance the hydrophilicity and bio-utility of CO, a robust Ru(I) carbonyl sawhorse skeleton were grafted with water-soluble PEGlyated sidearms. Twelve PEGlyted sawhorse Ru2(CO)4 complexes were prepared with satisfactory yields and characterized by IR and 1H- and 13C- NMR. X-ray diffraction analysis of CO-RM 8, 13 and 14 revealed the featured diruthenium sawhorse skeleton and PEGylated axial ligands. The flask-shaking method measures the hydrophilicity of CO-RMs, indicating that both bridging carboxylate ligand and PEGlyated axial ligands regulate the hydrophilicity of these CO-RMs. Under photolysis conditions, CO-RM 4-13 sustainable released therapeutic amounts of CO in myoglobin assay. The correlation of the CO release kinetics and hydrophilicity of CO-RMs demonstrated that the more hydrophilic CO-RM released CO faster. The biological test found the low cytotoxic CO-RM 4 showed a specific anticancer activity toward HT-29 tumour cells.

China is rich in coal resources, but the complex hydrogeological conditions lead to difficulties in coal mining, such as coal mine collapse, roof and water damage, and other accidents that occur frequently, resulting in many casualties and property losses. The use of coal mine hole detection technology to detect and analyze the internal environment of the coal mine in advance helps to reduce safety hazards and prevent coal mine accidents, for the existing coal mine hole detection technology operation is cumbersome, not easy to control, and insufficient depth of jacking prob-lems, this paper designs a new type of mine hole detection small robot. Firstly, this paper ana-lyzes the function and structural design of the mine hole detection robot, designs the variable diameter function according to the characteristics of narrow and uneven mine holes in coal mines, and analyzes the mechanics of the critical parts through theoretical calculations; secondly, based on the three-dimensional modeling software, established the structural model of the small robot for mine hole detection; after that, designed the robot's hardware circuits and control pro-grams for the presence of water and gas inside the mine hole, highlighting the need to carry out a new type of mine hole detection small robot. After that, we designed the robot's hardware circuit and control program, giving particular emphasis to the safety design of the circuit for the pres-ence of water and gas inside the mine hole of the coal mine. Finally, to verify the feasibility of the design program, the basic parameters and function tests of the mine hole detection small robot are carried out. The experimental results show that the mine hole inspection small robot realized by this design can adapt to the working hole diameter from 65 mm to 100 mm, the maximum working power is only 12 W, and the maximum crawling speed is 3.96 m/min. The maximum crawling slope reaches 90°, which can meet the actual mine hole inspection needs. The research can provide theoretical and design guidance for developing the mine hole detection robot with substantial engineering practical reference value.

The interpretation of land use and land cover (LULC) is an important issue in the fields of high-resolution remote sensing (RS) image processing and land resource management. Fully training a new or existing convolutional neural network (CNN) architecture for LULC classification requires a large amount of remote sensing images. Thus, fine-tuning a pre-trained CNN for LULC detection is required. To improve the classification accuracy for high resolution remote sensing images, it is necessary to use another feature descriptor and to adopt a classifier for post-processing. A fully connected conditional random fields (FC-CRF), to use the fine-tuned CNN layers, spectral features, and fully connected pairwise potentials, is proposed for image classification of high-resolution remote sensing images. First, an existing CNN model is adopted, and the parameters of CNN are fine-tuned by training datasets. Then, the probabilities of image pixels belong to each class type are calculated. Second, we consider the spectral features and digital surface model (DSM) and combined with a support vector machine (SVM) classifier, the probabilities belong to each LULC class type are determined. Combined with the probabilities achieved by the fine-tuned CNN, new feature descriptors are built. Finally, FC-CRF are introduced to produce the classification results, whereas the unary potentials are achieved by the new feature descriptors and SVM classifier, and the pairwise potentials are achieved by the three-band RS imagery and DSM. Experimental results show that the proposed classification scheme achieves good performance when the total accuracy is about 85%.

Since the electro-hydraulic servo shaking table exists many nonlinear elements, such as, dead zone, friction and blacklash, its acceleration response has higher harmonics which result in acceleration harmonic distortion, when the electro-hydraulic system is excited by sinusoidal signal. For suppressing the harmonic distortion and precisely identify harmonics, a combination of the adaptive linear neural network and least mean M-estimate (ADALINE-LMM), is proposed to identify the amplitude and phase of each harmonic component. Namely, the Hampel’s three-part M-estimator is applied to provide thresholds for detecting and suppressing the error signal. Harmonic generators are used by this harmonic identification scheme to create input vectors and the value of the identified acceleration signal is subtracted from the true value of the system acceleration response to construct the criterion function. The weight vector of the ADALINE is updated iteratively by the LMM algorithm, and the amplitude and phase of each harmonic, even the results of harmonic components, can be computed directly online. The simulation and experiment are performed to validate the performance of the proposed algorithm. According to the experiment result, the above method of harmonic identification possesses great real-time performance and it has not only good convergence performance but also high identification precision.

Outliers seriously affect the accuracy in geometric model fitting. Previous works in coping with outliers involve threshold selection and scale estimation. However most scale estimators suppose the inlier distribution as a Gaussian model, which usually poorly meets the cases in geometric model fitting. Outliers, considered as the points with big residuals to all the true models, share common items with big values in quantized residual preferences, thus making the outliers gather away from the inliers in quantized residual preference space. In this paper we make use of this outlier consensus in quantized residual preference space by extending the usage of energy minimization to combine the model error and the spatial smoothness in quantized residual preference space for outlier detection. The energy minimization based outlier detection process follows an alternate sampling and labeling framework. After the outlier detection, an ordinary energy minimization method is employed to optimize the inlier labels, which also follows the framework of alternate sampling and labeling. The experimental results in this study show that the energy minimization based outlier detection method can detect most of the outliers in the data. Furthermore, the proposed energy minimization based inlier segmentation process segments the inliers into different models quite accurately. Overall, the performance of the proposed method is better than most of the state-of-the-art methods.

Large-scale land cover plays a crucial role in global resource monitoring and management, as well as research on sustainable development. However, the complexity of the mapping process, coupled with significant computational and data storage requirements, often leads to delays between data processing and product publication, creating challenges for dynamic monitoring of large-scale land cover. Therefore, improving the efficiency of each stage in large-scale land cover mapping and automating the mapping process is currently an urgent and critical issue that needs to be addressed. We propose a high-performance automated large-scale land cover mapping framework(HALF) that introduces high-performance computing technology to the field of land cover production. HALF optimizes key processes, such as automated sample point extraction, sample-remote sensing image matching, and large-scale classification result mosaic and update. We selected several 10°×10° regions globally and the research makes several significant contributions:(1)We design HALF for land cover mapping based on docker and CWL-Airflow, which solves the heterogeneity of models between complex processes in land cover mapping and simplifies the model deployment process. By introducing workflow organization, this method achieves a high degree of decoupling between the production models of each stage and the overall process, enhancing the scalability of the framework. (2)HALF propose an automatic sample points method that generates a large number of samples by overlaying and analyzing multiple prior products, thus saving the cost of manual sample selection. Using high-performance computing technology improved the computational efficiency of sample-image matching and feature extraction phase, with 10 times faster than traditional matching methods.(3)HALF propose a high-performance classification result mosaic method based on the idea of grid division. By quickly establishing the spatial relationship between the image and the product and performing parallel computing, the efficiency of the mosaicking in large areas is significantly improved. The average processing time for a single image is around 6.5 seconds.

Although deep learning has received extensive attention and achieved excellent performances in various of scenarios, it suffers from adversarial examples to some extent. Especially, physical attack poses more threats than digital attack. However, existing researches pay less attention to physical attack of object detection in remote sensing images (RSIs). In this work, we systematically analyze the universal adversarial patch attack for multi-scale objects in the remote sensing field. There are two challenges for adversarial attack in RSIs. On one hand, the number of objects in remote sensing images is more than that of natural images. Therefore, it is difficult for adversarial patch to show adversarial effect on all objects when attacking a detector of RSIs. On the other hand, the wide range of height of photography platform causes that the size of objects diverse a lot, which brings challenges for generating universal adversarial perturbation for multi-scale objects. To this end, we propose an adversarial attack method on object detection for remote sensing data. One of the key ideas of the proposed method is the novel optimization of adversarial patch. We aim to attack as many objects as possible by formulating a joint optimization problem. Besides, we raise a scale factor to generate a universal adversarial patch that adapts to multi-scale objects, which ensures the adversarial patch is valid for multi-scale objects in the real world. Extensive experiments demonstrate the superiority of our method against state-of-the-art methods on YOLO-v3 and YOLO-v5. In addition, we also validate the effectiveness of our method in real-world applications.

In order to apply RAP fine aggregate to High Modulus Asphalt Concrete(HMAC), this study first extracts aged asphalt from RAP fine aggregate through extraction and distillation, and adds it to high modulus modified asphalt in proportions of 20%, 40%, 60%, and 80%. The performance changes of the recycled asphalt were investigated using conventional performance tests and dynamic shear rheological tests (DSR). Microscopic techniques such as four‐component analysis and infrared spectroscopy were employed to explain macroscopic performance changes in terms of component and functional group changes in the asphalt. Using HMAC‐20 gradation as an example, uniaxial compression dynamic modulus tests, rutting tests, freeze‐thaw splitting tests, and low‐temperature bending tests were conducted to evaluate the performance changes of recycled asphalt mixture with different RAP fine aggregate contents through four indices: dynamic modulus, dynamic stability, tensile strength ratio (TSR), and maximum bending strain. The results indicate that for every 20% increase in aged asphalt, the penetration at 25°C, ductility at 25°C, and dynamic viscosity at 60°C decrease by approximately 6.2%, 15.4%, and 3.9%, respectively, while the softening point increases by approximately 13.3%. It is concluded that the addition of aged asphalt significantly affects the ductility at 25°C and the softening point. As the aged content increases, the complex shear modulus (G*) and phase angle (δ) of the recycled asphalt decrease, while the rutting factor increases. The four‐component analysis and infrared spectroscopy of the asphalt demonstrate that the incorporation of aged asphalt is merely a physical blending phenomenon, involving changes in the content of the four components without the formation of new functional groups (new peaks). When RAP fine aggregate is applied to high modulus recycled asphalt mixture, compared to high modulus modified asphalt mixture, the recycled mixtures exhibit higher dynamic modulus and dynamic stability, but significantly reduced water stability and low‐temperature performance.

Identifying fake news on the media has been an important issue. This is especially true considering the wide spread of rumors on the popular social networks such as Twitter. Various kinds of techniques have been proposed for automatic rumor detection. In this work, we study the application of graph neural networks for rumor classification at a lower level, instead of applying existing neural network architectures to detect rumors. The responses to true rumors and false rumors display distinct characteristics. This suggests that it is essential to capture such interactions in an effective manner for a deep learning network to achieve better rumor detection performance. To this end we present a simplified aggregation graph neural network architecture. Experiments on publicly available Twitter datasets demonstrate that the proposed network has performance on a par with or even better than that of state-of-the-art graph convolutional networks, while significantly reducing the computational complexity.

Capacitive contact imaging has shown potential in measuring skin properties including hydration, micro relief analysis, as well as solvent penetration measurements. Through calibration we can also measure the absolute permittivity of the skin, and from absolute permittivity we then work out the absolute solvent content in skin. In this paper, we present our latest study of capacitive contact imaging for skin characterizations and vivo skin solvent penetration. We will show how to use capacitive occlusion measurements to characterize skin damages, and how to calculate the absolute water content and solvent content in skin.

The three-dimensional morphology of frictional sub-surfaces holds significant importance for studying tribological issues. However, the uniformity of horizontal datum in 3D scanning is limited for curved surfaces, resulting in the inability to obtain accurate contour characterization parameters from the scanning results. This study aims to address this issue by constructing regular surface equations and normalizing the 3D profiler scanning results. By fitting the data, a "plane" surface representative of the surface features is obtained, and the paper demonstrates this approach on the surface morphology of different worn parts in the frictional area of spherical bearings located in the specific environment of the Three Gorges gate. The results indicate that the obtained "plane" effectively reconstructs the three-dimensional morphology map of the regular surface. Moreover, this reconstructed plane not only clearly illustrates the surface characteristics but also provides the foundation for analyzing the wear mechanism.

This paper proposes a Mixed Integer Conic Programming (MICP) model for community microgrids considering the network operational constraints and building thermal dynamics. The proposed multi-objective optimization model optimizes not only the operating cost, including fuel cost, purchasing cost, battery degradation cost, voluntary load shedding cost and the cost associated with customer discomfort due to room temperature deviation from the set point, but also several performance indices, including voltage deviation, network power loss and power factor at the Point of Common Coupling (PCC). In particular, the detailed thermal dynamic model of buildings is integrated into the distribution optimal power flow (D-OPF) model for the optimal operation. The heating, ventilation and air-conditioning (HVAC) systems can be scheduled intelligently to reduce the electricity cost while maintaining the indoor temperature in the comfort range set by customers. Numerical simulation results show the effectiveness of the proposed model and significant savings in electricity cost with network operational constraints satisfied.

The deformation monitoring information of concrete dams contains some high-frequency com-ponents, and the high-frequency components are strongly nonlinear, which reduces the accuracy of dam deformation prediction. In order to solve such problems, this paper proposes a concrete dam deformation monitoring model based on empirical mode decomposition (EMD) combined with wavelet threshold noise reduction and sparrow search algorithm (SSA) optimization of long short-term memory network (LSTM). The model uses EMD combined with wavelet threshold to decompose and denoise the measured deformation data. On this basis, the LSTM model based on SSA optimization is used to mine the nonlinear function relationship between the reconstructed monitoring data and various influencing factors. The example analysis shows that the model has good calculation speed, fitting and prediction accuracy and it can effectively mine the date char-acteristics inherent in the measured deformation, and reduce the influence of noise components on the modeling accuracy.

Echinococcus granulosus is a harmful cestode parasite which could cause Cystic Echinococcosis in humans, various livestock species and wild animals. Calmodulin (CaM), a Ca²⁺ sensor protein, is widely expressed in eukaryotes and mediates a variety of cellular signaling activities. In our study, the CaM in Echinococcus granulosus (rEgCaM) was successfully cloned and the molecular and biochemical characterizations of rEgCaM were identified. The results showed that rEgCaM was a highly conserved calcium-binding protein, consisting of 149 amino acids. Immunoblot analysis revealed that rEgCaM could be identified using E. granulosus infected sheep serum. The usage of rEgCaM as antigen was evaluated by indirect ELISA which exhibited a high sensitivity of 90.3% but low specificity (47.1%). rEgCaM was mainly located in the tegument tissues and parenchymal region of protoscoleces, the tegument and inner body of adult worm and predominantly expressed in the germinal layer. The mRNA expression of rEgCaM in PSCs were gradually decreased with the increase death of PSCs. In electrophoretic mobility tests and ANS assays, rEgCaM showed a typical calcium-binding protein characteristics. This is the first report on CaM from E. granulosus and rEgCaM is considered to be involved in some important biological function of E. granulosus as a calcium-binding protein.

In recent years, laser engraving has received widespread attention as a convenient, efficient, and programmable method, which has enabled the obtaining of high-quality porous graphene from various precursors. Laser engraving is often used to fabricate the dielectric layer with micro-structure for capacitive pressure sensors, however, the usual choice of electrodes remains poorly flexible metal electrodes, which greatly limits the overall flexibility of the sensors. In this work, we propose a flexible capacitive pressure sensor made entirely of thermoplastic polyurethane (TPU) and laser-induced graphene (LIG) derived from wood. The capacitive pressure sensor consisted of a flexible LIG/TPU electrode (LTE), a LIG/TPU electrode with micro hole array, and dielectric layer of TPU with micro-cone array molded from laser-engraved hole array on wood, which provided high sensitivity (0.11 kPa-1), ultra-wide pressure detection range (100Pa to 1.4MPa), fast response (~300 ms) and good stability (&gt;4000 cycles, at 0-35 kPa). We believe that our research makes a significant contribution to the literature because the easily available materials derived from wood and overall consistent flexibility meet the requirements of flexible electronic devices.

Circular RNAs are a special type of RNAs which recently attracted a lot of research interest in studying its formation and function. RNA binding proteins (RBPs) that bind circRNAs are important in these processes but are relatively less studied. CLIP-Seq technology has been invented and applied to profile RBP-RNA interactions on the genome-wide scale. While mRNAs are usually the focus of CLIP-Seq experiments, RBP-circRNA interactions could also be identified through specialized analysis of CLIP-Seq datasets. However, many technical difficulties are involved in this process, such as the usually short read length of CLIP-Seq reads. In this study, we created a pipeline called Clirc specialized for profiling circRNAs in CLIP-Seq data and analyzing the characteristics of RBP- circRNAs interactions. In conclusion, this is one of the first few studies to investigate circRNAs and their binding partners through repurposing CLIP-Seq datasets to our knowledge, and we hope our work will become a valuable resource for future studies into the biogenesis and function of circRNAs. Clirc software is available at https://github.com/Minzhe/Clirc

Ocean wave energy conversion as one of the renewable clean energy sources is attracting the research interests of many people. This review introduces different types of power take-off technology of wave energy converters. The main focus is the linear direct drive power take-off devices as they have the advantages for ocean wave energy conversion. The designs and optimizations of power take-off systems of ocean wave energy converters have been studied from reviewing the recently published literature. Also, the simple hydrodynamics of wave energy converters have been reviewed for design optimization of the wave energy converters at specific wave sites. The novel mechanical designs of the power take-off systems have been compared and investigated in order to increase the energy harvesting efficiency.

As an emerging discipline, Design Morphology, with the advantage of "Form Study", has been integrated with many disciplines, and gradually formed its collaborative innovation paradigm. The inclusion of "Ecology" into Design Morphology is expected to promote the research of Design Morphology with the help of the systematic thinking and methods of ecology. The ecosystem of Design Morphology includes the natural ecosystem and the quasi-ecosystem closely related to human beings, and also put forward the concept of "Form Community" for the first time in the design field. In fact, this is exactly the research scope of Design Morphology. Advocating the ecological view of Design Morphology, can not only help to design researchers improve their values and world view, with new thinking and method to engage in "Form Study", but also contribute to the theoretical construction and thinking expansion of Design Morphology, and play a positive role in promoting interdisciplinary collaborative innovation led by Design Morphology. In addition, it can be used to evaluate the overall research and future development trend of Design Morphology, and provide the new research ideas and approaches for the development of design.

Cynomorium songaricum is an important endangered plant with significant medicinal and edible values. However, the lack of resources and quality variation have limited the comprehensive developments and sustainable utilization of C. songaricum. Here, we evaluated chemical and genetic traits of C. songaricum from the highly suitable habitat regions simulated with species distribution models. The PCA and NJ tree analyses displayed intraspecific variation in C. songaricum, that could be divided into two ecotypes: ecotype I and ecotype II. Furthermore, the LC-MS/MS-based metabolomic was used to identify and analyze the metabolites of two ecotypes. The results indicated that a total of 589 compounds were detected, 236 of which were significantly different between the two ecotypes. Specifically, the relative content and the kind of flavonoids were more abundant in ecotype I, which were closely associated with the medicinal activities. In contrast, amino acids and organic acids were more enriched in ecotype II, which may provide better nutritional quality and unique flavor. In summary, our findings demonstrate the ecotype division and chemical diversity of C. songaricum in China from different geographical regions and provide a reference for the development of germplasm and directed plant breeding of endangered medicinal plants.

In order to realize the sustainable utilization of water resources and the sustainable development of economy, the evaluation index system of water use efficiency system and economic development system was constructed. Entropy weight method and comprehensive evaluation method were adopted to determine the index weights and conduct comprehensive evaluation for the two systems. The coupling coordination model was used to calculate the coupling degree, coordination degree and coupling coordination degree of the two systems. The annual coupling stage and coupling coordination intensity of the two systems were analyzed and determined. The results showed that the comprehensive evaluation values of both water use efficiency system and economic development system in Jinan City increased greatly from 2008 to 2017, and showed a changing trend of ups and downs. The two systems were in the antagonistic stage, and were gradually approaching the running-in stage, indicating that they were in the state of common development. The coupling coordination degree of the two systems gradually increased in waves, progressed from the moderately to the highly coordinated coupling. In the future, if the water control path appropriate to Jinan City can be explored actively, the water-saving kinetic energy of economic development can be increased constantly, and the linkage effect between economic development and water resources utilization can be given full play to, the two systems will be in the orbit with the benign interaction and healthy harmonious development.

Speaker recognition methods based on convolutional neural networks (CNN) have been widely used in the security field and smart wearable devices. However, the traditional CNN has a large number of hyperparameters that are difficult to be determined, which makes the model easy to fall into local optimum or even fail to converge during the training process. Intelligent algorithms such as particle swarm optimization and genetic algorithm are used to solve the above problems. However, these algorithms have poor performance compared with the current emerging meta-heuristic algorithms. In this study, the dung beetle optimized convolution neural network (DBO-CNN) is proposed to identify the speakers, which is helpful in finding suitable hyperparameters for training. By testing the dataset of 50 people, it was demonstrated that the accuracy of the model was significantly improved by using this approach. Compared with the traditional CNN and CNN optimized by other intelligent algorithms, the accuracy of DBO-CNN has increased by 0.6%~4.8%, and reached 98.3%.

The eutrophication caused by excessive total nitrogen(TN) and total phosphorus(TP) emissions has been widely concerned by the whole society. Studies have revealed the relationship between land use and TN and TP, but the relationship between land use compound topographic position and TP and TN was seldom studied. Therefore, Spearman correlation and redundancy analyses were used to reveal the relationship between land use compound topographic position and TN and TP based on the monthly data of 28 water quality sampling sites and the land use data of 2013 and 2016 in the lakes of Guizhou Plateau. The results show that the nutritional state of the HBA watershed is medium. The trophic level index (TLI) value and TN concentration were high during flood, while TP concentration was high in dry period. The TN concentration in the tributaries was higher than that in the reservoir area. Construction and valley were the sources of the pollution, whereas forest land and gentle slope were the sink. According to the”source-sink”effect, the optimal zoning of land use was completed, and the urban land pollution govern area should be strengthened firstly. This paper can provide decision support for water environment management and sustainable development decision-making.

Polyvinyl guanidineacetic (PVG) was prepared by the chemical grafting between poly(vinyl alcohol) (PVA) and guanidineacetic acid. The results showed that the guanidineacetic groups were successfully introduced into the polyvinyl alcohol by fourier transform infrared (FTIR) and thermogravimetry (TG). The effects of the amount of catalyst and reaction time on the PVG grafting rate were investigated. The PVG/NWF composite membrane as a heterogeneous catalyst for biodiesel production was successfully prepared by the solvent phase inversion. The effects of mass ratio of methanol/soybean oil and reaction temperature on the conversions using the composite membrane for transesterification were studied. And the reusability of the composite membrane and the kinetics of the reaction catalyzed by the composite membrane were also investigated. The conversions obtained from the model are in good agreement with the experimental data.

Blind deconvolution (BD) is one of the effective methods that help pre-process vibration signals and assist in bearing fault diagnosis. Currently, most BD methods design an optimization criterion and use frequency or time domain information independently to optimize a deconvolution filter. It recovers weak periodic impulses related to incipient faults. However, the random noise interference may cause the optimizer to overfit. The time-domain-based BD methods tend to extract fault-unrelated single peak impulse, and the frequency-domain-based BD methods tend to retain the maximum energy frequency component, which will lose the fault-related harmonics frequency components. To solve the above issue, we propose a hybrid criterion that combines the kurtosis for time domain optimization and the $G-l_1/l_2$ norm for the frequency domain. These two criteria are monotonically increasing and decreasing, so they mutually constrain to avoid overfitting. After that, we design a multi-task one-dimensional convolutional neural network with time and frequency branches to achieve an optimal solution for this hybrid criterion. The multi-task neural network realizes the simultaneous optimization of two domains. Experimental results show that our proposed method outperforms other state-of-the-art methods.

Stress relaxation tests in cantilever bending were performed on the C7025 and C7035 alloys at 298K and 393K，respectively. The effect of stress-relief treatments on stress relaxation properties was investigated. The structural changes associated with the stress relaxation process were examined using transmission electron microscope. The stress relaxation curve fits well to empirical formula σ*=[Kˊln(t+α₀)+C]^-n for stress relaxation. The curves can be split into two stages. The stress relax quickly in the first stage, slows down in the second stage, and tends to be a certain limit value after a long time. The curve and microstructure reveals that the C7035 alloy has a lower rate of stress relaxation and a higher anti-stress relaxation capacity than the C7025. The first reason is that the movement of vacancies required by spinodal decomposition is inhibited, and the quantity of cobalt -containing vacancies decreases dramatically in the C7035 alloy. The other reason is that the precipitated phases became uniformly diffused in the C7035 alloy. The precipitate phase uniformly distributes in the grain boundaries and the matrix, during the relaxed condition, and thus the dislocations moving is blocked by the precipitates.

Background: Disulfidptosis, a recently identified form of cell death triggered by excessive cysteine accumulation and subsequent disulfide stress, has emerged as a novel mechanism of cell death. Despite its significance, the role of disulfidptosis in the tumor microenvironment (TME) remains poorly understood. Methods: In this study, we employed single-cell RNA sequencing data from 100,987 cells of 11 osteosarcoma (OS) patients. Using the non-negative matrix factorization (NMF) algorithm, we performed dimensionality reduction analysis to identify distinct subtypes characterized by 14 disulfidptosis-related genes across major cell types within the TME. Subsequently, we assessed the prognosis and immunotherapy response associated with each disulfidptosis-related subtype, leveraging publicly available databases comprising osteosarcoma data and immunotherapy cohorts. Results: We identified distinct subtypes within tumor-associated fibroblasts, tumor-infiltrating lymphocytes, and macrophages, which we named and annotated based on their characteristic genes. Furthermore, we observed a close association between disulfidptosis-related genes and key biological features of immune cells within the TME, elucidating inferred pseudotime trajectories. Notably, integrating bulk-seq data of osteosarcoma patients, we observed significant differences in overall survival rates among the disulfidptosis-related subtypes. Particularly, the disulfidptosis-related subtype within tumor-associated fibroblasts exhibited superior discriminatory ability in predicting the response of patients undergoing immunotherapy, surpassing other cell subtypes. Our cell-cell communication analysis highlighted extensive and specific interactions between disulfidptosis-related subtypes and osteosarcoma cells. Furthermore, we confirmed the histological localization of the CAPZB+CAF subtype within osteosarcoma tissue and osteoclastoma using immunofluorescence (IF) techniques. Conclusions: Collectively, our study sheds light on the intercellular communication facilitated by disulfidptosis in the TME, underscoring its involvement in the biological functions and immunotherapy response of osteosarcoma.

Fiber aggregation in nanocomposites has an important effect on the macroscopic electrical performance. To quantitatively evaluate its effect, an index to characterize the degree of aggregation is imperative, and ideally it should have three features simultaneously, i.e., single-parametric, dimensionless and physically meaningful, applicable to different aggregation topologies, and one-to-one corresponding to material electrical properties. To this end, a new aggregation degree is proposed, which is defined as the average increased number of fibers that connect with each one when fibers aggregate from a uniformly distributed state. This index is applicable to different aggregation topologies from lump-like aggregating clusters to network-like aggregating clusters. This index is proven to only depend on the local features of aggregating clusters, and can be concisely expressed by the characteristic parameters of local structure, via geometric probability analysis and numerical validations. Further, a one-to-one linear relation between the aggregation degree and percolation threshold is established by Monte Carlo simulations, which is independent of the distribution law of the fibers. This work provides a guide to the property characterization, performance prediction and material design of nanocomposites, and also gives a physical insight into the understanding of systems with similar non-uniform distributions.

The Kuroshio Extension(KE) System exhibits highly energetic mesoscale phenomena, but the impact of mesoscale eddies on marine ecosystems and biogeochemical cycling is not well understood. This study utilizes remote sensing and Argo floats to investigate how eddies modify surface and subsurface chlorophyll (Chl-a) concentrations. On average, cyclones (anticyclones) induce positive (negative) surface Chl-a anomalies, particularly in winter. This occurs because cyclones (anticyclones) lift (deepen) isopycnals and nitrate into (out of) the euphotic zone, stimulating (depressing) the growth of phytoplankton. Consequently, cyclones (anticyclones) result in greater (smaller) subsurface Chl-a maximum (SCM), depth-integrated Chl-a, and depth-integrated nitrate. The positive (negative) surface Chl-a anomalies induced by cyclones (anticyclones) are mainly located near (north of) the main axis of the KE. The second and third mode represent monopole Chl-a patterns within eddy centers corresponding to either positive or negative anomalies, depending on the sign of the principal component. Chl-a concentrations in cyclones (anticyclones) above the SCM layer are higher (lower) than the edge values, while those below are lower (higher), regardless of winter variations. The vertical distributions and displacements of Chl-a and SCM depth are associated with eddy pumping. In terms of frequency, negative (positive) Chl-a anomalies account for approximately 26% (18%) of the total cyclones (anticyclones) across all four seasons. The opposite phase suggests that nutrient supply resulting from stratification differences under convective mixing may contribute to negative (positive) Chl-a anomalies in cyclone (anticyclone) cores. Additionally, the opposite phase can also be attributed to eddy stirring, trapping high and low Chl-a, and/or eddy Ekman pumping. Based on OFES outputs, the seasonal variation of nitrate from winter to summer primarily depends on the effect of vertical mixing, indicating that convective mixing processes contribute to an increase (decrease) in nutrients during winter (summer) over the KE.

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.

The utilization for water resource has been of great concern to human life. To assess the natural water system in Kangding County, the integrated methods of hydrochemcial analysis, multivariate statistics and geochemical modelling were conducted on surface water, groundwater and thermal water samples. Surface water and groundwater were dominated by Ca-HCO₃ type, while thermal water belonged to Ca-HCO₃ and Na-Cl type. The analyzing results concluded the driving factors that affect hydrochemical components. Following the results of the combined assessments, hydrochemcial process was controlled by the dissolution of carbonate and silicate minerals with slight influence from anthropogenic activity. The mixing model of groundwater and thermal water was calculated using silica-enthalpy method, yielding cold-water fraction of 0.56-0.79 and estimated reservoir temperature of 130-199 ^oC, respectively. δD and δ¹⁸O isotopes suggested surface water, groundwater and thermal springs were of meteoric origin. Thermal water should have deep circulation through the Xianshuihe fault zone, while groundwater flows through secondary fractures where it recharges with thermal water. Those analytical results were used to construct a hydrological conceptual model, providing a better understanding of the natural water system in Kangding County.

The theory of electron spin has been proposed for a century, but the study of quantum effects in biological molecules is still in its infancy. Chirality-induced spin selectivity (CISS) is a very modern theory that can explain many biochemical phenomena. In this paper, we propose a new theoretical model based on CISS theory and quantum chemistry theory, which can well explain the theoretical explanation of the chiral selectivity of chiral proteins. Moreover, this theory can predict the spin state of corresponding chiral molecules. Taking L-DOPA and AADC enzyme as examples, this theoretical model solves the theoretical explanation of AADC enzyme's chiral catalysis selectivity problem and successfully predicts the spin state of L-DOPA and D-DOPA's valence electrons.

Renewable energy is essential to environmental sustainability and ranks high among the United Nations strategic goals. In this context, as opposed to conventional biomass gasification, co-gasification emerges as a promising technological pathway to effectively combine the distinct benefits of various gasification feedstocks in order to generate hydrogen-rich syngas. The goal of achieving net-zero emissions has further raised the demand for biomass co-gasification. However, the complicated reactions involved in co-gasification process pose challenge in optimizing the process parameters for increased productivity and performance. To the author’s knowledge, there is no consensus regarding the most suitable machine learning (ML) based regression models for optimizing biomass-plastics co-gasification process, as no prior research has examined the effectiveness of different regression models for this process. Further, the practical application of ML models is adversely affected by their black box nature and lack of interpretability. To address these gaps, the objective of the currect research is two-fold: Firstly, to model the co-gasification process using seven different ML algorithms. Secondly, to develop an evaluation framework and assess model interpretability to select an ideal model for co-gasification interpretation and optimization. The support vector regression(SVR) model demonstrated the most reliable predictive performance. The study employed learning curve analysis and cross validation analysis to substantiate the model predictive performance and exhibit its potential to generalize. Beyond performance analysis, Shapely additive explanation, (SHAP) is first explored in the realm of cogasification to interpret the prediction of the studied models from global and local perspective. The research findings are expected to provide valuable insights to better understand and optimize biomass-plastics cogasification process for H2-rich syngas production.

An outbreak caused by coronavirus disease 2019 (COVID-19) occurred in Wuhan City, Hubei Province, China, in December 2019. Up to March 2, 2020, at least 80180 cases have been reported. Most of the patients had a history of visiting Hubei Province or contacting with people who had ever stayed in or passed by Hubei Province, or exposed to symptoms. Some patients got infected only from asymptomatic contacts. This study aimed to report the epidemic features and lab identification of a patient confirmed with COVID-19 infection only from asymptomatic contact.

Directional modulation (DM), as an emerging promising physical layer security (PLS) technique at the transmitter side with the help of an antenna array, has developed rapidly over decades. In this study, a DM technique using a polarization sensitive array (PSA) to produce the modulation with different polarization states (PSs) at different directions is investigated. A PSA, as a vector sensor, can be employed for more effective DM for an additional degree of freedom (DOF) provided in the polarization domain. The polarization information can be exploited to transmit different data streams simultaneously at the same directions, same frequency, but with different PSs in the desired directions to increase the channel capacity, and with random PSs off the desired directions to enhance PLS. The proposed method has the capability of concurrently projecting independent signals into different specified spatial directions while simultaneously distorting signal constellation in all other directions. The symbol error rate (SER), secrecy rate, and the robustness of the proposed DM scheme are analyzed. Design examples for single- and multi-beam DM systems are also presented. Simulations corroborate that 1) the proposed method is more effective for PLS; 2) the proposed DM scheme is more power-efficient than the traditional artificial noise aided DM schemes; and 3) the channel capacity is significantly improved compared with conventional scalar antenna arrays.

Chitosan (CTS) is widely used in agriculture as a soil amendment, plant growth regulator and promoter of cold resistance. However, the effects of CTS on strawberry seedlings under the combined stress of high-temperature and high-light are unclear. In this study, Xuelixiang strawberry was used as a test material, and 100 mg·kg-1 CTS solution was sprayed onto the leaves. We measured the chlorophyll content, membrane peroxidation, reactive oxygen species content, antioxidant enzyme content, AsA-GSH cycle activity and other related indicators of strawberry seedling leaves under the combined stress of high-temperature and high-light and found that CTS can increase the contents of antioxidants, increase the contents of osmotic adjustment substances, increase the activity of antioxidant enzymes activity,; remove reactive oxygen species over time, reduce the damage of reactive oxygen species to photosynthetic organs and cell membranes, and improve the photosynthesis efficiency of leaves of strawberry plants under high-temperature and high-light stress, thereby reducing damage to strawberry seedlings caused by high-temperature and high-light.

Magnesium (Mg) alloy is a widely used lightweight metal structural material due to its high specific strength and stiffness, excellent damping performance, and recyclability. Wrought Mg alloys are widely favored in fields such as aerospace, transportation, and biomedical stents. However, most wrought Mg alloys with a hexagonal close-packed (HCP) crystal structure lack sufficient independent slip systems to meet the von Mises criterion for uniform plastic deformation at room temperature. This can result in the formation of strong basal texture during plastic deformation and poor room temperature plastic forming ability. Improving the room temperature forming performance is a crucial challenge that must be addressed to broaden the application of Mg alloy sheets. Our research group has comprehensively summarized significant work and latest research progress in improving the room temperature forming of Mg alloy sheets via extrusion technology in recent years. Specifically, we have developed a new type of asymmetric extrusion technology that combines material structure evolution, mechanical property, and forming behavior analysis. We have elucidated the extrusion process characteristics, texture control mechanism, and forming properties of Mg alloy sheets through plastic deformation mechanisms, mold design, and finite element numerical simulation. Our findings provide a novel extrusion technology for the fabrication of highly formable Mg alloy sheets, which can be utilized in various applications.

The effects of exogenous inorganic [i.e., nitrate (NO3-)/ammonium (NH4+)] and organic [i.e., glutamate (Glu)/argine (Arg)] N alone and in combination on the accumulation of proline (Pro) in rice plant under trivalent chromium [Cr(III)] stress were studied through the mass balance matrix model (MBMM). ‘NH4+’ application showed the largest contribution to the Pro content in rice shoots under different concentrations of Cr(III), followed by ‘NO3-’, ‘Arg’, and ‘Glu’ application respectively. While, ‘Arg’ application displayed the largest contribution to the Pro content in roots under Cr(III) stress, followed by ‘NH4+’, ‘Glu’, and ‘NO3-’ application. Among the combination cases of N sources used, the application of ‘NH4++Arg’ showed the greatest contribution to the Pro content in both roots and shoots of Cr(III)-treated rice seedlings, while the application of ‘NO3-+Glu’ showed the least contribution to the Pro content in rice seedlings under Cr(III) stress. Results from this study indicated that the level of indigenous Pro in rice seedlings is quite sensitive to Cr(III) stress under different N sources, and mathematical modeling showed a reliable result to estimate the relationship between Pro content and N source application in rice plants in response to Cr(III) exposure .

Studies report variable effects of sex hormones on serious diseases. Severe disease and mortality rates in COVID-19 show marked gender differences that may be related to sex hormones. Sex hormones regulate the expression of the viral receptors ACE2 and TMPRSS2, which affect the extent of viral infection and consequently cause variable outcomes. In addition, sex hormones have complex regulatory mechanisms that affect the immune response to viruses. These hormones also affect metabolism through obesity, and severe disease can result from complications such as thrombosis. This review presents the latest research on the regulatory functions of hormones in viral receptors, immune responses, complications as well as their role in COVID-19 progression. It also discusses the therapeutical possibilities of these hormones by reviewing the recent findings of clinical and assay studies.

Goldenhar Syndrome (GS), also known as oculoauriculovertebral spectrum (OVAS), is a rare congenital condition characterized by impaired development of structures such as ears, eyes, nose, palate, lip, mandible, maxilla, and teeth. The etiopathogenesis is multifactorial and dependent on genetic and environmental factors, yet the syndrome has many unknowns. We report a case of a 31-year-old male diagnosed clinically with GS as an infant with an absent left ear, hearing loss, absent left lung lobe, reduced growth of left upper limb, decreased size of left face, absent left kidney, and a missing left thumb, who was seen in the genetic clinic for prenatal genetic counseling. A microarray comparative genome hybridization (aCGH) was performed for copy number abnormalities and targeted NGS panels were performed for hereditary hearing loss and limb/digital malformations. aCGH revealed a 471kb loss at 16p12.2 and a mosaic 7.3Mb gain at 19p12q12. Metaphase FISH confirmed the orientation of 19p12q12 gain as small supernumerary ring chromosome 19. NGS revealed multiple variants (MYH14 c.4001C&gt;T, PDE1C c.8C&gt;T, ADGRV1 c.15502A&gt;G, CDH23 c.8772C&gt;A, MYO3A c.484G&gt;A, ADAMTS10 c.506G&gt;A, CHUK c.1294C&gt;T, CSPP1 c.1972A&gt;G, and TCTN2 c.160G&gt;A). Due to the heterogeneous clinical manifestation and genetic heterogeneity of GS, a comprehensive genetic testing strategy is needed for timely diagnosis and better patient care.

Dual generalized commutative quaternions have broad application prospects in many fields. Additionally, the matrix equation AXB = C has important applications in mathematics and engineering, especially in control systems, economics, computer science, and other disciplines. However, research on the matrix equation AXB = C over the dual generalized commutative quaternions remains relatively insufficient. In this paper, we derive the necessary and sufficient conditions for the solvability of the dual generalized commutative quaternion matrix equation AXB = C. Furthermore, we provide the general solution expression for this matrix equation, when it is solvable. Finally, a numerical algorithm and an example are provided to confirm the reliability of the main conclusions.

TiO2-based building materials have air purification, auto-cleaning and sterilization functions, and these innovative green building materials have great potential for energy-saving and emission reduction applications in the future. However, there are still great challenges in improving photocatalytic efficiency and stability from laboratory to practical applications. In recent years, researchers have done a lot of work to improve the efficiency and stability of TiO2-based building materials. This paper briefly discussed the air purification principle by photocatalytic building, and the preparation techniques of TiO2-based building materials and the strategies to improve the efficiency of TiO2. Moreover, this paper has outlined the key factors that affect the photocatalytic building performance in practical applications, and analyzed the limitations and future development trends. Finally, we proposed some suggestions for further research on photocatalytic buildings and its application in practice, aiming to provide an efficient reference for developing highly efficient and stable photocatalytic building materials. The aim of this paper is to provide effective guidance for the application of TiO2-based photo-catalysts in the field of green buildings, helping to develop more efficient and stable low-carbon buildings for the development of sustainable cities.

In tobacco plants, symbiont endophytic fungi are widely distributed in all tissues where they play important roles. It is therefore important to determine the species distribution and characteristics of endophytic fungi in tobacco. Here, two parasitic fungi Leptosphaerulina chartarum and Curvularia trifolii were isolated and identified from normal tobacco tissue. We sequenced the mitogenomes of these two species and analysed their features, gene content, and evolutionary histories. The L. chartarum and C. trifolii mitochondrial genomes were 68,926 bp and 59,100 bp long circular molecules with average GC contents of 28.60% and 29.31%, respectively. The L. chartarum mitogenome contained 36 protein coding genes, 26 tRNA genes, and 2 rRNA genes (rrnL and rrnS), which were located on both strands. The C. trifolii mitogenome contained 26 protein coding genes, 29 tRNA genes, and 2 rRNA genes (rrnL and rrnS). The L. chartarum 26 tRNAs ranged from 70 bp to 84 bp in length, whereas the 29 tRNAs in C. trifolii ranged from 71 bp to 85 bp. L. chartarum and C. trifolii mtDNAs had an identical mitochondrial gene order and orientation and were phylogenetically identified as sisters. These data therefore provide an understanding of the gene content and evolutionary history of species within Pleosporales.

Understanding maturation stress and wood properties of poplar tension wood are critical for improving lumber yields and utilization ratio. In this study, Released Longitudinal Maturation Strains (RLMS), anatomical features, physical and mechanical properties, and nano-mechanical properties of the cell wall were analyzed at different peripheral positions and heights in nine inclined, 12-year-old poplar (Populus×euramericana ‘Zhonglin46’) trees. The correlations between RLMS and wood properties were determined. The results showed that there were mixed effects of artificial inclination on wood quality and properties. The upper sides of inclined stems had higher RLMS, proportion of G-layer, bending modulus of elasticity, and elastic modulus of cell wall but lower microfibril angle than the lower sides. At heights between 0.7 m and 2.2 m, only the double wall thickness increased with height, RLMS and other wood properties such as fiber length and basic density fluctuated or changed little with height. RLMS was a good indicator of wood properties in the tension wood area and at heights between 0.7 m and 1.5 m. The results of this study present opportunities to identify and select better quality wood in poplar trees.

Based on the daily observation data of 2254 meteorological stations in China from 1961 to 2021 after homogenization and correction, the extreme value analysis method that combines relative threshold and absolute threshold was used to identify extreme climate events in the mainland of China, namely extreme high temperature, extreme low temperature, extreme drought, extreme precipitation and extreme typhoon events. The frequency and linear variation trends of individual extreme events in the past 60 years were investigated. On this basis, the multi extreme events composite risk grade index (MXCI) was constructed, which can objectively reflect the comprehensive characteristics of multi extreme climate events in different regions. The results show that the high value areas of MXCI were mainly located in Southeast China and Southwest China. The MXCI presented a decreasing trend in most of the western and southeastern regions of China, while an increasing trend from Southwest China to the south of Northeast China, due to the frequent occurrence of extreme high temperature, extreme drought and other extreme events in these regions.

In this study, the team employed full-scale crash tests to investigate the impact of post-densification technology on the safety performance of separated central median W-beam barriers under low compaction conditions. By precisely simulating the design and construction environment of the central median, the study comprehensively evaluated the barrier's containment, redirection, buffering, and anti-intrusion performances, as well as the deformation of both the barrier and vehicles under various collision scenarios. The results indicate that under low compaction soil conditions, the A-level separated central median barriers reinforced with post-densification technology effectively meet the specified protection requirements. By comparing the influence of soil strength variations on barrier performance under simulated rainfall conditions, it was confirmed that enhancing soil compaction significantly improves soil stability, effectively increases the overall strength and stability of the barriers, reduces deformation, and significantly enhances safety performance. This study not only validates the effectiveness of the reinforcement scheme but also provides new perspectives for the scientific research of safety barriers and offers crucial technical support for the optimal design of road safety protection facilities.

In this study, we aim to evaluate how cyclodextrin molecules affect the hydrophilicity and selec-tivity of PVDF membrane. Herein, we prepared PVDF-PVP(1-x) β-CDx membranes, with x rang-ing from 0 to 1 wt%. The membranes were deeply characterized by means of X-ray diffraction (XRD), attenuated total reflectance infrared (ATR-IR), Raman spectroscopies, Thermal gravimet-ric analysis (TGA), Contact angle measurement (CA), scanning electron microscopy (SEM) and atomic force microscopy (AFM). The study unequivocally demonstrates the effectiveness of the addition of β-CD molecules on membranes' structural, morphological, and dielectric properties. Adding 0.25wt% β-CD enhanced hydrophilicity, with CA decreasing from 72.6° to 56° and roughness decreasing from 81 to 29 nm. The PVDF-PVP(1-x) β-CDx membranes were then fully characterized using electrochemical impedance spectroscopy (EIS) to determine their dielectric properties, which clearly showed that the presence of β-CD induced polarization of the mem-brane. The separation of various dyes with different sizes and charges was utilized. These dyes included methylene blue (MB, positive, 0.504 nm), methyl red (MR, neutral, 0.487 nm), rose Bengal (RB, negative, 0.588 nm), and brilliant blue (BB, negative, 0.798 nm). Based on our re-search, we found that the membrane's selectivity is determined by both exclusion factors (such as size and dielectric properties) and inclusion inside the β-CD cage. We found that using alpha-CD instead of beta-CD led to the disappearance of dye inclusion. These findings strongly sug-gest that β-CD molecules can be a viable solution for dye removal from wastewater.

Marine soft corals are prolific sources of various natural products that have served as a wealthy reservoir of diverse chemical scaffolds for new drug leads. The genus Litophyton contains almost 100 species but only a small part of them had been classified and chemically investigated, which calls for more attentions from the global researchers. In the current work, 109 secondary metabolites have been discussed based on published data from 1975 to July, 2023, covering a period of near five decades. The studied species of the genus Litophyton inhabited various tropical and temperate regions and afforded a variety of biologically active natural products such as terpenes, steroids, alkaloids, and lipids. A wide spectrum of pharmacological effects of these compounds had been evaluated, including cytotoxic, anti-HIV, antibacterial, antifungal, anti-malarial, antifeedant, molluscicidal, PTP1B inhibitory, and insect growth inhibitory activities. This review aims to provide an up-to-date literature survey and comprehensive insight into chemical structures, taxonomical distributions, and biological activities of the reported metabolites from the title genus whenever available.

Simple summary: The noninvasive differentiation of hepatocellular carcinoma (HCC) from intrahepatic cholangiocarcinoma (ICC) remains challenging. In recent years, the number of studies on the application of radiomics in liver cancer has grown dramatically. However, there have been very few studies on the differentiation of HCC from ICC based on multisequence magnetic resonance imaging (MRI) radiomics. This study aimed to investigate the efficacy of a radiomic model based on preoperative fat suppression T2-weighted imaging (FS-T2WI) and dynamic contrast-enhanced MRI features in the arterial phase (A) and portal venous phase (P) for the differentiation of HCC from ICC. Abstract: The purpose of this study was to investigate the efficacy of magnetic resonance imaging (MRI) radiomics in differentiating hepatocellular carcinoma (HCC) from intrahepatic cholangiocarcinoma (ICC). The clinical and MRI data of 129 pathologically confirmed HCC cases and 48 ICC cases from April 2016 to December 2021 at the Affiliated Hospital of North Sichuan Medical College were retrospectively analyzed. Included cases were randomly divided at a ratio of 7:3 into a training group of 124 cases (90 HCC cases and 34 ICC cases) and a validation group of 53 cases (39 HCC cases and 14 ICC cases). Radiomic features were extracted from axial fat-suppression T2-weighted imaging (FS-T2WI) and axial arterial-phase (A) and portal-venous-phase (P) dynamic contrast-enhanced MRI sequences, and the corresponding datasets were generated. The least absolute shrinkage and selection operator (LASSO) method was used to select the best radiomic features. Logistic regression was used to establish a radiomic model for each sequence (FS-T2WI, A, and P models) and a joint model (M model) integrating the radiomic features of all the sequences. The performance of each model was evaluated using the area under the receiver operating characteristic curve (AUC). The AUC of the FS-T2WI, A, P, and M models for distinguishing HCC from ICC was 0.693, 0.863, 0.818, and 0.914 in the training group and 0.690, 0.784, 0.727, and 0.802 in the validation group, respectively. The results of this study suggest that MRI-based radiomics may help noninvasively differentiate HCC from ICC. The model integrating the radiomic features of multiple sequences showed further improvement in performance.

The three-phase separator was perforated after four years’ service. The perforation position is at the bottom of the vessel under the baffle plate in an oil transfer station. The cause of perforation was investigated by chemical analysis using a direct-reading spectrometer, microstructure examined by optical microscope(OM), and lab simulated corrosion experiments by electrochemical workstation, and the corrosion products examined with scanning electron microscopy(SEM), energy dispersive spectrometer(EDS) in this paper. The analyses indicated that the coating at the base of the pressure vessel failed and this led to the direct exposure of the carbon steel plate to the corrosive medium. The electrical contact between the carbon steel and the stainless steel, sets up a galvanic cell that accelerated the corrosion of the pressure vessel which eventually led leads to the perforation.

The centrifugal force field in the hydrocyclone was affected by the concave-wall curvature radius R0, the mechanism of droplet deformation was closely related to the mass transfer efficiency. Numerical simulation and experimental data were collected to reveal the deformation characteristics and mechanism of single droplet crossing concave-wall jet. Normalized interfacial energy γ and stretching performance were provided to investigate the droplet deformation process. The results showed that the droplet was stretched along the streamwise and shrank along the spanwise in the concave-wall jet. The droplet interfacial energy and deformation were the largest when the droplet crossed the jet boundary at t = 0.20 s. Maximum γ value increased with the increase of R0 by 57.3% to 71.4%, and the distance between droplet and concave-wall increased with R0. Q-criterion was exported to show the vortex strength increasing as the decrease of R0 in the jet boundary. The pressure distribution inside the droplet showed that the pressure decreased as R0 increased, while the pressure difference increased along the streamwise and wall-normal direction. The study suggested that the droplet breakup was more difficult for the smaller R0, which was beneficial for liquid-liquid heterogeneous separation.

Indoor positioning based on the received signal strength (RSS) of the WiFi signal has become the most popular solution for indoor localization. In order to realize the rapid deployment of indoor localization systems, solutions based on crowdsourcing have been proposed. However, compared to conventional methods, crowdsourced RSS values are more erroneous and can result in large localization errors. To mitigate the negative effect of the erroneous measurements, a graph-based semi-supervised learning (G-SSL) method is used to exploit the correlation between the RSS values at nearby locations to estimate an optimal RSS value at each location. Before using the G-SSL method, the Linear Regression (LR) algorithm is proposed to solve the device diversity problem in crowdsourcing system. Since the spatial distribution of the APs is sparse, the Compressed Sensing (CS) method is applied to precisely estimate the location of the APs. Based on the location of the APs and a simple signal propagation model, the RSS difference between different locations is calculated and used as an additional constraint to improve the performance of G-SSL. Furthermore, to exploit the sparsity of the weights used in the G-SSL, we use the CS method to reconstruct these weights more accurately and make a further improvement on the performance of the G-SSL. Experimental results show improved results in terms of the smoothness of the radio map and the localization accuracy.

Water area segmentation in remote sensing is of great importance for flood monitoring. To overcome some challenges in this task, we construct the Water Index and Polarization Information (WIPI) multi-modality dataset and propose a multi-Modality Fusion and Gated multi-Filter U-Net (MFGF-UNet) convolutional neural network. The WIPI dataset enhances the water information and reduces the data dimension. In particular, the Cloud-Free label provided in the database effectively mitigates the issue of scarcity of labeled samples Since a single form or uniform kernel size cannot handle the variety in size and shape of water bodies, we proposed the gated multi-filter inception (GMF-Inception) module in our MFGF-UNet. Moreover, we utilize the attention mechanism by introducing the Gated Channel Transform (GCT) skip connection and integrating GCT into GMF- Inception to further improve model performance. Extensive experiments on three benchmarks, including WIPI, Chengdu and GF2020 datasets demonstrate that our method achieves favorable performance with lower complexity and better robustness against six competing approaches. For example, on WIPI, Chengdu and GF2020 datasets, the proposed MFGF-UNet model achieves F1 of 0.9191, 0.7410, and 0.8421, respectively, which average F1 on three datasets is 0.0045 higher than the U-Net model and reduces 62% average GFLOPs. New WIPI dataset, code and trained models have been released on GitHub

Fringe projection profilometry(FPP) has been extensively applied in various fields for its superior fast speed, high accuracy and high data density. However, measuring some objects with high reflective surfaces or high dynamic range surfaces remains challenging for FPP. Some multiple exposure image fusion methods have been proposed and successfully improved the measurement performance for these kinds of objects. Normally, these methods have a relatively fixed sequence of exposure settings determined by artificial experience or trial and error experiments, which may decrease the efficiency of the entire measurement process and may have less robustness to various environmental lighting conditions and object reflective properties. In this paper, a novel self-adaptive multiple exposure image fusion method is proposed with two main aspects of improvement on adaptively optimizing the initial exposure and the exposure sequence. By introducing the theory of information entropy, combined with the analysis of the characterization of fringe image entropy, an adaptive initial exposure searching method is first proposed. Then, an exposure sequence generation method based on dichotomy is further described. On the base of these two improvements, a novel self-adaptive multiple exposure image fusion method for FPP as well as its detailed procedures are given. Experimental results validate the performance of the proposed self-adaptivity multiple exposure image fusion method by measuring the objects with different surface reflectivity and in different ambient lighting conditions.

Thorium (Th) is a natural radioactive element present in the environment and has a potential to be used as a nuclear fuel. Relatively little is known about the influence and toxicity of Th in the environment. In the present study, the toxicity of Th to the green algae Chlorella pyrenoidosa (C. Pyrenoidosa) was evaluated by algal growth inhibition, biochemical assays and morphologic observations. In the cultural medium (OECD TG 201), Th(NO₃)₄ was transformed to amorphous precipitation of Th(OH)₄ due to hydrolysis. Th was toxic to C. Pyrenoidosa, with a 96 h half maximum effective concentration (EC₅₀) of 10.4 μM. Scanning electron microscopy shows that Th-containing aggregates were attached onto the surface of the algal cells, and transmission electron microscopy indicates the internalization of nano-sized Th precipitates and ultrastructural alterations of the algal cells. The heteroagglomeration between Th(OH)₄ precipitation and alga cells and enhanced oxidative stress might play important roles in the toxicity of Th. To our knowledge, this is the first report of the toxicity of Th to algae with its chemical species in the exposure medium. This finding provides useful information on understanding the fate and toxicity of Th in the aquatic environment.

The majority of existing numerical simulations of the effect of bridge piers on water movement are based on a limited number of bridge piers at a laboratory scale. Furthermore, some 2D numerical simulations for actual bridge projects have deficiencies, including the use of overly large mesh sizes and an inadequate treatment of bridge piers. In this study, we compare three methods of structural mesh encryption, suspension mesh, and nonstructural mesh based on Delft3D, and apply the optimization scheme to a real bridge project. It is demonstrated that optimal results can be achieved by utilising a grid size comparable to the pier diameter (Dp) in the region away from the piers. In the vicinity of the piers, the grid cell size should be no larger than 1/9 Dp. The suspended grid technique (DD Boundary) can yield results consistent with those obtained using a full-area high-resolution grid, provided that the total number of grids can be reduced and the computational time is considerably reduced. In this study, the unstructured mesh (Deflt3D Flexible Mesh) scheme was unable to capture the oscillations of the wake flow behind the bridge piers. However, the application of the optimized scheme in bridge engineering has demonstrated its practical value. The findings of this study on mesh resolution and suspension mesh scheme can be applied to the Delft3D software and are also useful for other numerical simulation work.

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.

Safety of source water streams is an urgent environmental issue, while protections in monsoon controlled subtropical regions face difficulties because of the lack of small scaled observation and analysis in small source water catchments. Basing on continuous weekly water quality data (2014-2017) in Pingqiao River Catchment, the annual average values of TN, NO₃, NH₄ and TP are 3.36, 1.64, 0.28 and 0.02 (mg/L) respectively. During dry, normal and wet seasons, the variability of parameters is over 35%, which indicates an obvious seasonality. Multiple methods are combined in order to assess the water quality and find the driving factors during dry, normal and wet seasons. This study suggests precipitation and fertilization are the mainly seasonal factors, which can make water quality better in wet season than dry season due to the dilution effect. The mechanism between seasonality and compound of nutrients can also be traced by log(TN:TP), and log(NO₃:NH₄). Among six main land use types (forest, tea plantation, cropland (paddy), urban, bare soil and water), the former three ones are influential mostly during dry and wet season. Tea plantation has the largest nutrients discharge amount per area, which is similar to cropland in dry season. By contrary, forest has the double power in reducing nitrogen release in wet and normal seasons. When transformed into paddies, croplands can lower the phosphorus concentration. Conclusions of this study can be used in southeastern China and similar regions on source water protection and agricultural plans.

Vibrio parahaemolyticus is an important foodborne bacterium that causes severe gastroenteritis following the consumption of contaminated seafood. To identify V. parahaemolyticus and determine its pathogenicity, the U.S. Food and Drug Administration (FDA)’s Bacteriological Analytical Manual (BAM) recommends a multiplex polymerase chain reaction (PCR) protocol to simultaneously detect the species-specific thermolabile hemolysin (tlh) gene and the pathogenic thermostable-related hemolysin (trh) and thermostable-direct hemolysin (tdh) genes. However, this assay has shown two limitations: difficulty in separating the amplicons of the trh (486 bp) and tlh (450 bp) genes due to their similar sizes, and the weaker band exhibited by the tdh gene amplicon (270 bp). The present study aimed to improve the BAM’s multiplex PCR assay by separating the three amplicons with similar intensity. A new primer set was applied for the tlh gene (369 bp) alongside the existing primers for the trh and tdh genes. The amplicons for the three genes were effectively separated by electrophoresis on a 2% tris-borate-EDTA (TBE) agarose gel within 45 minutes. Primer concentrations of 0.2 µM for trh, 0.2 µM for tlh, and 0.4 µM for tdh produced a significant amount of amplicons among various combinations of primer concentrations with 35 PCR cycles (P &lt; 0.05). This assay exhibited a detection limit of 10 pg of bacterial DNA, demonstrating its high sensitivity. It did not display amplicons from nine Vibrio strains known to be human pathogens or from 18 well-documented foodborne pathogens. Therefore, the present multiplex PCR protocol could help overcome the limitations of existing assays and provide a more reliable method for detecting the three genes of V. parahaemolyticus.

The soil microbial community serves as a crucial indicator for assessing soil fertility and health. The composition and activity of soil microorganisms reflect the soil's well-being and its ability to provide proper nutrients for crops. Fertilization plays a prominent role in enhancing soil fertility, and novel types of fertilizers, such as stabilized fertilizers with nitrification/urease inhibitors and coated fertilizers, have gained popularity in rice and maize cultivation. However, the long-term effects of these stabilized and coated urea fertilizers on soil chemical properties, microbial di-versity and community structure, as well as nitrogen cycling functional genes, remain unclear. Therefore, it is essential to investigate the impact of extended use of stabilized and coated urea fertilizers on soil fertility and microbiota in rice paddy fields. This research will provide scientific and theoretical support for the development and promotion of stabilized and coated urea ferti-lizers. To examine the effects of long-term application of these stabilized and coated urea fertilizers on soil chemical properties and microorganisms in rice paddy fields, soil samples were collected from brown soil rice paddy fields treated with various urease and nitrification inhibitors, stable urea, sulfur-coated urea (SCU), and resin-coated urea (PCU). The study revealed that 16 years of long-term use of conventional urea nitrogen fertilizer led to a considerable reduction in soil TP. On the other hand, NBPT and conventional urea fertilizers, when applied for an extended period, significantly increased soil organic matter (SOM). Moreover, except for HQ and NBPT+DMPP, the prolonged application of new urea fertilizers also signifi-cantly enhanced soil total potassium (TK). Notably, among all the treatments, PCU treatment had higher values for various soil chemical properties. In the case of SCU fertilizer used in brown soil rice paddy fields, it resulted in a significant decrease in soil pH over time. However, this change in pH did not affect the population of ammonia-oxidizing bacteria (AOB), as it was primarily in-fluenced by soil available nitrogen. DMPP, HQ+DCD, NBPT+DMPP, SCU, and PCU significantly reduced the copy number of bacterial 16S rRNA genes in the soil, with the coated urea fertilizers (SCU and PCU) having a greater impact. The long-term use of stabilized urea fertilizers containing HQ significantly reduced the bacterial community in rice paddy soil. Conversely, HQ+DCD stable urea fertilizer significantly increased the population structure and abundance of Basidiomycota fungi while decreasing the population structure and abundance of Rozellomycota fungi. DMPP stabilized urea fertilizer notably increased the population structure and abundance of Ascomycota fungi while decreasing the population structure and abundance of Rozellmycota and Chytridiomycota fungi. Further-more, HQ stabilized urea fertilizer significantly reduced the population structure and abundance of Chytridiomycota fungi. It is important to note that SCU fertilizer is not suitable for long-term application in neutral to slightly acidic meadow brown soil with a background pH. On the other hand, stable urea fertilizers and resin-coated urea fertilizers containing HQ, NBPT, DCD, DMPP, and their combinations are suitable for long-term application in neutral to slightly acidic meadow brown soil.

Abstract: High power semiconductor laser is a kind of photoelectric device with high efficiency and high stability, the performance of its drive system directly affects its output characteristics and service life. In order to solve the problems of stability and robustness of the output power of semiconductor laser, a semiconductor laser driving power supply with high efficiency, low ripple and strong anti-interference ability was developed. The power supply adopts full-bridge LCC resonant power topology. Firstly, a mathematical model is established to analyze the relationship between LCC resonator parameters and output current gain. Secondly, a LCC resonator parameter design method is proposed to reduce the current stress of components, and the variable frequency phase shift (PFM-PWM) composite control strategy and linear active disturbance rejection control (LADRC) algorithm are proposed, which not only ensures the zero voltage (ZVS) conduction of MOS tube, but also reduces the on-off loss of MOS tube. Improved power efficiency and suppressed output current ripple; At the same time, the instability of the output current is ensured due to the input voltage, load and parasitic parameter change of the circuit. Finally, the simulation and experimental results show that the power supply can be continuously adjustable in the output current range of 0-40A, the current ripple is less than 0.8%, and the working efficiency is up to 92%. It has the characteristics of high stability, small ripple, high efficiency, low cost and good robustness.