In the future, the power of commercial ocean current generators can reach MW level, and the corresponding mooring rope tension is very great. But the power of the ocean current generator in research stage is KW level and it can bear less rope tension. Its main mooring rope adopts a single cable and a single foundation. This paper studies the dynamic response and rope tension of the MW-level ocean current generator mooring system. It is assumed that the commercial MW-level ocean current generator is similar to the research-type KW level, and the similarity law and several dimensionless similar parameters are proposed, including for the turbine and platform the power number, tip speed ratio, hydrodynamic damping and stiffness coefficient and others. Based on these dimensionless similar formula and the known parameters of the researched KW-level convertor, all parameters of the MW-level ocean current generator are derived. In order to overcome the extreme tension of a MW-level mooring system and provide good stability, this paper proposes the pulley-traction rope design to replace the traditional single traction rope design. The static and dynamic mathematical models of this mooring system subjected to typhoon wave impact and current are proposed and analytical solutions are obtained. The study found that the dynamic rope tension of the MW-level system with the traditional single rope system is significantly greater than its fracture strength and the dynamic tension of the pulley- traction rope system. It means that this design can effectively reduce the dynamic rope tensions of the mooring system. Moreover, if the length ratio of rope A to the seabed depth is within a safe range, the maximum rope dynamic tension will be less than the fracture strength. In addition to the MW level, the dynamic response of the 700kW level power generation system under the action of typhoon waves is also studied. It is discovered that the dynamic tension of rope D is the largest. In addition, the dynamic tension of rope D for 700kW system will exceed the original strength of design. However, only the specification of rope D is increased, the new dynamic tension is still close to the original such that the dynamic tension of rope D is significantly less than the adjusted fracture strength and the mooring system becomes safety.

To investigate the effect of montmorillonite on nonylphenol enrichment in a zebrafish model. The AB strain zebrafish were used as the animal subjects and three concentration gradients were set for both nonylphenol and montmorillonite, according to their actual concentrations in aquaculture water in Huzhou city. A group treated with nonylphenol alone was also set, adding up to 12 experimental groups. Concentrations of nonylphenol enriched in the liver, muscle, and gill of zebrafish were detected by solid phase microextraction–high performance liquid chromatography at Day 7, 15, and 30, respectively. Besides, the relative enzymatic activity of Superoxide dismutase (SOD) and the Glutathione S-transferase (GST) were also been detected, and the data were statistically analyzed. The results showed that the concentrations of nonylphenol in zebrafish peaked at Day 7 and gradually decreased afterwards for all the experimental groups. And the montmorillonite reduces short-term accumulation of nonylphenol in gills, and the high concentration of nonylphenol facilitates its enrichment in liver and muscle while the low concentration of nonylphenol doesn’t. Meanwhile, the low concentration of nonylphenol in liver exerts an influence on the inductive effect of SOD and GST while the high concentration of nonylphenol shows the inhibiting effect of SOD and GST.

The fast decoding of low-density parity-check (LDPC) is crucial for its future applications. In this paper, we propose to use Early Termination (ET) and Force Convergence (FC) techniques to accelerate the decoding of two new local/global two-phases decoding algorithms to reduce the Globally Coupled (GC) LDPC codes. Specifically, ET is applied in the local decoding phase of two- phases decoding of GC-LDPC codes to skip the local decoding which is highly likely to fail and avoid the unnecessary iterations. FC is applied in global decoding phase where converged variable nodes are identified and removed from Tanner graph and the decoding can be speed up shrinking parity check matrices. Two variants are proposed for the ET operation in local decoding phase. ET-1 merely stops iteration if it meets the stopping criterion while in ET-1, the iteration number saved in local decoding is added up in global decoding to improve the decoding performance. The simulation results show that the ET-1-FC scheme can save up to 42% decoding time complexity in the low SNR region while keeping the error rate performance nearly unchanged, the ET-2-FC can improve the error rate performance by 0.18dB at bit error rate 0.001 or 0.23dB at frame error rate 0.1. In the waterfalling region of BER/FER curves, both schemes can save about 25% decoding time complexity.

The shear stress generated by wall turbulence is the main cause of wall friction resistance in turbulent flow through pipes. This paper investigates the impact of inserting rest periods (regions of constant Reynolds number) within the pulsating operating cycle of velocity on the fully turbulent flow at large time-averaged Reynolds numbers, using the Large Eddy Simulation (LES) method. The study aims to explore the effect of increasing rest periods within pulsations on drag resistance. The dimensionless shear stress and drag reduction rates during different time periods of rest were analyzed. Numerical simulation results indicate that the pulsating velocity operation mode does not necessarily lead to drag reduction; it may even result in increased resistance. Inserting rest periods within the pulsation cycle can achieve drag reduction effects, with the maximum drag reduction rate reaching 21.8\%. Comparisons with experimental data and Direct Numerical Simulation (DNS) from the literature validate the feasibility of using the LES method for pipe pulsating operation modes.

We report a prebiotically relevant solution to the N1-ribosylation of pyrimidine nucleobases, a well-known challenge in the RNA World hypothesis. It is found that the presence of metal cations and clay mineral enables the previously unachievable direct ribosylation of uracil, providing by far the highest yield. Spectroscopy and chromatography analyses confirmed the formation of ribosylated uracil. The method can also be extended to the ribosylation of 2-pyrimidinone. These findings are also compatible with the metal-doped-clay model developed by our lab for the unified route of the selection of ribose and subsequent syntheses of nucleotide and RNA.

This paper uses panel data to find the determinants of tracking errors in exchange traded funds (ETFs) in the Hong Kong stock market. A comparison of tracking errors between physical and synthetic ETFs also indicates that the synthetic ETFs have higher tracking errors. The magnitude of tracking errors is found to be negatively related to size but positively related to dividend yield, trading volumes of funds, and market risk. However, this study also finds that expense ratio has a negative impact on tracking error, which is not consistent with previous studies, and which this paper addresses.

Real estate has the dual characteristics of consumption and investment. Under the inherent concept of "where there is land, there is wealth", real estate has become the investment target of the main asset. In addition to the supply and demand of the market will affect the price of real estate, many general economic factors will also have a certain impact on the price of real estate. This paper pays a special focus on the effects of MRT on housing prices, finding the closer a house is to an MRT station, the higher its price. In addition, convenience stores are very popularized, and this research report is also interested in whether the number of convenience stores within walking distance will affect the house price. In a word, these two factors do affect housing prices significantly.

Rapeseed (Brassica napus) is one of the most important oil crops in the world; however, drought significantly curtails its growth and productivity. Identifying drought-tolerant germplasm is an efficient and low-cost strategy for addressing water shortages. Using water loss ratio (WLR) as an index of drought tolerance, we screened a panel of 265 B. napus lines. We identified eight low-WLR and six high-WLR accessions, which were regarded as drought-tolerant and drought-sensitive, respectively. Further validated these selected accessions at the seedling stage under drought-stress conditions. The drought-tolerant accessions had significantly greater fresh and dry weights under drought stress than the drought sensitive accessions. Using RT-qPCR, we showed that a set of previously reported drought-adaptive marker genes were expressed at higher levels in the drought-tolerant lines than in the drought-sensitive lines. These results indicated that the drought-tolerant genotypes could be identified from natural populations using WLR. Then, we performed a genome-wide association study to identify loci harboring single nucleotide polymorphisms (SNPs). A total of 139 SNPs were significantly associated with the WLR, of which chromosome A10 harbored the largest number. Furthermore, four putative candidate genes were selected by combining the SNP–WLR association results and transcriptional expression data with the changes in drought tolerance. Thus, we have identified two drought-tolerant B. napus cultivars and uncovered genome-wide variation differentiating B. napus lines related to WLR, in addition to providing insights for further research into WLR-related drought mechanisms.

This paper discusses a significant public-private partnership (PPP) formed by the government and Taiwanese Farmer Associations. Particularly, it will investigate a pattern of the PPP that has successfully promoted rural development and agricultural modernization in Taiwan since 1950s. Taiwanese Farmer Associations (hereafter TFAs), similar to agricultural cooperatives in South Korea and Japan, have played a policy agent in fostering rural development in this island state since 1950s. TFA’s performance inherently came from Japanese Cooperatives before World War II. The Performances of those farmer organizations are combinations of economic, social, and educational synergies. The rural development experiences in Taiwan demonstrate that success of rural modernization is carried out by a special public-private partnership (PPP). First, this paper discusses formation and development of farmer cooperative organizations in East Asian societies and compare the similarities and differences of practice of those organizations and their relations to the governments among Taiwan, South Korea, and Japan. Secondly, this paper examines collaborative mold and process in which both the government and Taiwan Farmer Associations have been extensively involved. A specific cooperative apparatus between the government and TFA functioning and operating as a perfect PPP has been formed under administrative guidance of the state. Thirdly, this paper looks at input and various supports in financial and policy perspective by the public sector. Fourthly, the paper discusses legal framework, administrative apparatus, and governance pattern for TFA. Fifthly, the paper discuses that a specific PPP successfully involving in rural modernization in Taiwan is significantly derived from the state’ guidance that properly regulates a collaboration between the government and TFA. So-call East Asian model of PPP in agricultural modernization and rural community development may become a valuable experience for most of developing countries.

: In the automotive industry, high-strength plates have been increasingly used to reduce the vehicle body weight due to stringent regulations on fuel economy and safety. Such plates achieve tensile strengths as high as 1.5 GPa owing to the hot-stamping process. However, these plates suffer from scale generation and surface decarburization because of the surface oxidation of the material. Recently, studies on materials subjected to high-frequency induction heating have reported strength improvement owing to the coil shape and cooling method. This study presents the surface temperature changes, mechanical properties, and microstructures of boron steels subjected to longitudinal heating, which uses eddy currents generated from high-frequency induction heating. The surface temperature data were analyzed under different high-frequency induction heating powers (15, 18, 21, 24, 27, and 30 kW) and distances from the specimen (6, 9, and 15 mm). The mechanical properties and microstructures were also analyzed in different high-frequency induction heating coil directions. The correlations between the high-frequency induction heating power and the distance from the specimen with the maximum tensile strength were determined.

Maxwell's equations accurately describe the propagation of electromagnetic (EM) waves. However, the conventional formulation implies invariance to observers, posing challenges in explaining how the wave is perceived by different observers. For example, Doppler effect shows that observers perceive the same EM wave differently.By employing mathematical transformations, we derive a general form of Maxwell’s wave equations by incorporating a "time scaling" factor to account for observer perception. The original form is shown to be a special case when static. The Doppler effect and Sagnac effect are directly derived from Maxwell’s equations. All the results are consistent with established experiments.Our findings offer a fresh perspective, promising a deeper understanding and unification of EM phenomena. We extend Maxwell’s equations to describe not only the propagation of an EM wave, but also how it will be measured by different observers, say, antennas.

Frequently Asked Questions (FAQs) systems rely on semantic symmetry similarity measuring between two sentences. To address the challenges of insufficient training data and limited domain-specific understanding in low-resource FAQs, this paper proposes a general framework, PDAMF-FAQ, to solve these issues. Firstly, we propose a paraphrasing-based data augmentation model that integrates syntactic information and edit vectors. Using a rule-based approach, it retrieves template sentences from a corpus and masks relevant words with special characters. Edit vectors between the original and paraphrase sentences are added to a pre-trained model's encoding layer to enhance the model's ability to learn the differences between the original and reference paraphrase sentences. Additionally, this paper presents a mixed-feature semantic matching model based on SimBERT. The model extracts keyword features from the text, replacing these keywords with special characters to construct intent features. These intent features, along with the user question and keyword features, are then concatenated to form the model's input. Experiments were conducted respectively on the paraphrasing-based data augmentation model, mixed-feature semantic matching model and their comprehensive application in a low-resource domain-specific FAQ. The experimental results show that the proposed framework effectively improve the performance of domain-specific FAQ system.

Hydrothermal carbonization of cellulose was examined at 240 ℃ for 1 h. Ammonium sulfate and thiourea were selected as the doping sources of inorganic nitrogen and organic nitrogen for the preparation of supercapacitor carbon. The effect of boric acid on the properties of the resulting hydrochar after KOH activation was examined. The results showed that the proportion of functional groups and the specific surface area of the activated hydrochar would be reduced after the addition of boric acid, and the pore-forming process of the micropores would be inhibited. The hydrochar obtained from the reaction of cellulose and organic nitrogen compounds had better pore size distribution and electrochemical properties after activation. The largest specific surface area (952.27 m2 g-1) was obtained when only thiourea was used as the only doping source. In the three-electrode system, the specific capacitance resulting activated hydrochar reached 236.25 F g-1 at a current density of 1 A g-1. After 20,000 cycles of charging and discharging at a current density of 10 A g-1, the capacitance retention rate reached 99.96%. Therefore, this study proves that the supercapacitor carbon with good electrochemical properties could be obtained by the direct reaction of cellulose with organic nitrogen compounds.

We explored the dynamics of the two interacting information systems. We show that for the Markovian marginal systems the driving force for information dynamics is determined by both the information landscape and information flux. While the information landscape can be used to construct the driving force to describe the equilibrium time reversible information system dynamics, the information flux can be used to describe the nonequilibrium time-irreversible behaviours of the information system dynamics. The information flux explicitly breaks the detailed balance and is a direct measure of the degree of the nonequilibriumness or time irreversibility. We further demonstrate that the mutual information rate between the two subsystems can be decomposed into the equilibrium time-reversible and nonequilibrium time-irreversible parts respectively. This decomposition of the mutual information rate (MIR) corresponds to the information landscape-flux decomposition explicitly when the two subsystems behave as Markov chains. Finally, we uncover the intimate relationship between the nonequilibrium thermodynamics in terms of the entropy production rates and the time-irreversible part of the mutual information rate. We found that this relationship and MIR decomposition still hold for the more general stationary and ergodic cases. We demonstrate the above features with two examples of the bivariate Markov chains.

It is of great academic significance to understand how the atomic structure of interfaces and boundaries in materials impacts the magnetic coupling nature across the boundaries and encourage development of state-of-the-art magnetic devices. Here, we carry out a systematic investigation of the atomic and electronic structures of twin boundaries (TBs) in LiFe5O8 thin films and determine their concurrent magnetic couplings using atomic-resolution transmission electron microscopy and atomistic first-principles calculations. The results show ferromagnetic or antiferromagnetic coupling can exist across the different TBs in LiFe5O8 (LFO) thin films and electrical structures within a few atomic layers directly rely on the TB atomic core structures. Uncovering one-to-one relationship between the magnetic properties of individual TB and the local atomic structures will clarify a thorough comprehension of numerous fascinating magnetic properties of commonly utilized magnetic materials, which will undoubtedly encourage the progress of sophisticated magnetic materials and devices.

With the advances in industry and commerce, passengers have become more accepting of environmental sustainability issues; thus, more people now choose to travel by bus. Government administration constitutes an important part of bus transportation services as the government gives the right-of-way to transportation companies allowing them to provide services. When these services are of poor quality, passengers may lodge complaints. The increase in consumer awareness and developments in wireless communication technologies have made it possible for passengers to easily and immediately submit complaints about transportation companies to government institutions, which has brought drastic changes to the supply-demand chain comprised of the public sector, transportation companies, and passengers. This study proposed the use of big data analysis technology including systematized case assignment and data visualization to improve management processes in the public sector and optimize customer complaint services. Taichung City, Taiwan was selected as the research area. There, the customer complaint management process in public sector was improved, effectively solving such issues as station-skipping, allowing the public sector to fully grasp the service level of transportation companies, improving the sustainability of bus operations, and supporting the sustainable development of the public sector-transportation company-passenger supply chain.

Shear connectors are used in steel beam–concrete slabs of composite frame and bridge structures to transfer shear force according to design loads. The existing Y-type perfobond rib shear connectors are designed for girder slabs of composite bridges. Therefore, the rib and transverse rebars of the conventional Y-type perfobond rib shear connectors are extremely large for the composite frames of building structures. We performed push-out tests of stubby Y-type perfobond rib shear connectors for composite frames. These shear connectors have relatively small ribs than conventional Y-type perfobond rib shear connectors. To confirm the shear resistance of these stubby shear connectors, we performed an experiment by using transverse rebars D13 and D16. The results indicate that these shear connectors have suitable shear strength and ductility for application in composite frame structures. The shear strengths obtained using D13 and D16 were not significantly different. However, the ductility of the shear connectors with D16 was 45.1% higher than that of the shear connectors with D13.

The role of land surface temperature (LST) is of utmost importance in multiple academic disciplines such as climatology, hydrology, ecology, and meteorology. Until to now, many methods have been proposed to estimate LST from satellite thermal infrared data. The Thermal Infrared Sensor (IRS) on the Chinese ZY1-02E satellite is a pivotal instrument employed for gathering thermal infrared (TIR) data of land surfaces. The objective of this research is to evaluate the feasibility of a single-channel approach based on water vapor scaling (WVS) for deriving LST from ZY1-02E IRS data because of its wide spectrum range, i.e., 7~12μm, affected strongly by both atmospheric water vapor and ozone. Three study areas, namely Baotou, Heihe River Basin, and Yantai-sea sites, were selected as validation sites to evaluate the LST inversion accuracy. This evaluation was also conducted by cross-comparison between the retrieved LST and MODIS LST product. The results revealed that the WVS-based method exhibited an average bias of 0.63K and an RMSE of 1.62K compared to the in-situ LSTs. The WVS-based method demonstrated reasonable accuracy through cross-validation with the MODIS LST product, with an average bias of 0.77K and RMSE of 2.0K. These findings provide that the WVS-based method is effective to estimate LST from ZY1-02E IRS data.

The proliferation of ransomware poses a significant threat to global cybersecurity. This study presents a comprehensive review of the methodologies employed in the detection and analysis of ransomware, emphasizing the dichotomy between static and dynamic analysis approaches. It introduces the historical context and the necessity for robust cybersecurity measures, followed by an outline of the methodological framework used to evaluate existing ransomware analysis techniques. The results detail the effectiveness and limitations of various analysis strategies, identifying key features and patterns that aid in the detection and classification of ransomware threats. The study concludes by summarizing the primary achievements, including the identification of gaps in current research and proposing future research directions aimed at enhancing ransomware detection and mitigation strategies. The synthesis provided in this survey offers a consolidated view of the state-of-the-art in ransomware threat analysis and serves as a resource for cybersecurity professionals and researchers.

For an enterprise, the most critical aspect of development is resource management, which has a significant impact on all aspects of the enterprise. Therefore, enterprises must pay attention to resource management allocation, which can better promote the sustainable development of the enterprise and obtain optimal benefits. In the production and development of modern enterprises, the acquisition of benefits also involves the allocation of resources in enterprise management. This paper proposed a benefit optimization scheduling algorithm based on a macroeconomic prediction model under auction mechanism and a grid resource scheduling algorithm driven by a benefit function to allocate resources reasonably. This article used macroeconomic forecasting models to fully understand the resource needs of various departments and the resources held by enterprises, and rationally allocate various resources in various departments. This can improve the work efficiency of various departments, thereby reducing the cost of the enterprise, and achieving optimal benefits for the enterprise. The experimental results in this paper showed that the cost of resource management allocation for the benefit optimization scheduling algorithm and the grid resource scheduling algorithm based on the benefit function driven under the auction mechanism was 105.6 yuan and 46.8 yuan respectively when the task volume was 125 under the multi user environment. The time allocated for resource management was 36.6s and 18.9s respectively. It can be seen that the efficiency function driven grid resource scheduling algorithm had a lower cost and time for resource management allocation, so the efficiency function driven grid resource scheduling algorithm can achieve enterprise efficiency optimization.

The principle of the constancy of the velocity of light, which stated that the light velocity is invariant to the motion of the emitter, was well established and directly proven by experiments. Interestingly, the further assumption that the light velocity is independent of the motion of the observer was, arguably, never directly proven by any experiment for a century. This paper proposed the design of two experiments to directly test this assumption, which tried to address some perceived technical difficulty in such experiments. One is to directly measure the light speed as to moving sensors. The experiment setup is designed in such a way that the concerns of time synchronization and dilation can be avoided. Another experiment is to test the isotropy of the light speed to a moving particle in the electromagnetic accelerator by measuring the momentum to acceleration ratio. The experiment result, if positive, will provide direct and solid proof of the assumption. Otherwise, it may imply a need for further investigation. Since the light speed invariance to moving observers is a key assumption of some fundamental physical theory, either way, the experiments will have significant meanings.

The utilization of optical antennas for active control of far-field radiation at the subwavelength scale is crucial in various scientific and technological applications. We propose a thermally tunable disk design of indium tin oxide (ITO) and aluminum gallium nitride (Al0.18Ga0.82As), enabling a switch between absorption and scattering. Furthermore, the control of far-field radiation pattern can be easily realized by combining ITO and Al0.18Ga0.82As to enhance or suppress emission. Our results demonstrate that hybrid structure can be dynamically tuned with temperature variations. In the proposed design, a frequency is achieved at the epsilon-near-zero wavelength of 1240 nm. The thermal tunability of hybrid structure introduces new multifunctional possibilities for light manipulation, thereby enhancing the potential applications of new devices in the near-infrared range.

In this study, Brillouin optical time-domain analysis (BOTDA) sensing technology was utilized for monitoring settlement in a similarity model of a highway subgrade. As contact winding cannot be used for an optical fiber that is buried directly in soil, uncoupling between. the fiber and the soil can occur. Thus, an optical-fiber-embedded beam (OFEB) was developed, and a method for measuring and calculating the beam deformation was proposed. A calibration test and a test on a similarity model of a subgrade were carried out to investigate the applicability and monitoring accuracy of the OFEB. It was concluded that the OFEB can accurately measure beam deflection, where the maximum relative error between measurements by the optical fiber and a displacement transducer was approximately 5%. The OFEB was embedded directly into a similarity model of a subgrade to monitor settlement. The deflection deformation of the OFEB was found to be close to the subgrade settlement over a certain settlement range with a relative error below 8.1%. Thus, the OFEB can be used to realize measure large-range distributed settlement in a subgrade. A numerical simulation was performed to identify appropriate beam dimensions and material design parameters, thereby extending the measurement range before decoupling of the OFEB and soil occurs. The enhancement of the measurement range and accuracy of the OFEB based on the preliminary experiments carried out in this study enables further investigation of settlement monitoring.

This study examines the unique circumstances surrounding state-owned equity participation in non-state-controlled enterprises in China. Specifically, this study examines the impact of state-owned equity participation on the environmental, social, and governance (ESG) performance of non-state-controlled enterprises. Focusing on A-share listed firms on the Shanghai and Shenzhen Stock Exchanges and using data from 2013 to 2021, empirical testing shows that state-owned equity participation can significantly improve the ESG performance of non-state-controlled enterprises, with this conclusion remaining reliable after a series of robustness tests. Top management incentives is a mediating mechanism for state-owned equity participation in enhancing ESG performance. This study also finds that when state-owned equity participates in large enterprises or companies with a high degree of digital transformation, the effect on ESG performance is greater than that of small to medium-sized enterprises (SMEs) or enterprises with a low level of digital transformation. The findings of this study add to the current body of the existing field of research on the factors influencing corporate ESG performance and the impact of state-owned equity on corporate non-financial performance.

The study of co-fusion was one of the essential topics in the history of metallurgy in China. Simulation experiments had been an essential concept in the study of the co-fusion steelmaking process. This paper mainly studied the simulation experiments of co-fusion from two aspects: the replication of co-fusion swords by three different methods, and the micro-analysis of the co-fusion samples. The experimental results indicated that several co-fusion swords could be made by different processes, but the carbon content and surface hardness were quite different. During repeated forging welded, the microstructure of the samples transformed from laminated to homogenized, finally the steel with a uniform carbon content was obtained. It was challenging to find the characteristics of co-fusion from the homogenized samples. The results prompted people to rethink the microstructure characteristics of ancient co-fusion artifacts.

This paper begins with an introduction to porcelain tiles. A review of the major scientific and technological features of the mullite−based porcelain tile (MPT) and anorthite−based porcelain tile (APT), focusing primarily on the raw material, processing, phase evolution and mechanical behavior, is then presented. Based on the porcelain tile firing behavior and a series of physical and chemical changes that can occur, a comprehensive comparison is described. In the last part, the prospects for further developments related to MPT and APT are discussed.

(1) Background: The CEO message of hospital homepage contain various contents such as the hospital's future vision, promises with customers, upgraded services and public activities. The CEO’s message of the homepage includes non-financial information as well as financial information of corporates. Also, it provides useful information for not only company's goals and vision but also firm performance and strategies for the future. This study aims to investigate associations between CEO’s message of hospitals homepages and financial status. We used the balanced scorecard frame to analyze what content on the hospital's homepage is related to the hospital's various financial ratios. (2) Methods: We adopt a text mining method to extract significantly repeated keywords from the CEO’s message of hospital website. And we classify these keywords by a balanced scorecard frame. To examine the relationship between keywords of CEO’s message of the hospital homepage and hospital’s financial ratio, T-test is conducted for the difference in the TF-IDF (Term Frequency is Divided by Inverse Document Frequency) mean of the home page contents and its relationship with the views of the balanced scorecard framework. (3) Results: According to empirical results on 65 samples collected from local hospitals, there are some significant relationship between the qualitative content of the hospital's homepage and the quantitative financial ratio that indicates profitability, activity, leverage, liquidity, and transfer to essential business fund (EBF) income. (4) Conclusions: The introduction section of a homepage is most accessible to customers, containing the aims and ideals of hospitals and reflecting their values and visions [1]. In addition, in view of financial status, they can either emphasize financial strength or focus on other areas to mask weakness of financial information. This study reminds us of the importance of hospital website’s disclosure, and it can be inferred from the financial status of the hospital. It also highlights the need for harmonization between quantitative data, financial statements, and qualitative data, CEO’s messages. (5) Implications: To our best knowledge, this paper is the first research attempting to investigate the relation between text of hospital homepage and financial ratio of hospital through text mining technique and balanced scorecard frame. Hospitals take a crucial part in a country’s welfare and healthcare backbone industry. Nevertheless, in many countries, hospital organization sectors tend to remain a source of critical fiscal deficits due to its ineffective and sloppy management. We expect that the result of this paper can provide hospital managers to useful information.

The aim of this study is to investigate, by means of experimental measurements and full-wave simulations, the dominant factors for the very high-resolution (VHR) radar image speckles from exponential correlated rough surfaces. A Ka-band radar system was used to collect the return signal from such a surface sample fabricated by 3D printing, and that signal was further processed into images at different resolution scales, where the image samples were obtained by horizontally turning around the surface sample. To cross-validate the results and to further discuss the VHR speckle properties, full wave simulations by full 3D Finite Difference Time Domain (FDTD) method were conducted with 1600 realizations for the speckle analysis. At the considered very high resolution, speckle statistics show divergence from the fully developed Rayleigh distribution. The factors that impact on the high-resolution speckle properties from exponential correlated rough surface, are analyzed in views of the equivalent number of scatterers theory and scattering scales, respectively. From the data results and extended discussions, it is evident that both of the above factors matter for VHR speckle of backscattering, from the exponential correlated rough surface as a good representative for the ground surface.

Oriental lacquer, a natural and renewable polymeric coating, comes from the sap produced by lacquer trees. For practical application, oriental lacquer must be refined to reduce excess water and enhance its quality. In this study, drying oils were blended with oriental lacquer during the refining process to prepare an oil-modified refined lacquer (OMRL). The type and adding amount (0, 10, and 20% by wt.) of drying oils for wood coatings utilization were evaluated. Rhus succedanea oriental lacquer is composed of 54.1% urushiols, 34.3% water, 7.2% plant gum, and 4.4% nitrogenous compounds, and drying oils, including tung oil (TO), linseed oil (LO), and dehydrated castor oil (DCO) were used as materials in this study. The results show that the drying oil acts as a diluent, which reduces the viscosity and enhances the workability and could shorten the touch-free drying time and speed up the hardened drying of the OMRL. The results also indicate that the hardness, mass retention, Tg, tensile strength, abrasion resistance, and lightfastness of OMRL films decrease as more drying oils are blended. Conversely, the bending resistance, elongation at break, impact resistance increase, and particularly, the gloss, is greatly improved through the blending of more drying oils. In conclusion, the LO-modified refined lacquer (RL) has the highest film gloss and the DCO-modified RL has the shortest drying time for coating; otherwise, the film properties are similar among the three types of drying oil.

Chinese texts often feature a substantial volume of normative content, and their analysis has increasingly become a focal point in recent semantic analysis endeavors. Enhancing the effectiveness of text classification and clustering is pivotal in unveiling the intricate semantics within extensive textual data. Empirical research within the realm of computational social science has underscored the need for improved explanatory power when it comes to general text clustering methods applied to normative texts. This study introduces an innovative hierarchical clustering method that incorporates part-of-speech (POS) features and pioneers a novel semantic network model. It achieves this by amalgamating a POS-based feature weight calculation method with hierarchical clustering techniques. To assess its efficacy, the method is rigorously evaluated across three diverse text datasets, encompassing normative reports, news articles, and social media content. The experimental results unequivocally demonstrate the superior performance of the POS-HC method, surpassing the traditional TF and TF-IDF feature extraction methods in terms of clustering accuracy, and surpassing some existing clustering methods. Furthermore, its classification effectiveness exhibits notable advantages, particularly in the semantic classification of normative texts.

Corrosive burns lead to progressive esophageal stricture and dysphagia. There are many trials to prevent Esophageal stricture formation after corrosive burn. This study aimed to access the effects of EW-7197 on prevention for esophageal stricture formation after corrosive esophageal burn. animal study were classified divided into three groups: a healthy group, a control group (corrosive burn without EW-7197), and a treatment group (corrosive burn with EW-7197). Corrosive esophageal burns were produced using 30% NaOH on the lower esophagus. For 3 weeks, the control group received vehicle and the treatment group received 20 mg/kg/day EW-7197. Treatment efficacy was assessed by measuring the stenosis ratio by esophagogram with contrast media on day 21. histologic staining was performed to evaluate the fibrosis area ratio, and western blotting was performed to evaluate fibrotic markers. Among 20 rats that underwent surgery, 14 survived. Three in the treatment group died because of esophageal perforation, and three in the control group died due to their debilitating status. The esophageal stenosis ratio was significantly lower in the treatment group than in the control group (12.1 ± 9.5% and 42.2 ± 8.3%, respectively; p = 0.001). The histologic fibrosis area ratio was also significantly lower in the treatment group (12.5 ± 3.0% and 21.6 ± 2.1%, respectively; p = 0.001). The treatment group showed lower expressions of profibrogenic proteins such as TGF-β1, pSmad3, and α-SMA. EW-7197 may be a good alternative for the prevention esophageal stricture formation after corrosive burn.

The Agricultural Policy/Environmental eXtender (APEX) model is widely used for evaluating agricultural conservation efforts and their effects on soil and water. A key component of APEX application in Korea is simulating water quality impacts of rice paddies because rice agriculture claims the largest cropland area in the country. In this study, a computational module called APEX-Paddy is developed to simulate water quality with considering pertinent paddy management practices such as puddling, flood irrigation management. Data collected at two experimental paddy sites in Korea were used to calibrate and validate the model. Results indicate that APEX-Paddy performs well in predicting runoff discharge rate and nitrogen yield while the original APEX highly overestimates runoff rates and nitrogen yields on large storm events. With APEX-Paddy, simulated and observed flow and mineral nitrogen yield (QN) are found to be highly correlated after calibration (Nash & Sutcliffe Efficiency (NSE) = 0.87 and Percent Bias (PBIAS) = −14.6% for flow; NSE = 0.68 and PBIAS = 2.1% for QN). Consequently, the APEX-Paddy showed a greater accuracy in flow and QN prediction than the original APEX modeling practice using the SCS-CN method.

Using lightweight fire-rated board (LFRB) presents cost-effective opportunities for various passive fire protection measures. The aim of the project is to develop a LFRB with enhanced fire resistance, acoustic properties, and mechanical properties. These properties were determined using the Bunsen burner, furnace, energy dispersive X-Ray, impedance tube instrument, and Instron universal testing machine. To fabricate the LFRBs, vermiculite and perlite were blended with flame-retardant bind-ers, and four types of LFRBs were produced. A fire test was conducted to compare the fire-resistance performance of the LFRBs with a commercially available flame retardant board. The B2 prototype showed exceptional fire-resistant properties, with a temperature reduction of up to 73.0 °C as compared to the commercially available fire-rated magnesium board. Incorporating nano chicken eggshell into the specially formulated flame-retardant binder preserved the LFRBs’ structural integrity, enabling them to withstand fire for up to 120 minutes with an equilibrium temperature of 92.6 °C. This approach also provided an absorption coefficient of α = 2.0, a high flexural strength of 3.54 MPa, and effective flame retardancy properties with a low oxygen/carbon ratio of 2.60. These results make the LFRBs valuable for passive fire protection applications in the construction and building materials industry.

Background: People with Down syndrome (DS) have a trisomy of chromosome 21 and marked deficits in verbal memory but relatively preserved visuospatial perception. Verbal memories are related to semantic knowledge. Little is known about the organization of semantic knowledge in people with DS, which was the aim of this study. Aims: The extent of false memory in people with DS was examined. Possible differences in the number of false memories induced by nominal and verbal themes were examined. Methods and Procedures: In the study phase, ten word lists with semantically related associates were presented. In the recognition phase, participants made judgments on whether each word had been represented previously as semantically related lures, old words, and semantically unrelated new words. Outcomes and Results: Differences in the processing of nominal and verbal theme-related lures were observed among people with DS. When processing nominal theme-related lures, people with DS showed delayed false positives. When processing verbal theme-related lures, people with DS showed no differences compared to controls. Similar patterns have been observed in people with DS when processing nominal theme-related associates and verbal theme-related associates. People with DS have delayed recognition of associates. When processing unrelated words, they showed significantly higher false positives than controls for both nominal and verbal eliciting themes. Further analyses of the themes revealed differences in false positives across syntactic categories among groups. Conclusions and Implications: People with DS showed a delayed recognition of associates and deviance in recognizing unrelated words in the nominal and verbal theme categories. People with DS were delayed in terms of nouns, but deviated with verbs in associated and unrelated words. Additionally, people with DS showed distinct patterns in processing five nominal lures and three verbal lures, suggesting that they formed false memories differently based on distinct syntactic categories. Thus, it was concluded that people with DS develop a deviant semantic structure. Category-based interventions for people with DS should be implemented in order to improve their semantic knowledge through lexical connections.

Aging is associated with an increasing dysfunction of key brain homeostasis mechanisms and represents the main risk factor across most neurodegenerative disorders. However, the degree of dysregulation and the affectation of specific pathways set apart normal aging from neurodegenerative disorders. In particular, the neuronal metabolism of catecholaminergic neurotransmitters appears to be a specifically sensitive pathway that is affected in different neurodegenerations. In humans, catecholaminergic neurons are characterized by an age-related accumulation of neuromelanin (NM), rendering the soma of the neurons black. This intracellular NM appears to serve as a very efficient quencher for toxic molecules. However, when a neuron degenerates, NM is released together with its load (many undegraded cellular components, transition metals, lipids, antibiotics) contributing to initiate and worsen an eventual immune response, exacerbating the oxidative stress, ultimately leading to the neurodegenerative process. This review focuses on the analysis of the role of NM in normal aging and catecholaminergic metabolism due to its capability as a pro-oxidant and other harmful molecules, versus its involvement in oxidative stress and aberrant immune response, which it is highly dependent on NM saturation state and its extracellular release.

Public safety and intelligent surveillance systems critically depend on anomaly behavior detection for effective monitoring. In real-world pedestrian detection scenarios, prevalent challenges such as missed detections, complex background interference, and small target sizes hinder accurate anomaly identification. To address these issues, this study introduces YOLO-ABD, a lightweight method for anomaly behavior detection that integrates small target detection and channel shuffling. This method employs YOLOv8n as the baseline model, incorporating a small target detection mechanism in the Head part and utilizing GSConv convolution in the Backbone to enhance perceptual capability. Additionally, the SimAM attention mechanism is integrated to mitigate complex background interference, thereby improving target detection performance. Evaluation on the IITB-Corridor dataset demonstrated mAP50 and mAP50-95 scores of 89.3% and 60.6%, respectively. Generalization testing on the street-view-gdogo dataset further highlighted the superiority of YOLO-ABD over advanced detection algorithms, underscoring its effectiveness and generalizability. With a relatively small parameter count, YOLO-ABD presents an excellent lightweight solution for pedestrian anomaly behavior detection.

The Paeonia suffruticosa, called as 'Feng Dan', has been used for thousands of years in traditional Chinese medicine. In our chemical investigation on the root bark of the plant, five new phenolic dimers, namely paeobenzofuranone A‒E (1‒5), have been characterized. Their structures were determined by spectroscopic analysis including 1D and 2D NMR, HRESIMS, UV, and IR, as well as ECD calculations. Compounds 2, 4, and 5 showed cytotoxicity against three human cancer cell lines with IC50 values ranging from 6.7 to 25.1 μM. Compounds 1 and 2 showed certain inhibitory activity on NO production. To the best of our knowledge, the benzofuranone dimers and their cytotoxicity of P. suffruticosa are reported for the first time.

This study investigates how customers’ technological readiness affects service quality and the adoption of self-service banking by developing an empirical model. The model was proposed to explore the relationships between technology readiness, self-service quality, and customer satisfaction. The hypotheses and stability of the model were tested using structural equation modeling. The findings revealed that technology readiness, including the optimism, innovation, and insecurity dimensions, had a significant positive impact on self-service quality. In addition, service quality fully mediated the relationship between technological readiness and customer satisfaction. These results suggest that when customers are ready to embrace and use new technology, their evaluation of service quality is high. Thus, bank managers should drive customer perceptions of the quality of self-service banking by improving their technological readiness through various measures. Furthermore, based on the mediating effect of self-service quality, banks must be aware that improving service quality can enhance customer satisfaction and maintain a competitive advantage.

The recurrent coronavirus outbreaks in China (SARS-CoV and its relative, SARS-CoV-2) have raised speculations that perhaps Asians are somehow more susceptible to these coronaviruses. Here, we test this possibility based on an analysis of the lung-specific expression of ACE2, which encodes the known cell-entry receptor of both SARS-CoV and SARS-CoV-2. We show that ACE2 expression is not affected during tumorigenesis, supporting that the abundant transcriptomes in cancer genomic studies can be informatively used to study ACE2 expression among diverse individuals without cancer. We find that ACE2 expression in the lung increases with age, but is not associated with sex. Further, Asians do not differ from other populations for ACE2 expression and do not harbor unique genetic polymorphisms in the ACE2 locus. Thus, beyond illustrating an innovative method for assessing the potential impacts of demographic factors for non-cancer diseases from large-scale cancer sample datasets, our statistically robust findings emphasize that individuals of all races require the same level of personal protection against SARS-CoV-2.

In order to study the effect of explosion load on the flexural performance of RC beams, two RC beams of the same size were carried out explosion test and bearing capacity test successively. Piezoelectric intelligent aggregate was embedded in the beams in advance to monitor the damage state of the beams, which realized the whole process of damage monitoring of the concrete inside the structure from explosion damage to compression damage.Based on wavelet packet analysis and residual bearing capacity damage evaluation criteria, the beam damage was quantitatively evaluated, and the bending bearing capacity of RC beam after explosion damage was compared and analyzed.The results show that the change of concrete strain gauge signal, the phenomenon of crack development and the increase of internal crack development index indicate that the RC beam is damaged by explosion load.After explosion damage, the damage index of the beam increases and the residual bending capacity decreases, which proves that the piezoelectric intelligent aggregate sensor can effectively monitor the bending capacity change of the component after explosion damage.

In recent years, electroencephalogram (EEG) emotion recognition has emerged as a research hotspot in the field of artificial intelligence (AI). Despite advancements in EEG-based emotion recognition, room for enhancing performance persists due to EEG signal redundancy and limitations in feature extraction, leading to inefficient models and emotional information loss. To fully utilize EEG's emotional information and improve recognition accuracy while reducing computational costs, this paper proposes a Convolutional-Recurrent Hybrid Network with a dual-stream adaptive approach and an attention mechanism (CSA-SA-CRTNN). Firstly, the model utilizes a CSAM module to assign corresponding weights to EEG channels. Then, an adaptive dual-stream convolutional-recurrent network (SA-CRNN and MHSA-CRNN) is applied to extract local spatial-temporal features. After that, the extracted local features are concatenated and fed into a temporal convolutional network with a multi-head self-attention mechanism (MHSA-TCN) to capture global information. Finally, the extracted EEG information is used for emotion classification. We conducted binary and ternary classification experiments on the DEAP dataset, achieving 99.26% and 99.15% accuracy for arousal and valence in binary classification, and 97.69% and 98.05% in ternary classification, surpassing relevant algorithms. Additionally, the model's efficiency is significantly higher than other models, achieving better accuracy with lower resource consumption.

Trehalose is a non-reducing disaccharide and participates in physiological activities such as or-gan formation, energy metabolism, and stress resistance of insects. In the present study, phylo-genetic analysis divided 21 Bmtret1 orthologs into three clades. These genes are equally distrib-uted on the nine chromosomes. Cis-elements in the promoter regions of Bmtret1s indicated the possible function of Bmtret1s in response to hormones and environmental stimulus. The qPCR analysis showed the significantly different expression levels of Bmtret1s in different tissues and organs, indicating possible functional divergence. In addition, most Bmtret1s showed disturbed expression levels in response to BmNPV stresses. Our results provide a foundation for further functional dissection of Tret1s in Bombyx mori and implicate them as potential regulators for an-tiviral responses.

The potential effect of implementing environmental regulations on economic growth is a controversial issue for a long time. As portrayed by Porter hypothesis, environmental regulations may impact on economic growth by reconstructing the economic structure. A number of previous literature proved the connections between the above three parties. With the intention of exploring the nature of this mechanism, it is important to understand the internal inter-relation of the three parties, requiring data from a large economy experiencing the transition in economic structure. By constructing a panel containing data from 30 Chinese provinces over 10 years (2008-2019), this paper investigate the dynamic inter-relation of the three parties by introducing PVAR model with Granger Test. Results reveal that environmental regulations give a “U” shaped impact to economic growth. In return, economic growth promotes the development of economy with a weakening strength. In addition, results also support the hypothesis that economic structure is the intermediate of economic growth and environmental regulations. There is a rooftop for the effect of economic structure to environmental regulations. The rooftop may signify the best optimization of primary structure.

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

3D object detection is essential for an accurate and reliable autonomous driving system. Currently, the methods used by the state-of-the-art two-stage detectors are not flexible enough and their fea-ture extraction capabilities are very limited to cope effectively with the disorder and irregularity of point clouds. In this paper, we combine the advantages of both PV-RCNN and PAConv (Position Adaptive Convolution) to create a completely new network, FANet, in order to overcome the ir-regularity and disorder of point clouds. The convolution in our network builds convolutional ker-nels from a basic weight matrix, whose combined coefficients are learned adaptively by LearnNet from relative points. This network allows for flexible modeling of complex spatial variations and geometric structures in the 3D point cloud, enabling better extraction of point cloud features and producing high-quality 3D proposal boxes. Compared to other methods, FANet is superior in terms of 3D object detection accuracy. Extensive experiments on the KITTI dataset have shown a signif-icant improvement in our approach.

Directed energy deposition (DED) is an efficient method to fabricate functionally graded materials (FGMs) with gradient composition and complex structures, allowing for local tailoring of properties instead of the costly need for extraneous welds and joints. In this study, a FGM from stainless steel to Inconel alloy was successfully fabricated using the powder-based laser DED. A very refined grain structure has been observed in at the composition with 75 wt.% Inconel alloy content, which also exhibits the highest (entropy). For the first time, the post heat treatments, microstructure and aging precipitation behaviors of FGMs were systematically studied via experimental characterization and computation, to elucidate their effects on the gradient smoothing and mechanical properties. The diffusion and segregation of Ni, Nb and Ti elements underly the transformation mechanism between Laves, δ, γ’ and γ’’ phases during precipitation. Homogenization on FGMs not only eliminates the heterogeneity inherited from the AM process, but also provides a practical way to smoothen the gradient on composition and microstructure for the eventual good gradient properties. It has a direct influence on the following precipitation behaviors in the FGM, which highly relies on the diffusion degree of the elements in the matrix and grain boundaries. The high-throughput thermodynamic modeling and kinetic modeling were exploited to evaluate the experimental microstructure and address computational uncertainty using different thermodynamic conditions and databases, which enables an accelerated design through local tailoring of process-structure-property relationships to develop new functional materials.

Bone drilling is a common procedure used to create pilot holes for inserting screws to secure implants for fracture fixation. However, dis process can increase bone temperature, teh excessive heat can lead to cell death and thermal osteonecrosis, potentially causing early fixation failure or complications. We conducted a three-dimensional dynamic elastoplastic finite element model to evaluate teh propagation and distribution of heat during bone drilling and assess teh thermally TEMPeffected zone (TAZ) dat may lead to thermal necrosis. dis model investigates teh parameters influencing bone temperature during bone drilling, including drill diameter, rotational speed, feed force, and predrilled hole. Teh results indicate dat our FE model is sufficiently accurate in predicting teh temperature rise TEMPeffect during bone drilling. Teh maximum temperature decreases exponentially wif radial distance. When teh feed forces are 40 and 60 N, teh maximum temperature does not exceed 45 °C. However, wif feed forces of 10 and 20 N, both teh maximum temperature exceeds 45 °C wifin a radial distance of 0.2 mm, indicating a high-risk zone for potential thermal osteonecrosis. Wif teh two-stage drilling procedure, where a 2.5 mm pilot hole is pre-drilled, teh maximum temperature can be reduced by 14 °C. dis suggests dat higher feed force and rotational speed and/or using a two-stage drilling process could mitigate bone temperature elevation and reduce teh risk of thermal osteonecrosis during bone drilling.

Ransomware constitutes a distinctive category of pernicious software that sequesters a user's digital assets by encryption, holding them hostage until a sum is extorted from the victim. These incursions have escalated to become among the most prevalent and significant threats confronting both individuals and corporate entities. In combatting this virulent program, dynamic analysis has been established as the favored detection modality. Such analyses typically hinge on Windows API calls, the conduits through which programs requisition services from the operating system. Yet, the superfluous and unrelated Windows API calls interjected by adversaries into the execution stream of suspect binaries precipitate an excessively noisy behavioral sequence, which impairs the performance of counter-ransomware mechanisms. The research outlined herein introduces a novel non-signature-based detection paradigm that harnesses efficacious Windows API call sequences through supervised machine learning strategies. An innovative Enhanced Min Max (EmRmR) filter technique is proposed, aiming to purge noisy features and isolate the most indicative feature subset that encapsulates the ransomware's true behavior. The EmRmR method, diverging from the traditional Min Max approach, circumvents the superfluous calculations that are a hallmark of the conventional algorithms, thereby necessitating a reduced number of evaluations. Additionally, a refinement procedure has been integrated to contract the program's call trace volume by discarding those Windows API calls lacking a robust correlation with ransomware's pivotal behavior. Subsequent to rigorous experimental analyses and juxtaposition with extant behavior-based detection methodologies, the proposed strategy has demonstrated its efficacy in differentiating ransomware behavior, delivering high detection precision alongside a diminution in false-positive occurrences.

Automatic Voice Query Service can extremely reduce the artificial cost, which could improve the response efficiency for users. The automatic speech recognition (ASR) is one of the important component in AVQS. However, many dialect areas in China make the AVQS have to response the multi-accented Mandarin users by single acoustic model in ASR. This problem severely limits the accuracy of ASR for multi-accented speech in the AVQS. In this paper, a new framework for AVQS is proposed to improve the accuracy of response. Firstly, the fusion feature including iVector and filterbank acoustic features is used to train the Transformer-CTC model. Secondly, the transformer-CTC model is used to construct the end-to-end ASR. Finally, key words matching algorithm for AVQS based on fuzzy mathematic theory is proposed to further improve the accuracy of response. The results show that the final accuracy in our proposed framework for AVQS arrives at 91.5%. The proposed framework for AVQS can satisfy the service requirement of different areas in mainland of China. This research has a great significance for exploring the application value of artificial intelligence in the real scene.

This paper considers a non-mixture cure model for right censored data. It utilizes the maximum likelihood method to estimate model parameters in the non-mixture cure model. The simulation study is based on Fréchet susceptible distribution to evaluate the performance of the method. Comparing with Weibull and exponentiated exponential distributions, the non-mixture Fréchet distribution is shown to be the best in modeling a real data on allogeneic marrow HLA-matched donors and ECOG phase III clinical trial e1684 data.

This study proposes an image recognition method to assist swine farm managers in collecting health data related to pig feeding and excretion. Analyzing the correlation between sow health data and indoor air quality in the pigsties revealed significant influences of air quality indicators on sow health. Increased levels of TVOC, CO2, and temperature were found to negatively affect feeding health, while increased temperature, humidity, and PM10 were found to negatively impact excretion health. These findings provide a basis for evaluating variables when constructing future sow disease prediction models. Analyzing the correlation between pig health status and air quality can help swine farm managers improve sow production environments, reduce disease risks, enhance production efficiency, and provide valuable insights for future research on disease prediction models.

This paper proposed a new evaluation model based on analytic hierarchy process to quantitatively evaluate the capability of multi-satellite cooperative remote sensing observation. The analytic hierarchical process model is a combination of qualitative and quantitative analysis of systematic decision analysis method. According to the objective of the remote sensing cooperative observation mission, we decompose the complex problem into several levels and a number of factors, compare and calculate various factors in pairs, and obtain the combination weights of different schemes. The model can be used to evaluate the observation capability of resource satellites. Taking the optical remote sensing satellites such as China’s resource satellite series and GF-4 as examples, this paper verifies and evaluates the model for three typical tasks: point target observation, regional target observation and moving target continuous observation. The results show that the model can provide quantitative reference and model support for comprehensive evaluation of the collaborative observation capability of remote sensing satellites.

This study evaluated the mechanical strengths of three types of orthodontic micro-implants by analyzing their structural configurations. Thirty micro-implants of three types (diameter 1.5 mm, Types A, B, C) were assessed. All micro-implants were manually driven into artificial bones at an 8-mm depth. The insertion torque (IT), pullout strength (PS), and gripping volume (GV) of each type were measured. Intergroup comparisons and intragroup correlation were investigated by statistical analysis. Type B had the greatest inner–outer diameter ratio (0.67), and Type A had the smallest (0.53). The IT of Type A (5.26 Ncm) was significantly (p = 0.038) lower than that of Type C (8.8 Ncm). There was no significant difference in the pullout strength (p = 0.868). The GV of Type A (9.7 mm3) was significant (p < 0.01) greater than Type C (8.4 mm3). Type C was significant (p < 0.01) greater than Type B (7.2 mm3). Spearman’s rho rank correlation test showed that PS of Type B was correlated significantly with GV. In conclusion, the design of thread and its GV were the important factors on the mechanical strengths of micro-implant.

Post-evaluation of ecological redevelopment is a good method for its achievements. The eco-engineering technologies and achievements of landscape water reconstructed from aquaculture ponds in Shanghai Chenshan Botanical Garden have been introduced in this study. The sediments and water quality were also sampled and tested for basic physicochemical parameters and heavy metal concentration. The ecological redevelopment of landscape water reconstructed from aquaculture ponds was evaluated using the Nemero comprehensive pollution index method. The results shown that nutrients including organic matter, organic nitrogen and their ratio of sediment were found to be in a state of moderate pollution, while their ecological risk of heavy metals was low. Although total nitrogen and total phosphorus of water quality was really higher than that of other indexes, the decline trends of ammonia nitrogen, total nitrogen and total phosphorus was obvious presented over time. In general, this is a good example that redevelopment of water ecosystems from aquaculture ponds using eco-engineering technologies.

Purification of biologically-derived therapeutics is a major cost contributor to the production of this rapidly growing class of pharmaceuticals. Monoclonal antibodies comprise a large percentage of these products therefore new antibody purification tools are needed. Small peptides, as opposed to traditional antibody affinity ligands such as Protein A, may have advantages in stability and production costs. Multiple heptapeptides that demonstrate Fc binding behavior that have been identified from a combinatorial peptide library using M13 Phage Display are presented herein. Seven unique peptide sequences of diverse hydrophobicity and charge were identified. All seven peptides showed strong binding to the four major human IgG isotypes, human IgM, as well as binding to canine, rat, and mouse IgG. These seven peptides were also shown to bind human IgG4 from DMEM cell culture media with 5% FCS and 5 g/L ovalbumin present. These peptides may be useful as surface ligands for antibody detection and purification purposes. Molecular docking and classical molecular dynamics (MD) simulations were conducted to elucidate the mechanisms and energetics for the binding of these peptides to the Fc region. The binding site was found to be located between the two glycan chains inside the Fc fragment. Both hydrogen bonding and hydrophobic interactions were found to be crucial for the binding interactions. Excellent agreement for the binding strength was obtained between experimental results and simulations.

Background: We attempted to find if there were gender differences in different types of Negative life events and Suicidal ideation among Chinese adolescents, then analyze the relationship between different types of Negative life events and Suicidal ideation among these young students. Methods: Based on the data from 6 middle-schools and 3 universities in 3 cities of Western China, the gender difference in different types of Negative life events and Suicidal ideation and their related factors were investigated and analyzed in the study. Results: Gender differences were found during different types of Negative life events and Suicidal ideation; Negative life events could predict the intensity of Suicidal ideation by gender, to some specific types. Conclusions: Negative life events were proved to be risk factors of adolescents’ Suicidal ideation regardless of different gender stereotypes, but the specific classification of negative life events which had significant impact on adolescents’ Suicidal ideation also indicated significant gender divisions. For males, negative life events of punishment and adaptation had a significant and boosting impact on their Suicidal ideation, the higher the scores of punishment and adaptation negative life events had, the greater intensity of male adolescents were to have Suicidal ideation. Thus, the above two types of negative life events may be the main stressors predicting male adolescents' Suicidal ideation; For females, in addition to punishment, other types of negative life events all had significant impacts on their Suicidal ideation, which can be treated as the main stressors to trigger female adolescents' Suicidal ideation; Additionally, parents’ marital status of remarriage and divorce were proved to be significant indicators to adolescents’ Suicidal ideation, the age variable was proved to be strongly correlated with Suicidal ideation among female adolescents.

As an important part of urban terminal delivery, automated guided vehicle (AGV) has been widely used in the field of takeout delivery. Due to the real-time generation of takeout orders, the delivery system is required to be extremely dynamic, so the AGV needs to be dynamically scheduled. At the same time, the uncertainty in the delivery process (such as the meal preparation time) further increases the complexity and difficulty of AGV scheduling. Considering the influence of these two factors, the method of embedding stochastic programming model into rolling mechanism is adopted to optimize the AGV delivery routing. Specifically, To handle real-time orders under dynamic demand, an optimization mechanism based on rolling scheduling framework is proposed, which allows the AGV route to be continuously updated. Different from most VRP models, open chain structure is used to describe the dynamic delivery path of AGV. In order to deal with the impact of uncertain meal preparation time on route planning, a stochastic programming model is formulated with the purpose of minimizing the expectation of order timeout rate and the total customer waiting time. In addition, an effective path merging strategy and after-effects strategy are also considered in the model. In order to solve the proposed mathematical programming model, a multi-objective optimization algorithm based on NSGA-III framework is developed. Finally, a series of experimental results demonstrate the effectiveness and superiority of the proposed model and algorithm.

The controllability and consistency in the fabrication of micro-textures on large-scale remains a challenge for existing production processes. Mask electrolyte jet machining (MEJM) is an alternative to Jet-ECM for controllable and high-throughput surface microfabrication with more consistency of dimensional tolerances. This hybrid configuration combines the high-throughput of masked-ECM and the adjustable flow-field of jet-ECM. In this work, a duckbill jet nozzle was introduced to make MEJM more capable of batch micro-structuring. A multiphysics model was built to simulate the distribution of electrochemical reaction ions, the cur- rent density distribution and the evolution of the shape of the machined cavity. Experimental investigations are presented showing the influence of the machining voltage and nozzle moving speed on the micro cavity. Several 35 ×35 micro cavity arrays with a diameter of 24.92 − 11.73 µm and depth of 15.86 − 7.24 µm are generated on 304 stainless steel.

Metabolites present in the hemolymph of honey bees play a crucial role in modulating the metamorphic process within the species. However, the precise alterations in metabolite composition, along with the associated variances and regulatory pathways implicated during the larvae-to-pupae metamorphosis of honey bees, remain incompletely elucidated. In this investigation, we gathered hemolymph samples from honey bee larvae at three distinct physiological stages-feeding, prepupal, and pupae and subjected them to metabolite analysis utilizing the liquid chromatography-mass spectrometry (LC-MS) technique. Employing principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA), we identified significant differential metabolites and conducted a metabolic pathway analysis on those differentially up-regulated during the prepupal and pupae stages. Notably, metabolites up-regulated in the hemolymph of prepupal stage larvae primarily governed glucose metabolism and fat digestion and absorption, while those in pupae stage larvae were involved in regulating chitin and lipopolysaccharide precursor formation, as well as the biosynthesis of phenylalanine, tyrosine, and tryptophan. These findings bear significant implications for advancing our comprehension of the metamorphic processes in honey bees.

Background: It remains unclear whether transfer RNA-derived small RNAs (tsRNAs) play a role in pathological cardiac hypertrophy (PCH). We aimed to clarify the expression profile of tsRNAs and disclose their relationship to the clinical phenotype of PCH and the putative role. Methods: Small RNA sequencing was performed in the plasma of PCH patients and healthy volunteers. In a larger sample size and angiotensin Ⅱ (Ang II)-stimulated H9c2 cells, the data were validated by real-time qPCR. The atrial natriuretic peptide (ANP) and brain natriuretic peptide (BNP) were examined in Ang II-stimulated H9c2 cells. The role of tsRNAs in the pathogenesis of PCH was explored by bioinformatics analysis. Results: A total of 4185 differentially expressed tsRNAs were identified, of which 4 and 5 tsRNAs were observed to be significantly differentially upregulated and downregulated expressed. Of the 5 down-regulated tsRNAs, 4 of them were verified to be significantly down-regulated in the larger sample group, among which tRF-30-3JVIJMRPFQ5D, tRF-16-R29P4PE, tRF-21-NB8PLML3E, and tRF-21-SWRYVMMV0 had areas under the curve to diagnose concentric hypertrophy. The 4 down-regulated tsRNAs were negatively correlated with left ventricular posterior wall dimensions in PCH patients (r=-0.4227; r=-0.4517; r=-0.5567; r=-0.4223). The levels of ANP and BNP as well as cell size were decreased in Ang II-stimulated H9c2 cells with 21-NB8PLML3E mimic transfection. Bioinformatics analysis revealed that the target genes of tRF-21-NB8PLML3E were mainly enriched in the metabolic pathway and involved in the regulation of ribosomes. Conclusion: The plasma tsRNAs tRF-21-NB8PLML3E might be considered biomarkers in patients with PCH with early screening potential.

Saline-alkaline aquaculture has become important breakthrough to expand available space for aquaculture in China. However, the biochemical composition and quality of Eriocheir sinensis reared in carbonate alkalinity water are still unclear. Therefore, this study investigated the edible yield, coloration, nutritional and flavor quality of Eriocheir sinensis. Significantly lower gona-dosomatic index (GSI) and meat yield (MY) were detected in intensive pond (IP) than those in semi intensive reed wetland (SIWR) (P< 0.05). Six color parameters differed between IP and SIRW in the hepatopancreas (P< 0.05). The contents of crude protein and fat in the female hepatopan-creas of IP were significantly higher than those in SIRW(P< 0.05). The higher concentrations of ∑MUFA, ∑EFA, h/H in the female edible tissues were checked in IP than those in SIRW, with significant difference including ∑MUFA in the hepatopancreas and ovary, ∑EFA in the muscle, and h/H in the ovary (P<0.05). Better total free amino acid (∑FAA) contents of muscle were de-tected in SIRW than that in IP. Significantly increasing tendency was detected in K, Ca, Mg, Fe, Zn of ovary from SIRW to IP (P< 0.05). Overall, the Eriocheir sinensis reared in carbonate alkalinity water is an important source of nutrient.

Epitaxial lithium ferrite (LiFe5O8) films with different thicknesses have been successfully fabricated on SrTiO3 (001) substrates by magnetron sputtering deposition technique. The microstructural and magnetic properties are characterized by advanced transmission electron microscope and magnetic measurement device. It was found that the formation of structural defects can be influenced by the thickness of the film. Apart from the misfit dislocations, the orientation domains form in thinner film and twin boundaries appear in thicker film, respectively, contributing to the misfit strain relaxation in the heterosystem. The magnetic measurement shows that the thinner films have enhanced magnetization and a relatively lower coercive field compared with the thicker films containing the antiferromagnetic twin boundaries. Our results provide a way for tuning the microstructure and magnetic properties of lithium ferrite films by changing the film thickness.

Surface finishing is challenging for additively manufactured components with complex geometries. Magnetic abrasive finishing (MAF) is a promising surface finishing technology that can refine the surface quality of components with complex shapes produced by additive manufacturing. However, there is insufficient study regarding the impact of MAF on microstructure-property relationships for additively manufactured builds, which is critical for evaluating the mechanical performance. Furthermore, although MAF is usually used as the final step of post-processing, it remains unclear whether adjusting the sequence between MAF and other processes, e.g., heat treatment, can potentially improve the mechanical performance. In this work, the effects of MAF on the microstructure and mechanical property evolution of Inconel 718 superalloys made by laser powder bed fusion (LPBF) were studied. The application of MAF was found to significantly reduce the surface roughness of alloys and refine the grain size of aged samples. Moreover, MAF is able to increase the elongation of materials, which can be further influenced by the sequence of MAF and different heat treatments. The highest elongation can be achieved when MAF is performed between homogenization and aging processes. This work demonstrated a promising solution to improving the performance of LPBF Inconel 718 by combining MAF and heat treatment, which provides new perspectives on the post-processing development of additively manufactured alloys for advanced mechanical properties.

The UHPC grouted bellow is an innovative technology for connecting assembled buildings, where the anchorage performance of the rebar and UHPC filled in bellows plays a critical role in determining the overall connection effectiveness. To ascertain a dependable anchorage length and establish a bond-slip relationship between the rebar and UHPC within the bellow, we conducted tests on 8 groups of 16 specimens of metal corrugated pipes filled with UHPC and rebar under tension. The tests considered varying parameters such as the aperture ratio D/d and anchorage length L. By analyzing the failure modes, load versus deflection curves, and steel strain data, we gained valuable insights into the influence of the aperture ratio and anchorage length on the anchorage performance. Furthermore, we calculated the experimental curve of the bond-slip relationship between the rebar and the UHPC interface grouted in the bellows and derived a bond-slip model through fitting. These findings serve as a crucial foundation for the force analysis of assembled structures connected using UHPC grouted bellows.

Obesity is a highly prevalent chronic disease characterized by excessive weight gain and fat accumulation. There is growing evidence that Lactiplantibacillus plantarum strains with bile salt hydrolase (BSH) activity are effective in preventing and alleviating obesity. However, few of them has confirmed the anti-obesity effect of BSH by gene deletion. In this study, 23 BSH-positive Lp. plantarum strains were screened by bile salt precipitation halo assay. Among these strains, Lp. plantarum Lp20 showed the highest BSH activity with a hydrolysis rate to glycodeoxycholic acid (GDCA) by 91.62%. Genomic sequencing and bioinformatics analysis indicated that gene bsh1 was associated with BSH activity of Lp. plantarum Lp20 and gene deletion of bsh1 confirmed the role of Bsh1 in GDCA hydrolysis. To investigate if the Bsh1 from Lp. plantarum Lp20 could alleviate obesity, the wild type and bsh1 deletion mutant strains were administered daily for 8 weeks to diet-induced obese mice, respectively. Compared with mutant strain, the wild type strain Lp20 significantly reduced body weight gain, inguinal white adipose tissue and mesenteric fat mass in obese mice. In addition, Lp20 also reduced serum total cholesterol levels and LDL-C by 20.8% and 33.3%, respectively. Furthermore, the recovered liver steatosis was only observed in Lp. plantarum Lp20 treated mice. Taken together, the bile salt hydrolase Bsh1 from Lp. plantarum Lp20 was a key functional factor on ameliorating HFD-induced obesity by reducing cholesterol levels and suppressing adipogenesis in mice.

The construction industry is an important part of the national economic market of various countries; since 2013, the construction industry's added value in the gross domestic product has been more than 6%, reaching 6.89% in 2022, and is a pillar industry of the national economy. Intelligent construction is the realistic demand to promote the high-quality development of China's construction industry. It is the key focus of transforming and upgrading the traditional construction industry to information, digital, and intelligent. As a new production factor, construction robots have become the key to promoting intelligent construction. Under the guidance of various national and industry policies, thanks to China's huge construction market volume and rich application scenarios, many innovative and entrepreneurial entities have entered the field of construction robots. Architectural visualization is a crucial aspect of architectural design and communication. With the development of science and technology, artificial intelligence (AI) technology is increasingly becoming an essential tool for architectural visualization and communication. The emergence of AI technology has provided architects with more flexible and creative ways to present design ideas. All along, designers who love architecture have been passionate about exploring better solutions for architecture, but there is never an optimal solution for architectural design; AI is the fire of the future era; it brings us more opportunities but also forces us to face new challenges from the future.

Since smoke usually occurs before a flame arises, fire smoke detection is especially significant for early warning systems. In this paper, a DSATA(Depthwise Separability And Target Awareness) algorithm based on depthwise separability and target awareness is proposed. Existing deep learning methods with convolutional neural networks pretrained by abundant and vast datasets are always used to realize generic object recognition tasks. In the area of smoke detection, collecting large quantities of smoke data is a challenging task for small sample smoke objects. The basis is that the objects of interest can be arbitrary object classes with arbitrary forms. Thus, deep feature maps acquired by target-aware pretrained networks are used in modelling these objects of arbitrary forms to distinguish them from unpredictable and complex environments. In this paper, this scheme is introduced to deal with smoke detection. The depthwise separable method with a fixed convolution kernel replacing the training iterations can improve the speed of the algorithm to meet the enhanced requirements of real-time fire spreading for detecting speed. The experimental results demonstrate that the proposed algorithm can detect early smoke, is superior to the state-of-the-art methods in accuracy and speed, and can also realize real-time smoke detection.

Effect of abrasive shape on the three-body abrasion behaviors of monocrystalline silicon was investigated by Molecular dynamics modelling. The axial ratio of abrasive particle was varied from 1.00, i.e., a complete sphere, to 0.40 to mimic abrasive shape. The particle’s movement turns toward sliding from rolling when the axial ratio becomes less than a critical value 0.46. In the abrasion process, the friction force and normal force showed an approximately sinusoid-like fluctuation for the rolling ellipsoidal particles, while the front cutting of particle caused that friction force increased and became larger than normal force for sliding particles. The phase transformation process was tracked under different particle’ movement patterns. The Si-II and Bct5 phase producing in loading process can partially transform to Si-III/Si-XII phase and backtrack to original crystal silicon under pressure release, which also occurred in the abrasion process. The secondary phase transformation showed difference for particles’ rolling and sliding movements after three-body abrasion. The rolling of particle induced the periodical and inhomogeneous deformation of substrates, while the sliding benefited producing high-quality surface in CMP process. This study aiming to construct more precise model to understand the wear mechanism benefits evaluating the MEMS wear and CMP process of crystal materials.

The collaboration of multimodal transport documents is the foundation for conducting multimodal transport operations. Blockchain technology can effectively address trust issues and information sharing difficulties in current multimodal transport document collaboration. However, in current blockchain-based electronic document research, the bottleneck problem lies in the collaboration of multiparty in multimodal transport under the "one-bill coverage system". We design a blockchain platform architecture for multimodal transport, reshaping collaboration processes for different modes of transport based on the blockchain platform. It proposes a collaboration model for multimodal transport under the "one-bill coverage system" and performs model solving and case analysis. The obtained collaboration strategies are embedded into the platform's application layer. Finally, using Solidity language, it writes smart contracts related to multimodal transport under the "one-bill coverage system " and deploys and executes them on the Remix platform.

This study explored what motivates university counselors. By analyzing various factors like personal values and work environment, they found counselors experience greater career satisfaction when their work aligns with their own values and societal impact, and when they receive recognition and opportunities for growth. Universities can utilize these findings to create a more supportive environment for counselors by highlighting their impact, offering development opportunities, and fostering a positive work culture. This can ultimately lead to a more motivated and effective counseling team, benefiting both the counselors and the students they serve.

Pedestrian object detection plays a significant role in intelligent systems such as intelligent traffic and monitoring. Traditional machine learning methods on pedestrian detection have shown various drawbacks, \eg{} low accuracy, slow speed, \etc The Convolutional Neural Network (CNN) based object detection algorithms have demonstrated remarkable advantages in the field of pedestrian detection. However, the mainstream CNNs still face the problems of slow speed and low detection accuracy, especially on small and occluded targets from aerial perspective. In this paper, we propose Multi-Scale Attention YOLO (MSA-YOLO) detection algorithm to address the above issues. MSA-YOLO includes a Squeeze, Excitation and Cross Stage Partial (SECSP) channel attention module for CNNs to extract richer pedestrian features with a small number of extra parameters. It also contains a multi-scale prediction module to capture the information among different pedestrian scales, which can recognize the small objects with higher accuracy and significantly reduce the missed detection. To sufficiently evaluate our proposed model, we manually collect and annotate a new benchmark dataset, Luoyang Pedestrian Dataset \footnote{The dataset can be downloaded through this anonymous link: \url{https://drive.google.com/drive/folders/13po1FX7Qk5RDgb60-dzOi74cq_kqDJtM?usp=sharing} }, which has much more sample annotations, features, scenes and image view angles than the existing benchmark datasets. In addition, the images in our dataset have higher resolution than most of benchmark pedestrian detection datasets, which can provide more detailed features of pedestrians and thus improve the model performance. When tested on Luoyang Pedestrian Dataset, our proposed MSA-YOLO algorithm significantly outperform the most commonly used baseline models with almost the same model size. This shows the efficiency of our proposed model. (The code and new dataset will be released to the public later.)

Changing the film thickness to manipulate the microstructural properties has been considered as a potential method in practical application. Here, we report that atomic-scale structural properties regulated by film thickness in NiCO2O4(NCO)/CuFe2O4(CFO) bilayer heterostructure prepared on (001)-MgAl2O4 (MAO) substrate by means of aberration-corrected scanning transmission electron microscopy (STEM). The misfit dislocations at NCO/CFO interface and antiphase boundaries (APBs) bound to dislocations within the films both are found in NCO (40 nm)/CFO (40 nm)/MAO heterostructure to contribute to relaxation of mismatch lattice strain. In addition, the non-overlapping a/4[101]-APB is found and the structural transformation of this kind of APB is resolved at atomic scale. In contrast, only the interfacial dislocations form at interface without the formation of APBs within the films in NCO (10 nm)/CFO (40 nm)/MAO heterostructure. Our results provide evidence that formation of microstructural defects can be regulated by changing film thickness to tune magnetic properties of epitaxial bilayer spinel oxide films.

Abstract—Online learning platforms provide diverse course resources, but this often result in the issue of information overload. Learners always want to learn courses that are appropriate for their knowledge level and preferences quickly and accurately. Effective course recommendation plays a key role in helping learners select appropriate courses and improving the efficiency of online learning. However, when a user is enrolled in multiple courses, Existing course recommendation methods face the challenge in accurately recommending the target course that is most relevant to the user, because of the noise courses. In this paper, we propose a novel reinforcement learning model named Actor-Critic Hierarchical Reinforcement Learning (ACHRL). The model incorporates the Actor-Critic method to construct the profile reviser. This can remove noise courses and make personalized course recommendation effectively. Furthermore, we propose a policy gradient based on temporal difference error to reduce the variance in the training process, to speed up the convergence of the model, and improves the accuracy of the recommendation. We evaluate the proposed model on two real datasets, and the experimental results show that the proposed model is significantly outperforms the existing recommendation models (improving 3.77% to 13.66% in terms of HR@5).

According to the development needs of marine seismic station networking, it is necessary to develop a marine seismometer with a networking function to realize quasi-real-time and large-scale long-term observation of undersea seismic signals. This can lay a solid foundation for marine seismic research and research on earth tectonics, activities, and processes. Based on the advantages and disadvantages of the existing observation equipment, this study proposed to develop a new type of the Autonomous Glide Marine Seismometer(AGMS) that can be applied to the global sea area, focusing on the design and study of the main structure of the carrier of the AGMS. The ultimate strength of the ellipsoidal pressure-resistant spherical shell is investigated by using the finite element analysis method. A reasonable finite element analysis model is proposed through comparing the finite element parameter results with the theoretical formulas and relevant specifications. Finally, the design process and strength checking of the pressure-resistant shell of the AGMS are established. These relevant results can also provide a reference for the design of other deep-sea pressure-resistant chambers.

To investigate the photosynthetic change characteristics of mango leaves under enhanced UV-B radiation, adult ‘Tainong No. 1’ mango (Mangifera indica) trees were treated (N=nine individuals) with simulated enhanced UV-B radiation [24 and 96 kJ/(m2·d)] in the field, and the photochemical reactions, activities of key enzymes in carbon assimilation, and the expression of genes were observed. The results showed that compared with the control, there was a decrease in tree yield and nutritional flavor quality of the fruits under the 96 kJ/(m2·d) treatment, while no significant changes were observed under 24 kJ/(m2·d). After 20 or 40 days, leaves’ net photosynthetic rate (Pn), stomatal conductance (Sc), transpiration rate (Tr), intercellular CO2 concentration (Ci), and chlorophyll a/b under exposure to 96 kJ/(m2·d) of UV-B were significantly lower than in the control, whereas chlorophyll a, chlorophyll b, carotenoids, Hill reaction activity, photochemical quenching coefficient (qP), and Rubisco activities were significantly higher. By contrast, the Hill activity and Rubisco activity under 24 kJ/(m2·d) were significantly higher than the control, while Pn, Sc, Tr, Ci, and the content of photosynthetic pigments were similar to the control. The expression of gene coding the Rubisco big subunit (rbcL) was inhibited by the 96 kJ/(m2·d) treatment. We conclude that stomatal limitation was directly induced by 96 kJ/(m2·d), resulting in the inhibition of photosynthesis and the reduction in yield and deterioration of the quality of mango.

The Station logo is a way for a TV station to claim copyright, which can realize the analysis and understanding of the video by the identification of the station logo, so as to ensure that the broadcasted TV signal will not be illegally interfered. In this paper, we design a station logo detection method based on Convolutional Neural Network by the characteristics of the station, such as small scale-to-height ratio change and relatively fixed position. Firstly, in order to realize the preprocessing and feature extraction of the station data, the video samples are collected, filtered, framed, labeled and processed. Then, the training sample data and the test sample data are divided proportionally to train the station detection model. Finally, the sample is tested to evaluate the effect of the training model in practice. The simulation experiments prove its validity.

Due to its spatio-temporal variability, the mismatch between the weather and demand patterns challenges the design of highly renewable energy systems. A principal component analysis is applied to a simplified networked European electricity system with a high share of wind and solar power generation. It reveals a small number of important mismatch patterns, which explain most of the system's required backup and transmission infrastructure. Whereas the first principal component is already able to reproduce most of the temporal mismatch variability for a solar dominated system, a few more principal components are needed for a wind dominated system. Due to its monopole structure the first principal component causes most of the system's backup infrastructure. The next few principal components have a dipole structure and dominate the transmission infrastructure of the renewable electricity network.

Chronic hemodialysis (HD) patients have very high cardiovascular risk. Acute vascular changes during dialysis mediated by factors of the endothelium may have a crucial role in this. Aim: To study acute vascular changes during HD. In 29 consecutive chronic HD patients (age: 65.6±10.4 years) pre-, mid-, and post-HD plasma syndecan-1 (SDC-1) and endothelin-1 (ET-1) levels were measured. Applanation tonometry was performed before HD. SDC-1 levels increased during HD (p=0.004). Males had higher ET-1 levels. Patients were divided into 2 groups based on pulse wave velocity (PWV): PWV≥12 m/s and PWV<12 m/s. Pre-HD and mid-HD SDC-1 levels were higher in the group with PWV≥12 m/s (10.174±2.568 vs. 7.928±1.794 ng/ml, p=0.013, and 10.319±3.482 vs. 8.248±1.793 ng/ml, p=0.044, respectively). Post-HD ET-1 levels were higher in the patient group having PWV≥12 m/s (10.88±3.00 vs. 8.05±3.48 pg/l, p=0.027). Patients having PWV≥12 m/s had higher pre-HD peripheral and aortic systolic blood pressure (p<0.05). Total cholesterol correlated with the SDC-1 decrease during HD (r=0.539; p=0.008). Pre-, mid-, and post-HD SDC-1 correlated with the ultrafiltration (r=0.432, p=0.019; r=0.377, p=0.044; and r=0.401, p=0.012, respectively). SDC-1 and ET-1 contribute to vascular changes observed during HD, and they have correlations with some cardiovascular risk factors.

Natural killer cells are associated with the pathogenesis of ulcerative colitis (UC), but their precise contributions remain unclear. The present study sought to investigate the diagnostic value of activated NK-associated genes (ANAGs) in UC. Bulk RNA-seq and scRNA-seq datasets were obtained from the Gene Expression Omnibus (GEO) and Single Cell Portal (SCP) databases. In the bulk RNA-seq, 92 differentially expressed genes (DEGs) were screened out by the “Batch correction” and “Robust rank aggregation” (RRA) methods. The immune infiltration landscape was estimated by single-sample gene set enrichment analysis (ssGSEA) and CIBERSORT, which revealed a higher abundance of activated NK cells in noninflamed UC tissues. 54 DEGs correlated with activated NK cells were identified as ANAGs. Protein-protein interaction (PPI) analysis and least absolute shrinkage and selection operator (LASSO) regression were utilized to screen out 4 key ANAGs (SELP, TIMP1, MMP7, and ABCG2) and establish an activated NK-associated gene score (ANAG score). The ANAG score demonstrated excellent diagnostic value and was validated in three external datasets. The expression of the 4 key ANAGs was validated in UC patients and healthy controls (HC) samples. Through scRNA-seq data analysis, higher expression levels of SELP, TIMP1, MMP7, and ABCG2 were observed in post-capillary venules, inflammatory fibroblasts, enterocytes, and immature enterocytes. The cell scores based on the ANAGs showed enrichment in endothelial cells and fibroblasts. In conclusion, we established and validated an ANAG score with the ability to precisely diagnose UC. The 4 key ANAGs have the potential to serve as therapeutic targets in UC.

Three kinds of Ni based alloy cladding coatings were prepared on 316L stainless steel at different power. The microstructure of the cladding layer was observed and analyzed by XRD, metallographic microscope and SEM. The hardness of the cladding layer was measured, and the wear resistance of the cladding layer was tested by friction instrument. The results show that the effect of laser cladding is good and the cladding layer has a good metallurgical bonding with the substrate. Different microstructures such as dendritic and equiaxed grains can be observed in the cladding layer. With the increase of laser power, more equiaxed and columnar dendrites can be observed. The phase composition of the cladding layer is mainly composed of γ - Ni solid solution and some intermetallic compounds such as Ni3B, Cr5B3 and Ni17Si3. The results of EDS show that there are some differences in the distribution of C and Si between dendrites. The hardness of the cladding layer is about 600 HV0.2, which is about three times of the substrate (~ 200 HV0.2). Through the analysis of the wear morphology, the substrate wear is serious, there are serious shedding, mainly adhesive wear and abrasive wear. However, the wear of cladding layer is slight, which is abrasive wear, and there are some grooves on the surface.

Natural products are an important source of antibacterial agents. Canthin-6-one alkaloids have displayed potential antibacterial activity based on our previous work. In order to improve the activity, twenty-two new 3-N-benzylated 10-methoxy canthin-6-ones were designed and synthesized through quaternization reaction. The in vitro antibacterial activity against three bacteria was evaluated by double dilution method. Four compounds (6f, 6i, 6p and 6t) displayed 2-fold superiority (minimum inhibitory concentration (MIC) = 3.91 µg/mL) against agricultural pathogenic bacteria R. solanacearum and P. syringae than agrochemical propineb. Moreover, the structure–activity relationships (SARs) were also carefully summarized in order to guide the development of antibacterial canthin-6-one agents.

The incidence of carbapenem-resistant Enterobacteriaceae (CRE) has been increasing considerably annually since being first reported in 2008. Gyeonggi Province has the largest number of healthcare facilities in South Korea, which contribute to its regional vulnerability to CRE infections. Thus, there is a need to obtain up to date information on the occurrence of CRE infections in the Gyeonggi Province to take corrective measures. Therefore, in this study, we aimed to investigate the overall trends of CRE occurrence in Gyeonggi Province over the past 4 years and the epidemiological characteristics of CRE-related mortality. Patients admitted to a healthcare facility in Gyeonggi Province from January 2018 to December 2021 with positive blood cultures to CRE were included in the study and investigated. Additionally, the risk factors for CRE-related death were determined using data from CRE-positive patients who died within 30 days of last blood sampling. Older adults aged 70 and over accounted for the highest percentage of both survivors and non-survivors with CRE bacteremia. The number of non-survivors was higher in tertiary hospitals and among patients in intensive care unit. There were no significant differences in the mortality risk according to the use of antibiotics. Moreover, non-survivors were predominant among patients with hypertension, malignant tumor, and those having two or more underlying diseases. Klebsiella pneumoniae was the most common CRE strain in both survivors and non-survivors. Among the survivors, carbapenemase-producing Enterobacteriaceae was detected in 151 cases (71.2%) and 49 cases (23.1%) in the KPC and NDM groups, respectively. Among the non-survivors, it was detected in 25 cases (86.2%) and 5 cases (17.2%) in the KPC and NDM groups, respectively. The endemicity of CRE in South Korea has been proposed for several years; our results have suggested endemicity of CRE in the Gyeonggi Province. Despite the strengthened infection control policies in healthcare facilities during the pandemic, there has been an increasing trend in the isolation of CRE strains in South Korean long-term care hospitals and hospitals within Gyeonggi Province. Factors such as history of hospitalization and underlying diseases have been identified as risk factors for CRE-related deaths. However, to address this issue strictly, it is important to establish infection control infrastructure tailored based on each type of healthcare facility, and elaborate specific government support measures, accordingly.

Inflammation is the response of the immune system to infection and injury, with complex interactions with the body, tissues and cells, and plays an important role in the initiation and progression of many diseases such as cancer and cardiovascular disease. Traditional excipients functioning as drug delivery systems can reduce the side effects of systemic distribution of inflammatory drugs. Oil phase, a common excipient in nanoemulsions (NEs), has the advantages of assisting the formation of emulsions, loading lipophilic drugs, thermodynamic stability, wide sources, low price and easy availability. In particular, some of them, like linolenic acid and medium chain triglyceride (MCT), also function as inhibitors of systemic inflammation marker and vascular inflammation marker. However, the influences of different oil phases on the construction of NEs and their distribution in vivo have not been fully investigated. Herein, Tween 80 and ethyl alcohol were screened out as emulsifiers and co-emulsifiers, and three different oil phases used in clinical practice widely, including MCT, oleic acid (OA), and ethyl oleate (EO), were selected as the oil phase to prepare NEs delivery platform. Three NEs had consistent size, potential, morphology, excellent stability and mitochondrial localization function. Importantly, they exhibited superior cellular uptake capacity in inflammatory-injuried human umbilical vein endothelial cells and significantly targeted the brain, lung, heart and thoracic aorta in the lipopolysaccharide-induced mouse and zebrafish larvae inflammation models. Meanwhile, the fluorescence intensities of three NEs were different in these organs, suggesting that their differential enrichment might provide alternative delivery platform for disease treatment in the corresponding organs.

The application of AI technology in urban planning covers multiple levels, such as data analysis, decision support, and automated planning. Urban research relies on AI technology to understand and summarize the law of urban growth and improve the analysis of the evolution trend of urban space. Planning and design use AI technology to explore the relevant factors affecting urban development and their weights and discuss the critical role of green building technology in the sustainable development of the construction industry. With the increase in global energy consumption and carbon emissions, traditional building methods can no longer meet environmental protection requirements and efficient use of resources. As a sustainable development solution, green building technology has been paid more and more attention to and adopted by people. These technologies focus not only on the energy efficiency and environmental impact of buildings but also on the resource utilization and environmental load of green buildings over their entire life cycle driven by machine learning. This paper details the basic principles and applications of green building technologies, including AI-driven reduction of negative environmental impacts, improvement of occupant health, efficient use of resources, and optimization of indoor environmental quality. This paper focuses on the critical role of the LEED assessment system developed by the U.S. Green Building Council in advancing green building practices. In addition, the paper analyzes vital points such as water use in green building design, machine learning-driven wind environment optimization, solar technology application, and practical application cases of these technologies on a global scale.

Rose (Rosa spp.), especially R. hybrida, is one of the most popular ornamental plants in the world and the third largest cut flower crop in Taiwan. Rose mosaic disease (RMD), showing mosaic, line patterns and ringspots on leaves, is a common rose disease caused by complex infection of various viruses. Due to pests and diseases, the rose planting area in Taiwan has been decreasing since 2008; however, no rose virus disease has been reported in the past five decades. In the spring of 2020, rose samples showing RMD-like symptoms were observed at an organic farm in Chiayi, central Taiwan. The virome in the farm was analyzed by RNA-seq. Rose genomic sequences were filtered from the obtained reads. The remaining reads were de novo assembled to generate 294 contigs, 50 of which were annotated as viral sequences corresponding to 10 viruses. Through reverse transcription-polymerase chain reaction validation, a total of seven viruses were detected, including six known rose viruses, namely apple mosaic virus, prunus necrotic ringspot virus, rose partitivirus, apple stem grooving virus, rose spring dwarf-associated virus and rose cryptic virus 1, and a novel ilarvirus. After completing the whole genome sequencing and sequence analysis, the unknown ilarvirus was demonstrated as a new species, tentatively named rose ilarvirus 2. This is the first report of the rose viruses in Taiwan.

Artificial Intelligence (AI) is poised to revolutionize the architectural design and energy management of green buildings, offering significant advancements in sustainability and efficiency. This paper explores the transformative impact of AI on improving energy efficiency and reducing carbon emissions in commercial buildings. By leveraging AI algorithms, architects can optimize building performance through advanced environmental analysis, automation of repetitive tasks, and real-time data-driven decision-making. AI facilitates precise energy consumption forecasting and integration of renewable energy sources, enhancing the overall sustainability of buildings. Our study demonstrates that AI can reduce energy consumption and CO2 emissions by approximately 8% and 19%, respectively, in typical mid-size office buildings by 2050 compared to conventional methods. Further, the combination of AI with energy efficiency policies and low-emission energy production is projected to yield reductions of up to 40% in energy consumption and 90% in CO2 emissions. This paper provides a systematic approach for quantifying AI's benefits across various building types and climate zones, offering valuable insights for decision-makers in the construction industry.

This study presents a novel approach to enhance Large Language Models (LLMs) like Alpaca by dynamically integrating real-time information. This method addresses the issue of content hallucination and data relevancy by automatically collecting and integrating current data from credible sources into model prompts. Experiments show a significant improvement in accuracy and a decrease in content hallucination, with a manageable increase in response time. The research underscores the potential of real-time data integration in making LLMs more accurate and contextually relevant, setting a foundation for future advancements in dynamic data processing in AI.

Time series data having low signal-to-noise ratio, non-stationarity and non-linearity are commonly seen in high-frequency stock trading, where the objective is to increase the likelihood of profit by taking advantage of tiny discrepancies in prices and trading on them quickly and in huge quantities. For this purpose, it is essential to apply a trading method that is capable of fast and accurate prediction from such time series data. In this paper, we develop an online time series forecasting method for high-frequency trading (HFT) by integrating three neural network deep learning models, i.e., Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU) and Transformer; and we abbreviate the new method to online LGT or O-LGT. The key innovation underlying our method is its efficient storage management, which enables super-fast computing. Specifically, when computing the forecast for the immediate future time, we use only the output calculated from the previous trading data (rather than the previous trading data themselves) together with the current trading data. Thus, the computing involves updating only the current data into the process. We evaluate the performance of O-LGT by analyzing the high-frequency Limit Order Book (LOB) data from the China market. It shows that our model in most cases achieves similar speed with much higher accuracy than the conventional fast supervised learning models for HFT. However, with a slight sacrifice in accuracy, O-LGT is approximately 40 times faster than the existing high-accuracy neural network models for the LOB data in China market.

Many countries have implemented free early childhood education to solve the affordability and accessibility problems without considering the sustainability of policy; thus, they have to discontinue the policy. The city of Nanjing, China, is no exception. This case study adopted a mixed-methods approach to understanding how and why the policy was formulated, implemented, and failed in the city, using the “policy cycle” framework. Altogether 232 kindergarten principals and teaching/research staff were randomly sampled and surveyed, and 5 kindergarten principals and 5 teaching/researcher staff were interviewed. The results indicated that there were many obstacles to the policy’s sustainability, including the conflict of interest, the inefficient policy implementation, the insufficient funding, and more social inequality issues. And the policymakers made mistakes in the five domains of the policy cycle: the context of influence, the context of policy text production, the context of practice, the context of outcomes, and the context of political strategy. Finally, the lessons for a more sustainable policy decision process are discussed.

HIV-associated neurocognitive disorder (HAND) is an array of neurocognitive changes associated with HIV infection, and the roles of microRNAs in HAND are not completely revealed yet. Based on published data and publicly available databases, we constructed an integrated miRNA-mRNA network involved in HAND. Bioinformatics analyses, including gene ontology, network analysis, and KEGG pathway analysis, were applied for further study of the network and the genes of the network. The axon guidance KEGG pathway, three genes NTNG1, EFNB2, CXCL12, and 17 miRNAs which regulates them, are spotlighted in our study. This study provides new perspectives to the knowledge of miRNAs’ roles in the process of HAND, and our findings provided potential therapeutic targets and clues of HAND.

Climate change and environmental degradation are major threats to sustainable agricultural development in Southern Africa. Thus, the concept of sustainable intensification (SI) i.e. getting more output from less input using certain practices such as agroforestry, organic fertilizer, sustainable water management etc. has become an important topic among researchers and policy makers in the region in the last three decades. A comprehensive review of literatures on the adoption of SI in the region identify nine relevant drivers of adoption of SI among (smallholder) farmers. These drivers include (i) age, (ii) size of arable land, (iii) education, (iv) extension services, (v) gender, (vi) household size, (vii) income, (viii) membership in farming organization and (ix) access to credit. We present the results of a meta-analysis of 21 papers on the impact of these determinants on SI adoption among (smallholder) farmers in Southern African Development Community (SADC) using random-effects estimation techniques for the true effect size. While our result suggests that variables such as extension services, education, age, and household size may influence the adoption of SI in SADC, factors such as access to credit is also of great importance. Decision-makers should therefore concentrate efforts on these factors in promoting SI across the SADC. This includes increasing the efficiency of public extension service as well as involvement of private sector in extension service. Furthermore, both public and private agriculture financing models should consider sustainability indicators in their assessment process.

The purpose of this paper was to analyze the development trend of hazardous chemical packaging towards low carbon economy from both qualitative and quantitative perspectives. Four types of relatively small volume packaging with volume/weight less than 450L/400kg, respectively, and three intermediate bulk containers (IBCs), which are widely used for hazardous chemicals were studied to calculate the carbon footprint (CF) from cradle to grave using life cycle assessment (LCA) method and to predict the future carbon emission of hazardous chemical packaging in the next five years (2016-2020), based on the export data of Tianjin Port in China. Grey model (GM) was adopted in the prediction. The results showed that majority of IBCs have lower carbon footprint than other types when the packaging contained same amount of same hazardous chemical. With the development of international trading, the demand of hazardous chemicals will increase as well. As the result, carbon emission generated by hazardous chemical packaging will increase accordingly. However, based on GM simulation result, increasing the amount of IBC use will effectively reduce the relative amount of carbon emission.

Under the development mode of deep blending of emerging technologies, major projects are important for enhancing China's comprehensive national strength and independent innovation capability. Based on the social benefits of major projects, and considering the influence of reputation factors, an evolutionary game model composed of a general contractor and subcontractor of major projects is established. This paper studies the influence of various factors including the income distribution coefficient of collaborative innovation, and MATLAB simulation software is analyzed the influence of factors on an evolutionary path. The results show that a reasonable income distribution coefficient can promote the game behavior of both parties to the direction of active collaborative innovation; The reduction of innovation cost and the improvement of spillover technology absorption capacity can make innovation subjects tend to choose active collaborative innovation strategies. In addition, reputation loss above a specific threshold can effectively inhibit free-riding behavior and encourage innovation subjects to choose active collaborative innovation strategies. The research results provide reference for promoting major projects' technology innovation.

Epsilon-near-zero nanoantennas can be used to tune the far-field radiation pattern due to their exceptionally large intensity-dependent refractive index. Here, we propose hybrid optical antenna based on indium tin oxide (ITO) to optically tune the deflection of radiation. In particular, a hybrid structure antenna of ITO and dielectric material, which makes the deflection angle changes 17 ∘ as incident intensities increases. Finally, the array of ITO or hybrid nanodisks can enhance the unidirectionality to be needle-like, with the angular beam width α&lt; 8∘ of main lobe. The deflection angle of radiation pattern response with needle-like lobe pave the way for further studies and applications in beam steering and optical modulation where dynamic control of the nanoantennas is highly desirable.

To solve the problem of low efficiency of source seeking in implicit information field, this paper presents an autonomous souring method based on balanced searching strategy is enlighten by biological homing behaviors. At the beginning of the research, the source seeking task come down to a multi-objective convergence issue. By taking the feasibility search behaviors as the individual sample of the evolutionary population drawing on the thought of evolutionary algorithms, then combine motion searching with population evolution, so the carrier can be guide to complete source seeking task by solving the multi-objective problem. Furthermore, the distribution entropy is also considerated d to measure the searching bias in the process of source seeking. Combined with the demand of the source seeking process, a new source seeking method of balanced searching strategy is designed. Ultimately, through theoretical analysis and simulation verification confirm the effectiveness and rationality of the proposed method.

The electronic structural evolution of LLM-105 crystal and the (101) plane of LLM-105 crystal under different pressures is investigated by the density functional theory (DFT) calculations and the surface properties of seven low-Miller-index planes of LLM-105 crystal were investigated in this study. The result demonstrates that the surface energy of (101) plane of LLM-105 is much smaller when compared with other low-Miller-index planes of LLM-105.In order to further investigate the stability of crystal structure and (101) plane of LLM-105 under different pressures, a series of pressures ranged from 0 GPa to 55 GPa were applied during the DFT calculation, and the result shows that the electronic structures of LLM-105 crystal and the (101) plane changed with the increase of external pressure and the evolution process of (101) plane is different from that of LLM-105 crystal structure.

The Omicron EG.5 lineage of SARS-CoV-2 is currently on a trajectory to become a dominant strain. This phase 2 study aims to evaluate the immunogenicity of SCTV01E-2, a tetravalent protein vaccine, with a specific emphasis on its effectiveness against Omicron EG.5, comparing it with its progenitor vaccine, SCTV01E (NCT05933512). As of September 12, 2023, 429 participants aged ≥18 years were randomized to SCTV01E (N=215) or SCTV01E-2 (N=214) groups. Both vaccines showed increases in neutralizing antibody (nAb) against Omicron EG.5, with a 5.7-fold increase and a 9.0-fold increase in SCTV01E and SCTV01E-2 groups 14 days post-vaccination, respectively. The predetermined statistical endpoints were achieved, showing that the geometric mean titer (GMT) of nAb and the seroresponse rate (SRR) against Omicron EG.5 were significantly higher in the SCTV01E-2 group compared to SCTV01E. Additionally, SCTV01E and SCTV01E-2 induced a 5.5-fold and a 5.9-fold increase of nAb against XBB.1, respectively. Reactogenicity was generally mild and transient. No vaccine related SAEs, AESIs or deaths were reported. In summary, SCTV01E-2 elicited robust neutralizing responses against Omicron EG.5 and XBB.1 without safety concerns, underlining its potential as a versatile COVID-19 vaccine against SARS-CoV-2 variants.

Tourism sustainability is a significant approach to forming a synergistic model of industry and ecology in ecologically vulnerable areas. Scientifically detecting the effect mechanism of tourism development (TDI) on eco-environment resilience (ERI) is important in achieving regional social-ecological system sustainability. Empirical exploration is conducted on the levels of TDI and ERI in the Yangtze River Economic Belt (YREB) to study the spatiotemporal heterogeneity of TDI's effect on ERI. The results indicate a significant growth in TDI in the YREB, with the formation of tourist clusters around Shanghai and Chongqing as the core. Although ERI typically exhibits a declining trend, the rate of decline has notably slowed, forming a "high at the sides and low in the middle" spatial pattern. TDI and ERI are spatially dependent in the YREB, with predominantly high-high (HH) and low-high (LH) clusters in Shanghai, Zhejiang, and Jiangsu. Conversely, upstream regions with strong eco-environmental foundations exhibit low-low (LL) and high-low (HL) clusters. In general, TDI promotes ERI, but there is significant spatiotemporal heterogeneity in the YREB. Positive impact regions are expanding, while negative impact regions are shrinking. These results could provide scientific evidence for differentiated classification and control policies in the YREB.

We firstly present two popular space discretization models of the Nonlinear Schrödinger Equation in dark solitons motion : the Direct-Discrete model and the Ablowitz-Ladik model. Applying the midpoint scheme to the space discretization models, we get two time-space discretization models: the Crank-Nicolson method and the New-Difference method. Secondly, we demonstrate that the solutions of the two space discretization models converge to the solution of the Nonlinear Schrödinger Equation. Also, we prove that the convergence order of the two time-space discretization models are O(h2+τ2) in discrete L2-norm error estimates. Finally, the numerical experiments agree well with the proven theoretical results.

With the rapid development of Internet of Vehicles (IoV), particularly the introduction of mobile edge computing (MEC), vehicles can efficiently share data with one another. However, edge computing nodes are vulnerable to various network attacks, posing security risks to data storage and sharing. Moreover, the presence of abnormal vehicles during the sharing process poses significant security threats to the entire network. To address these issues, this paper proposes a novel reputation management scheme, which proposes an improved multi-source multi-weight subjective logic algorithm. This algorithm fuses direct and indirect opinion feedback of nodes through the subjective logic trust model while considering factors such as event validity, familiarity, timeliness, and trajectory similarity. Vehicle reputation values are periodically updated, and abnormal vehicles are identified through reputation thresholds. Finally, blockchain technology is employed to ensure the security of data storage and sharing. By analyzing real vehicle trajectory datasets, the algorithm is proven to effectively improve the differentiation and detection rate of abnormal vehicles.