Failure Mechanism of Foam Concrete with C-Channel Embedment

[EN] Forty-eight tests have been carried out to find of the failure mode of a new type of the foam concrete using C-Channels as embedements. Four groups of foam concrete specimens with various embedment depths of the steel in the concrete. The modes of failure of this new type of structure are summarized, which include the independent failure of the C-Channels with and without a concrete block inside the channel as well as the combined failure of the two channels, and the failure of the extrusion block. It is concluded that the failure involves independent slippage between two C-Channels, and the steel and the foam concrete blocks inside the C-Channels.The authors gratefully acknowledge funding from the National Natural Science Foundation of China. Project name: Failure mechanism research for lightweight steel and foam concrete composite structure Approval number: 51378238.Liu, D.; Wang, F.; Fu, F. (2018). Failure Mechanism of Foam Concrete with C-Channel Embedment. En Proceedings of the 12th International Conference on Advances in Steel-Concrete Composite Structures. ASCCS 2018. Editorial Universitat Politècnica de València. 675-681. https://doi.org/10.4995/ASCCS2018.2018.8367OCS67568

An Anatomy-aware Framework for Automatic Segmentation of Parotid Tumor from Multimodal MRI

Magnetic Resonance Imaging (MRI) plays an important role in diagnosing the parotid tumor, where accurate segmentation of tumors is highly desired for determining appropriate treatment plans and avoiding unnecessary surgery. However, the task remains nontrivial and challenging due to ambiguous boundaries and various sizes of the tumor, as well as the presence of a large number of anatomical structures around the parotid gland that are similar to the tumor. To overcome these problems, we propose a novel anatomy-aware framework for automatic segmentation of parotid tumors from multimodal MRI. First, a Transformer-based multimodal fusion network PT-Net is proposed in this paper. The encoder of PT-Net extracts and fuses contextual information from three modalities of MRI from coarse to fine, to obtain cross-modality and multi-scale tumor information. The decoder stacks the feature maps of different modalities and calibrates the multimodal information using the channel attention mechanism. Second, considering that the segmentation model is prone to be disturbed by similar anatomical structures and make wrong predictions, we design anatomy-aware loss. By calculating the distance between the activation regions of the prediction segmentation and the ground truth, our loss function forces the model to distinguish similar anatomical structures with the tumor and make correct predictions. Extensive experiments with MRI scans of the parotid tumor showed that our PT-Net achieved higher segmentation accuracy than existing networks. The anatomy-aware loss outperformed state-of-the-art loss functions for parotid tumor segmentation. Our framework can potentially improve the quality of preoperative diagnosis and surgery planning of parotid tumors.Comment: under revie

Segmentation of Parotid Gland Tumors Using Multimodal MRI and Contrastive Learning

Parotid gland tumor is a common type of head and neck tumor. Segmentation of the parotid glands and tumors by MR images is important for the treatment of parotid gland tumors. However, segmentation of the parotid glands is particularly challenging due to their variable shape and low contrast with surrounding structures. Recently deep learning has developed rapidly, which can handle complex problems. However, most of the current deep learning methods for processing medical images are still based on supervised learning. Compared with natural images, medical images are difficult to acquire and costly to label. Contrastive learning, as an unsupervised learning method, can more effectively utilize unlabeled medical images. In this paper, we used a Transformer-based contrastive learning method and innovatively trained the contrastive learning network with transfer learning. Then, the output model was transferred to the downstream parotid segmentation task, which improved the performance of the parotid segmentation model on the test set. The improved DSC was 89.60%, MPA was 99.36%, MIoU was 85.11%, and HD was 2.98. All four metrics showed significant improvement compared to the results of using a supervised learning model as a pre-trained model for the parotid segmentation network. In addition, we found that the improvement of the segmentation network by the contrastive learning model was mainly in the encoder part, so this paper also tried to build a contrastive learning network for the decoder part and discussed the problems encountered in the process of building

Parotid Gland MRI Segmentation Based on Swin-Unet and Multimodal Images

Parotid gland tumors account for approximately 2% to 10% of head and neck tumors. Preoperative tumor localization, differential diagnosis, and subsequent selection of appropriate treatment for parotid gland tumors is critical. However, the relative rarity of these tumors and the highly dispersed tissue types have left an unmet need for a subtle differential diagnosis of such neoplastic lesions based on preoperative radiomics. Recently, deep learning methods have developed rapidly, especially Transformer beats the traditional convolutional neural network in computer vision. Many new Transformer-based networks have been proposed for computer vision tasks. In this study, multicenter multimodal parotid gland MRI images were collected. The Swin-Unet which was based on Transformer was used. MRI images of STIR, T1 and T2 modalities were combined into a three-channel data to train the network. We achieved segmentation of the region of interest for parotid gland and tumor. The DSC of the model on the test set was 88.63%, MPA was 99.31%, MIoU was 83.99%, and HD was 3.04. Then a series of comparison experiments were designed in this paper to further validate the segmentation performance of the algorithm

Fully Microstrip Three-Port Circuit Bandpass NGD Design and Test

International audienceAn innovative design and test of three-port distributed circuit exhibiting double bandpass (BP) negative group delay (NGD) effect is investigated. The distributed topology is constituted by resistive transmission lines (TLs) with one input and two output accesses. The BP-NGD specifications are defined. The transfer matrix-based modelling is elaborated. The doublebranch NGD theorization is based on the equivalent model of voltage transfer function (VTF) between Port1-Port2 and Port1-Port3. The VTF analytical expressions in function of TL parameters are formulated. Group delay (GD) innovative formulas are derived. The feasibility study is based on the BP-NGD design of 3-port hybrid microstrip prototype implemented on Rogers Duroid-AD1000 dielectric substrate. To validate the concept, the VTF magnitudes and GDs computed with MATLAB® are compared with commercial tool simulation and experimental results. The modelled, simulated and measured three-port circuit results show NGD responses in very good agreement. It was emphasized that the two transmission ways of the tested circuit operate with BP-NGD behavior confirmation. The measured NGD value and bandwidth of about-3.8 ns and 75 MHz at center frequency of about 0.74 GHz are obtained

0IO-Shape PCB Trace Negative Group-Delay Analysis

International audienceThis paper elaborates a negative group delay (NGD) analysis of 0IO-shape printed circuit board (PCB) traces. This circuit topology is originally implemented with a tri-coupled line (3CL) six-port element with the lateral side connected through lossy transmission lines (TLs). After description of the electrical equivalent diagram, the S-matrix model is established. The group delay (GD) is formulated from the transmission coefficient as a function of the 0IO topological parameters. The effectiveness of the GD modelling is verified with a microstrip circuit proof-of-concept (POC). Simulations and measurements, which are in good agreement, confirm the dual-band bandpass NGD behavior of the 0IO POC. The fabricated prototype generates NGD levels better than −1 ns at NGD center frequencies of about 2.2 GHz and 3 GHz. In addition, to this good NGD performance, the 0IO POC operates with a low insertion loss better than 2.5 dB and reflection losses better than 12 dB in the NGD bandwidths. INDEX TERMS Microwave theory, distributed topology, negative group delay (NGD), tri-coupled line (3CL), modeling

Design and Synthesis of Inductorless Passive Cell Operating as Stop-Band Negative Group Delay Function

International audienceThis paper develops an original circuit theory of unfamiliar stop-band (SB) negative group delay (NGD) topology. The proposed NGD topology is implemented without inductor component. The developed theory is established with passive cell constituted by RC-network based high-pass (HP) and low-pass (LP) NGD composite circuits. The analytical investigation of the SB-NGD circuit is introduced from the elaboration of voltage transfer function (VTF). The canonical form enabling to identify SB-NGD circuit is analytically expressed. The different SB-NGD characteristics as GD value, and, center and cutoff frequencies are innovatively formulated in function of the circuit resistor and capacitor components. The existence condition of SB-NGD function is also established. The inductorless SB-NGD topology is validated by a proof-of-concept (POC) circuit implemented by surface-mounted-device (SMD) component based printed circuit board (PCB). The measured VTF magnitude and group delay (GD) are extracted from the experimented S-parameters. A good agreement between the calculated, simulated and measured results is obtained. The SB-NGD behavior has measured center frequency of about 32 MHz. The lower-and upper-NGD cutoff frequencies are about 9.15 MHz and 98.3 MHz. The optimal NGD values at low and higher frequencies are −3.25 ns and −56 ps. INDEX TERMS Circuit theory, negative group delay (NGD), stop-band (SB) NGD function, passive cell, inductorless topology

Molecular mechanism of resveratrol promoting differentiation of preosteoblastic MC3T3-E1 cells based on network pharmacology and experimental validation

Abstract The purpose of this study was to investigate the mechanism by which resveratrol (Res) inhibits apoptosis and promotes proliferation and differentiation of pre-osteoblastic MC3T3-E1 cells, laying the groundwork for the treatment of osteoporosis (OP). The TCMSP database was used to find the gene targets for Res. The GeneCards database acquire the gene targets for OP. After discovering the potential target genes, GO, KEGG, and Reactome enrichment analysis were conducted. Verifying the major proteins involved in apoptosis can bind to Res using molecular docking. CCK8 measured the proliferative activity of mouse pre-osteoblasts in every group following Res intervention. Alkaline phosphatase staining (ALP) and alizarin red staining to measure the ability of osteogenic differentiation. RT-qPCR to determine the expression levels of Runx2 and OPG genes for osteogenic differentiation ability of cells. Western blot to measure the degree of apoptosis-related protein activity in each group following Res intervention. The biological processes investigated for GO of Res therapeutic OP involved in cytokine-mediated signaling pathway, negative regulation of apoptotic process, Aging, extrinsic apoptotic signaling pathway in absence of ligand, according to potential therapeutic target enrichment study. Apoptosis, FoxO signaling pathway, and TNF signaling pathway are the primary KEGG signaling pathways. Recactome pathways are primarily engaged in Programmed Cell Death, Apoptosis, Intrinsic Apoptotic Pathway, and Caspase activation via extrinsic apoptotic signaling pathways. This research established a new approach for Res treatment of OP by demonstrating how Res controls the apoptosis-related proteins TNF, IL6, and CASP3 to suppress osteoblast death and increase osteoclastogenesis

Suitability of passive RC-network-based inductorless bridged-T as a bandpass NGD circuit

International audiencePurpose The purpose of this paper is to study, a bridged-T topology with inductorless passive network used as a bandpass (BP) negative group delay (NGD) function. Design/methodology/approach The BP NGD topology under study is composed of an inductorless passive resistive capacitive network. The circuit analysis is elaborated from the equivalent impedance matrix. Then, the analytical model of the C-shunt bridged-T topology voltage transfer function is established. The BP NGD analysis of the considered topology is developed in function of the bridged-T parameters. The NGD properties and characterizations of the proposed topology are analytically expressed. Moreover, the relevance of the BP NGD theory is verified with the design and fabrication of surface mounted device components-based proof-of-concept (PoC). Findings From measurement results, the BP NGD network with −151 ns at the center frequency of 1 MHz over −6.6 dB attenuation is in very good agreement with the C-shunt bridged-T PoC. Originality/value This paper develops a mathematical modeling theory and measurement of a C-shunt bridged-T network circuit

Whole chloroplast genome sequence of a subtropical tree Eriobotrya bengalensis (Rosaceae)

Eriobotrya bengalensis (Roxb.) is a subtropical plant under the family Rosaceae with high economic and medicinal value. The whole chloroplast genome of E. bengalensis was sequenced to better understand its phylogenetic position relative to other Rosaceae species. The total length of the E. bengalensis chloroplast genome was 159,270 bp, which was composed of a large single-copy (LSC) region of 87,362 bp, a small single-copy (SSC) region of 19,184 bp, and a pair of inverted repeats (IRs) with a length of 26,362 bp separated by LSC and SSC. The total G + C content of the whole chloroplast genome was 36.7%. Phylogenetic analysis of maximum likelihood (TVM + F+R2) was completed using 15 complete chloroplast genomes of Rosaceae species. The results of phylogenetic analysis show that sisterhood exists in E. bengalensis with nine other species of Eriobotrya