In the paper, by virtue of a Lévy–Khintchine representation and an alternative integral representation for the weighted geometric mean, the authors establish a Lévy–Khintchine representation and an alternative integral representation for the Toader–Qi mean. Moreover, the authors also collect an probabilistic interpretation and applications in engineering of the Toader–Qi mean.

In the paper, the authors survey integral representations of the Catalan numbers and the Catalan–Qi function, discuss equivalent relations between these integral representations, supply alternative and new proofs of several integral representations, collect applications of some integral representations, and present sums of several power series whose coefficients involve the Catalan numbers.

In the paper, the authors find two explicit formulas and recover a recursive formula for the generalized Motzkin numbers. Consequently, the authors deduce two explicit formulas and a recursive formula for the Motzkin numbers, the Catalan numbers, and the restricted hexagonal numbers respectively.

In the paper, the authors establish two identities to express the generating function of the Chebyshev polynomials of the second kind and its higher order derivatives in terms of the generating function and its derivatives each other, deduce an explicit formula and an identities for the Chebyshev polynomials of the second kind, derive the inverse of an integer, unit, and lower triangular matrix, present several identities of the Catalan numbers, and give some remarks on the closely related results including connections of the Catalan numbers respectively with the Chebyshev polynomials, the central Delannoy numbers, and the Fibonacci polynomials.

In this paper, we establish the generalized Qi-type inequality involving conformable fractional integrals. The results presented here would provide extensions of those given in earlier works.

In the paper, the authors establish two identities, which can be regarded as nonlinear differential equations, for the generating function of Eulerian polynomials, find two identities for the Stirling numbers of the second kind, and present two identities for Eulerian polynomials and higher order Eulerian polynomials, pose two open problems about summability of two finite sums involving the Stirling numbers of the second kind. Some of these conclusions meaningfully and significantly simplify several known results.

In the paper, the authors present unified generalizations for the Bell numbers and polynomials, establish explicit formulas and inversion formulas for these generalizations in terms of the Stirling numbers of the first and second kinds with the help of the Faà di Bruno formula, properties of the Bell polynomials of the second kind, and the inversion theorem connected with the Stirling numbers of the first and second kinds, construct determinantal and product inequalities for these generalizations with aid of properties of the completely monotonic functions, and derive the logarithmic convexity for the sequence of these generalizations.

In the paper, using two inversion theorems for the Stirling numbers and binomial coecients, employing properties of the Bell polynomials of the second kind, and utilizing a higher order derivative formula for the ratio of two dierentiable functions, the authors present two explicit formulas, a determinantal expression, and a recursive relation for a sequence of unnamed polynomials, derive two identities connecting the sequence of unnamed polynomials with the Bell polynomials, and recover a known identity connecting the sequence of unnamed polynomials with the Bell polynomials.

In the paper, by virtue of the Faà di Bruno formula, some properties of the Bell polynomials of the second kind, and an inversion formula for the Stirling numbers of the first and second kinds, the authors establish meaningfully and significantly two identities which simplify coefficients in a family of ordinary differential equations associated with higher order Bernoulli numbers of the second kind.

In the paper, by virtue of the Fa`a di Bruno formula, some properties of the Bell polynomials of the second kind, and the inversion formulas of binomial numbers and the Stirling numbers of the first and second kinds, the authors simplify meaningfully and significantly coefficients in two families of ordinary differential equations associated with higher order Frobenius–Euler numbers.

In the note, the authors find several simple and explicit forms for a family of inhomogeneous linear ordinary differential equations studied in "D. Lim, Differential equations for Daehee polynomials and their applications, J. Nonlinear Sci. Appl. 10 (2017), no. 4, 1303-1315; Available online at http://dx.doi.org/10.22436/jnsa.010.04.02".

In the paper, the authors nd a new closed expression for the Fibonacci polynomials and, consequently, for the Fibonacci numbers, in terms of a tridiagonal determinant.

In the paper, by virtue of techniques in combinatorial analysis, the authors simplify two families of nonlinear ordinary differential equations in terms of the Stirling numbers of the first kind.

The zero velocity update(ZUPT) algorithm is the core of a foot-mounted pedestrian navigation system. The zero velocity detection method is the premise and guarantee of the effective application of the ZUPT algorithm. To make ZUPT work properly, it is necessary to detect zero velocity intervals correctly. The detection accuracy of the existing zero velocity detection methods is easy to be affected by users and environment. A novel zero velocity detection method based on the plantar pressure is proposed in this paper, which has higher detection accuracy and better environmental adaptability. First, the paper analyzes the motion characteristics of foot during walking. Second, the inherent relationship between the plantar pressure and the gait change during walking is studied based on the pressure sensor. Then, the model of the zero velocity detection method using the plantar pressure is established. Finally, the indoor and outdoor multi-scene experiments show that this method not only has a high detection accuracy, but also has good adaptability to users and walking environment.

Fiber-based flexible sensors have promising applications potential in human motion and healthcare monitoring, owing to their merits of lightweight, flexibility, and easy processing. Now, high-performance elastic fiber-based strain sensors with high sensitivity, large working range and excellent durability are in great demand. Herein, we have easily and quickly prepared a highly-sensitive, durable fiber-based strain sensor by dip-coating of highly-stretchable polyurethane (PU) elastic fiber in MXene/ waterborne polyurethane (WPU) dispersion solution. Benefiting from the electrostatic repulsion force between the negatively charged WPU and MXene sheets in the mixed solution, very homogeneous and stable MXene/WPU dispersion was successfully obtained and the interconnected conducting networks were correspondingly formed in coated MXene/WPU shell layer, which makes as-prepared strain sensor exhibit a gauge factor of over 960, a large sensing range of over 90% and detection limit as low as 0.5% strain. As elastic fiber and mixed solution have the same polymer constitute, tight bonding of MXene/WPU conductive composite on PU fibers was achieved, enabling the as-prepared strain sensor endure over 2500 stretching-releasing cycles and thus show good durability. Full-scale human motion detection was also performed by the strain sensor, and a body posture monitoring, analysis, and correction prototype system was developed via embedding the fiber-based strain sensors into sweater, strongly indicating the great application prospect in exercise, sports and healthcare.

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

In the paper, the authors view some ordinary differential equations and their solutions from the angle of (the generalized) derivative polynomials and simplify some known identities for the Bernoulli numbers and polynomials, the Frobenius-Euler polynomials, the Euler numbers and polynomials, in terms of the Stirling numbers of the first and second kinds.

Cooking is a very decentralized and private way of energy consumption in human activities. The existing investigation and statistical analysis can’t effectively calculate the proportion of population relying on clean cooking fuel and utilization technology in the region. Therefore, based on the big data of the earth, this paper adopts the combination of spatial analysis and statistical analysis to determine the survey sample area, and according to the economic conditions, topographic characteristics, national policies for new energy construction and living habits of the provinces and cities under investigation, the questionnaire survey is conducted for the research area to calculate the proportion of the regional population relying on clean cooking fuels and utilization technologies. Taking the south of the Yangtze River in China as an example, the paper effectively calculates that 88.25% of the population depends on clean cooking fuel and technology in this region, of which 89.81% are in urban areas and 79.87% are in rural areas. Analysis of the survey data shows that the proportion of the population using clean cooking fuels and technologies is related to factors such as economic development, income and resource endowment. There is a large urban–rural gap in terms of energy consumption tendency and structure in the south of the Yangtze River in China and cooking energy consumption in rural households also varies from region to region. The technical ideas and conclusions of the paper have high reference application value, which can help promote the upgrading of clean energy utilization and provide data basis for relevant decision and policy making.

In the paper, by a very simple approach, the author establishes an expression in terms of a lower Hessenberg determinant for the Euler polynomials. By the determinantal expression, the author finds a recurrence relation for the Euler polynomials. By the way, the author derives the corresponding expression and recurrence relation for the Euler numbers.

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

Semi-continuous data are very common in the social science and economics. In this paper, a Bayesian variable selection procedure is developed to assess the influence of exogenous factors including observed and unobserved on the semi-continuous data. Our formulation is based on the two-part latent variable model with polytomous response. We consider two schemes for the penalties of regression coefficients and factor loadings: the Bayesian spike and slab bimodal prior and the Bayesian lasso prior. Within the Bayesian framework, we implement Markov Chains Monte Carlo sampling method to conduct posterior inference. To facilitate posterior sampling, we recast the logistic model in part one as the norm-like mixture model. Gibbs sampler is designed to draw observations from the posterior. Our empirical results show that with suitable hyper-parameters, the spike and slab bimodal method slightly outperforms the Bayesian lasso in the current analysis. Finally, a real example related to the China household finance survey is analyzed to illustrate the application of the methodology.. .

Expansion tube is ideal energy absorber which dissipates kinetic energy through plastic deformation and friction. There is an urgent need to understand the influence of key parameter, e.g. semi angle, tube material, and friction coefficient, on the mechanical response and energy absorption characteristics of expansion tube. In the present work, the material properties of the tubes were tested under quasi-static loading condition, and the numerical simulations were carried out by using commercial software ABAQUS. Based on the validated finite element simulation, all the semi angle, tube material, and friction have significant effects on the energy absorption capacity of expansion tube. The expansion tube with high tensile stress of parent material have high energy absorption capacity, while the specific energy absorption is linear with the tensile stress/density of tube material. This work would give a guidance to the structural design and parent materials selection for expansion tubes.

This study investigates anomaly detection of IoT device traffic using Convolutional Neural Networks (CNN) and Variational Autoencoders (VAE) to enhance the detection capability of security threats in IoT environments. A series of hardware configurations, software environments, and hyperparameters were utilized to optimize the training and testing processes of the models. The CNN model demonstrates robust classification performance, achieving an accuracy rate of 95.85% on the test dataset, effectively distinguishing between different types of IoT device traffic. Meanwhile, the VAE model exhibits proficient anomaly detection capabilities by effectively capturing abnormal patterns in the data using reconstruction loss and KL divergence. The combined use of CNN and VAE models offers a comprehensive solution to cybersecurity challenges in IoT environments. Future research directions include exploring diverse IoT traffic data, practical deployment for validation, and further optimization of model structures and parameters to improve performance and applicability.

In the paper, by virtue of the Faá di Bruno formula and two identities for the Bell polynomial of the second kind, the authors find a closed form for the Stirling polynomials in terms of the Stirling numbers of the first and second kinds.

In the paper, the authors present an explicit form for a family of inhomogeneous linear ordinary differential equations, find a more significant expression for all derivatives of a function related to the solution to the family of inhomogeneous linear ordinary differential equations in terms of the Lerch transcendent, establish an explicit formula for computing all derivatives of the solution to the family of inhomogeneous linear ordinary differential equations, acquire the absolute monotonicity, complete monotonicity, the Bernstein function property of several functions related to the solution to the family of inhomogeneous linear ordinary differential equations, discover a diagonal recurrence relation of the Stirling numbers of the first kind, and derive an inequality for bounding the logarithmic function.

In the paper, the authors consider the generating functions of the Hermite polynomials and their squares, present explicit formulas for higher order derivatives of the generating functions of the Hermite polynomials and their squares, which can be viewed as ordinary differential equations or derivative polynomials, find differential equations that the generating functions of the Hermite polynomials and their squares satisfy, and derive explicit formulas and recurrence relations for the Hermite polynomials and their squares.

Aiming at the problem that dynamic targets in indoor environments lead to low accuracy and large errors in the localization and position estimation of visual SLAM systems and the inability to build maps containing semantic information, a semantic visual SLAM algorithm based on the semantic segmentation network DeepLabV3+ and LK optical flow is proposed based on ORB-SLAM2 system. First, the dynamic target feature points are detected and rejected based on the lightweight semantic segmentation network DeepLabV3+ and LK optical flow method. second, the static environment occluded by the dynamic target is repaired using the time-weighted multi-frame fusion background repair technique. Lastly, the filtered static feature points are used for feature matching and position calculation. Meanwhile, the semantic labeling information of static objects obtained based on the lightweight semantic segmentation network DeepLabV3+ is fused with the static environment information after background repair to generate dense point cloud maps containing semantic information, and the semantic dense point cloud maps are transformed into semantic octree maps using the octree spatial segmentation data structure. The localization accuracy of the visual SLAM system and the construction of the semantic maps are verified using the TUM RGB-D widely used dataset and real scene data, respectively. The experimental results show that the proposed semantic visual SLAM algorithm can effectively reduce the influence of dynamic targets on the system, has a higher localization accuracy, and compared with other advanced algorithms, such as DynaSLAM, has the highest performance in indoor dynamic environments while considering both localization accuracy and real-time performance. In addition, semantic maps can be constructed so that the robot can better understand and adapt to the indoor dynamic environment.

In the paper, the authors find closed forms for derangement numbers in terms of the Hessenberg determinants, discover a recurrence relation of derangement numbers, present a formula for any higher order derivative of the exponential generating function of derangement numbers, and compute some related Hessenberg and tridiagonal determinants.

Analyzing horse behavior is crucial for assessing training quality, particularly in accurately identifying actions like standing, walking, and running. Research has been conducted both domestically and internationally in this regard; however, challenges persist, including reliance on single sensors, poor real-time performance, and low identification accuracy. In view of these challenges, this study investigated real-time identification of horse behavior based on wearable devices. The system, centered around a microcontroller and utilizing a 4G network as a carrier, employs multi-axis IMU sensors as input sources to perceive horse posture. The study proposed a behavior classification method based on analysis of acceleration thresholds. The method consists primarily of two sequential stages: first, the resultant acceleration interval counting method, which employs a nonlinear segmentation approach for initial behavior classification; and second, the statistical analysis of variance parameters between segments, which when coupled with multi-level threshold processing, achieves a refined classification. Experimental results indicated that the interval counting method alone achieved an accuracy of 87.55%, while for the variance analysis method alone the accuracy was 90.87%. The proposed method, comprising the two stages, reached a classification accuracy of 91.57%, underpinning its usefulness in supporting future equine research.

In the paper, the author introduces the notions "multi-order logarithmic numbers" and "multi-order logarithmic polynomials", establishes an explicit formula, an identity, and two recurrence relations by virtue of the Faa di Bruno formula and two identities of the Bell polynomials of the second kind in terms of the Stirling numbers of the fi rst and second kinds, and constructs some determinantal inequalities, product inequalities, logarithmic convexity for multi-order logarithmic numbers and polynomials by virtue of some properties of completely monotonic functions.

Desert ecosystem occupies an important position in the composition of global biodiversity. The Tarim Basin locates in south Xinjiang of China and has the world 's second largest mobile desert, the Taklamakan Desert. As an endemic species in this region, Phrynocephalus forsythii has been demonstrated with potential high extinction risk to climate change. In order to understand the overall genetic status and provide accordant conservation strategies of the species, we investi-gated the genetic diversity and population structure of P. forsythii from 15 sites in the Tarim Basin using 21 highly polymorphic microsatellite markers. We found significant genetic structure across the study region. We also revealed generally low levels of gene flow between the 25 sites, sug-gesting individual dispersal and migration may be restricted within populations. In addition, geographical distance and ambient temperature might be important factors in explaining the observed genetic structure. Our results will provide scientific basis for the future protection of P. forsythii in this area, as well as an important reference for the conservation and management of biodiversity in desert ecosystems.

Soil water content (SWC) and soil organic carbon (SOC) are two important factors to consider when revegetation in degraded land of arid and semiarid areas. Knowing the response of SWC and SOC to vegetation restoration as well as their coupling interaction is important for sustainability of vegetation restoration. In this study, three common plantations of the same recovery years were selected on China’s Loess Plateau, which included Pinus sylvestris, Pinus tabuliformis and Populus simonii, to evaluate the response of SWC and SOC to vegetation restoration as well as their interactions, and then revealed the influencing factors of SWC and SOC variations. Results showed that compared to the grassland, three plantations all exacerbated the deficit of deep soil water, but Populus simonii increased the SOC, while the rest all decreased the SOC. And tradeoff of Populus simonii had the lowest root mean squared error (RMSD). Therefore, Populus simonii was identified as representing a suitable revegetation technique for this region. There was strong interaction between SWC and SOC for shallow soil layers. Land use type (LUT) has an important effect on deep SOC variations, while SOC and soil texture for deep SWC variations. The results were helpful to the sustainable development of artificial forests in this region as well as other similar arid and semiarid areas.

This paper studies the integrated design problems of control and guidance with parameter uncertainties, target disturbances, input constraints and actuator faults. Firstly, based on the integrated design idea of the missile guidance and control, the auxiliary variable is used to establish and transform it into a cascade system with input constraints, actuator faults and disturbances of unknown upper bounds. Secondly, the adaptive anti-saturation dynamic surface fault-tolerant controller is designed by using the back-stepping method, adaptive control, auxiliary system and tracking differentiator. By introducing the tracking differentiator and tangent barrier Lyapunov function, the computational explosion problem in the traditional back-stepping method is avoided and the angle of attack can be guaranteed in prospective range, respectively. Finally, the theoretical proof of the designed control strategy is given to ensure that the states of the closed-loop system are bounded. At the same time, the digital simulation of the maneuvering target of different maneuvering forms is carried out, which further illustrate the effectiveness and robustness of the designed control schemes.

Background: Constipation is one of the chronic gastrointestinal functional diseases that affects the quality of life. While Qi Lang Formula (QLF) has demonstrated effectiveness in alleviating constipation symptoms, its precise mechanism remains elusive. Methods: QLF was analyzed using UPLC-MS/MS. Targets for QLF were collected from SwissADME, Herb, ITCM databases, and FC-related targets from scRNA-seq and Genecards databases. Overlapping targets suggested potential QLF therapy targets for FC. Enrichment analysis used the KOBAS database. A "drug-ingredient-target" network was constructed with Cytoscape, and AutoDock verified active component binding. H&E staining assessed colonic mucosa changes, TEM examined ICC structural changes. ELISA measured neurotransmitter levels, and western blot verified QLF's effect on target proteins. ICC proliferation was observed through immunofluorescence. Results: We identified 89 targets of QLF associated with ICC-related FC, with c-Kit emerging as the pivotal target. Molecular docking studies revealed that Atractylenolide Ⅲ, Apigenin, Formononetin, Isorhamnetin, Naringenin, and Ononin exhibited strong binding affinities for the c-Kit structural domain. QLF significantly enhanced first stool passage time, fecal frequency, fecal moisture content, and intestinal propulsion rate. Further analysis unveiled that QLF not only restored neurotransmitter levels but also mitigated colon muscular fiber ruptures. ICC ultrastructure exhibited partial recovery, while RT-qPCR and western blot confirmed upregulated c-Kit expression and downstream targets. Immunofluorescence results indicated ICC proliferation post QLF treatment in rat colon. Conclusion: Our findings suggest that QLF may promote ICC proliferation by targeting SCF/c-Kit and its downstream signaling pathway, thereby regulating intestinal motility.

Lignin is insoluble in water, limiting its use in the synthesis of adhesives. Therefore, in order to increase the amount of lignin raw materials used in the synthesis of adhesives, a kind of aminated lignin compounds was prepared through lignin amination reaction, and conducting structural analysis in this paper. The particle size of the amino lignin is about 100 nm, with the weight average molecular weight of 57,627 g/mol and a water solubility of 0.45g/100ml. The reaction mechanisms were proposed that the phenolic hydroxyl groups of lignin react with ammonia molecules, and thereby successfully introducing amino groups to generate the aminated lignin compounds. Therefore, this article enriches the scientific theory of lignin reactions and provides reference for the widespread application of lignin raw materials in the field of adhesives.

In the paper, the author finds bounds of the sine and cosine along a circle on the complex plane in terms of two double inequalities for the norms of the sine and cosine along a circle on the complex plane.

Currently the rapid growth of global economy has the competition among high-tech industries develop from regional to global, and the competition becomes fierce. In face of such fierce competition in global high-tech industry, it is realized that tangible assets could no longer be the differentiation basis, but intangible assets are regarded as the differentiation capital. An enterprise with sustainable innovation would dominate the world market and enhance the international competitiveness of domestic economy. When internal entrepreneurial culture is prevalent, an enterprise would naturally promote the innovation capability. Such a point of view also explains more popular of the innovative products or services of some enterprises than those with larger scales. Aiming at employees in high-tech industry in Guanxi Province, total 500 copies of questionnaire are randomly distributed, and 337 valid copies are retrieved, with the retrieval rate 67%. The research results reveal significantly positive correlations between 1.entrepreneurial culture and sustainable innovation capability, 2.sustainable innovation capability and patent, and 3.entrepreneurial culture and patent. According to the results, suggestions are proposed, expecting to explain how a high-tech business outperforms in the changeable digital era and acquires the sustainable innovation capability and patent to grasp the opportunity.

In the paper, the author discusses and computes bounds of the sine and cosine along straight lines on the complex plane.

In the paper, by convolution theorem for the Laplace transforms and analytic techniques, the author finds necessary and sufficient conditions for complete monotonicity, monotonicity, and inequalities of several functions involving polygamma functions. By these results, the author derives a lower bound of a function related to the sectional curvature of the manifold of the beta distributions. Finally, the author poses several guesses and open problems related to monotonicity, complete monotonicity, and inequalities of several functions involving polygamma functions.

For Lentinula edodes, its characteristic flavor is the key determinant for consumer pref-erences. However, the tissue-specific volatile flavor variations of the fruiting body have been overlooked. Here, we comprehensively investigated volatile flavor profiles of different tissues including the pileus skin, context, gill and stipe of the fruiting body of two widely cultivated L. edodes strains (T2 and 0912). We show that the eight-carbon and sulfur com-pounds, which represented 43.2-78.0% and 1.4-42.9% to the total volatile emissions for strain 0912 and T2, dominated their volatiles profiles. The sulfur compounds could rep-resent 32.2% and 42.9% to the total volatile emissions for the context of the strain 0912 and T2, respectively, whereas only represented 1.4% for the stipes of the strain 0912 and 9.0% for the skin of strain T2. Proportions of the predominant C8 compounds (1-Octen-3-one, 1-Octen-3-ol and 3-Octanone) and sulfur compounds (Lenthionine, 1,2,4-Trithiolane, Di-methyl disulfide and Dimethyl trisurfide) changed depending on tissues and strains. We further reveal that the overall volatile flavor profiles varied greatly in different tissues and strains. With machine learning algorithm, we show that volatile profiles could 100% pre-dict strains 0912 and T2. The prediction accuracy for different tissues could also reach 100%. Our results highlight the tissue-specific volatile flavor variations of the L. edodes fruiting body.

Background: Pittosporum tobira (Thunb.) Aiton is an aromatic medicinal plant widely cultivated in the world. However, the essential oils (EOs) from P. tobira flowers for anti-cancer potential is still not systematically studied. The present aim to elucidate the phytochemical composition of the EOs and to explore mechanism of anticancer action. Methods: The EOs were extracted and analyzed by headspace solid-phase microextraction (HS-SPME) with gas chromatography-mass spectrometry (GC-MS). Volatile components were identified according to Kovats retention index (KI) and NIST database. The anti-neoplasm mechanisms of the EOs was comprehensively investigated in lung carcinoma A549 and H460 cells. Results: A total of 47 secondary metabolites representing 94.18% of the EOs were successfully identified: monoterpenes and sesquiterpenes were the dominant terpenoids. The EOs exhibited antiproliferative activity on A549 and H460 lung carcinoma cells. Hoechst 33324 fluorescent staining indicated the typical characteristics of apoptosis and induced cycle phase arrest. AnnexinV/PI staining revealed that the number of apoptotic cells was increased. Furthermore, the EOs also induced the caspase-mediated mitochondrial apoptosis pathway. Conclusions: Findings suggest that the full-scale chemical composition and first characterization of anticancer activities of the EOs, it could be used for integrative natural anti-cancer agents in health care should be pay more attention.

Elderly individuals frequently perceive companion robots devoid of warmth, resulting in a reluctance to accept these robots' services. This perception has become a significant barrier to the introduction of companion robots into households. To address this issue, this study employs KE methods to translate the elderly's need for warmth perception from companion robots into elements of modelling design. Initially, 20 pairs of affective words and 22 sample images of companion robots were chosen. The "rational-emotional" and "dim-bright" dimensions were identified as positively influencing the elderly's warmth perception of companion robots through SD method analysis. Subsequently, a hierarchical analysis table was established, with warmth perception as the root layer, modelling style and color matching as the basic layer, "rational-emotional" and "dim-bright" as the expansion layer, and the eight characteristic elements of companion robots as the morphological layer. The link between affective imagery and design elements was then established from the sample robots with higher warmth perception scores. Based on the correlation between the two, various design schemes were formed through random combinations. Finally, the design schemes were evaluated using the warmth perception scale, and the warmth perception scores of each sample model were obtained. This research provides design references for designing companion robots for the elderly with a "sense of warmth".

Background: Covid-19 was first reported in Wuhan, China in Dec 2019. Since then, it has been transmitted rapidly in China and the rest of the world. While Covid-19 transmission rate has been declining in China, it is increasing exponentially in Europe and America. Although there are numerous studies examining Covid-19 infection, including an archived paper looking into the meteorological effect, the role of outdoor air pollution has yet to be explored rigorously. It has been shown that air pollution will weaken the immune system, and increase the rate of respiratory virus infection. We postulate that outdoor air pollution concentrations will have a negative effect on Covid-19 infections in China, whilst lockdowns, characterized by strong social distancing and home isolation measures, will help to moderate such negative effect. Methods: We will collect the number of daily confirmed Covid-19 cases in 31 provincial capital cities in China during the period of 1 Dec 2019 to 20 Mar 2020 (from a popular Chinese online platform which aggregates all cases reported by the Chinese national/provincial health authorities). We will also collect daily air pollution and meteorology data at the city-level (from the Chinese National Environmental Monitoring Center and the US National Climatic Data Center), daily inter-city migration flows and intra-city movements (from Baidu). City-level demographics including age distribution and gender, education, and median household income can be obtained from the statistical yearbooks. City-level co-morbidity indicators including rates of chronic disease and co-infection can be obtained from related research articles. A regression model is developed to model the relationship between the infection rate of Covid-19 (number of confirmed cases/population at the city level) and outdoor air pollution at the city level, after taking into account confounding factors such as meteorology, inter- and intra-city movements, demographics, and co-morbidity and co-infection rates. In particular, we shall study how air pollution affects infection rates across different cities, including Wuhan. Our model will also study air pollution would affect infection rates in Wuhan before and after the lockdown. Expected findings: We expect there be a correlation between Covid-19 infection rate and outdoor air pollution. We also expect that reduced intra-city movement after the lockdowns in Wuhan and the rest of China will play an important role in reducing the infection rate. Interpretation: Infection rate is growing exponentially in major cities worldwide. We expect Covid-19 infection rate is related to the air pollution concentration, and is strongly dependent on inter- and intra-city movements. To reduce the infection rate, the international community may deploy effective air pollution reduction plans and social distancing policies.

To improve carbon efficiency for urban logistics service system composed of a third-party logistics service provider (3PLs) and an e-business enterprise, low-carbon operation game between them was studied. Considering low carbon technology investment cost and sales expansion effect of low carbon level, profit functions for both players were constituted. Based on their different bargaining capabilities, totally 5 types of game scenarios were designed. Through analytical solution, Nash Equilibria under varied scenarios were obtained. By analyzing these equilibria, 4 major propositions were given, in which, some key variables and system performance index were compared. Results show that the best system yields could only be achieved under the fully cooperative situation; limited cooperation only for carbon emission reduction would not benefit the system performance improvement; E-business enterprise-leading game’s performance overtook 3PLs-leading ones.

Over the past decades, overweight and obesity has become a global epidemic and the leading threat for death. To prevent the serious risk, an overweight or obese individual must apply a long-term weight-management strategy to control food intake and physical activities, which is however, not easy. Recently, with the advances of information technology, more and more people can use wearable devices and smartphones to obtain physical activity information, while they can also access various health-related information from Internet online social networks (OSNs). Nevertheless, there is a lack of an integrated approach that can combine these two methods in an efficient way. In this paper, we address this issue and propose a novel mobile-social framework for health recognition and recommendation, namely, H-Rec². The main ideas of H-Rec² include (1) to recognize the individual's health status using smartphone as a general platform, and (2) to recommend physical activity and food intake based on personal health information, life science principles, and health-related information obtained from OSNs. To demonstrate the potentials of the H-Rec² framework, we develop a prototype that consists of four important components: (1) an activity recognition module that senses physical activity using accelerometer, (2) a health status modeling module that applies a novel algorithm to generate personalized health status index, (3) a restaurant information collection module that collects relevant information from OSN, and (4) a restaurant recommendation module that provides personalized and context-aware recommendation. To evaluate the prototype, we conduct both objective and subjective experiments, which confirm the performance and effectiveness of the proposed system.

Tack is one of the most important factors affecting the operability of prepregs, but it is still very difficult to obtain the change of prepreg tack with time at different temperatures. In this paper, a newly designed T-peel device is used to test the tack decay rate of prepregs at different temperatures. The obtained decay rate deviates less than 8.9% from the manufacturer's data. The maximum deviation of the ratio of tack decay speeds calculated by the Arrhenius equation from the experiments is not higher than -9.7%. It is proved that the present method can obtain the decay rate of tack of prepregs at different temperatures. This method is also applicable to the other two types of prepregs. The article proposes the handling life unit, an operational life measurement unit for prepregs, and establishes that the relationship between tack and remaining shelf life reduces prepreg management costs.

The control of the fine particle emission from the coal-fired power plants has been a big challenge in china. Either the conventional electrostatic precipitator or the fabric filter has some shortages. The electrostatic precipitator is hard to keep high efficiency for the submicron particles. The fabric filter could keep high efficiency but with very high pressure drop. One solution is to combine them together. Several types of hybrid particle collectors (HPC) combining the electrostatic precipitator and the fabric filter together have been developed and applied in a number of projects in China. In recent years, numerical simulation technology has been widely used in the design of the collectors. In this paper, an unsteady numerical model is used to investigate the particle deposition characteristics in a scale hybrid collector. The fluid field is modeled by using incompressible Navier-Stokes equations with the RNG turbulence equations. The corona discharge is solved by using a finite volume method. The particle charging is modeled by using a filed-diffusing combined model. And an unsteady cake formation model is used to simulate the filtration process.

Nitrogen (N) strongly affects plant growth and metabolism. For shikonin biosynthesis, although the ammonium toxicity phenomenon has been reported, the effects of nitrogen on the shikonin synthesis remains obscure. In this study, we carried out four different concentrations of NH4+ treatments on Arnebia euchroma hairy roots (AEHR) to clarify the influence of NH4+ on the growth and shikonin accumulation in A. euchroma and the possible mechanism. The results showed that compared with the 0% NH4+ treatment (only nitrate as nitrogen source), 10% NH4+ treatment increased the fresh weight and the dry weight of AEHR, and promoted the synthesis of shikonins; 20% NH4+ treatment started to show the inhibition effects on growth and shikonin accumulation of AEHR and 30% NH4+ treatment exhibited the strongest inhibition effects. With increased percentage of NH4+, AEHRs became shorter and thicker with more branches. To further elucidate the mechanism, we analyzed the time-course of nitrogen assimilation, gene expression level of key enzymes involved in the shikonin biosynthesis pathway, and contents of various endogenous hormones under NH4+ toxicity condition. Results indicated that auxin and cytokinin might regulate the growth and architecture of AEHR under NH4+ toxicity, and jasmonate level was reduced along with the inhibition of shikonin biosynthesis. This first comprehensive investigation into the effects of ammonium/nitrate ratio on shikonin biosynthesis not only provided valuable data for optimizing the in vitro culture and shikonin production in A. euchroma, but also suggested potential fertilizer strategies for its cultivation.

In the paper, the authors survey integral representations (including the Lévy--Khintchine representations) and applications of some bivariate means (including the logarithmic mean, the identric mean, Stolarsky's mean, the harmonic mean, the (weighted) geometric means and their reciprocals, and the Toader--Qi mean) and the multivariate (weighted) geometric means and their reciprocals, derive integral representations of bivariate complex geometric mean and its reciprocal, and apply these newly-derived integral representations to establish integral representations of Heronian mean of power 2 and its reciprocal.

The main purpose of this paper is to present a comprehensive view of the application mathematical models in the designing and implementing SSCM beside to solving problems and making decision. The research questions are: what mathematical models are used for designing and implementing sustainable supply chain management, how to use them, which industries implemented in, what modules of SSCM depth in and finally finding the gaps of researches. The methodology of research is Systematic Literature review through peer review papers which are published in high ranking journals. In this paper, First, we search all papers through scientific data bases like Scopus, science direct, MDPI, Springer, Google Scholar, then, screening papers based on the criteria such as subject of paper, journals impact factor which is published in-should be peer review journal- and relative content of the papers. Finally, we selected 245 papers with three steps screening through 2806 papers that they have enough quality and relative to our research goals for context analysis. Through context analysis, first we categorized the information of the papers and drew the current situation of researches in the framework of our topic. Then, we evaluate and compare the goals of sustainability and current situation and found the gapes, then, offered new suggestions like implementing SSCMs models in pollutant industries like casting industry, Heavy industry, coal Industry and so on. On the other hand, there are gaps in researches in some modules of SSCM such as packaging, designing products, etc.

In recent years, many algorithms based on end-to-end deep networks have been proposed to deal with the target detection problem of videos. However, the deep network models usually consume a lot of computing resources during the procedure of analysis of videos with complex dynamic backgrounds. In this paper, a new method of object detection based on information theory is presented. Firstly, each frame in a video is converted into an effective information map by using the Harris corner detection method. Secondly, the sensitive areas in the frame are extracted by using the context information and the effective information maps of the consecutive video frames. The sensitive areas in the video frame are the candidate areas where the target objects would be appeared at high probabilities. Thirdly, the information entropy features of each sensitive area are extracted to form the feature matrix, based on which, an SVM model is trained for selecting the target areas from the sensitive areas. Finally, the locations of the objects are detected based on the target areas in the video with a complex dynamic background. As a lightweight video detection framework, the method presented in this paper can save a lot of computing resources. Experimental results show that this method can achieve good results in the benchmark of CDnet 2014.

The goods and services produced by forest and vegetation ecology system is the power by which human society can be promoted fast in high-quality and sustainable way. With the increase of population and economic development in water-limited regions, there is an increasing demand for the quantity and variety of forest vegetation ecosystem products and services. To meet the demands of this situation, most of the original forest has changed into farmland, non-native forest and grass land. As a result, water-plant relationship changed from equilibrium to non-equilibrium, which led to soil drought, soil degradation and vegetation decline in dry years or waste of soil water in rainy years in most of water-limited regions. In order to solve the questions and realize the sustainable utilization of soil water resources and the high quality and sustainable development of social economy, it is necessary to apply the utilization limit theory of soil water resources by plants and the theory of soil water carrying capacity for vegetation to adjust the relationship between plant growth and soil moisture to obtain the maximum yield and benefit of vegetation and serve high-quality and sustainable development.

In the paper, by virtue of convolution theorem for the Laplace transforms, Bernstein's theorem for completely monotonic functions, and other techniques, the author finds necessary and sufficient conditions for a difference constituted by four derivatives of a function involving trigamma function to be completely monotonic.

In the paper, by induction and recursively, the author proves that the generating function of multivariate logarithmic polynomials and its reciprocal are a Bernstein function and a completely monotonic function respectively, establishes a Lévy-Khintchine representation for the generating function of multivariate logarithmic polynomials, deduces an integral representation for multivariate logarithmic polynomials, presents an integral representation for the reciprocal of the generating function of multivariate logarithmic polynomials, computes real and imaginary parts for the generating function of multivariate logarithmic polynomials, derives two integral formulas, and denies the uniform convergence of a known integral representation for Bernstein functions.

In the paper, by virtue of some properties for the Riemann zeta function, the author finds a double inequality for the ratio of two consecutive Bernoulli numbers with even indexes and analyzes the approximating accuracy of the double inequality.

In the paper, the author (1) presents an explicit formula and its inversion formula for higher order derivatives of generating functions of the Bell polynomials, with the help of the Faà di Bruno formula, properties of the Bell polynomials of the second kind, and the inversion theorem for the Stirling numbers of the first and second kinds; (2) recovers an explicit formula and its inversion formula for the Bell polynomials in terms of the Stirling numbers of the first and second kinds, with the aid of the above explicit formula and its inversion formula for higher order derivatives of generating functions of the Bell polynomials; (3) constructs some determinantal and product inequalities and deduces the logarithmic convexity of the Bell polynomials, with the assistance of the complete monotonicity of generating functions of the Bell polynomials. These inequalities are main results of the paper.

The goods and services produced by forest vegetation ecosystem are the driving force for the rapid, high-quality and sustainable development of human society. In history, with the increase of population and economic development, there is an increasing demand for the quantity and variety of forest vegetation ecosystem products and services in a country or a region. To meet the demands, most of the original forest has become farmland, plantation and grass and crops land. As a result, the plant water relationship changed from equilibrium to non-equilibrium, which easily led to soil drought, soil degradation and vegetation decline in dry years or waste of soil water in rainy years in most of water-limited regions. In order to solve the question and realize the sustainable utilization of soil water resources and the high-quality sustainable development of forest, it is necessary to apply the limit theory of plant utilization of soil water resources and the vegetation carrying capacity theory in the critical period of plant-water relationship regulation to adjust the relationship between plant growth and soil moisture to obtain the maximum yield and benefit and realize high-quality and sustainable development.

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

This paper investigates the polarization and heat generation characteristics of batteries under different ambient temperatures and discharge rates by means of using a coupled electric-thermal model. The study found that the largest percentage of polarization is ohmic polarization, followed by concentration polarization and electrochemical polarization. The values of the three types of polarization are generally small and stable under normal-temperature environments and low-discharge rates. However, they increase significantly in low-temperature environments and high-discharge rates and continue to rise during the discharge process. Additionally, ohmic heat generation and polarization generation also increase significantly under these conditions. Reversible entropy heat is less sensitive to ambient temperature but increases significantly with the increase of the discharge rate. Ohmic heat generation and polarization heat generation contribute to the total heat generation of the battery at any ambient temperature, while reversible entropy heat only contributes to the total heat generation of the battery at the end of discharge.

In this study, we investigate the behavior of randomly moving particles with a defined average energy, focusing on their biased motion around a specific point. These particles' velocity magnitudes follow a Maxwell distribution with a specific scale parameter. Our analysis derives the stochastic rotation rules for these particles and introduces the Ito equation conditions for biased stochastic rotation at a given curl value. We also consider the special relativistic-like effects in this context. The findings are validated through a representative example.

With the advancement of the economy and society, policymakers acknowledge the significance of improving rural households' well-being as a crucial factor in promoting sustainable economic and social development. Based on the matching data of China Household Finance Survey and Digital Rural County Index, this study empirically examines the effect and mechanisms of digital village construction on subjective well-being of rural households. The results revealed that digital village construction has a significant improvement in their subjective well-being. The impact of digital village construction is particularly significant in rural areas located in the western regions of China, as well as among households possessing higher levels of human capital. The process through which digital village construction enhances the subjective well-being of rural households involves the augmentation of household income, the promotion of non-farm employment opportunities, and the enhancement of rural governance. This study provides robust micro-empirical evidence highlighting the positive welfare effects of digital rural construction. This study provides insights into the digital village construction within the happiness economy framework, offering a new perspective. The imperative to strengthen rural digital infrastructure and improve farmers' proficiency in modern information skills is a strategic policy aimed at enhancing well-being of rural households.

The microglia, displaying diverse phenotypes, play a significant regulatory role in the development, progression, and prognosis of Parkinson's disease. Research has established that glycolytic reprogramming serves as a critical regulator of inflammation initiation in pro-inflammatory macrophages. Furthermore, the modulation of glycolytic reprogramming has the potential to reverse the polarized state of these macrophages. Previous studies have shown that levetistilide A (LA), a phthalide component derived from Angelica sinensis, possesses a range of pharmacological effects, including anti-inflammatory, antioxidant, and neuroprotective properties. In our study, we have examined the impact of LA on inflammatory cytokines and glucose metabolism in microglia induced by lipopolysaccharide (LPS). Furthermore, we explored the effects of LA on the AMPK/mTOR pathway and assessed its neuroprotective potential both in vitro and in vivo. The findings revealed that LA notably diminished the expression of M1 pro-inflammatory factors induced by LPS in microglia, while leaving M2 anti-inflammatory factor expression unaltered. Additionally, it reduced ROS production and suppressed IκB-α phosphorylation levels as well as NF-κB p65 nuclear translocation. Notably, LA exhibited the ability to reverse microglial glucose metabolism reprogramming and modulate the phosphorylation levels of AMPK/mTOR. In vivo experiments further corroborated these findings, demonstrating that LA mitigated the death of TH-positive dopaminergic neurons and reduced microglia activation in the ventral SNpc brain region of the midbrain and the striatum. In summary, LA exhibited neuroprotective benefits by modulating the polarization state of microglia and altering glucose metabolism, highlighting its therapeutic potential.

In a particle swarm with a fixed kinetic energy, the constituent particles move randomly and their velocity magnitudes follow a Maxwell distribution characterized by specific parameters. Within a certain time frame, particles in a sub-swarm may exhibit a bias in their movement direction. Thus, the particles may exhibit a special characteristic (biased random motion), where the group velocity in a particular direction remains constant u. For this biased particle swarm, composed of randomly moving particles with a fixed average speed c, particles have a higher probability of moving in a specific direction. Conversely, their likelihood of moving in all other directions is equally reduced. This study starts from the perspective of biased random walks and using Mathematica software proves that the diffusion rate of particles (in the reference frame R_u observed from R₀) in all directions is slower than that of an unbiased particle swarm with the same average speed c. Specifically, the degree of reduction is determined by the Lorentz-like factor. Lastly, we present the Ito equation for this biased random motion and provide associated verification examples. This study aims to serve as a reference for comprehending the underlying principles of the special relativity effect.

There is a balanced plant-water relationship in the primary vegetation of desert area. With the increase of population and social development in desert areas, people’s need for forest vegetation ecosystem’s goods and service have been changed. To meet the growing demand for plant community goods and services, more original vegetation has been changed into non-native vegetation such as in China loess plateau. However, with the plant growth, sometime soil drying happens and then becomes gradually serious with times in most of desert regions. Serious drying of soil eventually result in soil degradation, vegetation decline and agriculture failure，which influence the produce and supply of forest vegetation goods and service in market in dry year or waste of soil water resources in wet year, which wastes precious nature resources. In order to solve these problems, the soil water resources have to be used in sustainable way and plant-water relationship have to be regulated on Carrying Capacity of Soil Water for Vegetation in the key period of plant water relationship regulation, to carry out sustainable use of nature resources, high-quality and sustainable development of forest and grass or high-quality produce of fruit and crop in desert re-gions.

A Mw7.8 earthquake struck Turkey on February 6, 2023, causing severe casualties and economic losses. This paper investigates the characteristics of strong ground motion and seismogenic fault of the earthquake. We collected and processed the strong ground motion records of 379 stations using Matlab, SeismoSignal and Surfer software, and obtained the peak ground acceleration (PGA) contour map. We analyzed the near-fault effect, the fault locking segment effect and the trampoline effect of the earthquake based on the spatial distribution of PGA, the fault geometry and slip distribution. We found that the earthquake generated a very strong ground motion concentration effect in the near-fault area, with the maximum PGA exceeding 2000cm/s2. However, the presence of fault locking segments influenced the spatial distribution of ground motion, resulting in four significant PGA high-value concentration areas at a local dislocation, a turning point and the end of the East Anatolian Fault. We also revealed for the first time the typical manifestation of the trampoline effect in this earthquake, which was characterized by a large vertical acceleration with the positive direction significantly larger than the negative direction. This paper provides an important reference for understanding the seismogenic mechanism, damage mode, characteristics and strong earthquake law of Turkey earthquake.

Using the method of the beta function, Sun has recently evaluated some series of the type $\sum_{k=0}^{\infty}(ak+b)x^k/\binom{mk}{nk}$. By factorization of the polynomial $t^{m-n}(1-t)^n-x$, we will give a general method to find new $\pi$-series.

Anthocyanins extract from purple tomato (PTA) was incorporated with polyvinyl alcohol (PVA) so that a series of colorimetric films of PVA/PTA (based on PVA) were prepared. The role of anthocyanin on color response, FTIR, thickness, water content, mechanical properties, antioxidant activity, and permeation of water vapor through the films was examined. In addition, its application in smart packaging to assess the freshness of shrimp was studied. It was found that the tensile strength, contact angle and WVP of PVA/PTA films increases with the addition of more PTA, while the elongation at break and water content decreased. FTIR analysis showed that there are interactions between PTA and PVA matrix. The addition of anthocyanins caused to a significant improvement for the antioxidant properties of PVA films. Furthermore, the total volatile alkaline nitrogen (TVB-N), total plate count (TPC) and pH value of shrimp were monitored after 4 days of refrigeration, and the color change of the indexes was recorded. The PVA/PTA films changed color from purple to yellow-green during the storage time of 0-4d for shrimp, this suggests that the film could be used in smart packaging as a real-time freshness indicator for shrimp.

YOLOv8, as an efficient object detection method, can swiftly and precisely identify objects within images. However, traditional algorithms encounter difficulties when detecting small targets in remote sensing images, such as missing information, background noise, and interactions among multiple objects in complex scenes, which may affect performance. To tackle these challenges, we propose an enhanced algorithm optimized for detecting small objects in remote sensing images, named HP-YOLOv8. Firstly, we design the C2f-D-Mixer (C2f-DM) module as a replacement for the original C2f module. This module integrates both local and global information, significantly improving the ability to detect features of small objects. Secondly, we introduce a feature fusion technique based on attention mechanisms, named Bi-Level Routing Attention in Gated Feature Pyramid Network (BGFPN). This technique utilizes an efficient feature aggregation network and reparameterization technology to optimize information interaction between different scale feature maps, and through the Bi-level Routing Attention (BRA) mechanism, it effectively captures critical feature information of small target objects. Finally, we propose the Smooth Mean Perpendicular Distance Intersection over Union (SMPDIoU) loss function. The method comprehensively considers the shape and size of detection boxes, enhances the model's focus on the attributes of detection boxes and provides a more accurate bounding box regression loss calculation method. To demonstrate our approach's efficacy, we conduct comprehensive experiments across the RSOD, NWPU VHR-10, and VisDrone2019 datasets. The experimental results show that the HP-YOLOv8 achieves 95.11%, 93.05%, and 53.49% in the [email protected] metric, and 72.03%, 65.37%, and 38.91% in the more stringent [email protected]:0.95 metric, respectively.

In this work, we try to find a way to describe the physical law of micro-world under the frame of a space-time theory. By introducing the scalar fields $\mathcal{D}\left( x\right)$ and $\zeta\left( x\right) $, we rewrite the action of conventional field theory and the Lagrangian describing the motion of the particle, where a modified space-time relation is obtained. To test the correctness of this attempt, we demonstrate the Klein-Gordon equation by the Hamilton-Jacobi method in four dimensional form and present a time delay for the ground state of hydrogen atom.

A method of measuring the absolute pose parameters of a moving rigid body using a monocular camera is proposed, aiming at addressing calibration difficulties and inconsistencies of repeated measurements of the rigid-body pose for a camera having a varying focal length. The proposed method does not require calibration beforehand. Using more than six non-coplanar control points symmetrically arranged in the rigid-body and world coordinate systems, the matrices of rotation and translation between the camera and two coordinate systems are obtained and the absolute pose of the rigid body measured. In this paper, formulas of the absolute pose measurement of a moving rigid body are deduced systematically and the complete implementation is presented. Position and attitude measurement experiments carried out on a three-axis precision turntable show that the average absolute error in the attitude angle of a moving rigid body measured by an uncalibrated camera at different positions changes by no more than 0.2 degrees. Analysis of the three-dimensional coordinate errors of the centroid of a moving rigid body shows little deviation in measurements made at three camera positions, with the maximum deviation of the average absolute error being 0.53 cm and the maximum deviation of the standard deviation being 0.66 cm. The proposed method can measure the absolute pose of a rigid body and is insensitive to the position of the camera in the measurement process. This work thus provides guidance for the repeated measurement of the absolute pose of a moving rigid body using a monocular camera.

This study presents an advanced Simulated Shearer Machine Cutting Experiment System enhanced with digital twin technology. Central to this system is a simulated shearer drum, designed based on similarity theory to mirror the operational dynamics of actual mining cutters accurately. The setup incorporates a modified machining center equipped with sophisticated sensors that monitor various parameters such as cutting states, forces, torque, vibration, temperature and sound. These sensors are crucial for precisely simulating the shearer cutting actions. The integration of digital twin technology is pivotal, featuring a real-time data management layer, a dynamic simulation mechanism model layer, and an application service layer that facilitates virtual experiments and algorithm refinement. This multifaceted approach allows for in-depth analysis of simulated coal cutting, utilizing sensor data to comprehensively evaluate the shearer's performance. The study also includes tests on simulated coal samples. The system effectively conducts experiments and captures cutting condition signals via the sensors. Through time-domain analysis of these signals, gathered while cutting materials of varying strengths, it is determined that the cutting force signal characteristics are particularly distinct. By isolating the cutting force signal as a key feature, the system can effectively distinguish between different cutting modes. This capability provides a robust experimental basis for coal-rock identification research, offering significant insights into the nuances of shearer operation.

The challenging terrain and deep ravines characteristic of mountainous regions often result in slower path planning and suboptimal flight paths for Unmanned Aerial Vehicles (UAVs) when traditional meta-heuristic optimization algorithms are employed. This study investigates the application of an Improved Enhanced Snake Optimizer (IESO) for three-dimensional path planning in a simulated rugged mountainous terrain. The initialization process in the enhanced snake optimizer is refined by integrating the Chebyshev chaotic map. Additionally, a non-monotonic factor is introduced to modulate the "temperature," and a boundary condition is incorporated into the dynamic opposition learning mechanism. These modifications collectively reduce the likelihood of population convergence to local optima during optimization. The feasibility of IESO is validated through time complexity and global convergence analyses. Comparative simulation experiments benchmarked IESO against five state-of-the-art optimization algorithms across test functions and path-planning simulated scenarios. The experimental results indicate that the enhanced algorithm achieves superior optimization precision, faster convergence speeds, and improved quality in the planned trajectories by 30%.

China’s rural e-commerce has been developing rapidly. Taobao Villages are combination of e-commerce and rural industries. When rural e-commerce coverage evolves from Taobao village to Taobao town, the scale of industrial clusters has been expanding synchronously. This paper investigates flower and seedling industrial cluster in Xinhe Town, Yanji Town and Miaotou Town of Shuyang County, China, and conducts the econometric analysis of the expansive determinants of flower and seedling industrial cluster of Taobao Villages. An effective sample of 263 was obtained through a face-to-face survey of e-merchants of flower and seedling in the Shuyang County of Jiangsu Province. Bases on the structural equation modeling, series of test results show that the data can be used to calculate the path regression. The outcomes shows that creation of e-merchants of flower and seedling, integration of e-commerce platform, supply chain friendliness, involvement of e-commerce service providers, and governmental policy guidance are driving expansion of flower and seedling industrial cluster together, moreover, the five forces interact with each other. This implies that expansion of flower and seedling industrial cluster is a systematic process, each stakeholder needs to pay attention to the role of other forces, and five forces achieve a balanced situation in the cluster.

In modern warfare, the diversified tasks can sometimes be challenging to fulfill with a single projectile, necessitating the incorporation of cooperation constraints in trajectory planning. Limited by the stringent requirements of the launch platform and lower costs, the maneuverability and ability to adjust the flight time range of projectiles are weak. Therefore, the rationality of performance indicators and flight time coordination strategies is especially critical. To fully exploit the control capabilities of projectiles, a battlefield area segmentation method is proposed, differentiated performance indicators and a cooperative trajectory planning model that considers the entire range of projectiles are established. Considering the limitations of existing flight time coordination strategies in applications, targeted improvements have been made in different cooperation scenarios, and a bi-level adaptive cooperation strategy(BACS) with both optimality and flexibility is proposed. To rapidly determine feasible conditions, a simple and universal method for obtaining the capability ranges of cooperation is introduced. The multi-phase optimal control problems are transformed into nonlinear programming problems using the Radau pseudo-spectral method, and simulation results show that the proposed methods are capable of handling trajectory planning tasks in different cooperation scenarios. The improved strategies effectively enhance the planning success rate under relatively harsh conditions and BACS demonstrates good compatibility with the problems studied.

Due to constraints in launch platform and cost, the maneuverability of gliding-guided projectiles is limited, necessitating a rational design of their trajectory schemes. To reduce the sensitivity of trajectory schemes to uncertainties while ensuring compatibility between flight schemes and guidance control systems, and fully exploiting the control capability of the projectile, a closed-loop robust trajectory planning method is proposed. Models of major uncertain factors and states deviation at the control-start point are established. Based on the NIPCE method, the stochastic dynamic model is transformed into a high-dimensional deterministic model with PCE coefficients as state variables, and the uncertainty propagation law is obtained. A PID algorithm is employed to design a tracking guidance law based on position error feedback, and open-loop and closed-loop robust trajectory planning models are established accordingly. The optimal control problem is solved by transforming it into a nonlinear programming problem using the direct shooting method. Simulation results indicate that the NIPCE method can significantly improve the computational efficiency of uncertainty propagation while ensuring accuracy. Open-loop robust planning can effectively mitigate the sensitivity of gliding trajectories to uncertainties but cannot completely eliminate terminal dispersion. Closed-loop robust planning effectively improves control effort consumption on the basis of open-loop planning.

Oligopeptide transporters (OPTs) are a group of membrane localized proteins that have a broad range of substrate transport capabilities and contribute to numerous biological processes. However, limited information has been reported on OPTs in higher plants. In this study, a comprehensive analysis of the OPT gene family in Medicago truncatula was performed. A total of 26 OPT genes (MtOPT01-MtOPT26) have been identified in the Medicago truncatula genome. Phylogenetic analyses indicated that MtOPTs consisted of two distinct subgroups, 12 MtOPTs belonged to the peptide transport subgroup (PT-OPT) based on their predicted amino acid sequences containing the two highly conserved motifs (NPG and KIPPR) and 14 MtOPTs belonged to yellow stripe subgroup (YS-OPT). The MtOPTs distributed on each of 8 chromosomes in Medicago truncatula. Sequence analysis verified that MtOPTs significant similar to those in other plants. The copy number of MtOPTs was low and the multiply of MtOPTs was simple relatively. Gene structure analysis showed that most of the MtOPTs have various numbers of introns. The multiple of MtOPTs might play different biological roles which were supported by the fact that MtOPTs have a distinct tissue-specific expression pattern. The data obtained in this study will help to better understand the complexity of the MtOPTs gene family and provide new evidence for the function and evolution of the OPT gene family in higher plants.

Sperm gain fertilization ability and forward movement characteristics during epididymal transport. Sperm maturation is inseparable from the processing of the epididymis. Compared with other reproductive organs, relatively little is known about the epididymis. However, with the development of molecular biology and the improvement of single-cell sequence technology, we gradually realized that we should re-examine the importance of the epididymis for sperm mat-uration and for the entire male reproductive system. Recently, epididymis related reports have tended to be more regionalized and more refined. We can understand cell distribution and gene expression from the perspective of a single cell. It has been reported that different regions of the epididymis have different functions and different cell compositions, which may be determined by gene expression. Here, we comprehensively reviewed the epididymal studies. From the ana-tomical structure of the epididymis to the division of its regions, we focused on the cell compo-sition and region-specific genes differentially expressed in the epididymis. The gene expression of the epididymis extends to a series of biological processes of sperm in the epididymal cavity, and the serious effects of epididymal diseases on reproduction are discussed. Therefore, the importance of the epididymis in male reproduction is emphasized. With the maturity of single-cell spatial transcriptomics, it is hoped that the technology can be applied to epididymal research and bring about the spatiotemporal landscape of the epididymis at the single-cell level.

Using machine learning or deep learning to solve the problem of garbage recognition and classification is an important application in computer vision, but due to the incomplete establishment of garbage datasets and the poor performance of complex network models on smart terminal devices, the existing garbage classification models The effect is not good.This paper presents a waste classification and identification method base on transfer learning and lightweight neural network. By migrating the lightweight neural network MobileNetV2 and rebuild it, The reconstructed network is used for feature extraction, and the extracted features are introduced into the SVM to realize the identification of 6 types of garbage. The model was trained and verified by using 2527 pieces of garbage labeled data in the TrashNet dataset, which ultimately resulted in a classification accuracy of 98.4% of the method, which proves that the method can effectively improve the classification accuracy and time and overcome the problem of weak data and less labeling. The over-fitting phenomenon encountered by small data sets in deep learning makes the model robust.

We constrain two dynamical dark energy models that are parametrized by the logarithm form of $w(z)=w_{0}+w_{1}\left(\frac{\ln (2+z)}{1+z}-\ln 2\right)$ and the oscillating form of $w(z)=w_{0}+w_{1}\left(\frac{\sin(1+z)}{1+z}-\sin(1)\right)$. Comparing with the Chevallier-Polarski-Linder (CPL) model, the two parametrizations for dark energy can explore the whole evolution history of the universe properly. Using the current mainstream observational data including the cosmic microwave background data and the baryon acoustic oscillation data as well as the type Ia supernovae data, we perform the $\chi^2$ statistic analysis to global fit these models, finding that the logarithm parametrization and the oscillating parametrization are almost as well as the CPL scenario in fitting these data. We make a comparison for the impacts of the dynamical dark energy on the cosmological constraints on the total mass of active neutrinos. We find that the dark energy properties could significantly change the fitting results of neutrino mass. Looser constraints on $\sum m_{\nu}$ are obtained in the logarithm and oscillating models than those derived in the CPL model. Consideration of the possible mass ordering of neutrinos reveals that the most stringent constraint on $\sum m_{\nu}$ appears in the degenerate hierarchy case.

Saliency detection in synthetic aperture radar (SAR) image is a difficult problem. This paper proposed a multitask saliency detection (MSD) model for the saliency detection task of SAR image. Firstly, we extract four features of SAR image as the input of the MSD model, which include the intensity, orientation, uniqueness and global contrast. Then, the saliency map is generated by the multitask sparsity pursuit (MTSP) which integrates the multiple features collaboratively. Subjective and objective evaluation of the MSD model verifies its effectiveness. Based on the saliency maps of the source images, an image fusion method is proposed for the SAR and color optical image fusion. The experimental results of real data show the proposed image fusion method is superior to the presenting methods in terms of several universal quality evaluation indexes, as well as in the visual quality. The salient areas in the SAR image can be highlighted and the spatial and spectral details of color optical image can also be preserved in the fusion result.

To ensure consumers can purchase high-quality rice, accurate identification of rice varieties is particularly important. Methods: This article conducts research based on machine learning algorithms from the perspectives of image, spectrum, and spectrogram fusion. Six types of hyperspectral image data of rice were preprocessed using convolutional smoothing (SG) and multiple scatter correction (MSC). Texture information of the images was extracted using gray-level co-occurrence matrix. Spectra, texture, and spectrogram data were fused into a new matrix. Spectral, texture, and spectrogram fusion data were used as inputs for the model, and support vector machines (SVM), logistic regression (LR), and K-nearest neighbors (KNN) classification models were constructed and compared. Results: From the classification results, the spectrogram fusion classification performance was better than classification models using only spectra or texture. Conclusion: The research results showed that the accuracy of SVM and LR classification models exceeded 90%, and the LR model performed the best, effectively classifying rice varieties.

A challenge in building large-scale superconducting quantum processors is the precise control and manipulation of the qubit state. However, the crosstalk between the microwave control lines impedes the parallel execution of high-fidelity digital and analog quantum operations. Here, we propose and demonstrate a universal compensation protocol for calibrating the microwave signal crosstalk. We also introduce amplified error sequences to optimize the accuracy. Furthermore, we show a definitive improvement in parallel gate operations with crosstalk cancellation, demonstrating the technique's effectiveness. This work paves the way for superconducting hardware that features automated calibration of microwave crosstalk, leading to enhanced fidelities in multiqubit circuits.

Both drag and lift forces impact an inclined plane when it is dragged through a granular bed. In this paper, the following results have been obtained: the drag and lift forces grow with the velocity of motion; when the immersion depth is constant, the inclination angle has no effect on drag force, however, the lift force increases linearly with this inclination angle; the ratio of drag and lift forces is exactly equal to the tangent value of the inclined angle. In order to describe this physical process macroscopically, a continuum wedge model based on the Coulomb model is established to predict drag and lift forces. Particularly，the dynamic friction angle in the assumed shear band is predicted as a function of both inclined angle and moving velocity.

The limited understanding of how digital platforms, especially the Metaverse, influence public perception and attitude towards sustainable fashion in large scaled markets such as China highlights a critical gap. This study aims to examine the perspectives and perception of the Chinese public regarding sustainable fashion in the Metaverse. Through content analysis, this study evaluated 3,889 Weibo posts from Shanghai Fashion Week 2024 to identify key sentiments and discussions on sustainable and digital fashion. Results indicate that 76.08% of the conversations centered on sustainable fashion, reflecting strong public commitment to environmental issues. The findings highlight characteristics of public perception towards the utilization of immersive technologies and underscore the Metaverse's potential as a platform for fostering environmental consciousness in the fashion industry. This research provides crucial insights for fashion brands looking to integrate sustainability into their digital strategies, addressing a significant gap in current literature and offering practical guidance for leveraging digital platforms to promote sustainable consumption.

Pneumonia remains a major cause of morbidity and mortality worldwide, especially during COVID-19 pandemic. With the significant global health burden that pneumonia poses, it is es-sential to improve therapeutic and management strategies. The increasing emergence of antibiotic resistant bacterial strains limits options for effective antibiotic use. New antibiotics for treatment of pneumonia may address deficits in current antimicrobial drugs, with an ability to cover both typical, atypical, and resistance pathogen. Several of these newer drugs also have structural characteristics that allow for a decreased propensity in development of bacterial resistance. Po-tential use of stem cell therapies in place of corticosteroid treatments may also offer an im-provement in patient outcomes. Human mesenchymal stem cell treatments have shown efficacy and safety in treating COVID-19 induced pneumonia. Combined treatment with both stem cells and antibiotics in pneumonia in a rabbit model has also shown significantly increased efficacy in comparison to antibiotic treatment alone, presenting yet another possible route for a novel strategy in treating pneumonia, though additional future studies are necessary before clinical implementation. While pneumonia remains a major disease of concern, having newer approved antibiotics as well as novel therapies such as stem cell treatments in the pipeline offers clinicians more options in effectively treating pneumonia.

Deep learning has achieved remarkable success in diverse computer science applications, however, its use in other traditional engineering fields has emerged only recently. In this project, we solved several mechanics problems governed by differential equations, using physics informed neural networks (PINN). The PINN embeds the differential equations into the loss of the neural network using automatic differentiation. We present our developments in the context of solving two main classes of problems: data-driven solutions and data-driven discoveries, and we compare the results with either analytical solutions or numerical solutions using the finite element method. The remarkable achievements of the PINN model shown in this report suggest the bright prospect of the physics-informed surrogate models that are fully differentiable with respect to all input coordinates and free parameters. More broadly, this study shows that PINN provides an attractive alternative to solve traditional engineering problems.

As a manifestation of technological innovation achievements, patents reflect the frontier of technological development in the field. This paper constructs a multi-entity patent collaboration network and analyzes its evolution patterns to provide a reference for innovation organizations to grasp the general direction of innovation development and select partners. Based on the data of collaboration patents of two and three organizations in China's new energy vehicles (NEV) industry from 2008 to 2021, this paper constructs higher-order interaction collaboration innovation networks in different periods to analyze the spatial evolution of networks and patent cooperation activities. The results show that the generalized degree distribution of nodes and edges conforms to the power-law distribution. The two-dimensional simplex networks gradually form triangle groups centered on the core nodes, and the importance of key edges is beginning to emerge. Key organizations and partners, including State Grid Corporation of China, Tsinghua University, and China Electric Power Research Institute, will largely determine the direction for the future development of cooperation innovation. The study also reveals that Beijing, Jiangsu, Zhejiang, Guangzhou, and Shanghai are in central positions in the cooperative innovation network, based on their cooperation breadth and depth measures. Additionally, key links formed by Beijing as hubs are not only the center of information exchange but also function as bridges that connect to other regions.

Rollover prevention of partially-filled tank trucks is an industry teaser, with the core challenge being real-time perception and observation of the liquid state inside the tank. In order realize re-liable observation of sloshing liquid, this article firstly proposes a sloshing modeling method based on multi-degree-of-freedom pendulum model, and derives the double mass trammel pendulum model (DMTP, 2DOF) accordingly, which accurately reflects the sloshing dynamics under more pervasive working conditions. Secondly, a free surface fluctuation sensor is designed based on magnetostriction, capable of measuring the inclination and height of the liquid level inside tanks filled with hazardous chemical. Finally, the unscented Kalman filter (UKF) is utilized to synthesize the information of the two, establishing a credible real-time observation of the sloshing liquid. Verified through vehicle-fluid coupled co-simulation, under condition of con-secutive double lane change, observation error of the proposed method is only 25.9% that of the open-loop calculation, providing a secure guarantee for the observation of the state variables of the single pendulum model (SP) used for most kinds of anti-rollover controller.

Single nanowires (NWs) are of great importance for optoelectronic applications, especially solar cells serving as powering nanoscale devices. However, weak off-resonant absorption can limit its light-harvesting capability. Here, we propose a single NW coated with the graded-index dual shells (DSNW). We demonstrate that with appropriate thickness and refractive index of the inner shell, the DSNW exhibits significantly enhanced light trapping compared with the bare NW (BNW), and the NW only coated with the outer shell (OSNW) and the inner shell (ISNW), which can be attributed to the optimal off-resonant absorption mode profiles due to the improved coupling between the reemitted light of the transition modes of the leak mode resonances of the Si core and the nanofocusing light from the dual shells with the graded refractive index. We found that the light absorption can be engineered via tuning the thickness and the refractive index of the inner shell, the photocurrent density is significantly enhanced by 134% (56%, 12%) in comparison with that of the BNW (OSNW, ISNW). This work advances our understanding of how to improve off-resonant absorption by applying graded dual-shell design and provides a new choice for designing high-efficiency single NW photovoltaic devices.

Objective: To sort out the research hotspots of the application of VR in rehabilitation medicine, analyse its research themes and research trends, and offer a reference for future related research in this field. Methods: This paper provides an in-depth analysis of the development process, research hotspots and research trends in the field of VR application in rehabilitation medicine research, taking the Web of Science core dataset as the source and using bibliometric analysis by CiteSpace. Results: The application of VR in rehabilitation medicine was composed of three stages, and the research topics were reviewed in five aspects: neurological rehabilitation, psychology treatment, pain distraction, cardiopulmonary rehabilitation, and visual spatial disorder. Limitations: The literature data only come from the Web of Science core dataset, and the data sample size was not comprehensive. Conclusion: Overcoming VR technology-induced vertigo and mental disorders from overuse of VR are both challenges to research on the application of VR in rehabilitation medicine. In addition, developing VR products with better experience, developing standardized guidelines, and conducting more high-quality clinical studies are all future research trends for the application of VR in rehabilitation medicine.

Gestational Diabetes Mellitus (GDM) is related with adverse outcomes for both the mother and the offspring. Immune and senescence play a crucial role in GDM progression. This study aims to explore the diagnostic significance of immune-related senescence (IRS) genes in GDM. We used weighted gene co-expression network analysis (WGCNA) and single sample gene set enrichment analysis (ssGSEA) to compute the immune score and aging score in control and GDM samples. Machine learning identified core IRS genes. Then we performed unsupervised cluster analysis in GDM patients to explore immune infiltration. Finally, we validated the core genes in clinical samples. We used the intersection of MEblack module from WGCNA and differentially expressed genes (DEGs) to obtain the potential genes. Next, a univariate logistic regression model including 23 potential genes were constructed, and these genes were filtered by least absolute shrinkage and selection operator (LASSO) algorithm. There were 5 potential genes (COX17, RRAS2, RRAGC, CECR1, and TACC2), which defined as biomarkers, remained eventually, and the efficacy of these biomarkers was evaluated by nomogram. Finally, the results from both qRT-PCR and western blot analyses demonstrated CECR1 was down-regulated, while TACC2 was up-regulated in GDM placental tissue. Our study identified CECR1 and TACC2 as diagnostic biomarkers for GDM associating with immune and senescence, providing a new perspective on GDM progression.

Perovskite based solar cells have achieved tremendous progress reaching record efficiency in the past 5 years. Numerous new processes and chemistry have been reported and contribute to the perovskite rapid progress. Continuous efficiency improvements are still necessary for perovskite solar cells, and an exploratory data analysis on devices performance over multiple studies could boost the technology development. Such analysis could identify patterns or provide insights that are not obvious in a single study. Here we present a high quality dataset containing only independently certified Pb-based perovskite solar cells summarizing their efficiency, relevant I-V metrics, manufacturing processes and materials used. Analysis over the dataset provides insights on how aperture size, perovskite deposition methods and materials used in each functional layer affect the final solar cell efficiency and I-V metrics. Future directions are also suggested for efficiency improvements.

Corona viruses hijack human enzymes to assembly sugar coat on Spike glycoproteins. The mechanism that human antibodies may uncover the antigenic viral peptide epitopes hidden by sugar coat are unknown. In this study, we analyzed recombinant SARS-CoV-2 Spike protein secreted from BTI-Tn-5B1-4 cells, by trypsin and chymotrypsin digestion followed by mass spectrometry analysis. We acquired MS/MS spectrums for glycopeptides of all 22 predicted N-glycosylated sites. We further analyzed the surface accessibility of Spike proteins according to Cryo-EM and homolog-modeled structures, and available antibodies that bind to SARS-CoV-1. The results showed that all 22 N-glycosylated sites of SARS-CoV-2 are modified by high-mannose type of N-glycans. MS/MS fragmentation clearly established the glycopeptide identities. Electron densities of glycans cover most of the Spike receptor binding domain of SARS-CoV-2, except YQAGSTPCNGVEGFNCYFPLQSYGFQPTNGVGYQ, similar to a region FSPDGKPCTPPALNCYWPLNDYGFYTTTGIGYQ in SARS-CoV-1. Other surface-exposed domains included those located on Central Helix, between amino acids 967 and 1016 of SARS-CoV-1, and 985 to 1034 of SARS-CoV-2 Spike protein. As the majority of antibody paratopes bind to peptide portion with or without sugar modification, we propose a snake-catcher model that a minimal length of peptide is first clamped by a paratope, and the binding is either strengthened by sugars close to peptide, or not interfered by sugar modification.

Saudi Arabia is a prominent producers of dates, with 1.6 million tons annually. There is a need to evaluate physical properties and quality of fruits non-destructively and then be modeled and predicted throughout the storage period. The aim of the current study was to generate a quality index (Qi) and Near-infrared spectra (NIR) models non-destructively to predict properties of Barhi dates fruits including objective and sensory evaluations. The engineering properties of Barhi dates were measured and modeled with quality index (Qi) based on NIR of fresh Barhi fruits (hardness, color, TSS, pH, and sensory evaluations) and during storage in cold, ambient, and controlled at-mosphere (CA) for up to four months. The prediction of Qi is non- destructively based on NIR utilizing PLSR and ANN data analysis. The results showed that the Qi generated corresponds with high precision to the characteristics of the examined fruits through the duration of the storage period with R2 of 0.96. The NIR spectrum proves to be an efficient method to evaluate the Barhi fruits' quality index. where ANN was found to be more suitable than PLSR analysis. Thus, NIR can be utilized to accurately predict the Qi of fruits quality effectively throughout the handling, processing, transporting, storage, and retail sector supply chain.

The snap fit is a common mechanical mechanism. We have studied the spherical snap fit carefully for its physical asymmetry which is easy to assemble but difficult to disassemble, and obtained the general law.Because of the complexity of spherical structure, it is difficult to get a theoretical formula to describe its physical asymmetry.In this paper, through the method of combining theory, simulation and experiment, and based on the general rule of cylindrical snap fit obtained in the early stage, pushing assembly and pulling disassembly of spherical snap fit are studied,we not only get the theoretical formula of spherical snap fit, but also further verify the correctness of previous research conclusions on cylindrical snap fit.This research provides strong theoretical support and basis for the optimization design and further research of snap fit.

Manual interpretation of these huge amounts of image volumes are susceptible to inter-reader variability and human error. Thus, accurate automated CAD scheme is highly desirable in clinical pathological diagnosis. In this research, plethora of machine learning paradigms (e.g. feature extraction, dimensionality reduction and supervised classification methods) were explored, evaluated, compared and analyzed to identify the optimal pathway for brain MR images (normal vs neoplastic) binary classification task. External validation dataset was used to test the generalizability of the optimal predictive models implemented. Relevant and informative features were selected to construct cross-validated decision tree and eventually simple rule set was built based on the decision tree. The experimental results show that almost all pattern recognition paradigms achieve high accuracy with careful selection of number of attributes. LDA+ELM with 55 features are the optimal pipelines which achieve perfect classification when training and test data are of same source; and achieving (accuracy=97.5%, AUC=0.989, sensitivity=95% and specificity=100%) under balanced test dataset; (accuracy=99.5%, AUC=0.988, sensitivity=95% and specificity=100%). Cross-validated decision tree model also shows comparable performance: accuracy=98.8%, AUC=99.1%, sensitivity=99.6% and specificity=98.2%. Three highly relevant and robust attributes are visualized and selected for construction of decision tree models and finally a rule sets are read directly off the decision tree. This rule sets can potentially serve as fast and accurate classification algorithm.

To address the problems of insufficient semantic fusion between text and questions and the lack of consideration of global semantic information encountered in machine reading comprehension models, we proposed a machine reading comprehension model called BERT_hybrid based on BERT and hybrid attention mechanism. In this model, BERT is utilized to separately map the text and questions into the feature space. Through the integration of Bi-LSTM, attention mechanism, and self-attention mechanism, the proposed model achieves comprehensive semantic fusion between text and questions. The probabilities distribution of answers is computed using Softmax. Experimental results on the public dataset DuReader demonstrate that the proposed model achieves improvements in BLEU-4 and ROUGE-L scores compared to existing models. Furthermore, to validate the effectiveness of the proposed model design, we analyze the factors influencing the model’s performance.

Urbanization is considered as a main indicator of regional economic development due to its positive effect on promoting industrial development; however, many regions, especially developing countries, are troubled by its negative effect — the aggravating environmental pollution. Many researchers have indicated that rapid urbanization stimulated the expansion of industrial production scale and increased industrial pollutant emissions. However, this judgement contains a grave deficiency in that urbanization not only expands industrial production scales but can also increase industrial labour productivity and change the industrial structure. To modify this deficiency, we first decompose the influence which urbanization impacts on industrial pollutant emissions into the scale effect, the intensive effect and the structure effect by using the Kaya Identity and the LMDI Method; second, we perform an empirical study of the three effects’ impacts by applying the spatial panel model with data from 282 Chinese cities between 2003 and 2013. Our results indicate that (1) there are significant reverse U-shapes between Chinese urbanization rate and its industrial pollutant emissions; (2) the scale effect and the structure effect have aggravated Chinese industrial waste water discharge, sulphur dioxide emissions and soot (dust) emissions, while the intensive effect has generated a decreasing and ameliorative impact on that aggravated trend. The definite relationship between urbanization and industrial pollutant emissions depends on the combined influence of the scale effect, the intensive effect and the structure effect; (3) there are significant spatial autocorrelations of industrial pollutant emissions between Chinese cities, but the spatial spillover effect from other cities does not aggravate local urban industrial pollutant emissions, we offer an explanation to this contradiction that the vast rural areas surrounding Chinese cities have served as sponge belts and have absorbed the spatial spillover of cities’ industrial pollutant emissions. According to the results, we argue that this type of decomposition of the influence into three effects is necessary and meaningful, it establishes a solid foundation for understanding the relationship between urbanization and industrial pollutant emissions, and effectively helps to meet relative policy making.

There are four subtypes of adenosine receptors (ARs), named A1, A2A, A2B and A3, all of which are G protein-coupled receptors. The A2BAR, coupled to both Gαi and Gαq G proteins, is one of the several G-protein-coupled receptors that are expressed in a significantly higher level in some cancer tissues in comparison to adjacent normal tissues. There is growing evidence that the A2BAR plays an important role in tumor cell proliferation, angiogenesis, metastasis, and immune suppression. Thus, A2BAR antagonists are potentially novel attractive anticancer agents. Several antagonists targeting at the A2BAR are currently in clinical trials for various types of cancers. In this review, we first describe the signaling, agonists, and antagonists of the A2BAR. We further discuss the role of the A2BAR in the progression of various types cancers, and the rationale of using A2BAR antagonists in cancer therapy

Rapid urbanization has profoundly impacted regional ecosystem services. However, few studies have comprehensively examined the spatiotemporal relationship between multi-dimensional urbanization processes and ecosystem services. This study investigated the spatiotemporal dynamics of urbanization and ecosystem services value (ESV) in the Yangtze River Delta (YRD) region, China, from 2010 to 2020. We measured urbanization levels from two dimensions: Urbanization I (demographic, economic, and land urbanization) and Urbanization II (social and cultural urbanization). The ESV was quantified using the equivalent factor method. The results showed that: (1) The level of Urbanization I increased steadily, while Urbanization II, despite a lower level, exhibited a faster growth rate, especially after 2017; (2) The total ESV declined, with regulating services decreasing the most. The spatial distribution of ESV showed significant heterogeneity; (3) Urbanization had a significant negative correlation with ESV, with Urbanization I exerting a greater negative impact than Urbanization II; (4) The eastern region was dominated by high urbanization-low ESV clusters, while the western region was characterized by low urbanization-high ESV clusters. The findings provide important implications for regional sustainable development and can serve as a reference for related studies in other rapidly urbanizing areas around the world.