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To address one-dimensional river network models' difficult solution in complex areas and insufficient capability of capturing shock waves, this paper develops a hydrodynamic model suitable for complex river networks in mountainous and plain areas. The model is based on the finite volume discretization of the Saint-Venant equations and adopts the HyperLogLog (HLL) approximate Riemann solver to solve numerical fluxes at interfaces. Additionally, an extended Riemann method is employed to solve the water levels at bifurcation points. The model's validity is confirmed by a dam-break model, demonstrating strong capabilities for handling cross-critical flow changes. Meanwhile, the model features stable calculation with accurate results even under dry-bed situations. Thus, the model is further applied to the Jiaokou–Yinjiang Region and the results show that it effectively tackles the dry-bed problems encountered during low inflows in mountainous areas. Additionally, during floods, this model exhibits high simulation accuracy, accurately reflecting the flood rise and recession processes as well as the timing of flood peaks. Compared to the finite difference method, the model features comparable simulation accuracy and computational efficiency, with its computational efficiency improved by 15.7%. In terms of early warning and forecasting of water levels, the proposed model has higher accuracy and can provide significant support for flood control decision-making. The built model can provide new insights for flood forecasting and simulation in mountainous areas and other complex terrains.

Considering the influence of the center of gravity (CG) and mass variations on flight dynamics, a nonlinear L1 adaptive control approach is presented in this paper and applied to design a flight controller to achieve the aim of improving the robustness of the flight system against sudden changes in the CG. Based on L1 adaptive control, this approach introduces a feedback linearization strategy to eliminate the known nonlinear dynamics of the aircraft and realize the rapid decoupling of the aircraft states. The nonlinear L1 adaptive control also addresses the problem of insufficient robustness in conventional L1 adaptive control due to overcoming its own known nonlinearities, and then improves the robustness to external disturbances. Additionally, the modified piecewise constant is employed to design the adaptive law to improve the estimation accuracy. Finally, the control performance and robustness of the designed flight control law are verified in the hardware in the loop (HIL) flight control semi-physical experimental platform. Experimental results indicate that the nonlinear L1 adaptive flight control law has strong robustness, which can effectively overcome the disturbance of the CG and mass sudden variations. Moreover, the designed controller takes into account the transient performance while ensuring the steady-state performance of the aircraft with CG change.

UAVs formation is a complex nonlinear system. Although quadrotor has many advantages, its dynamics model is nonlinear, coupled, and under driven. For model-based controller design, physical constraints, model uncertainties and external disturbances significantly deteriorate control performance. Therefore, a multi-constraints MPC strategy based on error model is proposed for the quadrotor formation. Firstly, a 3D model for quadrotor is established by using the Lagrange-Euler formulation, in which the model is divided into RS and TS. The corresponding multi-constraint MPC is designed for the two subsystems respectively. The tracking errors caused by external disturbances can be eliminated because of the integrator embedded in the augmented model. Comparing with RMPC, by making reasonable modifications to the cost function, the asymptotic stability of the open loop and the closed-loop subsystem can be ensured by MMPC. Moreover, the stability analysis of the above-mentioned algorithm is carried out. The simulation results show that the controller of the formation can not only achieve good path tracking, but also robustness to the multiple constraints and disturbances.

Objective To explore the diagnostic values of different post-processing modes of dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) in the differentiation of glioma grade. Methods A total of 89 patients with glioma confirmed by postoperative pathology in our hospital from January 2013 to July 2019 were enrolled, including 29 patients of gradeⅡ, 24 of grade Ⅲ and 36 of grade Ⅳ. All patients underwent preoperative DCE-MRI examination, and corresponding parameters were collected and processed using post-processing software Tissue-4D and Omni-Kinetics (OK) respectively. One-way ANOVA was adopted to compare the differences of the obtained parameters among glioma of different grades. Spearman rank correlation analysis was performed to analyze the correlation between each parameter and glioma grade, and receiver operating characteristic (ROC) curve was used to evaluate the area under the curve (AUC) of each parameter. Results In hot spot analysis, the Ktrans values of both post-processing modes, as well as the iAUC value of Tissue-4D and the Vp value of OK were all significantly different among glioma of different grades (P < 0.05). The Kep value of grade Ⅳ glioma was obviously lower than that of grade Ⅱ glioma (P < 0.05), while the Ve values of grade Ⅳ and Ⅲ tumors were notably higher than that of gradeⅡ one (P < 0.05). The AUC value of Ktrans (Tissue-4D) was 0.949 in the differentiation of gradeⅡ from grade Ⅳ glioma (P < 0.01), indicating the highest diagnostic efficiency, and the correlation between Ktrans (OK) and glioma grade was the highest (r=0.775, P < 0.01). In the histogram analysis of OK, the 50th percentile of Ktrans value, the mean and the 75th and 90th percentiles of Ve value, the mean, entropy and the 50th percentile of Kep value, as well as the mean value of Vp showed significances in the differentiation of grade Ⅱ from grade Ⅲ and grade Ⅱ from grade Ⅳ glioma (P < 0.05). Moreover, the energy, entropy and 50th, 75th, 90th percentiles of Vp value, and the energy of Kep value were statistically different in the identification of grade Ⅳ from grade Ⅱ and grade Ⅳ from grade Ⅲ (P < 0.05). Conclusion The Ktrans and Ve values of the 2 post-processing modes have rather high diagnostic efficiency for glioma grading in the hotspot analysis, and the histogram analysis of OK software involves more abundant and comprehensive parameters.

Aiming at the situation constraint problem in air combat trajectory control, a constrained backstepping flight control law is proposed. This method considers the constraints of the amplitude and bandwidth of the state variables in the traditional flight process. At the same time, it also introduces the situation information of the two aircraft air combat into the control law. The correction error is defined in the control law error, and the angle situation information is used to update the correction error. When the situation is dominant, the system can perform the maneuver task normally, and the correction error converges to 0 quickly When it is a disadvantage, the correction error becomes larger, and affects the maneuver, so that the situation changes to the advantage. The simulation results show that the method can effectively make the situation change in a favorable direction during maneuvering flight.

Aiming at the problems of more blind monitoring areas and unable to show the distribution of gas flow field in single point monitoring mode of gas in mining face, based on edge computing technology, a method of constructing gas concentration field in mining face, visual display of gas flow field and monitoring and early warning of abnormal gas emission is proposed. The platform revolutionized the traditional methane monitoring model, replaced single-point monitoring with area monitoring, replaced methane substations with edge computing gateways, and realized global monitoring of methane in coal mining faces, built methane data fields underground, displayed methane cloud diagrams, and captured methane emission abnormally. The specific ideas are as follows: the distribution characteristics of “step rise” and “gradual rise” of methane in mining face are obtained by field measured data. Based on this, a full coverage monitoring scheme of methane is designed, and the full coverage monitoring layout system of methane is completed by using a new MEMS methane sensor; the monitoring data are transmitted to the edge computing gateway by wireless or wired means; edge computing gateway is located in mining roadway, embedded data processing model, single point methane concentration abnormal jump recognition model and periodic abnormal fluctuation discrimination model. The data processing model to build methane digital field, methane dynamic cloud diagrams, the jump model of single point methane concentration anomaly are used to judge the fluctuation of single point methane concentration anomaly, the discrimination by region mode to complete the mining face methane abnormal fluctuation behavior capture. Finally, the macroscopic display of methane concentration field cloud diagram and microscopic capture of abnormal fluctuation of methane concentration are realized.

Nonlinear Dynamic Inversion(NDI) control has excellent rapidity and decoupling ability, unfortunately it lacks the essential robustness to disturbance. From the perspective of enhancing the robustness, an adaptive NDI method based on L1 adaptive structure is proposed. The L1 adaptive structure is introduced into the NDI control to enhance its robustness, which also guarantees the stability and expected dynamic performance of the system suffering from the disturbance influence. Secondly, the flight control law of the advanced aircraft is designed based on the present method to improve the robustness and fault tolerance of the flight control system. Finally, the effectiveness of the flight control law based on the present approach is verified under the fault disturbance. The results showed that the flight control law based on L1 adaptive NDI has excellent dynamic performance and strong robustness to parameter uncertainties and disturbances.

As far as airborne sensors are concerned, the measurement accuracy is an important indicator that cannot be ignored and may directly affect final measurement results. In order to improve the measurement accuracy of a flush air data sensing (FADS), which is an advanced sensor, this paper proposed a new method based on the normal cloud model and the multi-objective programming (MOP). First, the high-precision FADS model is established by using the database obtained with the CFD software and aerodynamics knowledge. Meanwhile, the uncertainty and randomness of signals caused by measurement noise are quantitatively analyzed by using the normal cloud model. Then, in the process of data fusion, a new method for calculating the weights is proposed based on the slack variable method and the Lagrange multiplier method. The simulation results show that the proposed method can improve the measurement accuracy by 3.2% and reduce the dispersion of measurement data by 68.88%.

Objective To determine the localization of axillary artery on body surface through computed tomography angiography (CTA), so as to provide imaging data of axillary artery anatomy for clinical treatment. Methods The imaging data of patients undergoing CTA of head and neck in our hospital from July to November in 2020 were collected. A total of 456 sides (228 cases) were initially included, and then 197 sides were excluded due to improper body position. 3-D reconstruction was performed on the remaining 259 sides, and the distances as well as position relationship of axillary artery with clavicle, coracoid process and body surface were measured and observed. After the further exclusion of 110 sides with unlocatable axillary arteries, 149 sides were finally included; the length and inner diameter of axillary arteries were measured, and the origin and types of branches were observed and analyzed. Results The distance from the starting point of axillary artery to the perpendicular line of the posterior edge of clavicle and to the midclavicular line was 16.9±5.3 mm and 11.9±6.1 mm, respectively. The length of the vertical line of the lower edge of the coracoid process intersecting the axillary artery was 29.4±9.4 mm, and the proximal end of the third segment of the axillary artery lay below the coracoid process. In terms of the branches, the highest frequency of superior thoracic artery (ST) which branched out of the first segment of axillary artery was 49.0%; the thoracoacromial artery (TA) and lateral thoracic artery (LT) originated from the second segment, with the highest frequency of 49.7% and 47.7%, respectively; the highest frequencies of subscapularis artery (SS), anterior humeral circumflex artery (CHA) and posterior humeral circumflex artery (CHP) from the third segment were 71.1%, 11.4% and 64.4, respectively. The occurrence rate of TA, SS and CHP was all 100%; although that of LT was 96.6%, it presented the most types (4 types). In addition, the occurrence rate of CHA was 12.1%, and that of deep brachial artery (DB) with single stem originated from the third segment was 37.6%. Conclusion In supine position and adduction of the upper limb, the starting point of the axillary artery and the proximal of its third segment can be localized by one fingerbreadth from the medial midclavicular line as well as posterior to the clavicle, and by two fingerbreadths below the coracoid process, respectively.

Aiming at problems of traditional discriminant model of mine inrush water source, such as poor nonlinear ability, poor model stability and low discrimination accuracy, PCA -CRHJ discriminant model of mine inrush water source is constructed based on principal component analysis (PCA) method and cycle reservoir with hierarchical jumps (CRHJ). PCA is introduced to reduce dimension of multivariate time water inrush sequence and extract key features, the water inrush data is reconstructed to obtain principal component water inrush series, and the CRHJ model is trained by reconstructed sequence. The model completed by the training is applied to water inrush source discrimination in Zhangji Coal Mine and Xinzhuangzi Coal Mine for validity verfication. The results show that: ① By comparing with CRHJ、cycle reservoir with regular jumps (CRJ) and echo state network (ESN) models, the results show that PCA -CRHJ model has the best actual discriminant effect and the accuracy can reach 100%. ② The PCA -CRHJ model has five main types of parameters, namely, reserve pool size, input connection weight, one -way connection weight, hierarchical two -way jump weight and jump step size, the sensitivity analysis of these five types of parameters shows that the input weight parameters have the greatest impact on the model discrimination accuracy. When three kinds of weight parameters obtain the optimal value and remain unchanged, the reserve pool size has the greatest impact on the model error, while the jump step size has less effect.

Objective To explore the correlation between multimodal magnetic resonance imaging (MRI) and expression of tissue factor (TF) in glioblastoma (GBM), and investigate the values of MRI parameters as imaging markers for TF. Methods The preoperative routine and functional MRI data of 60 patients with GBM confirmed by surgery and pathology in our hospital from August 2014 to November 2018 were retrospectively collected and analyzed for the parameters, including necrosis ratio, surface regularity, enhanced area volume, edema area volume, volume transfer constant Ktrans, relative cerebral blood volume (rCBV) and relative cerebral blood flow (rCBF) by post-processing. The expression of TF in the GBM tissue was detected with immunohistochemical staining, and then the correlation between above each parameter and TF expression was analyzed. Receiver operating characteristic (ROC) curve analysis was used to obtain the optimal threshold values, sensitivity and specificity of various imaging parameters in differentiation between GBM with TF of high expression and of low expression. Results The necrosis ratio, and Ktrans, rCBV and rCBF values were positively correlated with TF expression level (r=0.665, r=0.631, r=0.661, r=0.619, all P < 0.001). The necrosis ratio and Ktrans, rCBV and rCBF values were significantly higher in the highly-expressed TF group than the lowly-expressed TF group (P < 0.01). ROC analysis showed that all these MRI parameters presented TF level well, with area under curve (AUC) of rCBF reaching 0.907 (0.889, 0.857), that of necrosis ratio 0.869 (0.846, 0.676), that of Ktrans 0.854 (0.813, 0.833), and that of rCBV 0.804 (0.944, 0.571). The combination of conventional magnetic resonance and perfusion magnetic resonance parameters showed even better presention for TF expression level, with the AUC of necrosis ratio combined with Ktrans 0.982 (1, 0.875), necrosis ratio with rCBV 0.939 (0.889, 0.905), and necrosis ratio with rCBF 0.971 (0.944, 0.857). Conclusion Various magnetic resonance parameters (necrosis ratio, Ktrans, rCBV and rCBF) can better reflect TF expression in GBM patients, and can be used as imaging markers for TF expression in GBM.

In FE modeling of port crane structures, errors may be caused due to the simplification of complicated components, unclear physical properties, local approximation and inaccurate boundary conditions. So it is very important to update the FE model accuracy according to the experiment model and results. However there are two major problems when solving the model updating of port crane structure, the one is the difficulty of collecting the structure modal parameters with traditional modal experiment method because of the large scale of port crane structure, the other is mismatching problem while updating processing due to most of the model updating method currently constructing the objective function only by frequency. In this paper, an operational modal analysis is adopted to estimate the modal parameters of port crane structure based on the operational condition. A parametric model updating methodology of finite element (FE) model is proposed to solve port crane structure model updating: a series of design parameters of the FE model of port crane structure are selected as the main factors based on the sensitivity analysis, the objective function is built by considering the frequency correlation and the modal assurance criterion (MAC) together, and finally a zero-order/first-order combination algorithm is utilized to get the final accurate FE model of port crane structure. Research results showed that methodology proposed in this paper has satisfied updating accuracy for port crane structure, which verifies that the proposed method is suitable for model updating problem of this kind of structure.

Desmoplastic small round cell tumor (DSRCT) was a soft tissue sarcoma of mesenchymal cell origin that typically exhibited a multi-phenotypic pattern of immunohistochemical staining. DSRCT mainly presented in the abdomen sites and primary occurrence in bone was exceptional. In this study, we reported a new case of primary DSRCT of the tibia in a 33-year-old man who had intermittent pain in the left tibia. Radiographs showed transparent lesions in the left upper tibial. MRI revealed a lobular, lytic and ill-identified lesion with adjacent soft tissues swelling of the upper left tibia. CT confirmed notable destruction and wormlike osteolysis of the bone cortex. PET/CT showed a mass of high uptakes, indicating the malignance. He accepted surgical resection with followed multi-agent chemotherapy, containing vincristine, doxorubicin, ifosfamide and etoposide. Clinically and radiologically, the patient did not show any evidence of recurrence or metastasis at 30 months after surgical treatment. Primary osteogenic DSRCT was extremely rare and should be considered in differential diagnosis of bone tumors. Keywords: Bone, PET/CT, MRI, Desmoplastic small round cell tumor, Prognosis

Graphene nanowalls (GNWs) exhibit outstanding optoelectronic properties due to their peculiar structure, which makes them a great potential in infrared (IR) detection. Herein, a novel IR detector that is composed of polydimethylsiloxane (PDMS) and designed based on GNWs is demonstrated. Such detector possesses an anomalous temperature coefficient of resistance of 180% K−1 and a relatively high change rate of current (up to 16%) under IR radiation from the human body. It primarily attributes to the ultra-high IR absorption of the GNWs and large coefficient of thermal expansion of PDMS. In addition, the GNW/PDMS device possesses excellent detection performance in the IR region with a responsivity of ~1.15 mA W−1. The calculated detectivity can reach 1.07×108 cm Hz1/2 W−1, which is one or two orders of magnitude larger than that of the traditional carbon-based IR detectors. The significant performance indicates that the GNW/PDMS-based devices reveal a novel design concept and promising applications for the future new-generation IR photodetectors.

A display implementation method of coal mine business data based on 3DGIS was put forward. The method adopts way of data center to manage basic spatial data and business system data. Combining with 2DGIS and 3DGIS, it can comprehensively and intuitively show coal mine business data taking desktop platform and Web platform as the carrier. The method not only can provide intuitive and efficient way of data acquisition and perception for coal users, but also can provide functions of efficient space analysis and hidden information mining.

For cable drive with different rope number,the transmission error prediction method is explored based on BP neural network. A prediction model for transmission error is developed by a double hidden layer BP neural network. The input parameters of the model are preload,load and rotation angle respectively. The output parameter is the transmission error. The transmission errors under different conditions are tested firstly.And then the results are divided to training samples and prediction samples,which are used to train the network and verify the performance of the trained network. The experiment results show that the transmission error increases with the increase of rotation angle at the range of 0 to 180. And the biggest value is 5. 6 mrad,the prediction error is less than 0. 294 mrad. In conclusion,the double hidden layer BP neural network is effective to predict transmission error.

When the prehistoric man began to pick up stones, wood and other materials to make tools, we can confirm that creativity is not only the designer’s personal patent but a natural gift of humanity. As product designers, we must have more creativity than ordinary people. By analyzing a large number of actual design works and award-winning works in international competitions for many years, the author summarizes the similarities of creative design and explores the application of innovative product design methods in design.

In today’s fashion field, in addition to clothing and footwear, luggage also has most of the consumer market. Bags and luggage products are different from consumer goods such as clothing and accessories. The luggage market has greater potential and expansion capacity. With the advent of 2020, major progress has been made in building a well-off society in an all-round way, the level of the national economy has continued to improve, and the quality of life of our residents has become better and better. Consumers purchasing items not only consider quality and function, but also put forward requirements on quality and personalization. Compared with the traditional offline luggage stores, experiential offline stores pay more attention to consumers’ purchase process, optimize the purchase process, and satisfy the spiritual consumption experience. Today, many brands have begun to pay attention to the experience design of offline physical stores, but it is not enough, especially for luggage stores. In the era of the explosion of the experience economy, exploring the user experience and integrating experience design into the physical stores of luggage and bags has become a research hotspot in the new era.

In order to explore the design characteristics and application of materials, the role of materials in product innovation design needs to be given full play. From the perspective of material characteristics, this paper studies the user experience and innovation of the design and application of paper characteristics, ceramics and other materials, and summarizes the application mode of material experience in product innovation. To enrich users’ experience, it is necessary to break through the barrier of materials suitably, bring experience to users, and meet users’ dual demands for product functions and emotions.

In view of the state that the graphics of mining system software mostly use analog graph display, the paper introduced an implementation scheme of GIS graphics system based on OpenLayers. The scheme is secondary to be developed on the basis of OpenLayers, and uses HTML + CSS + JavaScript development technology to realize graph information browse on Web and mobile terminal on the basis of common GIS graphics function. The system has a good generality by means of graphical data driven.

Advantages and disadvantages of existing data keyt management methods were analyzed. A database keyt management method for coal mine safety monitoring and control system was proposed which was based on double dynamic password, and principle, realization and key technologies of the method were introduced. The method improves security and operability of database through identity authentication agent software and dynamic password generation algorithm. Key words:

In order to solve the problem that the competition for network traffic between business data and communication data in safety monitoring and control system of large coal mine, the paper proposed a load balancing communication solution using multiple network devices. Application results show that the solution can effectively guarantee data upload completely and timely, and plays an effective role in promoting stable and reliable running of safety monitoring and control system of large coal mine.

A series of directional solidification experiments have been performed to study the effect of cooling rate on the precipitation behavior of MC carbide in nickel-based superalloy under the temperature gradient of 500 K·s-1. Results reveal that the morphology of MC carbide changes from coarse block to fine strip, then to Chinese-script, and their sizes reduce gradually with the increasing of cooling rate from 2.53 K·s-1 to 36.4 K·s-1. At low cooling rates, most of these carbides are found to be located at the grain boundary and interdendritic regions, while the coupled growth of some carbides and γ matrix in the center of γ grains is occurred at high cooling rate. The main elements forming MC carbide are Ta, W, and Hf.

Antaibao Open Pit Coal Mine(AOPCM)'s mining activities have caused heavy metals contamination of surface, so it was urgent task to find a suitable method and survey full and prompt and long-term monitor on the heavy metals pollution. We chose methods of environmental magnetism and chemical analysis to analyze the surface materials on heavy metals contamination, by correlation of magnetic parameters and contents of chemical analysis, we can greatly reduce workload of chemical analysis and then achieve greater, faster, better, non-destructive, less chemical pollution and more economical results. The magnetic parameters and its groups act as proxy for the contents from chemical analysis. Three different sample areas sediments: loess or loess-like sediments, sedimentary rocks and alluvium, samples have different values of magnetic parameters. The values of magnetic susceptibility in this study were lower than others sediments and soils, secondly, the base rock and sedimentary rocks from the FD were of lower values of magnetic susceptibility than others of AOPCM. Contamination of Pb and Cd are more serious than other heavy metals. we can infer the contaminated level of anthropogenic heavy metals, DS > OD > FD. The mechanism may be mainly by the origin of the magnetic fraction in the anthropogenic particulate pollution and connected with the high-temperature technological processes during production and/or processing materials which have significant Fe content. Another point, when we want to study mechanism of magnetic properties used as proxy of heavy metals, the weak magnetic samples were measured and analyzed, we should be carefully.

The primary dendrite morphology and spacing of DZ125 superalloy have been observed during directional solidifi cation under high thermal gradient about 500 K/cm. The results reveal that the primary dendrite arm spacing decreases from 94 μm to 35.8 μm with the increase of directional solidifi cation cooling rate from 2.525 K/s to 36.4 K/s. The regression equation of the primary dendrite arm spacings λ1 versus cooling rate is λ1=0.013(GV)-0.32. The predictions of Kurz/Fisher model and Hunt/Lu model accord reasonably well with the experimental data. The infl uence of directional solidifi cation rate under variable thermal gradient on the primary dendrite arm spacing has also been investigated.