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The digital twin (DT) technology is currently considered a key technology for the digital representation of real-world systems. The application of DT technology in smart manufacturing can provide accurate model support for the analysis of mechatronic equipment applications based on model simulations. However, for such a mechanics-electric-hydraulic-control coupled complex system of mechatronics equipment, how to quickly and effectively construct its consistent multi-domain DT mechanism model has become the biggest obstacle to the wide application of DT technology in this field. Therefore, based on the synthesis of existing model construction methods for mechatronics equipment, this paper proposes multi-domain, multi-level, parametric, and consistent mechatronics equipment DT mechanism model construction guidelines. Based on the proposed model construction guidelines, a DT mechanism model construction process for mechatronics equipment is given. Finally, a consistent multi-domain DT mechanism model of computer numerical control machine tools (CNCMT) is constructed by Simscape, to verify the feasibility of the proposed method. The solutions in this paper provide a reliable, rapid, and consistent mechanism model along with construction guidelines and theoretical systems for engineers or researchers that use DT technology to solve specific application problems. Also, the implementation of the virtual commissioning application case in this paper provides application guidance for service analysis based on the DT model. [ABSTRACT FROM AUTHOR]

Digital twin (DT) technology, as one of the top strategic technology trends for 2020, has received widespread attention and has gradually been widely used in the smart manufacturing field. DT-based mechatronics equipment emphasizes the timeliness of online simulation decision-making and the promptness of model response. However, the established DT model covering all elements of mechatronics equipment involves multi-domain, multi-scale, and multi-dimensional. If this model is directly used for simulation analysis of specific applications, it will make the solution tedious and complicated and bring a waste of computational resources. Motivated by this need, an application-oriented reconfigured lightweight DT model design method for mechatronics equipment is studied in this paper. The method starts with an application-oriented analysis of the system decomposition, decomposition scheme evaluation, and core module identification criteria. Then, the above criteria are used as a guide to identifying the core system modules for this application, and the core system modules are optimized based on the idea of inheritance. Finally, the optimal system modules are validated and analyzed to ensure that the model-solving efficiency is improved as much as possible without losing this model's necessary behavioral characteristics and dominant effects. A case study of virtual machining dynamic performance test bench (VM-TB) design scheme validation is carried out to show the implementation flow of the proposed method and verify its operability and effectiveness. [ABSTRACT FROM AUTHOR]

Digital twin (DT) technology, as one of the top strategic technology trends for 2020, has received widespread attention and has gradually been widely used in smart manufacturing equipment. However, there is a lack of systematic evaluation guidance, which accesses the applicability of DT technology for specific applications of smart manufacturing equipment. At the same time, CNC machine tool (CNCMT) as an essential part of smart manufacturing equipment also faces the above dilemma. Motivated by this need, a digital twin technology applicability evaluation method for CNCMT is proposed in this paper. This method firstly analyzes the application-oriented requirements of DT-based CNCMT to obtain the optimal evaluation index and structure model. And then, the DT technology applicability evaluation of CNCMT based on the optimal evaluation model as well as system engineering algorithms is researched. With this effort, DT technology applicability of CNCMT is quantified starting from the initial stage aiming at its specific application. Then, the applicability of DT technology to address specific applications of CNCMT can be clarified. At last, the applicability evaluation for DT-based CNCMT cutting tool life prediction is carried out as an application case to show the implementation flow of the proposed method and verify its operability and effectiveness. [ABSTRACT FROM AUTHOR]

In the workshop scheduling problem, frequent disturbances lead to continuous and frequent rescheduling. This is detrimental to the optimal utilization of production resources, the maximization of production efficiency, and the minimization of operational costs. Therefore, finding an effective method to reduce frequent rescheduling is crucial for stable and efficient workshop operations. This paper introduces digital twin (DT) technology. Serving as a digital replica of a physical system, DT establishes an interactive connection between the physical entity and its digital counterpart. It has been applied in multiple fields. A disturbance evaluation method for scheduling mechanisms based on DT technology is proposed and studied in this paper. Firstly, this method evaluates the impact of disturbances by using a causal factor chart (CFC) and convolutional neural networks (CNN). Then, corresponding scheduling mechanisms are proposed based on the degree of disturbance impact. DT technology is used to provide data and model support throughout the entire process. Through the experimental verification, workshop disturbances were accurately evaluated by this method. Two unnecessary instances of rescheduling were avoided, resulting in a 66.3% reduction in the time to handle disturbances. The experimental results show that the proposed method can enhance the adaptability of scheduling mechanisms and contribute to a more agile response to disturbances. [ABSTRACT FROM AUTHOR]

In the product design stage, the effective performance analysis method is the premise to guarantee the application performance of products. However, digital simulation, as a widely used performance analysis method, has a long simulation cycle and high requirements for computer hardware performance, which leads to long product design and iteration time. Facing this problem, a product performance rapid simulation approach driven by digital twin (DT) data for variable product structures is proposed to replace the digital simulation method. Firstly, the framework for variable product structures is designed, which includes a digital simulation module, a data-driven module, and a surrogate-based simulation module. Then, module implementation of the proposed framework is introduced in detail, in which the twin data-driven product performance rapid simulation model (RSM) for variable product structures is studied based on the makeTwin reference architecture. Finally, a case study is conducted on the iterative design of a connecting rod, focusing on equivalent stress evaluation. The result shows that the proposed method is feasible, as well as costs a shorter simulation time than traditional digital simulation. [ABSTRACT FROM AUTHOR]

As mentioned in Part 1, for product iterative design, the digital simulation method, as the product performance analysis method, has the problems of time cost and computing resources. To address this issue, a product performance rapid simulation approach driven by digital twin (DT) data for variable product structures in Part 1 was proposed, which could replace the digital simulation method. Meanwhile, for performance analysis under variable operating conditions during the product design and operation phase, digital simulation also has the above problems. Therefore, based on the method for variable product structures proposed in Part 1, a product performance rapid simulation approach driven by DT data for variable operating conditions is proposed in this paper. Firstly, the framework for variable operating conditions is designed based on the makeTwin reference architecture, including twin source data acquisition for the product under different operating conditions, twin data-driven product performance rapid simulation model (RSM) construction for variable operating conditions, and rapid evaluation of product critical performance based on RSM. Then, the implementation of the framework is introduced in detail. At last, a case study for critical loosening load evaluation of bolted joint is carried out. The result indicates that the proposed method is feasible, as well as costs shorter simulation time than the traditional digital simulation method. [ABSTRACT FROM AUTHOR]

Feedrate scheduling is one of the most important factors of computer numerical control (CNC) machining and has become a crucial research problem. In order to improve the machining accuracy and motion smoothness, an optimized feedrate scheduling method considering round-off error compensation based on S-shaped acceleration/deceleration (ACC/DEC) algorithm is proposed in this paper. There are two main stages, namely initial feedrate scheduling and parameters calculation of round-off error compensation. In the stage of initial feedrate scheduling, a novel time rounding principle is introduced to reduce the round-off error. Meanwhile, the motion parameters of each section can be calculated based on the proposed feedrate scheduling method. The constant feedrate section used for round-off error compensation is always guaranteed to exist although the actual maximum feedrate might be smaller than the command feedrate. Then, in the stage of compensation parameters calculation, the round-off error can be obtained based on the proposed time rounding principle and the scheduled parameters should be updated. In order to maintain the continuity of the acceleration profile, the improved trapezoidal ACC/DEC algorithm is introduced to conduct the error compensation and the crucial parameters can be calculated based on its special properties. In addition, the feedrate look-ahead strategy is also tweaked to enhance the reliability of feedrate scheduling. Finally, a series of simulations and practical experiments with two non-uniform rational B-spline (NURBS) curves are conducted to verify the good performance and applicability of the proposed method. [ABSTRACT FROM AUTHOR]

As the key component of intelligent CNC machine tool, CNC controller is expected to provide various intelligent functions, among which, autonomous process planning is one of the most important functions. However, current machining data models are not very suitable to support this function. G&M code gives movement and auxiliary instructions directly, making the CNC controller just an executor. A new standard STEP-NC, providing semantically rich information, aims to overcome the drawbacks of G&M code. However, information in the data model specified in STEP-NC is not very suitable for intelligent CNC controller autonomous process planning because of the lack of important machining requirements. Also, in STEP-NC model, machining strategies, which are supposed to be decided by CNC controller, have already been included. Namely, decision right is not totally handed over to the controller. To solve these problems, a STEP-based machining data model is proposed in this paper. The machining data model is an ARM, and it is designed as the machining task input of intelligent CNC controller. It can provide necessary workpiece information for intelligent process planning functions based on knowledge base. With the consideration of interoperation with design stage, STEP data format is used in the machining data model. Detailed structure and implementing method is introduced. In order to verify the feasibility of this data model, generation method of machining task complied with this data model and process plan generation based on the machining task have been put forward through a case. Results show the machining task complied with this data model can provide sufficient information for the autonomous process planning function of CNC controller. [ABSTRACT FROM AUTHOR]

The fast-neutron burst reactor is a chain reactor that can operate in a prompt critical state. In order to ensure the operational safety of the fast-neutron-pulse reactor and prevent the supercritical pulse from causing physical damage to the material, it is necessary to simulate and analyze the pulse operating conditions of the fast-neutron-pulse reactor. Godiva-I is a spherical assembly of highly enriched uranium metal made during the 1950s. A prompt-critical transient in such a nuclear system impels a quick power excursion, which will cause a temperature rise and a subsequent reactivity reduction because of the metal sphere's expansion. The overall transient lasts for a few fractions of a millisecond. Based on the point kinetics and Monte Carlo method, the temporal and spatial characteristics of transient input power were calculated, the difference of the average reactivity temperature coefficient between uniform density and non-uniform density was compared, and the transient power distribution condition was loaded into the thermal–mechanics calculation of the MOOSE platform; thus, the pulse process of Godiva-I with different initial reactivity periods was simulated. The JFNK (Jacobian–Free–Newton–Krylov) direct method and multi-app indirect method were used to analyze the transient response of the pulse dynamic process using the heat conduction module and tenor mechanics module, respectively. After considering the influence of the inertia effect and wall-reflected neutrons, the simulation results were much closer to the experimental values. Based on the stochastic tools module, the uncertainty propagation and sensitivity analysis of the Godiva-I model were carried out, the uncertainty of external surface displacement of Godiva under input disturbance of material properties and heat source amplitude factor was obtained, and the sensitivity of different input parameters to output parameters was quantified. The research results can lay a technical foundation for the thermal–mechanics coupling analysis and uncertainty quantification of the metal fast reactor. [ABSTRACT FROM AUTHOR]

The Xi'an Pulsed Reactor (XAPR) is characterized by its small core size and integrated fuel moderator structure, which results in a non-uniform core power and temperature distribution. Consequently, a complex coupling relationship exists between its core neutronics and thermal hydraulics, necessitating the assurance for the operational safety of the XAPR. To optimize the experimental scheme in the reactor, a refined three-dimensional steady-state nuclear-thermal coupling analysis is imperative. This study focuses on investigating the coupling calculation of a three-dimensional steady-state neutronics and thermal-hydraulics model for the XAPR by utilizing an open-source multi-physical coupling framework known as Cardinal. The neutron transport equation is effectively solved using OpenMC, while a three-dimensional heat conduction model is employed to compute the heat conduction of the fuel elements. Furthermore, a parallel multi-channel model is utilized to determine the fluid heat transfer. The research is centered on the XAPR, whereby Monte Carlo and thermal-hydraulics coupling calculations of the core under steady-state full-power conditions are conducted, specifically at an operational capacity of 2 MW. The results demonstrate a strong agreement between the simulation and experimental outcomes. The maximum temperature recorded for the thermometric fuel element in the XAPR is 795.1 K, with a deviation of approximately −5.7% from the measured value. Moreover, the outlet fluid temperature of the thermal channel is observed to be 360 K, exhibiting a deviation of around −2.7% from the measured value. [ABSTRACT FROM AUTHOR]

Nowadays, the using of real-time Ethernet (RTE) in CNC system becomes a main trend because of its low cost and high performance. In order to guarantee the performance of CNC systems which use RTE, the characteristics of RTEs must be tested according to the description in IEC61784-2 standard. In this paper, the performance indicators (PIs) described in IEC61784-2 are analyzed and the testing approaches for some selected PIs which are closely related to CNC system performance are researched. According to these PIs, the hardware and software of RTE performance testing system are implemented. With this system, the evaluation of RTEs which are going to be used in CNC system can be more general purpose to fit to different RTE communication profiles (CPs) and the accuracy of sampling can be less than 10 ns. Also, with the designed flexible software structure, analysis software can adapt to different kinds of RTE CP testing. Testing scenario and a case study for the test of EtherCAT are also given to show the feasibility of the designed testing system. With the testing system designed in this paper, the evaluation for RTEs which will be used in CNC system can be done in a simple way to guarantee the CNC system performance. [ABSTRACT FROM AUTHOR]

Due to the low structural rigidity of six-degree-of-freedom (DOF) industrial robots, the chattering phenomenon is prone to occur under the excitation of periodic milling force, which has an effect on the processing quality of workpieces. In this paper, the influence of milling parameters on the stability of six-DOF robot milling is studied, under the consideration of the mode coupling effect and the regenerative effect on milling stability. First, a mode equation considering both the mode coupling effect and the regenerative effect is developed. Second, based on the fully discrete method, the chatter stability domain model of six-DOF robot (namely, the stability lobe diagram) is established, and the influences of the spindle speed, axial depth of cut, radial depth of cut, and feed rate on the stability of the machining system are analyzed. Finally, the accuracy of the prediction results of the chatter stability domain model is verified by milling experiments. [ABSTRACT FROM AUTHOR]

Speed control is a very important factor to machining quality. In order to get high dynamic performance at the time of the machining speed changing, many kinds of algorithm for the acceleration/deceleration control have been proposed. The techniques which employ polynomial functions or digital convolution to generate velocity profile have been widely used and achieved good performance in motion control system. However, the control cycle of all these methods is one interpolation interval at least, and the velocity jump between two adjacent interpolation intervals during the acceleration/deceleration stage cannot be avoided. In this paper, a hardware fine acceleration/deceleration algorithm inside a single interpolation cycle is proposed to make the velocity change smoothly all the time even inside the interpolation interval. Based on this approach, an acceleration/deceleration fine interpolation circuit is designed with Verilog hardware description language and implemented in field programmable gate array. At last, the algorithm is applied in a three-axes motion controller and achieves a better machining performance than the one without this algorithm. [ABSTRACT FROM AUTHOR]

In this paper, a new CNC core design method, the function-separated design (FSD) method, is proposed to increase the modularity and reconfigurability of CNC systems, simplify the CNC development process, as well as gain a secondary development ability to allow customers or third parties to add or modify NC functions at the shop floor level. With the FSD method, a new CNC core structure is built. In this structure, the CNC core is composed of three main components: engine machine interface, event processor (EP), and system description data (SDD). The engine machine interface provides an interface to machine tools through the parameter settings via a human machine interface (HMI). The EP and SDD are the most important parts. The SDD stores the control rules and modularized NC functions. It is designed as the relatively separated part inside the CNC core. It can also be modified according to the specification changes to access the functions of the CNC core at the shop floor level. To ease the modification of the SDD on the shop floor, the Statechart modeling tool is used to generate a CNC function model; meanwhile, an SDD generator is developed to convert this model into the SDD. The EP is driven by events from the event generator and processes these events by referring to the SDD. The EP always remains the same. With such a structure, the control rules and NC functions of a CNC core can be redesigned or upgraded easily. A case study for implementing a non-circular piston-turning system verifies the feasibility of the proposed design method at the shop floor level. [ABSTRACT FROM AUTHOR]

Non-uniform rational B-spline (NURBS) curve has been widely used in manufacturing systems. A good interpolator can help the system to improve the contour accuracy and get smooth dynamics performance, but it is hard to get a balance between the interpolation performance and computational load. As the derivative and curvature of NURBS curves used in manufacturing systems are high-order continuous, it is possible to predict a desired interpolation arc length based on the relationship of historical feed chord length and its corresponding arc length in one interpolation cycle. Therefore, this paper proposes a novel interpolation method, which consists three stages. Firstly, a NURBS curve is split into several high-order continuous segments based on its degrees and control points. Secondly, a prediction model based on Newton’s divided differences interpolation equation is derived from the relationship of interpolated chord length and its corresponding arc length, so that the target arc length of the next interpolation cycle can be predicted. Finally, target parameter u of every interpolation cycle is calculated with Taylor’s expansion, whose values are corrected by iteration, and then the position of the target interpolation point can be achieved. Performance of the proposed algorithm is tested and compared with other methods, and the simulation results show the proposed method can achieve smaller velocity fluctuation with low computational load. [ABSTRACT FROM AUTHOR]

• A novel thiol-functionalized covalent organic framework was prepared. • High binding ability and fast uptake kinetics for BTEX and Hg(II) ion. • High binding selectivity for Hg(II) in the presence of other common metal ions. • Efficiently simultaneous removal of BTEX and Hg(II) ion in simulated sewage. A novel thiol-functionalized covalent organic framework (COF-S-SH) was prepared as an adsorbent for the simultaneous removal of BTEX (benzene, toluene, ethyl benzene and xylenes) and Hg(II) ion from water. The COF-S-SH was obtained via a Schiff-base reaction between a new triamino-monomer (TABPB) and 2,5-divinylterephthalaldehyde, followed by the thiol-ene "click" reaction between 1,2-ethanedithiol and the vinyl groups. The COF-S-SH was characterized by FT-IR spectrum, energy-dispersive X-ray spectrum, 13C MAS NMR spectrum, nitrogen adsorption–desorption isotherms, thermo-gravimetric analysis, scanning electron microscope, X-ray diffraction, and zeta potential. The new adsorbent showed high binding ability with the maximum adsorption capacities (Q max) of 150.2–255.8 mg/g for BTEX and 588.2 mg/g for Hg(II). The adsorbent also presented fast adsorption kinetics with rate constants of 0.01043–0.05002 g/mg/min for BTEX and 7.254 × 10−4 g/mg/min for Hg(II). Moreover, the adsorbent had good binding selectivity for Hg(II) against common metal ions in water. The adsorbent also showed good simultaneous uptake ability and good reusability for BTEX and Hg(II), and it has been applied to simultaneously removing BTEX and Hg(II) in the simulated sewage with the removal efficiencies of 63.6, 82.1, 94.6, 95.3 and 94.1% for benzene, toluene, ethyl benzene, m-xylene and Hg(II), respectively. Especially, it can reduce the low-concentration Hg(II) in the simulated sewage to a level lower than the drinking water limit. Therefore, COF-S-SH can be used as an excellent adsorbent material for simultaneously removing BTEX and Hg(II) in from the produced water and wastewater in petroleum chemistry industries. [ABSTRACT FROM AUTHOR]

When fixed abrasive wire saw is used to cut polysilicon, free SiC abrasives are added into the cutting coolant to form the fixed and free abrasive combined wire sawing process, so as to impact and roll the as-sawn wafer surface to remove the ductile amorphous silicon layer. Then, the as-sawn wafer can be textured by acid etching technology. The movement characteristics of free abrasives in sawing area directly affect their lapping behavior and the morphology generation of as-sawn wafer surface. In this paper, the flow field characteristics of cutting coolant and the movement characteristics of free SiC abrasives in the sawing area were studied, when using an abrasive groups interval distribution diamond wire for sawing. A three-dimensional model of cutting coolant in sawing area was established. Based on FLUENT, the influences of wire speed, feed speed, wire pretensioning force, viscosity of cutting coolant and wire surface structure parameters on the concentration peak position of free SiC abrasives in the cutting coolant along the wire axial direction were analyzed. The results show that the concentration peak of free abrasives will gradually shift to both sides along the circumferential direction of the wire in the sawing area. The deflection angle and width angle of free abrasives concentration peak are only related to the length of the bare wire area, and decrease with the increase of its length. Comprehensively considering the hydrodynamic pressure effect in the bare wire area, reducing the wire speed and tension, and increasing the feed speed and cutting coolant viscosity are conducive to enhance the lapping effect of free SiC abrasives on the as-sawn wafer surface. The change of wire structure parameters has no regular effect on the lapping behavior of free SiC abrasives in the bare wire area. [ABSTRACT FROM AUTHOR]

Chatter is the main problem that limits the application of industrial robots in the field of machining process. It is critically important to establish an adaptive chatter detection solution for robot machining process and realize the online detection of chatter. However, different from machine tool chatter, the chatter in robotic machining process is more complex to be detected due to the variable stiffness characteristics and weaker stiffness of normal industrial robot, and the existing literature has less research on this problem. This paper presents a comprehensive solution for online chatter detection in robotic machining process. Firstly, in order to detect the chatter in robotic machining process and avoid mode mixing problem in variational mode decomposition (VMD) process, an adaptive variational mode decomposition (AVMD) method based on kurtosis and instantaneous frequency is proposed, which realizes the adaptive selection of the decomposition parameter. Secondly, optimal decomposition parameters are calculated by using genetic algorithm. By optimizing the discrete step length of decomposition parameter, it greatly reduces the optimization time. Last but not least, approximate entropy, energy entropy, and proposed entropy drift coefficient are extracted to distinguish chatter and stable machining state. Simulation and experimental results show that the proposed method can meet the real-time requirements of online detection and detect the occurrence of chatter effectively. [ABSTRACT FROM AUTHOR]

CNC machine tool plays a vital role in intelligent manufacturing, but up to now, CNC controller, which works as the "brain" of the machine tool, is just a loyal executor of machining command without intelligence. This paper is aimed to improve the intelligence of CNC controller from the aspect of machining process planning, which has a great effect on product quality and production efficiency. A STEP-compliant data model is adopted. Compared to previous STEP-NC controller, this paper presents a new paradigm to integrate the ability of autonomous process planning into CNC controller based on cloud knowledge base. A hierarchical and modular architecture is designed to obtain machining process planning from cloud knowledge base timely and to conduct the machining implementation on shop floor. Furthermore, efficient and matching operation mechanism is researched. It offers a proposal to use cloud knowledge to implement intelligent manufacturing. Finally, a case study is demonstrated to verify the feasibility of this intelligent CNC controller. [ABSTRACT FROM AUTHOR]

Master node delay is an unavoidable factor in a networked control system (NCS), which will lead to performance deterioration of the system, and large delay may even cause instability. In order to measure the master node delay in NCSs, its influence factors are analyzed and a non-perturbative black-box measurement method is proposed. In this method, a FPGA-based (Field-Programmable Gate Array) measurement device is developed, which sends out testing frames to master node periodically and triggers the master node to send out a response frame for every testing frame. Then the measurement device can get the measurement delay value by calculating the time interval between sending the testing frame and receiving the response frame, which consists of master node delay and some other delay that can be calculated precisely. Therefore, the accurate master node delay can be obtained by further processing the measurement delay value. A set of experiments were carried out and the results show that the proposed method can effectively measure the master node delay without a thorough understanding about its hardware and operating system software, and is not constrained by the type of operating system. Besides, as the master node delay can be measured exactly in the actual working condition without perturbing its user program by using this method, the results can reflect the real-time performance of the master node accurately. So that, it can provide a direct reference for choosing an appropriate master node for NCSs. [ABSTRACT FROM AUTHOR]

Background: Colorectal cancer (CRC) is a leading cause of cancer-related deaths worldwide. Early detection of CRC can significantly reduce its mortality rate. Current method of CRC diagnosis relies on the invasive endoscopy. Non-invasive assays including fecal occult blood testing (FOBT) and fecal immunological test (FIT) are compromised by low sensitivity and specificity, especially at early stages. Thus, a non-invasive and accurate approach for CRC screening would be highly desirable. Results: A new qPCR-based assay combining the simultaneous detection of the DNA methylation status of ten candidate genes was used to examine plasma samples from 56 normal controls, 6 hyperplastic polys, 9 non-advanced adenomas (NAAs), 22 advanced adenomas (AAs) and 175 CRC patients, using 10 ng of cfDNA. We further built a logistic regression model for CRC diagnosis. We tested ten candidate methylation markers including twist1, vav3-as1, fbn1, c9orf50, sfmbt2, kcnq5, fam72c, itga4, kcnj12 and znf132. All markers showed moderate diagnostic performance with AUCs ranging from 0.726 to 0.815. Moreover, a 4-marker model, comprised of two previously reported markers (c9orf50 and twist1) and two novel ones (kcnj12 and znf132), demonstrated high performance for detecting colorectal cancer in an independent validation set (N = 69) with an overall AUC of 0.911 [95% confidence interval (CI) 0.834–0.988], sensitivity of 0.800 [95% CI 0.667–0.933] and specificity of 0.971 [95% CI 0.914–1.000]. The stage-stratified sensitivity of the model was 0.455 [95% CI 0.227–0.682], 0.667 [95% CI 0.289–1.000], 0.800 [95% CI 0.449–1.000], 0.800 [95% CI 0.449–1.000] and 0.842 [95% CI 0.678–1.000] for advanced adenoma and CRC stage I-IV, respectively. Conclusion: kcnj12 and znf132 are two novel methylation biomarkers for CRC diagnosis. The 4-marker methylation model provides a new non-invasive choice for CRC screening and interception. [ABSTRACT FROM AUTHOR]

Background: Current non-invasive tests have limited sensitivities and lack capabilities of pre-operative risk stratification for bladder cancer (BC) diagnosis. We aimed to develop and validate a urine-based DNA methylation assay as a clinically feasible test for improving BC detection and enabling pre-operative risk stratifications. Methods: A urine-based DNA methylation assay was developed and validated by retrospective single-center studies in patients of suspected BC in Cohort 1 (n = 192) and Cohort 2 (n = 98), respectively. In addition, a prospective single-center study in hematuria patient group (Cohort 3, n = 174) was used as a second validation of the model. Results: The assay with a dual-marker detection model showed 88.1% and 91.2% sensitivities, 89.7% and 85.7% specificities in validation Cohort 2 (patients of suspected BC) and Cohort 3 (patients of hematuria), respectively. Furthermore, this assay showed improved sensitivities over cytology and FISH on detecting low-grade tumor (66.7–77.8% vs. 0.0–22.2%, 0.0–22.2%), Ta tumor (83.3% vs. 22.2–41.2%, 44.4–52.9%) and non-muscle invasive BC (NMIBC) (80.0–89.7% vs. 51.5–52.0%, 59.4–72.0%) in both cohorts. The assay also had higher accuracies (88.9–95.8%) in diagnosing cases with concurrent genitourinary disorders as compared to cytology (55.6–70.8%) and FISH (72.2–77.8%). Meanwhile, the assay with a five-marker stratification model identified high-risk NMIBC and muscle invasive BC with 90.5% sensitivity and 86.8% specificity in Cohort 2. Conclusions: The urine-based DNA methylation assay represents a highly sensitive and specific approach for BC early-stage detection and risk stratification. It has a potential to be used as a routine test to improve diagnosis and prognosis of BC in clinic. [ABSTRACT FROM AUTHOR]

Background: Colorectal cancer (CRC) is a leading cause of cancer-related deaths worldwide. Early detection of CRC can significantly reduce its mortality rate. Current method of CRC diagnosis relies on the invasive endoscopy. Non-invasive assays including fecal occult blood testing (FOBT) and fecal immunological test (FIT) are compromised by low sensitivity and specificity, especially at early stages. Thus, a non-invasive and accurate approach for CRC screening would be highly desirable. Results: A new qPCR-based assay combining the simultaneous detection of the DNA methylation status of ten candidate genes was used to examine plasma samples from 56 normal controls, 6 hyperplastic polys, 9 non-advanced adenomas (NAAs), 22 advanced adenomas (AAs) and 175 CRC patients, using 10 ng of cfDNA. We further built a logistic regression model for CRC diagnosis. We tested ten candidate methylation markers including twist1, vav3-as1, fbn1, c9orf50, sfmbt2, kcnq5, fam72c, itga4, kcnj12 and znf132. All markers showed moderate diagnostic performance with AUCs ranging from 0.726 to 0.815. Moreover, a 4-marker model, comprised of two previously reported markers (c9orf50 and twist1) and two novel ones (kcnj12 and znf132), demonstrated high performance for detecting colorectal cancer in an independent validation set (N = 69) with an overall AUC of 0.911 [95% confidence interval (CI) 0.834–0.988], sensitivity of 0.800 [95% CI 0.667–0.933] and specificity of 0.971 [95% CI 0.914–1.000]. The stage-stratified sensitivity of the model was 0.455 [95% CI 0.227–0.682], 0.667 [95% CI 0.289–1.000], 0.800 [95% CI 0.449–1.000], 0.800 [95% CI 0.449–1.000] and 0.842 [95% CI 0.678–1.000] for advanced adenoma and CRC stage I-IV, respectively. Conclusion: kcnj12 and znf132 are two novel methylation biomarkers for CRC diagnosis. The 4-marker methylation model provides a new non-invasive choice for CRC screening and interception. [ABSTRACT FROM AUTHOR]

Colorectal cancer (CRC) is the second leading malignancy worldwide. Accurate screening is pivotal to early CRC detection, yet current screening modality involves invasive colonoscopy while non-invasive FIT tests have limited sensitivity. We applied a DNA methylation assay to identify biomarkers for early-stage CRC detection, risk stratification and precancerous lesion screening at tissue level. A model of biomarkers SFMBT2, ITGA4, THBD and ZNF304 showed 96.1% sensitivity and 87.0% specificity in CRC detection, with 100.0% sensitivity for advanced precancerous lesion and stage I CRC. Performances were further validated with TCGA data set, which showed a consistent AUC of 0.99 and exhibited specificity against other cancer types. KCNJ12, VAV3-AS1 and EVC were further identified for stage stratification (stage 0-I versus stage II-IV), with AUC of 0.87, 83.0% sensitivity and 71.2% specificity. Additionally, dual markers of NEUROD1 and FAM72C showed 83.2% sensitivity and 77.4% specificity in differing non-advanced precancerous lesions from inflammatory bowel diseases. • Three sets of methylation markers for CRC management were identified at tissue level. • SFMBT2, ITGA4, THBD and ZNF304 were markers for early-stage CRC detection. • Methylation of KCNJ12, VAV3-AS1 and EVC were identified for CRC stage stratification. • NEUROD1 and FAM72C differentiated non-advanced precancerous lesions from IBD. [ABSTRACT FROM AUTHOR]

The round-off error, which is caused by cycle sampling of the interpolation period, affects the interpolation accuracy and motion smoothness of computer numerical control (CNC) machining. To consider the round-off error while restricting the motion parameters within their specified ranges, a time-rounding-up-based feedrate scheduling method is proposed. Firstly, the characteristics of S-shaped acceleration/deceleration (ACC/DEC) algorithm are analyzed by setting the jerk of each section as a variable. The expressions of jerk are derived and some important properties are discovered. According to these properties, it is possible to limit all the motion parameters in their given ranges through increasing the interpolation time and adjusting other motion parameters. Secondly, a new time-rounding-up scheme is designed to guarantee that the total interpolation time of each curve segment is an integer multiple of interpolation period. Then, based on the rounded time, the adjustment principles of the displacement and maximum feedrate are proposed to satisfy the various constraints. Its feasibility is also analyzed. Finally, based on the time-rounding-up scheme and the parameter adjustment principles, a series of feedrate scheduling methods are designed for different situations. For most situations, a non-standard S-shaped ACC/DEC profile can be generated with no round-off error and all the motion parameters can be restricted within their given ranges. A series of simulations and practical experiments are conducted to verify the good performance and applicability of the proposed method. [ABSTRACT FROM AUTHOR]

Suction plays an important role in the disordered manufacturing scenarios because of its single-point contact and reliability. The prediction of suction region is the primary problem needs to be solved in these applications. However, the traditional non-deep learning methods is insufficient for its poor generalization performance, and the deep learning method is inconvenient as it requires manually labeled datasets for training. Therefore, a suction region prediction method from knowledge to learning is proposed to overcome these challenges, which adopts a suction reliability matrix based on the depth image to label the disordered manufacturing datasets without manual labeling, where the effects of suction cup model, part centroid and depth are all considered. The disordered manufacturing dataset annotated is used to train the suction region prediction model based on fully convolutional neural network, which can be customized according to the model of suction cup and parts. Experiments and analysis show that the proposed method has the advantages of short detection time, high robustness and strong generalization ability. [ABSTRACT FROM AUTHOR]