P2P Cloud Manufacturing Based on a Customized Business Model: An Exploratory Study.

To overcome the problems of long production cycle and high cost in the product manufacturing process, a P2P (platform to platform) cloud manufacturing method based on a personalized custom business model has been proposed in this paper by integrating different technologies such as deep learning and additive manufacturing (AM). This paper focuses on the manufacturing process from a photo containing an entity to the production of that entity. Essentially, this is an object-to-object fabrication. Moreover, based on the YOLOv4 algorithm and DVR technology, an object detection extractor and a 3D data generator are constructed, and a case study is carried out for a 3D printing service scenario. The case study selects online sofa photos and real car photos. The recognition rates of sofa and car were 59% and 100%, respectively. Retrograde conversion from 2D data to 3D data takes approximately 60 s. We also carry out personalized transformation design on the generated sofa digital 3D model. The results show that the proposed method has been validated, and three unindividualized models and one individualized design model have been manufactured, and the original shape is basically maintained.

Improvements in Temperature Uniformity in Carbon Fiber Composites during Microwave-Curing Processes via a Recently Developed Microwave Equipped with a Three-Dimensional Motion System.

Curing processes for carbon-fiber-reinforced polymer composites via microwave heating are promising alternatives to conventional thermal curing because this technology results in nonhomogeneous temperature distributions, which hinder its further development in industries. This paper proposes a novel method for improving heating homogeneities by employing three-dimensional motion with respect to the prepreg laminate used in the microwave field by using a recently developed microwave system. The maximum temperature deviation on the surface of the laminate can be controlled within 8.7 °C during the entire curing process, and it produces an average heating rate of 1.42 °C/min. The FT-IR analyses indicate that microwave heating would slightly influence hydroxyl and methylene contents in the cured laminate. The DMA measurements demonstrate that the glass transition temperatures can be improved by applying proper microwave-curing processes. Optical microscopy and mechanical tests reveal that curing the prepreg laminate by using a multistep curing process that initially cures the laminate at the resin's lowest viscosity for 10 min followed by curing the laminate at a high temperature for a short period of time would be favorable for yielding a sample with low void contents and the desired mechanical properties. All these analyses are supposed to prove the feasibility of controlling the temperature difference during microwave-curing processes within a reasonable range and provide a cured laminate with improved properties compared with conventional thermally cured products.

Impact of ion beam irradiation on two-dimensional MoS2: a molecular dynamics simulation study.

Two-dimensional (2D) materials such as MoS2have extraordinary properties and significant application potential in electronics, optoelectronics, energy storage, bioengineering, etc. To realize the numerous application potential, it is needed to modulate the structure and properties of these 2D materials, for which ion beam irradiation has obvious advantages. This research adopted classical molecular dynamics simulations to study the sputtering of atoms in 2D MoS2, defect formation and the control rule under Ar ion beam irradiation, considering the influence of ion irradiation parameters (i.e., ion beam energy, ion dose), layer number of 2D MoS2, substrate. Furthermore, the uniaxial mechanical performance of the ion-irradiated nanostructures was investigated for actual applications loading with mechanical stress/strain. This research could provide important theoretical support for fabricating high-performance 2D MoS2-based nanodevices by ion beam irradiation method.

Molecular dynamics simulations of ion beam irradiation on graphene/MoS2 heterostructure.

The interaction between ion irradiation and two-dimensional (2D) heterostructures is important for the performance modulation and application realization, while few studies have been reported. This paper investigates the influence of Ar ion irradiation on graphene/MoS2 heterostructure by using molecular dynamics (MD) simulations. The generation of defects is studied at first by considering the influence factors (i.e., irradiation energy, dose, stacking order, and substrate). Then uniaxial tensile test simulations are conducted to uncover the evolution of the mechanical performance of graphene/MoS2 heterostructure after being irradiated by ions. At last, the control rule of interlayer distance in graphene/MoS2 heterostructure by ion irradiation is illustrated for the actual applications. This study could provide important guidance for future application in tuning the performance of graphene/MoS2 heterostructure-based devices by ion beam irradiation.

Cloud Health Resource Sharing Based on Consensus-Oriented Blockchain Technology: Case Study on a Breast Tumor Diagnosis Service.

BACKGROUND: In recent years, researchers have made significant efforts in advancing blockchain technology. This technology, with distinct features of decentralization and security, can be applied to many fields. In areas of health data and resource sharing, applications of blockchain technology are also emerging. OBJECTIVE: In this study, we propose a cloud health resource-sharing model based on consensus-oriented blockchain technology and have developed a simulation study on breast tumor diagnosis. METHODS: The proposed platform is built on a consortium or federated blockchain that possesses features of both centralization and decentralization. The consensus mechanisms generate operating standards for the proposed model. Open source Ethereum code is employed to provide the blockchain environment. Proof of Authority is selected as the consensus algorithm of block generation. RESULTS: Based on the proposed model, a simulation case study for breast tumor classification is constructed. The simulation includes 9893 service requests from 100 users; 22 service providers are equipped with 22 different classification methods. Each request is fulfilled by a service provider recommended by the weighted k-nearest neighbors (KNN) algorithm. The majority of service requests are handled by 9 providers, and provider service evaluation scores tend to stabilize. Also, user priority on KNN weights significantly affects the system operation outcome. CONCLUSIONS: The proposed model is feasible based on the simulation case study for the cloud service of breast tumor diagnosis and has the potential to be applied to other applications.

Laminarin enhances the activity of natural killer cells in immunosuppressed mice.

The aim of the study was to investigate the effects of laminarin on natural killer (NK) cell cytotoxicity of immunosuppressive mice and its mechanism. Cyclophosphamide (cy) was used to make an immunosuppressive model of mice. The mice of two groups were given interventions by gavage with laminarin 500 mg/kg and 1000 mg/kg every day for 10 days. MACS was adopted to isolate spleen NK cells, and cytotoxicity of NK cells and IL-12, IFN-γ level in serum were detected in vivo. Cytotoxicity of NK92-MI cells, activating receptors (NKp30, NKp44, NKp46 and NKG2D) and perforin and granzyme B expression were detected in vitro. Compared to the normal control group, the cytotoxicity of NK cells, IL-12 and IFN-γ level in serum in the cy model group were all reduced significantly (p < 0.01). Compared to the cy model group, laminarin increased the cytotoxicity of NK cells, IL-12 and IFN-γ levels in serum significantly (p < 0.05). In vitro, laminarin increased the cytotoxicity, NKp30 and NKG2D, perforin and granzyme B expressions of NK92-MI cells (p < 0.01). This research showed that laminarin can promote NK cell cytotoxicity in immunosuppressive mice by increasing the levels of IL-12 and IFN-γ in serum and expressions of NKp30 and NKG2D, perforin and granzyme B.

Simulation and Test of a Contactless Voltage Measurement Method for Overhead Lines Based on Reconstruction of Integral Node Parameters.

To improve the stability and adaptability of the voltage measurement based on the E-field (electric field) integral method, in this paper we introduce a new method for the contactless voltage measurement of the overhead lines. The method adopts the node parameter reconstruction technology, which is based on the Gauss-Chebyshev algorithm. In order to achieve high-quality E-field detection at the reconstructed node position, we designed a novel D-dot sensor with parallel distributed electrodes. A Maxwell simulation model of multi-level voltages of the overhead lines was carried out to determine a comprehensive criterion of the reconstruction factors. The simulation employed a three-phase overhead line experiment platform to calculate and measure the distribution and the changing trend of the E-field. The deviations of the voltage measurement were reduced at a significantly low level within 0.4%. The result of the simulation demonstrates that the method optimizes sensor distribution by reconstructing node parameters, which enables the system to have high accuracy and reliability on the contactless voltage measurement of the overhead lines.

High expression of ALDOA and DDX5 are associated with poor prognosis in human colorectal cancer.

PURPOSE: The identification of prognostic markers for colorectal cancer (CRC) is needed for clinical practice. Fructose-bisphosphate aldolase A (ALDOA) and DEAD box p68 RNA helicase (DDX5) are commonly overexpressed in cancer and correlate with tumorigenesis. However, association between expression of ALDOA and DDX5, and CRC outcome has not been reported. PATIENTS AND METHODS: We used 141 formalin-fixed paraffin-embedded (FFPE) specimens collected from 105 patients with CRC treated at the Affiliated Hospital of Guilin Medical University and the People's Hospital of Liuzhou. We performed tissue microarray based immunohistochemistry to explore expression features and prognostic value (overall survival, OS; disease-free survival, [DFS]) of ALDOA and DDX5 in CRC tissues. The prognostic values were evaluated using Kaplan-Meier analysis, and Cox regression analyses. RESULTS: ALDOA and DDX5 were highly expressed in CRC tissues and liver metastatic CRC tissues compared with normal glandular epithelium tissues (all p<0.05). Interestingly, primary CRC tissues highly expressing ALDOA or DDX5 had poor outcome (p<0.0001 for both OS and DFS for ALDOA; p=0.001 for OS; and p=0.011 for DFS for DDX5) compared with patients who had low expression of those proteins. Furthermore, multivariate Cox analysis showed that ALDOA/DDX5 combination was an independent risk factor for OS and ALDOA was an independent risk factor for DFS. CONCLUSION: High levels of ALDOA and DDX5 contribute to the aggressiveness and poor prognosis of CRC. ALDOA/DDX5 expression could be a biomarkers for the prognosis of CRC.