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Deterministic networking for industrial manufacturing is a frontier technology with both theoretical innovativeness and technical practicability; it is significant for promoting technological innovations of the new-generation industrial Internet and for promoting the integrated development of industrial manufacturing and high-quality network, thereby providing opportunities for occupying the commanding height of network technology and seizing new economic growth points. This study investigates the development requirements for deterministic networking for industrial manufacturing from the aspects of manufacturing and communication enterprises, summarizes the development status and trends of the technology in detail, and further addresses development challenges. We classify the development stages of the technology into pilot demonstration, large-scale replication, and spontaneous innovation. Research reveals that the “deterministic network + industrial manufacturing” development in China needs to focus on the following aspects: establishing industry alliances to improve the industrial ecology, maximizing the existing public networks, carefully selecting industry development paths, increasing resource guarantee for application innovation, strengthening research on basic theories and key technologies, and training personnel through collaboration among industry, universities, and research institutes.

This paper addresses task assignment (TA) for multivehicle systems. Multivehicle TA problems are formulated as a combinatorial optimization problem and further as a global optimization problem. To fulfill heterogeneous tasks, cooperation among heterogeneous vehicles is incorporated in the problem formulations. A collaborative neurodynamic optimization approach is developed for solving the TA problems. Experimental results on four types of TA problems are discussed to substantiate the efficacy of the approach.

With the development of green agriculture, the demand of farmers for operation loans is increasing. Supply chain finance is becoming a new way to solve the problem of difficult credit in agricultural development. As the importance of sustainability issues continues to rise, there are growing numbers of practical examples of combining agricultural supply chain finance (ASCF) with sustainability, and the attendant risks are emerging. The objectives of this study are first to construct a risk indicator system for sustainable ASCF, then to propose a fuzzy decision method that considers the confidence of decision-makers, and finally to perform a risk assessment of a credit case in the coffee bean supply chain. A combination of the neutrosophic enhanced best–worst method (NE-BWM) and combined compromise solution (COCOSO) is used to evaluate risk problems. The practicality and effectiveness of this research method is verified by a numerical simulation and a comparison with the method. The results show that the credit rating of core companies is the most important indicator. In the context of green and sustainable development, this indicator system is more suitable for the current green transformation development of agriculture and can help decision-makers scientifically and reasonably assess the risk level of ASCF. When loans are needed to transform green agriculture, this study provides new ideas for credit models for various actors in the agricultural supply chain and offers a new entry point to the issue of sustainable agricultural development.

Kaposi sarcoma (KS) is a mesenchymal tumor characterized by angioproliferation in the setting of infection by human herpesvirus 8 (HHV-8), also known as KS–associated herpesvirus. The disease has several manifestations, the most common of which is a violaceous-to-dark brown macule, plaque, or nodule on the skin. Involvement of the gastrointestinal tract is less common, only affecting 10% of patients but is much more prevalent in the immunocompromised.1 Involvement of visceral organs outside the gastrointestinal tract such as the lungs, liver, and bone is extremely rare in immunocompetent patients. Clinically, most cases of KS fit into 1 of 5 reported subtypes: classical, African endemic, AIDS epidemic, iatrogenic, and nonepidemic. Very rarely do patients present who do not conform to 1 of the 5 subtypes. We present 3 such patients and discuss their fit in the current classification system.

In this paper, a method is presented for antidisturbance constrained control of autonomous underwater vehicles subject to uncertainties and constraints. The uncertainties stem from uncertain hydrodynamic parameters, modeling errors, and unknown forces due to the ocean currents in an underwater environment. An antidisturbance constrained controller is developed by designing a command governor and a disturbance observer. Specifically, the disturbance observer is developed to estimate the lumped disturbance composed of parametric model uncertainties, modeling errors, and unknown environmental forces. The command governor is designed for optimizing command signals in the receding horizon within the state and input constraints. The command governor is formulated as a quadratically constrained quadratic programming problem. To facilitate online implementations, a neurodynamic optimization method based on a one-layer recurrent neural network is employed for solving the quadratic optimization problem subject to inequality constraints with finite-time convergence. The efficacy of the proposed antidisturbance constrained control method for autonomous underwater vehicles is substantiated via simulations and comparisons.

This article presents a collaborative neurodynamic optimization (CNO) approach to multivehicle task assignments (TAs). The original combinatorial quadratic optimization problem for TA is reformulated as a quadratic unconstrained binary optimization (QUBO) problem with a quadratic utility function and a penalty function for handling load capacity and cooperation constraints. In the framework of CNO with a population of discrete Hopfield networks (DHNs), a TA algorithm is proposed for solving the formulated QUBO problem. Superior experimental results in four typical multivehicle operation scenarios are reported to substantiate the efficacy of the proposed neurodynamics-based TA approach.

Flip chip technology has been rapidly developed and widely used in the field of microelectronic packaging, and defect detection has also received more and more attention. Aiming at the problem that noise affects the location and extraction of signal defects in ultrasonic testing, the sparse Bayesian learning based on generalized approximate message passing (GAMP-SBL) algorithm is used to extract signal defects, and the over-complete Gabor dictionary is used to reconstruct signal defects to effectively improve Sparse decomposition algorithm. The precision experiment tested the defect simulation signal and the actual ultrasonic signal respectively, and compared with the greedy algorithm. The experimental results show that the GAMP-SBL algorithm can more effectively extract the defect signal under the noise background.

This article presents a neurodynamic approach to nonlinear programming. Motivated by the idea of sequential quadratic programming, a class of two-timescale multilayer recurrent neural networks is presented with neuronal dynamics in their output layer operating at a bigger timescale than in their hidden layers. In the two-timescale multilayer recurrent neural networks, the transient states in the hidden layer(s) undergo faster dynamics than those in the output layer. Sufficient conditions are derived on the convergence of the two-timescale multilayer recurrent neural networks to local optima of nonlinear programming problems. Simulation results of collaborative neurodynamic optimization based on the two-timescale neurodynamic approach on global optimization problems with nonconvex objective functions or constraints are discussed to substantiate the efficacy of the two-timescale neurodynamic approach.

This article contains a new subnet training method for modular neural networks, proposed with the inspiration of the principle of “an expert with other capabilities”. The key point of this method is that a subnet learns the neighbor data sets while fulfilling its main task: learning the objective data set. Additionally, a relative distance measure is proposed to replace the absolute distance measure used in the classical subnet learning method and its advantage in the general case is theoretically discussed. Both methodology and empirical study of this new method are presented. Two types of experiments respectively related with the approximation problem and the prediction problem in nonlinear dynamic systems are designed to verify the effectiveness of the proposed method. Compared with the classical subnet learning method, the average testing error of the proposed method is dramatically decreased and more stable. The superiority of the relative distance measure is also corroborated.

Impingement cooling is applied on the turbine blade leading edge which suffers the highest heat transfer and needs priority protection. The current work focuses on the rotational effects in an impingement cooling channel with film extraction, in which heat transfer is obtained with experiment whereas the flow field is predicted by numerical simulation. The dimensionless spacing of jet-to-jet (s/Dj) and jet-to-target surface (l/Dj) are both 3. The jet Reynolds number and the channel orientation (the angle between jet direction and rotating orientation) are 5,000 and 135°, respectively. The jet rotation number changes from 0 to 0.24, and the maximum jet buoyancy number reaches 0.57. The results show that the heat transfer on the suction side is better than that on the pressure side where the recirculation region generates. The heat transfer deteriorates from high to low radius due to the non-uniform mass flow rate distribution. Once the channel rotates, the non-uniformity of mass flow rate increases because the vortex occurs in the supply channel, resulting in the heat transfer increase by 140% in the low radius region on the pressure side. On the pressure side in the impingement channel, the rotation-induced secondary flow breaks the recirculation region, promoting the heat transfer. On the suction side, however, the secondary flow and rotation-driven jet deflection decrease the heat transfer. Besides, the jet buoyancy number is inappropriate to describe the combined influences of jet rotation number and wall-to-fluid temperature ratio at high jet buoyancy number in current experimental conditions.

The heat transfer characteristics in a rectangular channel under rotating conditions with impingement jet and film holes was studied. The key features of the geometry are multiple impingement jets and film holes in the leading edge model. The jet Reynolds number (Rej), jet rotation number (Roj) and buoyancy number (Buo) varied from 5000 to 10,000, from 0 to 0.24, and from 0 to 0.57, respectively. Four temperature ratio (TR) cases (0.07, 0.10, 0.13, and 0.16) and three channel orientations (β = 90, 135, and 180) are selected. For all experiment cases, the spacing of jet-to-jet (s/d = 3) and jet-to-target surface (l/d = 3) were held constant. In the non-rotating cases, the heat transfer level of the T2 region (stagnation point), impinged by the jet directly, is the strongest and about twice to the other regions. The overall heat transfer distribution almost does not change significantly as the Rej varied from 5000 to 10,000. The jet rotation number plays an important role under the rotation state. For the orientation of 135°, the Coriolis force deflects the jet and weakens the heat transfer of the medium radius in the T2 region. No obvious variation in the heat transfer distribution for different temperature ratio under non-rotating and rotating cases was observed. The Coriolis force generated by different rotation directions causes two influences on the flow structure, leading to the different heat transfer distribution. The overall heat transfer level for the orientation of 90° and 135° varies little (5%) with the rotation number, while that of 180° decreases much (25%).

OBJECTIVE To observe the clinical effect of catheter-directed thrombolysis on deep venous thrombosis (DVT) of lower extremity after burn. STUDY DESIGN An observational study. PLACE AND DURATION OF STUDY Invasive Technology Department, Binzhou City Center Hospital, China, from January 2015 to November 2017. METHODOLOGY Eighty-two patients with lower extremity DVT after burn were selected as the study object. All patients received catheter-directed thrombolysis and the clinical efficacy was evaluated. The blood coagulation parameters including plasma prothrombin time (PT), activated partial thromboplastin time (APTT), thrombin time (TT), and fibrin original (FIB) and inflammatory response factors including interleukin (IL)-6, C-reactive protein (CRP) and D-dimer were compared before and after treatment. RESULTS All interventional surgeries that the patients received were successful. The effective rate of catheter-directed thrombolysis was 98.78% (81 cases). After 6 days of treatment, compared with that before treatment, serum PT, APTT and TT were up-regulated (all p

The degeneration mechanism of viscoelastic food material in specific processing mode affects the formulation of food material processing technology. On the other hand, it determines the taste of food in the chewing process. The viscoelastic food material was taken as the research object, and experimental data were obtained through stress relaxation experiments and strain relaxation experiments of texture analyzer material. Based on Maxwell model and Kelvin model, describing small deformation of the nonlinear viscoelastic constitutive model, building a composite model was proposed. By making analysis and comparison between constructed composite model and Maxwell model and Kelvin model, it was verified that the constructed composite model can be better described as the mechanical behavior of viscoelastic food material under the mode of compressed chewing, which is also providing a more precise theoretical model for the processing and development of viscoelastic food material.

Objective: As a member of the S100 proteins family, the involvement of S100A11 has been suggested in a wide range of biological processes such as cell growth and motility, cell-cycle progression, transcription, differentiation and smooth muscle cell migration. However, the expression of S100A11 and its exact function in laryngeal squamous cell carcinoma (LSCC) have not been elucidated. Methods: The protein and mRNA expression levels of S100A11 were analyzed in primary tumors and matched tumor-adjacent tissues of LSCC by western blotting and semi-quantitative reverse transcription polymerase chain reaction (RT-PCR) or quantitative real time PCR (Q-RT-PCR), respectively. Cell proliferation, colony formation, migration and wound-healing assays were performed to assess whether the knockdown of S100A11 by small interfering RNA (siRNA) could influence the biological behavior of human laryngeal carcinoma Hep-2 cells in vitro. Results: We found that both protein and mRNA levels of S100A11 were overexpressed in laryngeal tumor tissues when compared to the corresponding noncancerous tissues. Further, it was demonstrated that the expression of S100A11 could induce migration but not proliferation of Hep-2 cells. Additionally, S100A11 altered a series of intracellular events, including the down-regulation of epidermal growth factor receptor (EGFR), CD44 and MMP2. Conclusions: These results highlight the significance of S100A11 in LSCC progression and suggest that the dysregulation of S100A11 might contribute to the metastatic progression of LSCC.

To discover candidate biomarkers for diagnosis and detection of human laryngeal carcinoma and explore possible mechanisms of this cancer carcinogenesis, two-dimensional strong cation-exchange/reversed-phase nano-scale liquid chromatography/mass spectrometry analysis was used to identify differentially expressed proteins between the laryngeal carcinoma tissue and the adjacent normal tissue. As a result, 281 proteins with significant difference in expression were identified, and four differential proteins, Profilin-1 (PFN1), Nucleolin (NCL), Cytosolic non-specific dipeptidase (CNDP2) and Mimecan (OGN) with different subcellular localization were selectively validated. Semiquantitative RT-PCR and Western blotting were performed to detect the expression of the four proteins employing a large collection of human laryngeal carcinoma tissues, and the results validated the differentially expressed proteins identified by the proteomics. Furthermore, we knocked down PFN1 in immortalized human laryngeal squamous cell line Hep-2 cells and then the proliferation and metastasis of these transfected cells were measured. The results showed that PFN1 silencing inhibited the proliferation and affected the migration ability of Hep-2 cells, providing some new insights into the pathogenesis of PFN1 in laryngeal carcinoma. Altogether, our present data first time show that PFN1, NCL, CNDP2 and OGN are novel potential biomarkers for diagnosis and therapeutic targets for laryngeal carcinoma, and PFN1 is involved in the metastasis of laryngeal carcinoma.