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Spiral concentrator has been widely applied in large scale in beneficiation process for iron, tin, titanium, tantalum niobium and other metals and sulfur, coal and other non-metallic ores in the beneficiation production has been a large number of applications, but at present the spiral concentrator concentrate adjustment relies on artificial control, there is an urgent need to develop an adaptive interception of concentrates instead of the artificial interception in order to improve the production efficiency of the spiral concentrator. The first task to achieve this goal is the need to solve the problem of relying on the artificial naked eye to obtain information about the location of the concentrate zone, so an improved UNet network model, Res50-UNet-FD, is proposed. The model uses the UNet model as the base model, and replaces the residual network ResNet50 with the feature extraction network in the coding part of the UNet network, which solves the problems of feature gradient disappearance as well as network disappearance in the process of deep feature extraction, and effectively improves the accuracy of feature information extraction in the concentrate zone of the spiral concentrator. The algorithm model uses the UNet model as the base model, and the residual network ResNet50 replaces the feature extraction network in the coding part of the UNet network, which solves the problems of feature gradient disappearance as well as network disappearance in the process of deep feature extraction, and effectively improves the accuracy of feature information extraction in the concentrate zone of the spiral concentrator. At the same time, in order to improve and optimize the problem of imbalance of the sample data of the spiral concentrator concentrate image, a hybrid loss function of Focal Loss and Dice Loss is utilized instead of the original Cross-Entropy loss function. Upon comparison, this paper s algorithm outperforms the VGG-UNet, Res34-UNet, and DC-UNet network models, and the mlOU, mPA, Fl score, and precision of the algorithm's model are 0.963 2, 0.986 9, 0.987 0, and 0.990 7, respectively. In terms of performance metrics, the overall performance of this paper s algorithm, both in terms of mlOU, mPA, and Fl scores, is better than that of VGG-UNet, Res34-UNet, and DC-UNet network models, and the algorithm s overall performance is stable. The algorithm realizes the segmentation and identification of the concentrate band of the spiral concentrator, and the segmentation precision can meet the demand for the identification of the feature information of the concentrate band of the spiral concentrator in the production, and lays the foundation for the realization of the adaptive interception of the concentrate of the spiral concentrator. [ABSTRACT FROM AUTHOR]

Based on three processing parameter combinations of optimized layer thickness, the influences of processing parameter combinations on the basic properties of AlSilOMg alloy samples printed by SLM was analyzed. In samples of the three processing parameter combinations, hardness is more than 63HRB, wear loss of per area is below 1.5X10-5/(s · mm²), porosity is below 0.05%, tensile strength is higher than 440 MPa, and dimensional errors are within ± 0.1 mm. Surface roughness Ra of the upper surface is less than 4 µm, and surface roughness Ra of the side surface is less than 5 µm. The surface quality of the samples printed by the layer thickness 30 µm is the best. [ABSTRACT FROM AUTHOR]

The detection background of the infrared target is always complex and non-stationary. In order to improve the performance of target detection, the target signal is often enhanced by suppressing the background. Aiming at the problems of low detection rate and high false alarm rate of traditional background suppression methods, a complex background suppression algorithm based on improved filter and image multi-scale transformation is proposed. Firstly, the infrared image is filtered to obtain the preprocessed image. Secondly, the image background is smoothed by Gaussian pyramid multi-resolution technology. Thirdly, the Cubic interpolation algorithm is used to improve the resolution of the image and get the background estimation image. Finally, the difference between the preprocessed image and the background estimated image is estimated to obtain the result of background suppression. Experiments show that the real-time performance of the proposed algorithm is 19% better than that of the traditional method, and it has good adaptability to a variety of complex background situations. Meanwhile, the algorithm has low computational complexity, which is conducive to the realization of real-time engineering applications. [ABSTRACT FROM AUTHOR]

The integrity and usability of the navigation system are important safeguards to small unmanned aerial vehicles' autonomous flight. A quadrotor aircraft with ARM microprocessor is designed. A multi-information fusion navigation scheme is proposed, which consists of micro-electro mechanical system (MEMS) inertial components, magnetometers, GPS, optic-flow imaging sensor and barometer. And an asynchronous centralized filter method is designed for separating the time update period and the measurement update period. According to the nonlinear characteristics of the navigation scheme, a nonlinear Kalman filter based on Sigma-point Kalman filter(SPKF) is proposed. In all, a micro multi-information navigation system of the quadrotor aircraft is built. Experiments are carried out and the results show that the designed navigation system can supply good attitude, velocity and position reference both in a static-state test and in a dynamic flight test. The navigation system can meet the accuracy and reliability requirements of the quadrotor aircraft under different flight tasks. [ABSTRACT FROM AUTHOR]

The influence of the working environment on MEMS inertial sensors in the MEMS attitude reference system and the key technologies are analyzed. A thermal analysis model is built based on finite element method. Some heat dispersion schemes are proposed and the optimal selection is made based on the finite element analysis. The selected heat dispersion design is validated by the prototype of the MEMS inertial system. A piecewise linear model is put forward to solve the strong nonlinear errors of MEMS inertial sensors overall temperature. The calibration method is improved and the accuracy is improved in practice. The worthiness condition for the attitude integrated algorithm is investigated and the constraints for the attitude filter based on the flight state identification from the data of MEMS inertial sensors are optimized. The tests based on the rotation table and flight test are carried on and the validation of optimization method is demonstrated. The attitude errors are no more than 2.50° overall the flight and they are no more than 1° at the stable flight state. The result shows that the MEMS inertial attitude reference system can be used in micro and small UAV or as the backup of main inertial navigation system(INS) in aircraft. [ABSTRACT FROM AUTHOR]

Objectives: Methamphetamine (METH) is an illicit psychoactive substance that can damage various organs, with the urinary system being one of its significant targets. This study aims to explore the role of microtubule affinity-regulating kinase 4 (MARK4) in METH-induced acute kidney injury (AKI)., Methods: A total of 10 healthy adult male C57BL/6 mice were randomly divided into a control group and a METH group, 5 mice in each group. The METH group was administered METH (20 mg/kg, intraperitoneally, once daily for 3 consecutive days), while the control group received an equal volume of physiological saline. The mice were executed 24 hours after the final injection, and the success of the AKI model was detected by blood serum creatinine, blood urea nitrogen, and renal HE staining. Proteins differentially expressed between kidney tissues with METH-induced AKI and normal kidney tissues were screened by proteomics techniques and subjected to gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and bioinformatics analysis. The accuracy of proteomic data was validated using Western blotting, and the expression levels of MARK4 and cleaved caspase-3 in mouse kidneys were measured. We further explored the role of MARK4 in METH-induced AKI. Firstly, a METH toxicity model was established in BUMPT cells to screen the appropriate concentration and time of METH treatment; the viability of BUMPT cells after METH treatment and the expression of cleaved caspase-3 were detected by interfering with MARK4 expression through inhibitors., Results: The proteomic analysis of kidney tissues from METH and control groups screened for a total of 17 differentially expressed proteins, of which 11 were up-regulated and 6 were down-regulated (all P <0.05). The expression levels of MARK4 and cleaved caspase-3 were elevated in the kidneys of METH-treated mice (both P <0.05). The activity of BUMPT cells gradually decreased with increasing METH treatment concentration (all P <0.05), where the viability of BUMPT cells decreased to about 60% after METH treatment at 4 mmol/L. Compared with the control group, expression levels of MARK4 and cleaved caspase-3 were increased with higher METH concentrations and longer exposure times in a concentration- and time-dependent manner (all P <0.05). Inhibition of MARK4 expression improved METH-induced decrease in BUMPT cell activity, down-regulated the expression of cleaved caspase-3, and decreased the apoptosis of BUMPT cells induced by METH., Conclusions: MARK4 is highly expressed in a mouse model of METH-induced AKI, and MARK4 mediates METH-induced AKI by regulating cell apoptosis.

Objective: To reconstruct tumor clonal haplotypes based on the third-generation sequencing data to effectively identify tumor heterogeneity., Methods: We developed an algorithm for extracting somatic mutational event from the mixed tumor data and determining the connection weight of each somatic cell mutation site through the probability function. A reconstruction algorithm of the haplotype was designed based on the maximum spanning tree, and following the principle of inheritance between tumor clones, the connection pattern was determined at each mutation site in the clonal maximum spanning tree in a stepwise manner. The number, ratio and evolution of the sub-clones were estimated using the depth stripping method., Results: In the simulation experiments, we analyzed the accuracy of the algorithm based on 4 indexes, namely the coverage, read length, subclone number and somatic variant rate, and the Results demonstrated a good robustness of the algorithm. The Results of the experiments showed that the mean sub-clone haplotypes accuracy exceeded 97%, suggesting that this algorithm significantly outperformed the previous Methods., Conclusions: The proposed method can accurately reconstruct tumor subclonal haplotypes and clarify the process of tumor clonal evolution, and can thus provide a theoretical basis for tumor heterogeneity research and assist in clinical decision-making.

Objective: To present our initial experience with robot-assisted laparoscopic prostatectomy (RALP) for complicated cases.
 Methods: Clinical and pathological data from 4 complicated prostate cancer cases, who underwent RALP from October to November in 2015, were analyzed retrospectively. All the cases were conducted transurethral plasmakinetic enucleation of prostate and hormonal therapy before RALP.
 Results: All surgeries were done successfully. The age, baseline prostatic special antigen, clinical tumor stage, operation time and estimated blood loss were 58-70 years, 6.04-70.15 ng/mL, T2b-T3b, 210-360 min and 50-250 mL, respectively. No blood transfusion was needed. All surgical margin were negative.
 Conclusion: Although previous transurethral surgeries and hormonal therapies may increase the difficulty for operations, RALP is still appropriate for the complicated cases of prostate cancer.

The electrocardiac signals exhibit obvious unsteadiness and contain many noises in the processing of detecting. In this paper, a wavelet transform, which can be located in the fields of time and frequency, is introduced to decompose the ECG signals on multi-scales. In characteristic scales, the electrocardiac signals can be decomposed. After removal of various noises, the electrocardiac signals are formed again perfectly. This method provides more accurate ECG data for use in medical diagnosis.

The study of pulse wave, including its quantitative analysis and propagation, is one of the hot topics in the fields of clinical medicine, such as how to detect cardiovascular diseases and make early diagnosis without harm. In this paper are discussed a new type of automatic cardiovascular diagnosis method and the corresponding test instrument. The cardiovascular system parameters can be achieved through the wave changes, related data processing and analyzing. This system includes piezo-film transducer, signal amplifier, data collecting and data analyzing equipment. Various pulse diagrams can be shown in omnidirectional and multifunctional ways. The measurement error can be reduced effectively by introducing Mini-wave analysis in the design of software. The research indicates that combination of this equipment with the traditional Chinese medicine will provide wide practical application.