Bridge Method Research Articles

LSPpred Suite: Tools for Leaderless Secretory Protein Prediction in Plants.

Plant proteins that are secreted without a classical signal peptide leader sequence are termed leaderless secretory proteins (LSPs) and are implicated in both plant development and (a)biotic stress responses. In plant proteomics experimental workflows, identification of LSPs is hindered by the possibility of contamination from other subcellar compartments upon purification of the secretome. Applying machine learning algorithms to predict LSPs in plants is also challenging due to the rarity of experimentally validated examples for training purposes. This work attempts to address this issue by establishing criteria for identifying potential plant LSPs based on experimental observations and training random forest classifiers on the putative datasets. The resultant plant protein database LSPDB and bioinformatic prediction tools LSPpred and SPLpred are available at lsppred.lspdb.org. The LSPpred and SPLpred modules are internally validated on the training dataset, with false positives controlled at 5%, and are also able to classify the limited number of established plant LSPs (SPLpred (3/4, LSPpred 4/4). Until such time as a larger set of bona fide (independently experimentally validated) LSPs is established using imaging technologies (light/fluorescence/electron microscopy) to confirm sub-cellular location, these tools represent a bridging method for predicting and identifying plant putative LSPs for subsequent experimental validation.

Enhancing Fire Resilience of Cable-Supported Bridges: Current Knowledge and Research Gaps

Fires are increasingly recognized as one of the major hazards causing damage to bridges and disruption in their operational continuity. As a transportation hub, cable-supported bridges are particularly critical to social sustainability and economic development. However, ensuring the resilience of cable-supported bridges in unexpected fire events has arisen as a challenge in recent years due to the lack of available standards and guidance for practitioners. In this context, this paper presents an up-to-date review of the fire resilience enhancement methods for cable-supported bridges and proposes research needs for impending decades. Representative fire incidents and the concerns of bridge managers are analyzed to define the critical fire scenarios that need to be considered in future fire-resistant designs. The fire performance of cable-supported bridges whose cables, girders, and pylons are exposed to fires are analyzed respectively. To enhance the fire resilience of cable-supported bridges, this paper compiles probabilistic methods, including fire risk evaluation and mitigation based on identified vulnerable bridges, and deterministic methods, including active and passive fire protection measures. This paper reveals that guidance on the fire resilience of cable-supported bridges should be further improved with regard to aspects including the fire performance of cable systems, the ability of cable-supported bridges to provide continued service in fires, risk- and cost–benefit-based fire resistance design, multi-level fire damage determination, and emergency response strategies.

Lignin-based polymer with high phenolic hydroxyl group content prepared by the alkyl chain bridging method and applied as a dopant of PEDOT

Lignin-based polymer with high phenolic hydroxyl group content prepared by the alkyl chain bridging method and applied as a dopant of PEDOT

Research on BIM Model Decomposition, Component Hierarchy, and Structural Organization Methods of Highway Conventional Bridges

Research on BIM Model Decomposition, Component Hierarchy, and Structural Organization Methods of Highway Conventional Bridges

Critical data modeling and the basic representation model

AbstractThe increasing role and impact of information systems in modern life calls for new types of information studies that examine sociotechnical factors at play in the development and use of information systems. This article proposes critical data modeling—the use of data modeling and systems analysis techniques to build critical interrogations of information systems—as a method for bridging between social factors and technical systems, presents the Basic Representation Model as an analytical tool for critical data modeling, and discusses the results of critical data modeling of a police arrest record dataset. The Basic Representation Model is a conceptual model of information objects that supports a detailed examination of data modeling and information representation within and across information systems, and functions as a synthesizing concept for existing critical work on information systems. Critical data modeling adds an essential complement to existing approaches to critical information studies by grounding the analysis of an information system in both the technical realities of computational systems and the social realities of our communities.

Point Cloud Registration Methods for Long-Span Bridge Spatial Deformation Monitoring Using Terrestrial Laser Scanning

In recent years, efforts have been devoted to utilizing terrestrial laser scanning for bridge spatial performance inspection, but they are still restricted to small or medium-span bridges, like some historical heritages. Due to the large-scale dimensional features of long-span bridges, applications of 3D point cloud techniques still remain challenging, such as the extra-long scan range and extreme-small incidence angle when scanning a bridge with a span over 1000 m. Moreover, rare attempts can be found for the performance evaluation of point cloud registration methods for long-span bridges as well, which is a critical basis for further spatial deformation recognition on the point cloud data. Hence, in this study, a cross-evaluation of three iterative closest point (ICP) registration methods is conducted for long-span suspension bridges, namely, traditional ICP, kd-tree-based ICP, and feature point-based ICP algorithms. We conducted field laser scanning on the Ma’anshan Yangtze Bridge, an 1880 m long suspension bridge located in China. The results show that the feature point-based ICP algorithm outperforms the other two in terms of convergence rate and execution time for a single iteration due to the smaller number of registration points compared to the other two algorithms. Moreover, it also gives more precise values in terms of bridge tower spatial deformation identification. Meanwhile, due to efficient data organization, the kd-tree-based ICP algorithm takes less time for a single iteration than the traditional ICP algorithm. Finally, two suggestions for algorithm improvement in terms of efficiency optimization and accuracy improvement of long-span bridge deformation analysis are proposed based on the assessment results.

Neoadjuvant programmed cell death 1 inhibitor before liver transplantation for HCC is not associated with increased graft loss.

Immune checkpoint inhibitors (ICIs) may lead to rejection and even graft loss of solid organ transplant recipients, making them not widely used in transplant patients. There is insufficient clinical experience in using ICIs as a bridging or downstaging therapy before transplantation. We performed a retrospective review of patients receiving programmed cell death 1 inhibitor (PD1) before liver transplantation for HCC in our center and analyzed the data of these patients with the purpose of investigating the safety and feasibility of preoperative PD1 inhibitor among liver transplant recipients and exploring the preoperative correlation ICIs and the postoperative risk of rejection and immune-related graft loss. A total of 16 patients enrolled in this study. Acute rejection occurred in 9 patients, with an incidence of 56.3%. The median time of rejection was 7 days after surgery. The median FK506 concentration at the time of rejection was 7.1μg/L. All rejection reactions were reversed after adjusting the immunosuppression regimen. The interval between the last PD1 inhibitor and transplantation in the rejection group was shorter than that in the nonrejection group, and there was a statistical difference [21.0 (15.5-27.5) days vs. 60.0 (34.0-167.0) days, p =0.01]. In conclusion, PD1 inhibitor is a safe and feasible method for bridging or downstaging treatment before liver transplantation. Although preoperative PD1 inhibitor may increase the incidence of postoperative rejection, it is not associated with increased immune-related graft loss and patient death.

Prediction of Composite Mechanical Properties: Integration of Deep Neural Network Methods and Finite Element Analysis

Extracting the mechanical properties of a composite hydrogel; e.g., bioglass (BG)–collagen (COL), is often difficult due to the complexity of the experimental procedure. BGs could be embedded in the COL and thereby improve the mechanical properties of COL for bone tissue engineering applications. This paper proposed a deep-learning-based approach to extract the mechanical properties of a composite hydrogel directly from the microstructural images. Four datasets of various shapes of BGs (9000 2D images) generated by a finite element analysis showed that the deep neural network (DNN) model could efficiently predict the mechanical properties of the composite hydrogel, including the Young’s modulus and Poisson’s ratio. ResNet and AlexNet architecture were tuned to ensure the excellent performance and high accuracy of the proposed methods with R-values greater than 0.99 and a mean absolute error of the prediction of less than 7%. The results for the full dataset revealed that AlexNet had a better performance than ResNet in predicting the elastic material properties of BGs-COL with R-values of 0.99 and 0.97 compared to 0.97 and 0.96 for the Young’s modulus and Poisson’s ratio, respectively. This work provided bridging methods to combine a finite element analysis and a DNN for applications in diverse fields such as tissue engineering, materials science, and medical engineering.

3D nanopolymerization and damage threshold dependence on laser wavelength and pulse duration

Abstract The dependence of the polymerization and optical damage thresholds in multi-photon polymerization (MPP) lithography was studied using a broadly-tunable laser system with group delay dispersion (GDD) control. The order of non-linearity and the light–matter interaction mechanisms were investigated using the resolution bridges method for non-photosensitized SZ2080TM and photosensitized SZ2080TM + IRG369 prepolymers. Energy deposition, voxel dimension growth, and the size of the dynamic fabrication window (DFW) were measured in the 700–1300 nm wavelength range at three different pulse durations measured at the sample – 100, 200 and 300 fs. Polymerization was observed at all wavelengths and pulse durations without significant differences in the achieved minimal spatial dimension ( < 300 ${< } 300$ nm). This was achieved despite the broad range of excitation wavelengths used which spanned two- and three-photon absorption bands, and the differences in the absorption spectra of the prepolymers. The lateral and longitudinal voxel growth dynamics revealed an abrupt change in the power dependence of polymerization and a significant variation of the DFW – from 1 at 1250 nm to 29 at 700 nm. This result can be interpreted as a consequence of a change in the instantaneous refractive index and a lowering of the polymerization but not the damage threshold. The optimization of energy delivery to the material by a wavelength-tunable laser source with pulse duration control was experimentally validated. These findings are uncovering the complexity of polymerization mechanisms and are useful in further development of MPP technology.

Multi-Lane Traffic Load Clustering Model for Long-Span Bridge Based on Parameter Correlation

Traffic loads are the primary external loads on bridges during their service life. However, an accurate analysis of the long-term effect of the operating traffic load is difficult because of the diversity of traffic flow in terms of vehicle type and intensity. This study established a traffic load simulation method for long-span bridges based on high authenticity traffic monitoring data, and an improved k-means clustering algorithm and Correlated variables Sampling based on Sobol sequence and Copula function (CSSC) sampling method. The monitoring traffic data collected through a weigh-in-motion (WIM) system was processed to generate a multi-lane stochastic traffic flow. The dynamic response of a prototype suspension bridge under a traffic load was analyzed. The results show that the traffic load can be divided into clusters with identical distribution characteristics using a clustering algorithm. Combined with CSSC sampling, the generated traffic flow can effectively represent daily traffic and vehicle characteristics, which improves the accuracy of the assessment of the loads long-term effect. The dynamic response of the bridge to different traffic flows varied significantly. The maximum and minimum vertical displacement of the main girder was 0.404 m and 0.27 m, respectively. The maximum and minimum bending stresses of the short suspender were 50.676 MPa and 28.206 MPa, respectively. The maximum equivalent bending stress and axial stress were 16.068 MPa and 10.542 MPa, respectively, whereas the minimum values were 9.429 MPa and 8.679 MPa, respectively. These differences directly influence the short and long-term evaluation of bridge components. For an accurate evaluation of the bridge operation performance, the traffic flow density must be considered.

Time-dependent reliability calculation method of RC bridges based on the dual neural network

Time-dependent reliability calculation method of RC bridges based on the dual neural network

Direct Extracorporeal Membrane Oxygenation Bridged Heart Transplantation: The Importance of Multi-Organ Failure.

Recently, approximately 40% of all heart transplantation (HTx) in South Korea are performed using the direct extracorporeal membrane oxygenation (ECMO) bridging method. We conducted a study to examine the clinical outcome of direct ECMO-bridged HTx and to investigate the impact of multi-organ failure (MOF). From June 2014 to September 2022, a total of 96 adult patients who underwent isolated HTx at a single tertiary hospital were included in the study. The patients were sub-grouped into ECMO (n=48) and non-ECMO group (n=48), and the ECMO group was subdivided into awake (n=22) and non-awake (n=26) groups based on mechanical ventilator (MV) dependency. Baseline characteristics, 30-day, and 1-year mortality were analyzed retrospectively. The 1-year survival rate was significantly lower in the ECMO group (72.9% vs. 95.8%, p=0.002). There was a significant difference in the 30-day survival rate between the awake and non-awake ECMO groups (81.8% vs. 65.4%, p=0.032). In the univariate analysis of logistic regression for 1-year mortality, the odds ratio was 8.5 for ECMO bridged HTx compared to the non-ECMO group, 12.3 in patients who required MV (p=0.003), and 23 with additional hemodialysis (p<0.001). Patients who required MV in ECMO bridged HTx showed higher preoperative MOF rates and early mortality than those extubated. When considering ECMO bridged HTx, the severity of MOF should be thoroughly investigated, and careful patient selection is necessary.

A Stress Index-based Tendon Optimization Method for Prestressed Concrete Continuous Girder Bridges

PDF HTML XML Export Cite reminder A Stress Index-based Tendon Optimization Method for Prestressed Concrete Continuous Girder Bridges DOI: 10.59238/j.pt.2023.01.001 Author: Affiliation: (1. Department of Bridge Engineering, Tongji University, Shanghai 200092, China; 2. Anhui Transport consulting & Design Institute Co., Ltd. Anhui 230088, China) Clc Number: Fund Project: Article | Figures | Metrics | Reference | Related | Cited by | Materials | Comments Abstract:Traditional tendon design methods for prestressed concrete (PC) continuous girder bridges are tedious since they obtain feasible solutions based on trial calculation, and the existing optimization methods that can obtain the optimal solution have deficiencies regarding structural stress. In this study, based on research on the refined bridge design conducted in the Department of Bridge Engineering at Tongji University in recent years, a stress index-based tendon optimization method for PC continuous girder bridges is pro-posed. First, various tendon layouts are summarized, and a reasonable tendon layout is selected. Then, a mathematical tendon optimization model is established. After meeting the specifications and construction feasibility requirements, a genetic algorithm is used to find the optimal solution. This method not only realizes tendon forward design but also obtains a satisfactory solution. Finally, this method is used to successfully optimize the tendons of a three-span PC continuous girder bridge, which verifies the ration-ality of the method. Reference Related Cited by

Investigation on Distributed Vibration Damping of Bridge Based on Energy Harvesting Technique and Finite Element Analysis

Based on the vibration control method and energy harvesting principle in the bridge field, this paper proposes a distributed vibration reduction and energy harvesting method for bridges. Firstly, the analytical solutions of the induced electromotive force, output power and magnetic damping generated by a coil in a magnetic field were deduced through an electromagnetic theory analysis. In addition, the structural vibration equation under the magnetic damping was deduced. Then, a new method of joint simulation and modeling analysis of vibration and energy output was proposed. Finally, the structural vibration reduction and energy output power were analyzed and calculated. The main research results are as follows: by calculating the instantaneous power of the energy collection of the designed circuit, the average instantaneous power collected by the design method is 1.093 × 10−9 W; the initial vibration signal of the target node is obtained through analysis, and the vibration signal of the node before and after applying the electromagnetic damping force is transformed. For the energy analysis, the energy of the acceleration curve before and after the node was calculated to be 3.1048 × 108 and 3.1044 × 108, respectively, and the reduction rate of the node vibration energy was 0.01% and 0.02%, respectively. Thus, the feasibility and vibration reduction effect of the designed bridge distributed vibration reduction and energy harvesting method is verified when the electromagnetic damping force is small. This method can provide new ideas for bridge structure vibration reduction and energy harvesting research and is of great significance to the infrastructure construction and utilization of renewable energy.

Hybrid Swarm Intelligence Optimization Methods for Low-Embodied Energy Steel-Concrete Composite Bridges

Bridge optimization is a significant challenge, given the huge number of possible configurations of the problem. Embodied energy and cost were taken as objective functions for a box-girder steel–concrete optimization problem considering both as single-objective. Embodied energy was chosen as a sustainable criterion to compare the results with cost. The stochastic global search TAMO algorithm, the swarm intelligence cuckoo search (CS), and sine cosine algorithms (SCA) were used to achieve this goal. To allow the SCA and SC techniques to solve the discrete bridge optimization problem, the discretization technique applying the k-means clustering technique was used. As a result, SC was found to produce objective energy function values comparable to TAMO while reducing the computation time by 25.79%. In addition, the cost optimization and embodied energy analysis revealed that each euro saved using metaheuristic methodologies decreased the energy consumption for this optimization problem by 0.584 kW·h. Additionally, by including cells in the upper and lower parts of the webs, the behavior of the section was improved, as were the optimization outcomes for the two optimization objectives. This study concludes that double composite action design on supports makes the continuous longitudinal stiffeners in the bottom flange unnecessary.

Seismic Damage Identification of Composite Cable-Stayed Bridges Using Support Vector Machines and Wavelet Networks

A seismic damage identification method for composite cable-stayed bridges has been developed. The proposed method is based on a Support Vector Machine (SVM) and Wavelet Network (WN). A shaking table test of a composite cable-stayed bridge is employed to verify the identification accuracy of the WNSVM method; the test results show that the nonlinear Finite Element Model (FEM) can correctly simulate the single-tower cable-stayed bridge, and the learning samples of WNSVM can be produced based on the nonlinear FEM. The structural damage results identified by the WNSVM method are in good agreement with those obtained by the shaking table test, and the maximum error is less than 8%. Therefore, the WNSVM method can be used for the seismic damage identification of composite cable-stayed bridges.

Multiscale bridging method to characterize elasto-plastic properties of polymer nanocomposites

A multiscale bridging method is proposed to describe the elasto-plastic behavior of polymer nanocomposites affected with the interphase elasto-plastic constitutive law (near the nanoparticle). The inverse characterization method of the interphase elasto–plastic constitutive law was proposed by combining full atomistic molecular dynamics and finite element homogenization. Based on the proposed multiscale bridging method, the influences of the crosslink ratio of the epoxy network and radius of nanoparticles on the elasto-plastic behavior of the interphase were investigated. Additionally, a multiscale homogenization analysis of the representative volume element of the multi-particulate systems was conducted using the elasto–plastic constitutive law of interphase.

Digital twin-based life-cycle seismic performance assessment of a long-span cable-stayed bridge

Long-span cable-stayed bridges often have a design service life of more than a hundred years, during which they may experience multiple earthquake events and accumulate seismic damage if they are located in seismic-prone regions. Earthquake occurrence is discretely and randomly distributed over the life cycle of a long-span cable-stayed bridge and often causes sudden drops in the structural performance instead of yearly fixed seismic performance degradation. This study thus proposes a digital twin-based life-cycle seismic performance assessment method for long-span cable-stayed bridges. The major components of this method include: (1) a seismic hazard analysis-based generation method of earthquake occurrence sequence; (2) a digital twin-based structural response prediction method considering lifetime earthquake occurrence and sequence; and (3) a service life quantification method. The proposed method is applied to a scaled long-span cable-stayed bridge with a series of shake table tests. The results show that the digital twin can closely reproduce the life-cycle seismic response of the bridge under sequential earthquakes. The proposed assessment method provides a more intuitive presentation of the life-cycle seismic damage accumulation process and a more accurate estimation of the service life of a long-span cable-stayed bridge.

3D Gelatin Microsphere Scaffolds Promote Functional Recovery after Spinal Cord Hemisection in Rats.

Spinal cord injury (SCI) damages signal connections and conductions, with the result that neuronal circuits are disrupted leading to neural dysfunctions. Such injuries represent a serious and relatively common central nervous system condition and current treatments have limited success in the reconstruction of nerve connections in injured areas, especially where sizeable gaps are present. Biomaterial scaffolds have become an effective alternative to nerve transplantation in filling these gaps and provide the foundation for simulating the 3D structure of solid organs. However, there remain some limitations with the application of 3D bioprinting for preparation of biomaterial scaffolds. Here, the approach in constructing and testing mini-tissue building blocks and self-assembly, solid 3D gelatin microsphere (GM) scaffolds with multiple voids as based on the convenient preparation of gelatin microspheres by microfluidic devices is described. These 3D GM scaffolds demonstrate suitable biocompatibility, biodegradation, porosity, low preparation costs, and relative ease of production. Moreover, 3D GM scaffolds can effectively bridge injury gaps, establish nerve connections and signal transductions, mitigate inflammatory microenvironments, and reduce glial scar formation. Accordingly, these 3D GM scaffolds can serve as a novel and effective bridging method to promote nerve regeneration and reconstruction and thus recovery of nerve function after SCI.

High-Content RNAi Phenotypic Screening Unveils the Involvement of Human Ubiquitin-Related Enzymes in Late Cytokinesis

CEP55 is a central regulator of late cytokinesis and is overexpressed in numerous cancers. Its post-translationally controlled recruitment to the midbody is crucial to the structural coordination of the abscission sequence. Our recent evidence that CEP55 contains two ubiquitin-binding domains was the first structural and functional link between ubiquitin signaling and ESCRT-mediated severing of the intercellular bridge. So far, high-content screens focusing on cytokinesis have used multinucleation as the endpoint readout. Here, we report an automated image-based detection method of intercellular bridges, which we applied to further our understanding of late cytokinetic signaling by performing an RNAi screen of ubiquitin ligases and deubiquitinases. A secondary validation confirmed four candidate genes, i.e., LNX2, NEURL, UCHL1 and RNF157, whose downregulation variably affects interconnected phenotypes related to CEP55 and its UBDs, as follows: decreased recruitment of CEP55 to the midbody, increased number of midbody remnants per cell, and increased frequency of intercellular bridges or multinucleation events. This brings into question the Notch-dependent or independent contributions of LNX2 and NEURL proteins to late cytokinesis. Similarly, the role of UCHL1 in autophagy could link its function with the fate of midbody remnants. Beyond the biological interest, this high-content screening approach could also be used to isolate anticancer drugs that act by impairing cytokinesis and CEP55 functions.