The finite element (FE) model of the pelvic joint is helpful for clinical diagnosis and treatment of pelvic injuries. However, the effect of an FE model boundary condition on the biomechanical ...behavior of a pelvic joint has not been well studied. The objective of this study was to study the effect of boundary condition on the pelvic biomechanics predictions. A 3D FE model of a pelvis using subject-specific estimates of intact bone structures, main ligaments and bone material anisotropy by computed tomography (CT) gray value was developed and validated by bone surface strains obtained from rosette strain gauges in an in vitro pelvic experiment. Then three FE pelvic models were constructed to analyze the effect of boundary condition, corresponding to an intact pelvic joint, a pelvic joint without sacroiliac ligaments and a pelvic joint without proximal femurs, respectively. Vertical load was applied to the same pelvis with a fixed prosthetic femoral stem and the same load was simulated in the FE model. A strong correlation coefficient (R(2)=0.9657) was calculated, which indicated a strong correlation between the FE analysis and experimental results. The effect of boundary condition changes on the biomechanical response depended on the anatomical location and structure of the pelvic joint. It was found that acetabulum fixed in all directions with the femur removed can increase the stress distribution on the acetabular inner plate (approximately double the original values) and decrease that on the superior of pubis (from 7 MPa to 0.6 MPa). Taking sacrum and ilium as a whole, instead of sacroiliac and iliolumber ligaments, can influence the stress distribution on ilium and pubis bone vastly. These findings suggest pelvic biomechanics is very dependent on the boundary condition in the FE model.
We experimentally explore the practicality of integrated multiwavelength laser arrays (MLAs) for photonic convolutional neural network (PCNN). MLAs represent excellent performance for PCNN, except ...for imperfect wavelength spacings due to fabrication variation. Therefore, the performance of PCNN with non-ideal wavelength spacing is investigated experimentally and numerically for the first time. The results show that there exists a certain tolerance for wavelength deviation on the degradation of the structural information of the extracted feature map, leading to the robustness of photonic recognition accuracy under non-ideal wavelength spacing. The results suggest that scalable MLAs could serve as an alternative source for the PCNN, to support low-cost optical computing scenarios. For a benchmark classification task of MNIST handwritten digits, the photonic prediction accuracy of 91.2% for stride 1 × 1 scheme using the testing dataset are experimentally obtained at speeds on the order of tera operations per second, compared to 94.14% on computer. The robust performance, flexible spectral control, low cost, large bandwidth and parallel processing capability of the PCNN driven by scalable MLAs may broaden the application possibilities of photonic neural networks in next generation data computing applications.
•CNP-OMV were efficiently taken up by macrophages, resulting in a significant increase of cell proliferation and cytokines secretion.•CNP-OMV induced a high level of IgG production against Bordetella ...bronchiseptica and induced a mixed Th1/Th2/Th17 immune response in rabbits.•CNP-OMV could effectively prevent the immunized rabbits from Bordetella bronchiseptica infection.
The outer membrane vesicle (OMV) of bacteria is a bilayer membrane vesicle with a diameter of about 10–300 nm that is secreted during the growth of Gram-negative bacteria. OMV is considered as a high-quality vaccine candidate antigen because of its natural immunogenicity and non-replicability. Although the excellent antigenicity of OMV has been widely confirmed, its instability and heterogeneity greatly affect its immune effect. Many studies have demonstrated that in combination with nanoparticles can enhance the stability of OMV. In this study, OMVs were used to coat chitosan nanoparticles (CNPs) and obtain a stable OMV vaccine. The characteristics, including morphology, hydrodynamic size, and zeta potential were evaluated. The immune protection of CNP-OMV and anti-infection efficacy were examined and compared in vivo and in vitro. The results showed that the CNP-OMV were homogenous with a size of 139 nm and a stable core–shell structure. And CNP-OMV could significantly increase the cell proliferation, phagocytosis and TNF-α, IL-6 and IL-10 secretion of RAW264.7 in vitro. In vivo, CNP-OMV could significantly increase the levels of anti-Bb and OMV IgG antibodies. Levels of blood lymphocyte, and Th1 (IFN-γ, IL-12), Th2 (IL-4, IL-5), and Th17 (IL-17, TNF-α) type cytokines in the serum were all significantly increased. At the same time, CNP-OMV could significantly reduce the bacterial invading the lungs of challenged rabbits. And CNP-OMV could largely protect the lungs from injury. The above results showed that CNP-OMV had a good immune efficacy and could resist the infection of Bordetella bronchiseptica. This study provided a scientific basis for the development of novel effective and safe vaccine against Bordetella bronchiseptica, and also provided a new idea for the development of new bacterial vaccine.
Bordetella infection can be efficiently prevented through vaccination. The current study investigated the effects of an extract of Cochinchina momordica seed (ECMS) combined with oil on the immune ...responses to the inactivated Bordetella vaccine in mice. Serum IgG and IgG1 level was significantly increased in ECMS-oil group compared to any other group (P<0.05) 2 weeks after immunization, while groups ECMS200 μg/400 μg-oil had a markedly higher level of serum IgG2b and IgG3 than any other groups (P<0.05). Moreover, lipopolysaccharide/ConA-stimulated proliferation of splenocytes was significantly enhanced in ECMS 400 μg-oil immunized mice in comparison with mice in any other group (P<0.05). RT-PCR assay revealed that while ECMS800 μg-oil group had significantly higher levels of serum IL-4, IL-10, Toll-like receptor (TLR)2, and IL-1 beta than any other group (P<0.05), the levels of serum IL-2, IL-4, and IL-10 were markedly increased in ECMS 400 μg-oil group as compared to any other groups (P<0.05). Blood analysis showed that ECMS800 μg-oil and oil groups had a significantly higher number of immunocytes than any other groups (P<0.05). There were significant differences in the number of IgG+, IgG2b+, and IgA+ cells in the lung between ECMS800 μg-oil group and any other groups (P<0.05). Western blot analysis demonstrated that stimulation with ECMS 25 μg/mL or 50 ng/mL led to a significant increase in the expression of TLR2, MyD88, and NF-κB in Raw264.7 cells (P<0.05). Compared with any other group, the expression of MyD88 was markedly increased in the cells stimulated with ECMS 50 ng/mL, as indicated by the RT-PCR analysis (P<0.05). Overall, we observed that ECMS-oil efficiently enhanced the humoral or cellular immune responses against Bordetella and suggested that the mechanism of adjuvant activity of ECMS-oil might involve TLR2/MyD88/NF-κB signaling pathway.
We summarized the design, fabrication challenges and important technologies for multi-wavelength laser transmitting photonic integration. Technologies discussed include multi-wavelength laser arrays, ...monolithic integration and modularizing coupling and packaging. Fabrication technique requirements have significantly declined with the rise of reconstruction-equivalent-chirp and second nanoimprint mask technologies. The monolithic integration problem between active and passive waveguides can be overcome with Butt-joint and InP array waveguide grating technologies. The dynamic characteristics of multi-factors will be simultaneously measured with multi-port analyzing modules. The performance of photonic integration chips is significantly improved with the autoecious factors compensation packaging technique.
Electron energy‐loss spectroscopy (EELS) is widely applied combining with transmission electron microscopes with high spatial resolution, but its interpretation is a challenging task. One of the ...reasons is that the factors affecting EELS are very complicated. In this paper, we focus on the several factors involved in density functional theory (DFT) calculations. The sensitivity of calculated energy‐loss near‐edge structure (ELNES) to spin order, pressure and on‐site Coulomb energy U has been discussed. Since EELS technique detects the local environment of atoms, the influence of spin order cannot be ignored. The chemical shifts and peak intensity of ELNES are also closely related to corresponding pressure. The correlation effects are very important for transition metal compounds and play a key role in EELS simulations. An overview of the effects of these factors on the ELNES is presented with the help of Wien2k code. The antiferromagnetic order results in the decreasing of intensities of related peaks and the moving of the peaks to high energy loss. The decreasing of lattice parameters causes the ELNES peaks to shift to high energy loss, and the peak shifts at the higher energy loss are more significant. The increase of correlation effect leads to the ELNES peaks to shift to high energy loss accompanied by the increase of the relative intensity of the peaks which locate at higher energy loss. Our work helps to understand how these factors affect EELS and to explain and predict the experimental EELS spectra. Through the discussion of these factors, we propose that some factors could not be ignored in EELS simulations.
Lay description
Transmission electron microscope (TEM) is a powerful scientific instrument, which can be used for small size imaging. In recent decades, it has helped scientists to make important discoveries such as carbon nanotube and quasicrystal and has been widely used in materials science, condensed matter physics, structural biology and other fields. The principle of transmission electron microscope is similar to that of optical microscope, but its resolution is far superior to that of optical microscope. Compared with the resolution of optical microscope about 300 nm, the resolution of transmission electron microscope can reach 0.039 nm at present. In addition to excellent spatial resolution, transmission electron microscope has many functions such as structural analysis, elemental composition analysis and electronic structure analysis. TEM can be also used to carry out in situ observation and time resolution observation. Because of its several advantages mentioned above, transmission electron microscopy attracts much attention since its birth in the early 1930s. The early TEM was considered to be used only to magnify the observed object, but the electron energy‐loss spectroscopy (EELS) gives it the ability to determine the composition of the sample and analyse the electronic structure. EELS is widely applied combining with transmission electron microscopes with high spatial resolution, but its interpretation is a challenging task. One of the reasons is that the factors affecting EELS are very complicated. In this paper, we focus on several factors involved in density functional theory calculations. The sensitivity of calculated energy‐loss near‐edge structure to spin order, lattice compression and expansion, and on‐site Coulomb energy is discussed. Since EELS technique detects the local environment of atoms, the influence of spin order cannot be ignored. The chemical shift and peak intensity of EELS are also closely related to corresponding lattice parameters. The correlation effects are very important for transition metal compounds and play a key role in EELS simulations. Our work helps to understand how these factors affect EELS and to explain and predict the experimental EELS spectra. Through the discussion on these factors, we provide a useful guidance for more precise EELS simulations.
This paper proposes a tunable multiple-passband microwave photonic filter (MPF) that is incorporated with an injection-locked Fabry-Pérot (FP) laser. In the proposed MPF, multiple passbands can be ...easily generated based on the frequency-selection effects of the laser structure in the case of multiple light waves injection. The novelty here is that the obtained multiple-passband MPF can achieve either a dual-passband or a single-passband by using merely one experimental scheme. Moreover, since the laser injection ratio of the proposed scheme is high, the central frequency of each passband has a large tunable range. More tunable passbands can be generated by employing more external wavelengths. By fine-detuning the injection parameters, the frequency tuning range of 17 GHz and the out-of-band rejection ratio of 24.1 dB are achieved for the dual-passband MPF, and the out-of-band rejection ratio of 22 dB and the 3-dB bandwidth of 360 MHz are achieved for the single-passband MPF. In addition, the attained peak power and bandwidth of the proposed MPF are investigated with respect to the injection parameters, including detuning frequency, injection ratio and bias current of FP laser. The stability and dynamic range of the MPF are also evaluated through experiments.
The monitoring of harmful phytoplankton is very important for the maintenance of the aquatic ecological environment. Traditional algae monitoring methods require professionals with substantial ...experience in algae species, which are time-consuming, expensive, and limited in practice. The automatic classification of algae cell images and the identification of harmful phytoplankton images were realized by the combination of multiple convolutional neural networks (CNNs) and deep learning techniques based on transfer learning in this work. Eleven common harmful and 31 harmless phytoplankton genera were collected as input samples; the five CNNs classification models of AlexNet, VGG16, GoogLeNet, ResNet50, and MobileNetV2 were fine-tuned to automatically classify phytoplankton images; and the average accuracy was improved 11.9% when compared to models without fine-tuning. In order to monitor harmful phytoplankton which can cause red tides or produce toxins severely polluting drinking water, a new identification method of harmful phytoplankton which combines the recognition results of five CNN models was proposed, and the recall rate reached 98.0%. The experimental results validate that the recognition performance of harmful phytoplankton could be significantly improved by transfer learning, and the proposed identification method is effective in the preliminary screening of harmful phytoplankton and greatly reduces the workload of professional personnel.
With the explosive growth of data, tensor processing has emerged as a pivotal component of the next generation of artificial intelligence (AI) algorithms. Current photonic convolutional processors ...transform tensor convolutions into multi-channel general matrix multiplication (GeMM), which follows the path of electronic counterparts, leading to data replication and hardware complexity. In this study, we experimentally and theoretically demonstrate a photonic tensor processing unit (PTPU) with a single modulator, which offers a more concise approach for multi-channel standard tensor convolution processing, different from the channel-wise convolution method. By executing multi-tensor parallel computing instead of multi-channel parallel computing, PTPU can directly produce feature tensors without clock synchronization and delay compensation between multiple channels and allows more release of physical hardware resources. Furthermore, an integrated array of semiconductor optical amplifiers (SOAs) are used to be photonic synapses for programmable weight bank, demonstrating record-high precision of 9.2 bits for weights. In the proof-of-concept experiment, we extracted features from a 3-channel (RGB) image in horizontal and vertical directions, using integrated multi-wavelength photonic tensor kernels. We then built a 3D convolutional neural network to predict the presence of COVID-19 based on computer tomography (CT) scan data consisting of 64-channel tensors.
Xanthate-mediated reversible addition–fragmentation chain transfer (RAFT) methodologies have been applicable to preparation of branched or star polymers. In this article, novel star copolymers have ...been synthesized through xanthate-mediated RAFT polymerization with p-acetoxystyrene and tert-butyl acrylate. Fourier transfer infrared, nuclear magnetic resonance spectra, and gas chromatography analyses indicated that the polymerization was successful between both of the monomers and the star RAFT agent. The intrinsic viscosity and Zimm branching factor (g′) were used to confirm the copolymers’ architecture. The ultraviolet absorbance of the copolymer solutions indicated that the copolymer was suitable for use as a krypton fluoride (KrF) laser photoresist. Moreover, the photolithography performance of the positive-tone chemically amplified photoresist was evaluated. The results indicated that the photosensitive based on the star copolymer was higher than the linear one, and the pattern resolution was around 200 nm at a low exposure energy.
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