Search

This retrospective study aimed to evaluate the diagnostic value of early secretory antigenic target-6 (ESAT-6) and culture filtrate protein-10 (CFP-10) in immunoglobulin A nephropathy (IgAN) associated with renal tuberculosis (RT).Forty patients with IgAN (IgAN group), 32 patients with RT (RT group), and 52 patients with IgAN associated with RT (IgAN + RT group) were retrospectively selected for this study. A tuberculin skin test (TST) was conducted, and Mycobacterium tuberculosis (MTB) antibody levels were measured. Immunohistochemistry and western blotting were used to determine the expression of ESAT-6 and CFP-10 proteins in renal tissues.The positive results of TST and levels of serum and urinary MTB antibodies were higher in the RT group than in the IgAN + RT group. The expression levels of ESAT-6 and CFP-10 proteins were the highest in the IgAN + RT group and lowest in the IgAN group. The receiver operating characteristic curves indicated that the area under curve (AUC) value of the ESAT-6 protein for the diagnosis of IgAN associated with RT was 0.907 and the cut-off value of the integral optical density (IOD) was 26.72. Diagnosis based on ESAT-6 protein levels showed 75% sensitivity and 94.2% specificity. The AUC value of the CFP-10 protein for the diagnosis of IgAN associated with RT was 0.8 and the cut-off value of IOD was 25.67. Detection based on CFP-10 protein levels showed 63.9% sensitivity and 84.6% specificity.Our study provides evidence for the potential of ESAT-6 and CFP-10 proteins as candidate markers in the diagnosis of IgAN associated with RT.

The multi-directionality of polished surface topography (PST) is a key index to characterize the polished surface quality and surface integrity, and its prediction before actual machining is of great significance to the toolpath planning, verification, and optimization. However, most related works reported thus far focus mainly on the material removal modeling but few on the prediction of multi-directionality. Hence, this paper proposes a fast method to precisely predict the multi-directionality of the PST for the pad-polishing process of freeform surfaces. With this method, a pressure distribution model and a material removal profile (MRP) model are first established, in which the MRP is founded subject to the quadratic function distribution. Then, to avoid the time-consuming integral operation in the MRP model, an artificial neural network is developed to fit the quadratic function of MRP. With this model, a multi-directionality prediction algorithm is further proposed based on the angular spectrum of the PST. Simulation and experimental studies have shown that the proposed method can predict the multi-directionality of the PST with very high accuracy and efficiency for various freeform surface polishing, showing great application potential in promoting the efficiency of toolpath planning and optimization to obtain isotropic PST.

Industrial robot provides a promising alternative in free-surface milling. However, due to its low stiffness, it is difficult to guarantee the machining quality. While existing research considers mainly the influence of robot posture on stiffness, the workpiece setup's influence is equally important. In this study, to ensure the overall workpiece's robot stiffness meets the requirement of stiffness threshold in robotic milling, a method for simultaneously optimizing the robot posture and the workpiece setup is proposed. Firstly, to evaluate the robot stiffness during machining, this work presents a new stiffness index considering the robot's rotational deformation. And then, an optimization model is established to optimize both the robot redundancy and the workpiece setup, considering the constraints of joint limitation, singularity-free and collision-free. Moreover, for complex free-surface, to obtain the minimum number of posture changes of the robot and workpiece under the premise of meeting the limit of stiffness threshold, this work constructs a minimum set covering problem, which is solved by a clustering algorithm and a greedy algorithm. Finally, simulations and experimental studies are conducted to validate the effectiveness of the proposed robot stiffness index and the proposed optimization method, showing that the robot stiffness is improved during a milling process of the entire workpiece.

Virtual assembly technology is of great significance to training of mechanical engineers. However, existing force rendering models for virtual assembly are not accurate enough with less consideration of geometrical properties of the parts, which may lead to unpractical perceptions during assembly. This paper presents a novel force rendering model for virtual assembly, which takes into account parts’ geometrical properties according to the new generation of geometrical product specification (GPS). More specifically, skin model shapes of parts for force rendering are constructed and then the contact between the mating surfaces is analyzed. Based on which, the axial frictional and radial contact resistances are calculated and rendered. To verify the proposed model, two comparative case studies are designed using a shaft-bushing assembly as the example. The results have shown that with the proposed approach, the rendered assembly force is more realistic and can reflect different tolerances more precisely.

When using a force feedback device to interact with a virtual world, the effect of immersion is highly dependent on its performance of gravity compensation. In this work, an active and passive combined gravity compensation approach is presented for a horizontally mounted 6-DOF hybrid force feedback device (HFFD-6). Both active and passive methods are analyzed with simulation and corresponding parameters in the passive approach are then optimized. And to evaluate the performance of the gravity compensation approach, physical experiments are also conducted to measure the gravity compensation errors in the workspace. Moreover, comparison studies are conducted to illustrate the superiority of the proposed approach in terms of output force capability. These experiments have demonstrated that the proposed approach is feasible to achieve gravity compensation and improve the output force capability of the device.

In current work, the effects of drying temperature (60, 65, 70, and 75 °C), vacuum pressure duration (VPD; 6, 9, 12, and 15 min), and ambient pressure duration (APD; 2, 3, and 4 min) on drying kine...

Rapid simulation of grinding surface topography at different machining conditions can assist users to determine appropriate grinding parameters. Most simulation methods reported so far are time-consuming and can only simulate the surface topography on a micro-scale, which are certainly not effective and intuitive enough. Hence, in this work, a novel GPU-based prediction and simulation method of the grinding surface topography is proposed. With the method, an artificial neural network (ANN) model is first developed to model the grinding surface roughness and fractal dimension. Then, the Cook-Torrance illumination model is introduced to render the color and glossiness of the grinding surface, and a normal map generation method is proposed to render the rugged detail features of grinding surface topography. Finally, a GPU-based prediction and simulation algorithm is developed. A performance evaluation experiment of the ANN model and a comparative experiment between the simulated and actual grinding surface topography are conducted. The experimental results show that the proposed method can achieve fast prediction and photorealistic simulation of the grinding surface topography for the whole part surface, which provides a more intuitive and effective way to evaluate the surface quality under given processing parameters.

In this paper, an additive manufacturing prepared porous stainless steel felt (AM-PSSF) is proposed as a novel catalyst support for hydrogen production via methanol steam reforming (MSR). In the method, 316 L stainless steel powder with diameter of 15–63 μm is processed by the additive manufacturing technology of selective laser melting (SLM). To accomplish the preparation, the reforming chamber where the AM-PSSF is embedded is firstly divided into an all-hexahedron mesh. Then, the triply periodic minimal surface (TPMS) unit with mathematical form, high interconnectivity and large specific surface area is mapped into the hexahedrons based on shape function, forming the fully connected three-dimensional (3D) micro pore structure of the AM-PSSF. By correlating the mathematical parameter and the porosity of the TPMS unit, and taking into account the SLM process, the porosity of the AM-PSSF is well controlled. Based on the designed 3D pore structure model, the AM-PSSF is produced using standard SLM process. The application of the AM-PSSF as catalyst support for hydrogen production through MSR indicates that: 1) both the naked and catalyst-coated AM-PSSF have the characteristics of high porosity, large specific surface area and high connectivity; 2) the MSR hydrogen production performance of the AM-PSSF is better than that of the commercial stainless steel fiber sintered felt. The feasibility of AM-PSSF as catalyst support for MSR hydrogen production may pave a better way to balance different requirements for catalyst support, thanks to the excellent controllability provided by AM on both the external shape and the internal pore structure, and to the produced rough surface morphology that benefits the catalyst adhesion strength. In addition, catalyst support with pore structures that are more accommodated with the flow field and the reaction rate of MSR reaction may be prepared in future, since the entire catalyst support structure, from macro scale to micro scale, is under control.

The porous copper fiber sintered felts with gradient porosity structure (gradient PCFSFs) as catalyst supports is beneficial for heat and mass transfer for methanol steam reforming (MSR). However, the previously developed gradient PCFSF based on the velocity distribution introduces curved interface between different porosity portions, making the mold pressing method for its preparation more sensitive to tiny process changes. To improve its manufacturability, a novel gradient PCFSF with planar interface (PCFSF-SLR) is proposed in this paper by fabrication with multi-step mold pressing and solid phase sintering method using cutting copper fibers. Furthermore, MSR experiments under different gas hourly space velocities and reaction temperatures are conducted to verify the characteristics of PCFSF-SLR loaded with Cu/Zn/Al/Zr catalyst. The results have shown that the reaction characteristics of the PCFSF-SLR were similar to those with curved interfaces, and PCFSF-SLRs with a middle portion porosity of 0.9 have better hydrogen production performance and lower carbon monoxide concentration. More importantly, the results indicated that the methanol conversion and hydrogen flow rate of the gradient PCFSF with planar interface and porosity of 0.7-0.9-0.8 were close or even almost the same with that of the best gradient PCFSFs with curved interface and porosities of 0.7-0.9-0.8 and 0.8-0.9-0.7. Therefore, the proposed PCFSF-SLR provides a superior alternative to gradient PCFSFs with better manufacturability.

Detecting and locating surface defects in textured materials is a crucial but challenging problem due to factors such as texture variations and lack of adequate defective samples prior to testing. In this paper we present a novel unsupervised method for automatically detecting defects in fabrics based on a deep convolutional generative adversarial network (DCGAN). The proposed method extends the standard DCGAN, which consists of a discriminator and a generator, by introducing a new encoder component. With the assistance of this encoder, our model can reconstruct a given query image such that no defects but only normal textures will be preserved in the reconstruction. Therefore, when subtracting the reconstruction from the original image, a residual map can be created to highlight potential defective regions. Besides, our model generates a likelihood map for the image under inspection where each pixel value indicates the probability of occurrence of defects at that location. The residual map and the likelihood map are then synthesized together to form an enhanced fusion map. Typically, the fusion map exhibits uniform gray levels over defect-free regions but distinct deviations over defective areas, which can be further thresholded to produce a binarized segmentation result. Our model can be unsupervisedly trained by feeding with a set of small-sized image patches picked from a few defect-free examples. The training is divided into several successively performed stages, each under an individual training strategy. The performance of the proposed method has been extensively evaluated by a variety of real fabric samples. The experimental results in comparison with other methods demonstrate its effectiveness in fabric defect detection.

Based on the Z-map model of a workpiece and the dynamic cutting forces model of peripheral milling in which the regenerative effect of tool radial runout and axial drift are considered, a model for the prediction of surface topography in peripheral milling operations is presented. According to the stability lobe diagram obtained by the zero-order analytical method, the relationship between spindle speed and surface topography, the tool radial runout, and the axial drift following the chatter are studied. The results show that a stable cutting status but a poor surface finish is obtained at the spindle speeds at which the dominant frequency of the milling system is integral multiples of the selected machining frequency, and a stable cutting status with a good surface finish can be obtained near and on the left side of the resonant spindle speeds determined by the predicted stability lobe diagram. The motion equations of any tooth end mill for peripheral milling are established, and these equations are based on the transformation matrix and the vector operation principle of motion-homogeneous coordinates. In addition, the simulation algorithm and the system of surface topography generated in peripheral milling are given based on the Z-map model. Cutting tests are carried out, and good agreement between the measured surface topographies and the topographies predicted by the model in this study is found in terms of their shape, magnitude, feed mark, profile height of cross-section, and surface roughness. The simulation results show that the milling surface roughness increases with the increase in feed per tooth, which further shows that this simulation system has high credibility. Thus, the simulation and experimental results can provide some practical instructions for the actual peripheral milling in determining the optimal machining conditions.

Polishing is one of the key processes for surface finishing. It can achieve mirror-effect on surface by removing the tool masks caused by milling. Since the process is now automated, tilted polishing disk is applied more and more widely, and the prediction of material removal map is vital for polishing trajectory planning to reduce scrap rate and shorten production cycle. This work proposed an improved material removal model of tilted elastic polishing disk by considering the geometric features of contact region, contact pressure, and velocity distribution while polishing. More specifically, based on the FEM simulation results, the contact region and the pressure distribution are discussed in three diverse types according to the geometric features of surface at contact point. The material removal map is then generated by numerical convolution of this model and trajectory planned, with which the issues of material removal, such as over-polishing, under-polishing, and waviness, can be graphically illustrated. To validate the approach, case studies on both planar and freeform surfaces are conducted. Comparative study reveals that the predicted result by the approach agrees with the actual polishing very well. Moreover, according to the generated material removal map, process optimization can be carried out to adjust process parameters, such as feedrate, interval, and step, and hence, mirror-effect surface quality can be achieved.

Composite porous vapor chamber (CPVC) with uniform radial grooves is a recently developed vapor chamber, exhibiting good temperature uniformity and excellent stability under high heat flux of 280 W/cm2 with the thermal resistance less than 0.15 °C/W. However, the maximum pressure drop in CPVC due to liquid flow is prone to exceed the limits of capillary pressure, and the shape design of the wicks lacks scientific and objective enough criteria. This paper proposes a shape optimization method to optimize the shape of the evaporator wick in CPVC, based on the study on the minimization of the maximum pressure drop. In this method, the discrete adjoint method is utilized to efficiently analyze the sensitivities and find the most rapid descendant directions for the minima problem. The shape of the evaporator wick is updated by the polynomial-based approach based on the sensitivity information. Results indicate that the bottom contours of the wick blocks’ surfaces surrounding the circular cavity contribute the highest sensitivities. Consequently, the mesh deformations near the contours change the shape of the lateral surfaces of wick blocks from rectangular to concave trapezoidal in both Cylindrical and Cartesian coordinate systems. This reduces the maximum velocities and flow resistance in CPVC, due to the smoother structural transition from the condenser wick to the evaporator wick, thus reducing the maximum pressure drop by about 18.5% and 23.3% in Cartesian and Cylindrical coordinate systems, respectively. The proposed method may pave a more objective and scientific alternative to design the shape of the wicks in CPVC.

A new parametric method for the design of Voronoi-based lattice porous structures is proposed in this paper. First, the functional relationship between the porosity p, the number of seed points n, and the beam radius r is established. The design space is then divided into individual unit cells, and the seed points and beam radius values of each unit cell are calculated. In each unit cell, Voronoi tessellation is used to generate uniformly distributed seed points. Finally in the design space, all seed points are Voronoi tessellated globally, and the edges are cylindered with corresponding beam radius values. With this design method, not only can the lattice structures with uniform or graded distribution of porosity be generated, but the customized lattice structures can also be generated according to the porosity of each unit cell. Through the analysis of model data, it is verified that the uniform distribution of seed points in this paper is stable and the porosity of the model is consistent with the design value. The distribution of pore spheres between pores is used to illustrate that the lattice porous structures designed in this paper is globally controllable and locally uniform.

Background: This study evaluated the diagnostic value of early secretory antigenic target 6 (ESAT-6) and culture filtrate protein 10 (CFP-10) in immunoglobulin A nephropathy (IgAN) associated with renal tuberculosis (RT).Methods: Between January 2013 and January 2016, 40 patients with IgAN (IgAN group), 32 patients with RT (RT group), and 52 patients with IgAN associated with RT (IgAN + RT group) were selected for this study. A Tuberculin skin test (TST) was conducted, and serum Mycobacterium tuberculosis (MTB) antibody levels were measured. Urine samples were collected to culture MTB. Immunohistochemistry and western blotting were used to determine the expression of ESAT-6 and CFP-10 in renal tissues. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic values of ESAT-6 and CFP-10 in IgAN associated with RT.Results: TST, serum MTB antibody, and urine MTB assessments were negative in the IgAN group. The positive rates of the TST and serum MTB antibody and urine MTB testing were higher in the RT group than in the IgAN + RT group. Among the three groups, expression levels of ESAT-6 and CFP-10 were found to be the highest in the IgAN + RT group and were found to be the lowest in the IgAN group. The ROC curves indicated that the area under curve (AUC) value of ESAT-6 protein for IgAN + RT diagnosis was 0.907 with a cut-off of 26.72 as the critical value. Detection by ESAT-6 protein levels achieved 75.0% sensitivity and 94.2% specificity. The AUC value of the CFP-10 protein for diagnosis of IgAN + RT was 0.800, with a cut-off of 25.665 as the critical value. Detection by the protein levels of CFP-10 showed 63.9% sensitivity and 84.6% specificity.Conclusions: Our study provides evidence for the potential of the proteins ESAT-6 and CFP-10 as candidate markers for the diagnosis of IgAN associated with RT.

In current work, air impingement drying (AID), infrared-assisted hot air-drying (IR-HAD), and hot air drying based on temperature and humidity control (TH-HAD) drying technologies were employed to drying potato cubes and their effects on drying kinetics, color, ascorbic acid content, rehydration ratio, microstructure, and specific energy consumption (SEC) were explored. Besides, artificial neural network (ANN) was used to predict changes in moisture ratio during the drying process. Results indicated that TH-HAD had the shortest drying time, followed by IR-HAD and AID. The effective moisture diffusivity (Deff) of potato under TH-HAD, IR-HAD and AID were 1.35 × 10−9, 1.18 × 10−9, and 0.90 × 10−9 m2/s, respectively. TH-HAD contributed to excellent physicochemical properties of dried potato when compared to samples dried by IR-HAD and AID. Overall, TH-HAD provided higher ascorbic acid content, better rehydration ability, brighter color, and had lower specific energy consumption (SEC). The microstructure well explained the difference of rehydration ratio and drying kinetics under different drying methods. The ANN models with the optimal topology could predict the moisture ratio under different drying methods with satisfactory accuracy. The current findings indicate that TH-HAD is a promising drying technology for potato cubes and has the potential to be applied in commercial scale.

A new type of data processing model for a ball-end milling process based on biharmonic spline interpolation (BSI) is presented for the first time. The model aims to solve the problem of determining the discrete point number in the conventional machining topography simulation method. The kinematic model of the ball-end milling is established based on the consideration of the tool vibration, and the sweeping point cloud of the cutting edge is generated and extracted based on the servo bounding box. Moreover, the BSI method is introduced to reconstruct the machined surface. In view of the scarcity of prior research studies on the topographical prediction for free-form workpiece surfaces, this study evaluates the prediction model of surface topography of free-form surface milling and extends the application of BSI in the point cloud. The computation error that is caused by the large-scale use of the analytic nonlinear equations in other simulation processes is significantly reduced, and the complex optimization operators that ensure that each microelement of the cutting edge sweeps no more than one grid point within a unit time step are avoided. Correspondingly, this method becomes superior compared to the conventional approximation-processing method of discrete data—such as IMAGEWARE—thereby simplifying data manipulation, improving the calculation accuracy by 7.6%, and reducing the large computation time for the surface topography simulation by linearly expanding the valid data. The effectiveness and accuracy of this algorithm are demonstrated by comparing some computer simulation results with the machining results at different experimental conditions, and some topography evaluation parameters are also analyzed in this study. The shape error (Sba) and surface roughness (Sa) values of the simulated topographies are compared with those of the measured topographies (error within 15.9%).

The method of combining simulations with experiments is used in this paper. Both traditional grinding and point grinding are considered as the research objects. The motion paths of grains in the point grinding process will completely differ from those in the traditional grinding process because of the non-zero inclination angle α. Thus, a coordinate transformation between the grinding wheel and the workpiece is performed. Then, a brand-new formation mechanism for a 3D workpiece surface is established by combining selected trajectories to simulate the formation of the surface. The interference trajectories are effectively screened by iterating over the cutting paths of all grains on the grinding wheel surface to improve the prediction accuracy for the machined surface. Both the surface features of the grinding wheel and the elastic-plastic deformation of the workpiece material are investigated and analyzed for the first time in this paper; they are considered in the motion trajectories of the abrasive grains to make the simulated grinding surface topography closer to that formed in the actual grinding process. The trend of the influence of the variable angle α on the surface roughness is obtained and analyzed. The comparison and analysis of the simulation and experimental results prove that the simulated surface quality of the grinding workpiece is consistent with that measured in a 3D microtopography analysis, and the curve shapes in the cross-section and surface roughness evaluations are also consistent. The surface quality of a grinding workpiece can be effectively predicted using this simulation method.

This work presents a novel milling strategy for complex pocket machining by integrating radius-varying trochoidal (RVTR) toolpath with contour parallel (CP) toolpath. Based on a quantitative analysis on the fluctuation of material removal rates (MRR), the proposed strategy is able to precisely identify critical regions from complex pocket geometries, and then by integrating flexible trochoidal radius with adaptive trochoidal step, the proposed approach is able to integrate the RVTR toolpath into CP toolpath under a consistent transition of material removal rate. Moreover, by applying RVTR toolpath, the cutting force can be maintained constantly when machining critical regions. Comparing with the trochoidal milling function available with current mainstream CAM software, experimental investigation has shown that the proposed RVTR-CP toolpath integration strategy offers a better machining condition with minimized fluctuation of cutting forces. Moreover, the total length of toolpath is decreased considerably and hence the machining efficiency is greatly improved.

Methanol steam reforming inside micro-reactors is considered as one of the effective approaches for on-board supplying hydrogen for fuel cells. Porous copper fiber sintered felts (PCFSFs) are a new kind of catalyst support for micro-reactors developed in recent years. However, there is a lack of approach to control their porosity configurations due to their random structure. A two-step optimization method was proposed to optimize the PCFSFs’ porosity configuration. Firstly, the topology structures of PCFSFs were optimized based on the best flow distributions obtained from macroscopic numerical analyses, and two kinds of PCFSFs with twelve porosity distributions were fabricated through the multi-step mold pressing and solid-phase sintering method. Secondly, the porosity distributions of the semi-optimized PCFSFs were optimized by investigating their reaction characteristics under different gas hourly space velocities (GHSVs) and reaction temperatures. The results indicated that PCFSFs with porosity distribution along the Left-Right direction (PCFSF-LRs) exhibited better reaction performance than PCFSFs with porosity distribution along the Upside-Underside direction (PCFSF-UUs). The methanol conversion and H2 flow rate for the PCFSF-LRs with porosity distribution of 0.7–0.9–0.8 and 0.8–0.9–0.7 kept on a high level (above 92% and 0.59 mol/h, respectively), regardless of the change of GHSVs and reaction temperatures in most cases. The H2 selectivity of the PCFSF-LR of 0.7–0.9–0.8 was the highest under large GHSVs and all tested reaction temperatures. The demonstrated effect of counteracting, even reversing the conventional influence of the GHSV and temperature on the performance of methanol steam reforming may be attributed to the more uniform flow distribution in the two PCFSF-LRs.

Parameterisation-based methods for planning tool paths on mesh surfaces have been developing for years. The issue of existing mapping deformation which results in machining error has not been suffi...