Stretching Micro Metal Particles into Uniformly Dispersed and Sized Nanoparticles in Polymer.

There is a longstanding challenge to disperse metal nanoparticles uniformly in bulk polymers for widespread applications. Conventional scale-down techniques often are only able to shrink larger elements (such as microparticles and microfibers) into micro/nano-elements (i.e. nanoparticles and nanofibers) without much altering their relative spatial and size distributions. Here we show an unusual phenomenon that tin (Sn) microparticles with both poor size distribution and spatial dispersion were stretched into uniformly dispersed and sized Sn nanoparticles in polyethersulfone (PES) through a stack and draw technique in thermal drawing. It is believed that the capillary instability plays a crucial role during thermal drawing. This novel, inexpensive, and scalable method overcomes the longstanding challenge to produce bulk polymer-metal nanocomposites (PMNCs) with a uniform dispersion of metallic nano-elements

Influence of porosity on osteogenesis, bone growth and osteointegration in trabecular tantalum scaffolds fabricated by additive manufacturing

Porous tantalum implants are a class of materials commonly used in clinical practice to repair bone defects. However, the cumbersome and problematic preparation procedure have limited their widespread application. Additive manufacturing has revolutionized the design and process of orthopedic implants, but the pore architecture feature of porous tantalum scaffolds prepared from additive materials for optimal osseointegration are unclear, particularly the influence of porosity. We prepared trabecular bone-mimicking tantalum scaffolds with three different porosities (60%, 70% and 80%) using the laser powder bed fusing technique to examine and compare the effects of adhesion, proliferation and osteogenic differentiation capacity of rat mesenchymal stem cells on the scaffolds in vitro. The in vivo bone ingrowth and osseointegration effects of each scaffold were analyzed in a rat femoral bone defect model. Three porous tantalum scaffolds were successfully prepared and characterized. In vitro studies showed that scaffolds with 70% and 80% porosity had a better ability to osteogenic proliferation and differentiation than scaffolds with 60% porosity. In vivo studies further confirmed that tantalum scaffolds with the 70% and 80% porosity had a better ability for bone ingrowh than the scaffold with 60% porosity. As for osseointegration, more bone was bound to the material in the scaffold with 70% porosity, suggesting that the 3D printed trabecular tantalum scaffold with 70% porosity could be the optimal choice for subsequent implant design, which we will further confirm in a large animal preclinical model for better clinical use

Bridge structure deformation prediction based on GNSS data using Kalman-ARIMA-GARCH model

Bridges are an essential part of the ground transportation system. Health monitoring is fundamentally important for the safety and service life of bridges. A large amount of structural information is obtained from various sensors using sensing technology, and the data processing has become a challenging issue. To improve the prediction accuracy of bridge structure deformation based on data mining and to accurately evaluate the time-varying characteristics of bridge structure performance evolution, this paper proposes a new method for bridge structure deformation prediction, which integrates the Kalman filter, autoregressive integrated moving average model (ARIMA), and generalized autoregressive conditional heteroskedasticity (GARCH). Firstly, the raw deformation data is directly pre-processed using the Kalman filter to reduce the noise. After that, the linear recursive ARIMA model is established to analyze and predict the structure deformation. Finally, the nonlinear recursive GARCH model is introduced to further improve the accuracy of the prediction. Simulation results based on measured sensor data from the Global Navigation Satellite System (GNSS) deformation monitoring system demonstrated that: (1) the Kalman filter is capable of denoising the bridge deformation monitoring data; (2) the prediction accuracy of the proposed Kalman-ARIMA-GARCH model is satisfactory, where the mean absolute error increases only from 3.402 mm to 5.847 mm with the increment of the prediction step; and (3) in comparision to the Kalman-ARIMA model, the Kalman-ARIMA-GARCH model results in superior prediction accuracy as it includes partial nonlinear characteristics (heteroscedasticity); the mean absolute error of five-step prediction using the proposed model is improved by 10.12%. This paper provides a new way for structural behavior prediction based on data processing, which can lay a foundation for the early warning of bridge health monitoring system based on sensor data using sensing technolog

Venous thromboembolism after oral and maxillofacial oncologic surgery : report and analysis of 14 cases in Chinese population

Venous thromboembolism (VTE) including deep vein thrombosis (DVT) and pulmonary embolism (PE) is a leading cause of death in cancer patients. The aim of this study was to explore the potential risk factor of VTE in oral and maxillofacial oncological surgery. The data of patients who received operation in our institution were gathered in this retrospective study. A diagnosis of VTE was screened and confirmed by computer tomography angiography (CTA) of pulmonary artery or ultrasonography examination of lower extremity. Medical history and all perioperative details were analyzed. 14 patients were diagnosed as VTE, including 6 cases of PE, 7 cases of DVT, 1case of DVT and PE. The mean age of these patients was 62.07 years. Reconstruction was performed in 12 patients of these cases, most of which were diagnosed as malignance. Mean length of surgery was 8.74 hours, and lower extremity deep venous cannula (DVC) was performed in all these patients. We analyzed several characters of oral and maxillofacial surgery and suggested pay attention to lower extremity DVC which had a high correlation with DVT according to our data

Two-Link Flexible Manipulator Modeling and Tip Trajectory Tracking Based on Absolute Nodal Coordinate Method

Abstract It has been demonstrated that the absolute nodal coordinate formulation (ANCF) proposed recently in literature can be used to exactly describe the flexible multibody system unlike traditional methods such as the floating coordinate method and assumed mode method. Therefore, in this paper a new dynamic modeling technique for a two-link flexible manipulator based on absolute nodal coordinate method is proposed. The link shear effect was taken into account by using the 2D ANCF shear beam element. The resulting state equation can be explicitly described by generalized coordinate since the system mass matrix is constant in the ANCF framework. The proposed method is validated through the two-link flexible manipulator tip circle and square trajectory tracking control simulations by using a simple PD controller. To improve computational efficiency, the invariant matrix method and the Broyden quasi-Newton method are introduced. To improve the tracking accuracy, different PD parameters in different simulation periods are used. The simulation results indicate that modeling and controlling the flexible manipulator based on the ANCF is effective

The Spread of Infectious Disease with Household-Structure on the Complex Networks

In this paper we study the household-structure SIS epidemic spreading on general complex networks. The household structure gives us the way to distinguish inner and the outer infection rate. Unlike household-structure models on homogenous networks, such as regular and random networks, here we consider heterogeneous networks with arbitrary degree distribution p(k). First we introduce the epidemic model. Then rate equations under mean field appropriation and computer simulations are used here to analyze our model. Some unique phenomena only existing in divergent network with household structure is found, while we also get some similar conclusions that some simple geometrical quantities of networks have important impression on infection property of infectous disease. It seems that in our model even when local cure rate is greater than inner infection rate in every household, disease still can spread on scale-free network. It implies that no disease is spreading in every single household, but for the whole network, disease is spreading. Since our society network seems like this structure, maybe this conclusion remind us that during disease spreading we should pay more attention on network structure than local cure condition.Comment: 12 pages, 2 figure

The Optimal Design Method and Standardized Mathematical Model of Tooth Profile Modification of Spur Gear

The paper reports a tooth profile modification method of spur gear. After establishing a standardized mathematical model for optimized tooth profile and simulating meshing process with ANSYS finite element analysis, we obtained 625 groups of gear models with different modification parameters. The group with minimum transmission errors owns the optimal parameters. Genetic algorithm was adopted in the entire process for the purpose of reducing the variation of transmission errors in meshing process. The arc and parabolic modification were doing the same processing. After comparing the transmission errors fluctuation produced by the meshing process of gear of nonmodification with arc modification and parabolic modification, we found that the best modification effects of arc modification and parabolic modification were both reduced by 90%. The modification method makes the gear drive process more stable and efficient, and it is also promising in general application for gear drive

Clinical implication of PD-L2 in the prognosis assessment of HNSCC immunotherapy

Background and purpose: Programmed death-1 (PD-1) monoclonal antibody therapy plays an increasingly important role in the treatment of head and neck squamous cell carcinoma (HNSCC). However, low response rate and lack of predictive biomarkers are still the challenging problems. This study aimed to confirm that programmed death ligand-2 (PD-L2) is a predictive biomarker for the outcome of HNSCC anti-PD-1 immunotherapy. Methods: The samples and clinical data of 50 HNSCC patients undergoing PD-1 monoclonal antibody immunotherapy were collected. Immunohistochemical staining was used to analyze the level of programmed death ligand-1 (PD-L1) and PD-L2. Kaplan-Meier overall survivals were analyzed using SPSS 26.0 software, grouped by the basic clinical characteristics and the PD-L1 and PD-L2 levels. Survival curves were plotted using GraphPad Prism. Results: HNSCC had a relatively high expression rate of PD-L2 with more than 80% of cases detected as PD-L2 positive. The expression of PD-L2 significantly correlated with the clinical outcome of immunotherapy, with a mean survival of 18.8 (16.0-21.7) months for patients with high PD-L2 expression and 11.0 (9.1-12.8) months for patients with low PD-L2 expression, this difference being statistically significant. Conclusion: PD-L2 has the potential to be used as a predictive biomarker for HNSCC anti-PD-1 immunotherapy