EFFECTS OF MINIMALIST FOOTWEAR ON THE LOWER LIMB LINEAR ACCELERATION AND ANGULAR VELOCITY DURING RUNNING

The purpose of this study was to explore if the tri-axial linear acceleration and angular velocity of knee and ankle joints differ between barefoot and minimal footwear running through investigating the extreme value difference. Eight participants were recruited for this experiment, acceleration parameters were measured utilizing IMU sensors. For the angular velocity, the minimum value in the frontal plane (p = 0.028) showed a decrease in the ankle joint. The minimal value in the sagittal plane and maximal value in the transverse plane (p = 0.001, p = 0) increased significantly. For the knee joint, the extreme values in the frontal plane increased (p = 0, p = 0), the maximal value increased and minimal value decreased with p = 0 and p = 0 in the sagittal plane. A significant decrease in the maximal value (p = 0) was exhibited in the transverse plane. The increased angular velocity may contribute to a result, with an insufficient arch support condition (minimalist shoes running) causing the foot’s intrinsic and extrinsic muscles and lower limb joints injury. These injuries should be a consideration for the novice minimalist runners

Establishment and characterization of a multi-drug resistant cell line for canine mammary tumors

Background and purposeCanine mammary tumors are the most common tumor disease of female dogs, and adjuvant chemotherapy often results in multi-drug resistance. Currently, the mechanisms underlying the development of tumor multi-drug resistance are unclear. The translation of research applications that can be used to effectively overcome tumor resistance is similarly hampered. Therefore, it is urgent to construct multi-drug resistance models of canine mammary tumors that can be used for research, to explore the mechanisms and means of overcoming resistance.Materials and methodsIn this study, the canine triple negative breast cancer cell line CMT-7364 was induced to develop multidrug resistance using doxorubicin by high-dose drug pulse method. The drug resistance and the expression of drug transport pumps of the cells was verified by CCK8 assay, immunoblotting, qPCR and immunofluorescence. Next, we used scratch assay and Transwell invasion assay to compare the migration and invasion abilities of the two cell lines and examined the expression of EMT-related proteins in both using immunoblotting. The differences of transcriptome between parental and drug-resistant cell lines were detected by RNA-seq sequencing. Finally, mouse xenograft models of drug-resistant and parental cell lines were constructed to evaluate the tumorigenic ability.ResultsAfter more than 50 generations of continuous passages stimulated by high-dose drug pulse method, the morphology of drug-resistant cell line CMT-7364/R tended to be mesenchymal-like and heterogeneous under light microscopy compared with the parental cell line CMT-7364/S, and developed resistance to doxorubicin and other commonly used chemotherapeutic drugs. In CMT-7364/R, BCRP was expressed at higher levels at both transcriptional and protein levels, while P-glycoprotein was not significantly different. Secondly, the migration and invasion ability of CMT-7364/R was significantly enhanced, with decreased expression of E-cadherin and increased expression of vimentin and mucin 1-N terminus. Finally, mouse xenograft models were constructed, while there was no significant difference in the volume of masses formed at 21 days.ConclusionIn summary, by using the canine mammary tumor cell line CMT-7364/S as the parental cell line, we successfully constructed a multidrug-resistant CMT-7364/R with high-dose drug pulse methods. Compared to its parental cell line, CMT-7364/R has decreased growth rate, overexpression of BCRP and increased migration and invasion ability due to EMT. The results of this study showed that CMT-7364/R might serve as a model for future studies on tumor drug resistance

Fundamental CRB-Rate Tradeoff in Multi-Antenna ISAC Systems with Information Multicasting and Multi-Target Sensing

This paper investigates the performance tradeoff for a multi-antenna integrated sensing and communication (ISAC) system with simultaneous information multicasting and multi-target sensing, in which a multi-antenna base station (BS) sends the common information messages to a set of single-antenna communication users (CUs) and estimates the parameters of multiple sensing targets based on the echo signals concurrently. We consider two target sensing scenarios without and with prior target knowledge at the BS, in which the BS is interested in estimating the complete multi-target response matrix and the target reflection coefficients/angles, respectively. First, we consider the capacity-achieving transmission and characterize the fundamental tradeoff between the achievable rate and the multi-target estimation Cram\'er-Rao bound (CRB) accordingly.Comment: 32 page

SNP-Based Genetic Linkage Map of Soybean Using the SoySNP6K Illumina Infinium BeadChip Genotyping Array

This study reports a high density genetic linkage map based on the ‘Maryland 96-5722’ by ‘Spencer’ recombinant inbred line (RIL) population of soybean [Glycine max (L.) Merr.] and constructed exclusively with single nucleotide polymorphism (SNP) markers. The Illumina Infinium SoySNP6K BeadChip genotyping array produced 5,376 SNPs in the mapping population, with a 96.75% success rate. Significant level of goodness-of-fit for each locus was tested based on the observed vs. expected ratio (1:1). Out of 5,376 markers, 1,465 SNPs fit the 1:1 segregation rate having ≤20% missing data plus heterozygosity among the RILs. Among this 1,456 just 657 were polymorphic between the parents DNAs tested. These 657 SNPs were mapped using the JoinMap 4.0 software and 550 SNPs were distributed on 16 linkage groups (LGs) among the 20 chromosomes of the soybean genome. The total map length was just 201.57 centiMorgans (cM) with an average marker density of 0.37 cM. This is one of the high density SNP-based genetic linkage maps of soybean that will be used by the scientific community to map quantitative trait loci (QTL) and identify candidate genes for important agronomic traits in soybean

Fabrication and Tribological Performance of Zr-Coated Carbide against 40Cr Hardened Steel

In order to enhance the tribological performance of YT14 carbide, pure Zr coating was deposited on the substrate surface using a multi-arc ion plating method. The surface topography, adhesion strength, thickness, and micro-hardness of the Zr coating were tested. Dry sliding friction experiments against a 40Cr hardened steel ring were conducted with Zr-coated carbides and traditional ones. The average coefficients of friction were measured and compared. The wear characteristics of the samples were examined by scanning electron microscope (SEM) and energy dispersive X-ray analysis (EDX). The test results indicated that the Zr coating deposited on the carbide surface exhibited excellent adhesive strength and lower hardness. The average friction coefficient of Zr coated carbide decreased by 20%–30% in comparison with that of the uncoated one. The Zr coated carbide could reduce the adhesive wear compared with the uncoated one, and the main tribological degradation mechanisms of the coating were abrasive wear, coating flaking and delamination

Tribological Performance of Microhole-Textured Carbide Tool Filled with CaF2

To enhance the friction and wear performance of cemented carbide, textured microholes were machined on micro Electron Discharge Machining (EDM) on the tool rake face, and Calcium Fluoride (CaF2) powders were burnished into the microholes. The friction and wear characteristics of the microhole-textured tool filled with CaF2 were investigated using sliding friction tests and dry cutting tests. Results exhibited that the working temperature could affect the tribological performance of the microhole-textured tool filled with CaF2 due to the temperature-sensitive nature of CaF2. There is no obvious lubrication effect for the textured tool filled with CaF2 at room temperature, while it was shown to be more effective in improving tribological property at a cutting speed of higher than 100 m/min with a corresponding to cutting temperature of 450 °C. The possible mechanisms for the microhole-textured tool filled with CaF2 were discussed and established

Robust Vehicle Speed Measurement Based on Feature Information Fusion for Vehicle Multi-Characteristic Detection

A robust vehicle speed measurement system based on feature information fusion for vehicle multi-characteristic detection is proposed in this paper. A vehicle multi-characteristic dataset is constructed. With this dataset, seven CNN-based modern object detection algorithms are trained for vehicle multi-characteristic detection. The FPN-based YOLOv4 is selected as the best vehicle multi-characteristic detection algorithm, which applies feature information fusion of different scales with both rich high-level semantic information and detailed low-level location information. The YOLOv4 algorithm is improved by combing with the attention mechanism, in which the residual module in YOLOv4 is replaced by the ECA channel attention module with cross channel interaction. An improved ECA-YOLOv4 object detection algorithm based on both feature information fusion and cross channel interaction is proposed, which improves the performance of YOLOv4 for vehicle multi-characteristic detection and reduces the model parameter size and FLOPs as well. A multi-characteristic fused speed measurement system based on license plate, logo, and light is designed accordingly. The system performance is verified by experiments. The experimental results show that the speed measurement error rate of the proposed system meets the requirement of the China national standard GB/T 21555-2007 in which the speed measurement error rate should be less than 6%. The proposed system can efficiently enhance the vehicle speed measurement accuracy and effectively improve the vehicle speed measurement robustness

Real and Pseudo Pedestrian Detection Method with CA-YOLOv5s Based on Stereo Image Fusion

With the development of convolutional neural networks, the effect of pedestrian detection has been greatly improved by deep learning models. However, the presence of pseudo pedestrians will lead to accuracy reduction in pedestrian detection. To solve the problem that the existing pedestrian detection algorithms cannot distinguish pseudo pedestrians from real pedestrians, a real and pseudo pedestrian detection method with CA-YOLOv5s based on stereo image fusion is proposed in this paper. Firstly, the two-view images of the pedestrian are captured by a binocular stereo camera. Then, a proposed CA-YOLOv5s pedestrian detection algorithm is used for the left-view and right-view images, respectively, to detect the respective pedestrian regions. Afterwards, the detected left-view and right-view pedestrian regions are matched to obtain the feature point set, and the 3D spatial coordinates of the feature point set are calculated with Zhengyou Zhang’s calibration method. Finally, the RANSAC plane-fitting algorithm is adopted to extract the 3D features of the feature point set, and the real and pseudo pedestrian detection is achieved by the trained SVM. The proposed real and pseudo pedestrian detection method with CA-YOLOv5s based on stereo image fusion effectively solves the pseudo pedestrian detection problem and efficiently improves the accuracy. Experimental results also show that for the dataset with real and pseudo pedestrians, the proposed method significantly outperforms other existing pedestrian detection algorithms in terms of accuracy and precision

Finite Element Simulation of Stainless Steel Porous Scaffolds for Selective Laser Melting (SLM) and Its Experimental Investigation

In recent years, bone defect and bone tissue damage have become common clinical diseases. The development of bionic bone has had an important impact on the repair and reconstruction of bone tissue. Porous scaffolds have the advantages of adjustable pore size and controllable shape, which can solve the problem of mismatch in the process of bone repair, but traditional processing methods cannot overcome the challenge of the preparation of complex porous scaffolds. Therefore, 316L porous stainless steel scaffolds with different pore sizes (200 μm, 300 μm, 400 μm and 500 μm, respectively) were prepared by selective laser melting. Stress and strain were simulated and analyzed by using a finite element simulation method. Combined with a heat treatment experiment, a hardness test, a metallographic observation and a compression test, porous scaffolds were studied. The mechanical properties and microstructures of the scaffolds were studied and analyzed, and the optimized porous scaffolds were obtained. With reasonable melting parameters, the porous scaffolds that could meet the mechanical property requirements of load-bearing bone restorations were prepared by SLM

An Improved Human-Body-Segmentation Algorithm with Attention-Based Feature Fusion and a Refined Stereo-Matching Scheme Working at the Sub-Pixel Level for the Anthropometric System

This paper proposes an improved human-body-segmentation algorithm with attention-based feature fusion and a refined corner-based feature-point design with sub-pixel stereo matching for the anthropometric system. In the human-body-segmentation algorithm, four CBAMs are embedded in the four middle convolution layers of the backbone network (ResNet101) of PSPNet to achieve better feature fusion in space and channels, so as to improve accuracy. The common convolution in the residual blocks of ResNet101 is substituted by group convolution to reduce model parameters and computational cost, thereby optimizing efficiency. For the stereo-matching scheme, a corner-based feature point is designed to obtain the feature-point coordinates at sub-pixel level, so that precision is refined. A regional constraint is applied according to the characteristic of the checkerboard corner points, thereby reducing complexity. Experimental results demonstrated that the anthropometric system with the proposed CBAM-based human-body-segmentation algorithm and corner-based stereo-matching scheme can significantly outperform the state-of-the-art system in accuracy. It can also meet the national standards GB/T 2664-2017, GA 258-2009 and GB/T 2665-2017; and the textile industry standards FZ/T 73029-2019, FZ/T 73017-2014, FZ/T 73059-2017 and FZ/T 73022-2019