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The effect of acid-soluble aluminum content on precipitates and magnetic properties of grain oriented silicon steel was researched by optical microscopy and zeiss ultra 55 Scanning Electron Microscope (SEM) technique respectively. The results show that the number of precipitates increases with the increase of acid-soluble aluminum content, and the size of precipitates is relatively large after hot rolling. Under the low hot rolling temperature, the number of precipitates in the samples is large and the size is small, moreover, the grain size of the primary recrystallized grain is small. The matching of process parameters under different production process lines is the key to obtain good magnetic performance. The effect of nitriding on magnetic properties of the samples is related to the acidsoluble aluminum content of the samples. Too much acid-soluble aluminum can deteriorate the magnetic properties.

Abstract Topological superconductors have long been predicted to host Majorana zero modes which obey non-Abelian statistics and have potential for realizing non-decoherence topological quantum computation. However, material realization of topological superconductors is still a challenge in condensed matter physics. Utilizing high-resolution angle-resolved photoemission spectroscopy and first-principles calculations, we predict and then unveil the coexistence of topological Dirac semimetal and topological insulator states in the vicinity of Fermi energy (E F ) in the titanium-based oxypnictide superconductor BaTi2Sb2O. Further spin-resolved measurements confirm its spin-helical surface states around E F , which are topologically protected and give an opportunity for realization of Majorana zero modes and Majorana flat bands in one material. Hosting dual topological states, the intrinsic superconductor BaTi2Sb2O is expected to be a promising platform for further investigation of topological superconductivity.

Data clustering is the process of identifying natural groupings or clusters based on a certain similarity measure in muti-dimensional data. Aiming at the dynamic clustering problem where the number of clusters cannot be determined in advance, a hybrid dynamic clustering method based on the marine predators algorithm (MPA) and particle swarm optimization (PSO) algorithm was proposed. The position update strategy of the PSO algorithm was used to make up for the lack of MPA in global searching. The fixed-length coding strategy with the real number coding method was used to deal with the variable length clustering optimization problem, and the unfeasible solution processing strategy and the penalty function strategy are adopted to improve the performance of the algorithm and achieve simultaneous optimization of the number of clusters and cluster centers. The proposed MPA-PSO algorithm with PSO algorithm, MPA, Differential Evolution (DE) algorithm, Spotted Hyena Optimizer (SHO), Lightning Searching Algorithm (LSA) and Equilibrium Optimizer (EO) are adopted to carry out the clustering simulation experiments on four artificial data sets and six real data sets (Iris, Wine, Wisconsin breast cancer, Vowel, Seeds, and Wdbc) in UCI databases. Three performance indicators (the number of clusters, ARI and Accuracy) are used to evaluate the clustering results. The experimental results show that the proposed method can not only successfully find the correct number of clusters, but also obtain stable results for most test problems.

Abstract To investigate the optimal androgen concentration for culturing Hetian sheep wool follicle and to detect effects of androgen concentration on wool follicle cell proliferation and apoptosis using immunofluorescence labeling and real-time quantitative fluorescence determinations of wool keratin-associated protein gene expression levels. Wool follicles were isolated by microdissection and wool follicles and skin pieces were cultured in various concentrations of dihydrotestosterone (DHT) in culture medium. Next, daily lengthwise growth measurements of wool follicles were obtained using a microscopic micrometer. Cultured Hetian wool follicles were stained using the SACPIC method to reveal wool follicle structure, while sheep skin slices were used to observe cell proliferation by immunostaining and cell apoptosis using the TUNEL method. At the molecular biological level, keratin-associated protein (Kap) gene expression was studied using wool follicles cultured for various numbers of days in vitro. Effects of androgen concentrations on Hetian wool follicle growth and development were experimentally studied. EdU proliferation assays revealed that androgen promoted cell proliferation within wool follicle dermal papillae. TUNEL apoptosis detection demonstrated that androgen treatment could delay cell apoptosis. Quantitative reverse transcription polymerase chain reaction (qPCR) results demonstrated that gene expression level patterns of Hetian mountain sheep super-high sulfur protein. Kap1.1, KIF1.2, Kap2.12 and Kap4.2 gene expression level of the mountainous experimental group was significantly higher than plains Hetian sheep. An androgen concentration of 100 nM can promote the growth of Hetian wool follicle cells in vitro, resulting in overexpression of some genes of the Kap family.

Clustering validity function is an index used to judge the accuracy of clustering results. At present, most studies on clustering validity are based on single clustering validity function. Research shows that no clustering validity function can handle any data and always perform better than other indexes. Therefore, a hybrid weighted combination evaluation method based on fuzzy C-means (FCM) clustering validity functions was proposed. The weighting method combines expert weighting with information entropy weighting to improve the subjective factor influence of expert weighting and the shortcoming of information entropy weighting in the value judgment of each clustering validity function. Four clustering validity function combination methods of linear, exponential, logarithm and proportion was studied. Finally, the proposed fuzzy clustering validity evaluation method is verified by experiments on artificial data sets and UCI data sets. The experimental results show that the proposed fuzzy clustering validity evaluation method can overcome the shortcoming of single clustering validity function, and can get the optimal clustering number more accurately for different data sets.

Despite local people’s frequent visits to the local temples having historic sites, close attention is seldom paid to the existence of the sites. This research was a qualitative research study based on the theory of Genius Loci by Norberg Schultz in the context of in-situ concept, conducted on four local temples (Wat) in the Northeast of Thailand. From the perspective of ‘in-situ’, the study found the historic sites in these local temples in a dilemma where conservation or renovation was performed with a lack of scientific and rational guidance although the temples still play important roles in the local people’s daily life. The in-situ concept was not abided during the restoration and revitalization processes under the negotiation and conflict of multiple discourses. The historic sites were not integrated with other building and surrounding landscape, especially the extending boundary. The four elements: “atmosphere, belongingness, culture, and aesthetics” were thus weakened or became ambiguous and embodied in the sense of place. When the historic sites are revitalized based on the concept of in-situ under the protection of normality in everyday life, the sense of place should be perfectly represented through popularizing of the conscious conservation of cultural heritage and strengthened negotiation of multi-social forces. This is an alternative way of safeguarding cultural heritage in order to strengthen the aesthetic and cultural value of historic sites in local temples.

Aiming at the problems of low accuracy and slow speed in the current remote sensing image classification algorithm,In order to improve remote sensing image classification, a quantum entanglement algorithm is proposed.The model transforms the classification process of remote sensing image into a random self-organization process of quantum particles in the state configuration space. The state configuration formed by entanglement of quantum particles evolves with time and finally converges to an average probability distribution.Taking Kunming city of Yunnan province as the research area, this paper compares the classification method in this paper with the traditional remote sensing classification method by using the 02C image data of yuanyuan1.Compared with other classification methods, the classification accuracy of this paper meets the requirements.

Ecology and environmental suitability are widely used in urban ecology and regional ecology. However, there is still a lack of systematic evaluation method system for the research impacts of tourism development and tourism resource development on ecology and environment in ecologically sensitive scenic spots. Taking Lijiang River Basin, an ecologically sensitive area with typical karst landforms, as an example, this paper analyses the ecological and environmental suitability of tourism development from the perspective of space. In this paper, TM image and DEM model were firstly used to extract NDVI, slope, slope aspect and other related data. Then, based on the characteristics of the study area, the data of each factor was graded and assigned with a grade value, and the spatial situation of each single factor was analyzed, and superposition was carried out at last. Meanwhile, the study area is divided into three levels for tourism development, namely, unsuitable area, sub-suitable area and suitable area.

There are some problems in the visualization of 3D model of buildings at present, such as redundant texture data and large memory occupation of loading texture data, which pose challenges to the smooth loading of 3D building visualization. In this paper, we propose a method which using fractal quadtrees to simplify texture data and compress management. Firstly, this method uses the fractal self-similarity and the feature that the same texture has the same fractal dimension to screen all the textures, when the fractal dimension of multiple textures is within the threshold range. Radon transform will be performed on these textures to calculate their standard deviation and further simplify the texture. Secondly, we use fractal texture compression to create a multi-resolution texture data structure with quadtree structure, so that the building 3D model can achieve dynamic visualization of different scales. Finally, the parallel texture mapping of all faces of the 3D model of the building is implemented according to the texture calling rules. Experimental results demonstrate that the texture is managed by the method proposed in this paper, which shortens the loading time of texture and reduces the memory occupation by about 48.92%. Therefore, the method of texture simplification and compression proposed in this paper has a significant effect in the process of building 3D model visualization.

The evaluation of the bathymetric capability of traditional airborne lidar system is mostly based on the formula of bathymetric capability by evaluating the diffuse attenuation coefficient (Kd). This method is derived form the assumption that the reflectance of sediment is fixed. In this study ,however,the reflectance of sediment is not fixed. Therefore, this study improves the ability of bathymetric formula, and proposes a particle scattering classification algorithm to obtain the transmissivity value. The algorithm filters the scattering modes of particles by scattering discrimination factor (q), and obtains the transmissivity values by using the scattering intensity formulas. Experiments show that, when the transmissivity is in the range of 0–1 and the average values of Kd(532 nm) are 0.1150 m−1, 0.0894 m−1 and 0.0903 m−1 in January, June and October respectively, accordingly, the bathymetric capabilities are 0–44 m, 0–61.5 m and 0–52.5 m, respectively. Compared with the original bathymetric method, these results show that the maximum bathymetric value has measured by the improved bathymetric capability formula and scattering classification algorithm has decreased under the influence of the change of sediment reflectance, and the result is more consistent with the actual situation and more accurate.

The wavelet threshold method is widely used in signal denoising. However, traditional hard threshold method or soft threshold method is deficient for depending on fixed threshold and instability. In order to achieve efficient denoising of echo signals, an adaptive wavelet threshold denoising method, absorbing the advantages of the hard threshold and the soft threshold, is proposed. Based on the advantages of traditional threshold method, new threshold function is continuous, steerable and flexibly changeable by adjusting two parameters. The threshold function is flexibly changed between the hard threshold and the soft threshold function by two parameter adjustments. According to the Stein unbiased risk estimate (SURE), this new method can determine thresholds adaptively. Adopting different thresholds adaptively at different scales, this method can automatically track noise, which can effectively remove the noise on each scale. Therefore, the problems of noise misjudgement and incomplete denoising can be solved, to some extent, in the process of signal processing. The simulation results of MATLAB show that compared with hard threshold method and soft threshold method, the signal-to-noise ratio (SNR) of the proposed de-noising method is increased by nearly 2dB, and 4dB respectively. It is safely to conclude that, when background noise eliminated, the new wavelet adaptive threshold method preserves signal details effectively and enhances the separability of signal characteristics.

The essential oil from the aerial parts of Lobularia maritima was investigated for its chemical composition, and its repellent and insecticidal efficacy against the grain pests Callosobruchus maculatus, Tribolium castaneum and Sitophilus oryzae. A number of 41 compounds were identified by GC-MS from which azeleonitrile (39.7%), trans-3-pentenenitrile (36.3%) and 4-isothiocyanato-1-butene (10.9%) were the most abundant. A fumigant bioassay-guided fractionation of the essential oil constituents led to the isolation of trans-3-pentenenitrile. Its structure was confirmed by EI-MS and NMR techniques. Fumigant effect of the essential oil was strong (LC50 = 7.48 μL/L) on C. maculatum and moderate on S. oryzae and T. castaneum (LC50 = 35.37 and 59.94 μL/L, respectively). trans-3-pentenenitrile showed strong fumigant effect on the three pest species (LC50 = 6.62–8.36 μL/L). Both the oil and trans-3-pentenenitrile showed strong contact effect with LD50 values in the range 4.84–7.81 µg/adult. The oil showed a repellency of 100% on C. maculatus and S. oryzae at concentrations higher than 0.05 and 0.1 nL/cm2, respectively, and 93% against T. castaneum yet at 0.2 nL/cm2. trans-3-pentenenitrile also showed 100% repellency against C. maculatus (≥ 0.05 nL/cm2), S. oryzae (≥ 0.15 nL/cm2) and T. castaneum (0.2 nL/cm2). The results in this study indicated that the essential oil of L. maritima is an important source of trans-3-pentenenitrile which can be used in the development of insecticidal agents against the three grain pests.

Clustering as an unsupervised learning method is a process of dividing a data object or observation object into a subset, that is to classify the data through observation learning instead of example learning without the guidance of the prior class label information. Bat algorithm (BA) is a swarm intelligence optimization algorithm inspired by bat's ultrasonic echo localization foraging behavior, but it has the disadvantages of being easily trapped into local minima and not being highly accurate. So an improved bat algorithm was proposed. In the global search, a Gaussian-like convergence factor is added, and five different convergence factors are proposed to improve the global optimization ability of the algorithm. In the local search, the hunting mechanism of the whale optimization algorithm (WOA) and the sine position updating strategy are adopted to improve the local optimization ability of the algorithm. This paper compares the clustering effect of the improved bat algorithm with bat algorithm, flower pollination algorithm (FPA), harmony search (HS) algorithm, whale optimization algorithm and particle swarm optimization (PSO) algorithm on seven real data sets under six different convergence factors. The simulation results show that the clustering effect of the improved bat algorithm is superior to other intelligent optimization algorithms.

Cluster analysis refers to the process of grouping a collection of physical or abstract objects into multiple classes of similar objects. Determining the optimal classification number of a data set is the key to the clustering problem, that is to say whether the data set can be effectively partitioned. Cluster validity study is a process of establishing clustering effectiveness indicators, evaluating clustering quality and determining the optimal number of clusters. A validity function of fuzzy C-means (FCM) clustering algorithm is proposed by adopting the division of intra-class compactness and inter-class separation, whose minimum represents the best clustering. Then, the proposed validity function on FCM clustering algorithm is compared with the known typical validity functions by carrying out simulation experiments to compare the related clustering performance. Three data sets are adopted to carry out FCM clustering, which includes three classical data sets, two artificial data sets and six real data sets in UCI database. Simulation experimental results show that the proposed validity function can effectively partition the data set.

Currently, multivariate time series anomaly detection has made great progress in many fields and occupied an important position. The common limitation of many related studies is that there is only temporal pattern without capturing the relationship between variables and the loss of information leads to false warnings. Our article proposes an unsupervised multivariate time series anomaly detection. In the prediction part, multiscale convolution and graph attention network are mainly used to capture information in temporal pattern with feature pattern. The threshold selection part uses the root mean square error between the predicted value and the actual value to perform extreme value analysis to obtain the threshold. Finally, the model in this paper outperforms other latest models on actual datasets.

Compared to the wide use of digital elevation model (DEM), digital surface model (DSM) receives less attention because that it is composed by not only terrain surface, but also vegetations and man-made objects which are usually regarded as useless information. Nevertheless, these objects are useful for the identification of obstacles around an aerodrome. The primary objective of the study was to determine the applicability of DSM in obstacle clearance surveying of aerodrome. According to the requirements of obstacle clearance surveying at QT airport, aerial and satellite imagery were used to generate DSM, by means of photogrammetry, which was spatially analyzed with the hypothetical 3D obstacle limitation surfaces (OLS) to identify the potential obstacles. Field surveying was then carried out to retrieve the accurate horizontal position and height of the obstacles. The results proved that the application of DSM could make considerable improvement in the efficiency of obstacle clearance surveying of aerodrome.

The intrinsic magnetic topological insulator MnBi_{2}Te_{4} exhibits rich topological effects such as quantum anomalous Hall effect and axion electrodynamics. Here, by combining the use of synchrotron and laser light sources, we carry out comprehensive and high-resolution angle-resolved photoemission spectroscopy studies on MnBi_{2}Te_{4} and clearly identify its topological electronic structure. In contrast to theoretical predictions and previous studies, we observe topological surface states with diminished gap forming a characteristic Dirac cone. We argue that the topological surface states are mediated by multidomains of different magnetization orientations. In addition, the temperature evolution of the energy bands clearly reveals their interplay with the magnetic phase transition by showing interesting differences between the bulk and surface states, respectively. The investigation of the detailed electronic structure of MnBi_{2}Te_{4} and its temperature evolution provides important insight into not only the exotic properties of MnBi_{2}Te_{4}, but also the generic understanding of the interplay between magnetism and topological electronic structure in magnetic topological quantum materials.

The photoelectrical characteristics of field-effect phototransistors (FEPTs) are investigated experimentally based on a graphene-PbS quantum dot (QD) hybrid. The device presented a wide spectral response range from 300 to 1400 nm because of multiple-exciton generation of PbS QDs. The photoelectrical responsivity reached up to 2×105A/W at low bias voltage ( ~10 mV) and became more sensitive with increasing bias voltage. The transient response of the hybrid FEPTs was also measured with the relaxation times and the decay times around several seconds. Such devices exhibit great competitiveness in wide spectral response, flexible integrated circuits with low cost, large area, low energy consumption, and high responsivity.

A series of plate impact shock-reshock and shock-release experiments were conducted by using an one-stage light gas gun to determine the critical shear strength of the 2024 aluminum alloy under shock compression levels ranging from 0.66 to 3.05 GPa in the present study. In the experiments, a dual flyer plate assembly, i.e., the 2024 aluminum alloy flyer backed either by a brass plate or a PMMA plate, was utilized to produce reshock or release wave. The stress profiles of uniaxial plane strain wave propagation in the 2024 aluminum alloy sample under different pre-compressed states were measured by the embedded stress gauges. The stress-strain data at corresponding states were then calculated by a Lagrangian analysis method named as path line method. The critical shear strengths at different stress levels were finally obtained by self-consistent method. The results show that, at the low shock compression level (0.66 to 3.05 GPa), the critical shear strength of the 2024 aluminum alloy cannot be ignored and increases with the increasing longitudinal stress, which may be attributed to rate-dependence and/or pressure dependent yield behavior of the 2024 aluminum alloy.

Interferon- (IFN-) λ1 is regarded as a potent bio-active molecule in innate immunity. However, little is known about its role in chronic spontaneous urticaria (CSU). We therefore investigated expression of IFN-λ1 in CSU, its cellular location, and its influence on inflammatory cell accumulation by using flow cytometry analysis, skin tissue dispersion, immunohistochemical stain, and a mouse peritoneal inflammation model. The results showed that level of IFN-λ1 was 2.0-fold higher in plasma of the patients with CSU than the level in healthy control (HC) subjects. Among leukocytes examined, only CD8+ T cells expressed more IFN-λ1 in CSU blood. Double labeling immunohistochemical staining revealed that IFN-λ1+ inflammatory cells such as mast cells, eosinophils, B cells, neutrophils, and macrophages were mainly located in dermis, whereas epidermis tissue highly expressed IFN-λ1. IFN-λ1 induced a dose-dependent increase in number of eosinophils, lymphocytes, mast cells, macrophages, and neutrophils in the peritoneum of mice at 6 h following injection, which was inhibited by pretreatment of the animals with anti-intercellular adhesion molecule- (ICAM-) 1 and/or anti-L-selectin antibodies. In conclusion, IFN-λ1 is likely to play a role in the pathogenesis of CSU. Blocking IFN-λ1 production may help to reduce the accumulation of inflammatory cells in the involved CSU skin.

We present a new regime to generate high-energy quasimonoenergetic proton beams in a “slow-pulse” regime, where the laser group velocity v_{g}