Longitudinal Response Research Articles

General Solution for Longitudinal Response of Shield Tunnel Considering the Effects of Joints and Soil Shear Resistance

ABSTRACTThis study introduces a general solution for assessing the longitudinal response of shield tunnels, incorporating the combined effects of joints and soil shear resistance. The analysis employs the Timoshenko beam spring model atop a Vlasov foundation, subjected to arbitrary loads and various boundary conditions. Governing equations and relevant boundary conditions are derived using a variational formulation. Validation is conducted against existing simplified analytical solutions and finite element method simulations, showing the efficacy of the proposed solution. Comparative analyses of different models are undertaken based on the potential energy considerations. Additionally, a parametric study explores influential factors such as subgrade shear and reaction coefficients, as well as joint stiffnesses. Findings highlight the significance of accounting for the soil shear resistance and caution against underestimation when using equivalent continuous beam models. The proposed solution improves the prediction accuracy for the longitudinal response of shield tunnels and offers several benefits including compatibility with other analytical models, computation efficiency, and versatility in considering diverse loads and boundary conditions.

Regulating interlayer charge transfer in MoS2 via in-situ loading of Pd-metallene to enhance piezo-catalytic degradation efficiency: Contributions of low free energy

Molybdenum disulfide (MoS2) is a promising piezoelectric catalytic material that has garnered considerable research attention. However, its application in the water treatment field is hindered by electron/hole recombination, leading to relatively low piezoelectric efficiency. This study proposes a strategy of establishing interlayer electron bridges by anchoring Palladium metallene (Pd-ene) with ultra-high conductivity and high longitudinal strain response into MoS2, aiming to accelerate carrier migration. The Pd-ene/MoS2-3 catalyst exhibited outstanding piezoelectric catalytic activity, achieving a tetracycline degradation efficiency of 96.51 % and a Cr6+ reduction efficiency of 90.45 % within 30 min. PFM and d33 measurements indicated that the piezoelectric response signal and piezoelectric coefficient were 2.17 times and 6.4 times higher, respectively, compared to pure MoS2. Electrochemical tests revealed that the improved piezoelectric performance is primarily due to enhanced transient piezoelectric current response, reaching 5.9 mA/cm2. The presence of Pd-ene significantly boosts the catalyst’s performance in terms of current density, electrochemically active surface area, and impedance when compared to MoS2 alone. Notably, the theory calculations and quantitative experiments on radicals showed a reduction in the band gap width from 2.62 eV to 1.31 eV, creating favorable conditions for lowering the system’s free energy and facilitating the formation of H2O2. Among them, the free energy of H2O adsorption, dissociation to 2OH*, deprotolation to 2O* and desorption to O2 path decreased by 5.21, 4.96, 2.64 and 4.15 eV, respectively. This study presents an innovative strategy for enhancing the piezocatalytic activity of MoS2 and explores the application of metallene in the field of piezoelectronics.

Using Machine Learning for Personalized Prediction of Longitudinal COVID-19 Vaccine Responses in Transplant Recipients

The COVID-19 pandemic has underscored the importance of vaccines, especially for immunocompromised populations like solid organ transplant (SOT) recipients, who often have weaker immune responses. The purpose of this study was to compare deep learning architectures for predicting SARS-CoV-2 vaccine responses 12 months post-vaccination in this high-risk group. Utilizing data from 303 SOT recipients from a Canadian multicenter cohort, models were developed to forecast anti-receptor binding domain (RBD) antibody levels. The study compared traditional machine learning models—logistic regression, epsilon-support vector regression, random forest regressor, and gradient boosting regressor—and deep learning architectures, including long short-term memory (LSTM), recurrent neural networks, and a novel model, routed LSTM. This new model combines capsule networks with LSTM to reduce the need for large datasets. Demographic, clinical, and transplant-specific data, along with longitudinal antibody measurements, were incorporated into the models. The routed LSTM performed best, achieving a mean square error (MSE) of 0.02±0.02 and a Pearson correlation coefficient (PCC) of 0.79±0.24, outperforming all other models. Key factors influencing vaccine response included age, immunosuppression, breakthrough infection, BMI, sex, and transplant type. These findings suggest that AI could be a valuable tool in tailoring vaccine strategies, improving health outcomes for vulnerable transplant recipients.

Improving antibody-mediated protection against HSV infection by eliminating interactions with the viral Fc receptor gE/gI.

Herpes simplex virus (HSV) encodes surface glycoproteins that are host defense evasion molecules, allowing the virus to escape immune clearance. In addition to their role in neuropathogenesis and cell-cell spread, glycoproteins E and I (gE/gI) form a viral Fc receptor (vFcR) for most subclasses and allotypes of human IgG and promote evasion of humoral immune responses. While monoclonal antibodies (mAbs) protect mice from neonatal HSV (nHSV) infections, the impact of the vFcR on mAb-mediated protection by binding to IgG is unknown. Using HSV-1 with intact and ablated gE-mediated IgG Fc binding, and Fc-engineered antibodies with modified ability to interact with gE/gI, we investigated the role of the vFcR in viral pathogenesis and mAb-mediated protection from nHSV. The gD-specific human mAb HSV8 modified to lack binding to gE exhibited enhanced neutralization and in vivo protection compared to its native IgG1 form. This improved protection by the engineered mAbs was dependent on the presence of the vFcR. Human IgG3 allotypes lacking vFcR binding also exhibited enhanced antiviral activity in vivo, suggesting that vaccines that robustly induce IgG3 responses could show enhanced protection. suggesting the value of vaccination strategies that robustly induce this subclass. Lastly, analysis of longitudinal responses to acute primary genital infection in humans raised the possibility that unlike most viruses, HSV may exhibited slow induction of IgG3. In summary, this study demonstrates that mAbs lacking the ability to interact with the vFcR can exhibit improved protection from HSV-offering new prospects for antibody-based interventions.

Incremental Nonlinear Dynamics Inversion Control with Nonlinear Disturbance Observer Augmentation for Flight Dynamics

A flight controller formulation based on incremental nonlinear dynamics inversion (INDI) control with nonlinear disturbance observer (NDO) is proposed. INDI control is a nonlinear controller based on incremental dynamics. Aimed to attain robustness for nonlinear dynamics inversion (NDI)-based controller, incremental dynamics are derived using the first-order Talyor series expansion to nonlinear systems. The incremental dynamics-based controller requires information on state derivative terms to strengthen the robustness property of the nonlinear controller. The proposed controller utilizes the first-order low-pass filter to obtain the state derivative estimate to implement incremental dynamics into the system. Because the incremental form creates uncertainty term which is an aftermath of the Taylor series expansion, the proposed controller adopts the NDO to eliminate this effect. The controller is applied to the generic transport model which was developed by NASA for simulation purposes. The proposed NDO-based INDI control underwent simulations, together with an INDI controller without disturbance observer, and showed that the developed method results in better performances, providing important advantages where it compensates the uncertainties, removes the steady-state error, and shows less oscillating longitudinal body rate response than the baseline controller, desirable for aerodynamics applications with faster system response.

Clinical Subtype Trajectories in Sepsis Patients Admitted to the ICU: A Secondary Analysis of an Observational Study.

Sepsis is an evolving process and proposed subtypes may change over time. We hypothesized that previously established sepsis subtypes are dynamic, prognostic of outcome, and trajectories are associated with host response alterations. A secondary analysis of two observational critically ill sepsis cohorts: the Molecular diAgnosis and Risk stratification of Sepsis (MARS) and the Medical Information Mart for Intensive Care-IV (MIMIC-IV). ICUs in the Netherlands and United States between 2011-2014 and 2008-2019, respectively. Patient admission fulfilling the Sepsis-3 criteria upon ICU admission adjudicated to one of four previously identified subtypes, comprising 2,416 admissions in MARS and 10,745 in MIMIC-IV. Subtype stability and the changes per subtype on days 2, 4 and 7 of ICU admission were assessed. Next, the associated between change in clinical subtype and outcome and host response alterations. In MARS, upon ICU admission, 6% (n = 150) of the patient admissions were α-type, 3% (n = 70) β-type, 55% (n = 1317) γ-type, and 36% (n = 879) δ-type; in MIMIC-IV, this was α = 22% (n = 2398), β = 22% (n = 2365), γ = 31% (n = 3296), and δ = 25% (2686). Overall, prevalence of subtypes was stable over days 2, 4, and 7. However, 28-56% (MARS/MIMIC-IV) changed from α on ICU admission to any of the other subtypes on day 2, 33-71% from β, 57-32% from γ, and 50-48% from δ. On day 4, overall subtype persistence was 33-36%. γ or δ admissions remaining in, or transitioning to, subtype γ on days 2, 4, and 7 exhibited lower mortality rates compared with those remaining in, or transitioning to, subtype δ. Longitudinal host response biomarkers reflecting inflammation, coagulation, and endothelial dysfunction were most altered in the δ-δ group, followed by the γ-δ group, independent of the day or biomarker domain. In two large cohorts, subtype change to δ was associated with worse clinical outcome and more aberrant biomarkers reflecting inflammation, coagulation, and endothelial dysfunction. These findings underscore the importance of monitoring sepsis subtypes and their linked host responses for improved prognostication and personalized treatment strategies.

Kinin B1- and B2-Receptor Subtypes Contract Isolated Bovine Ciliary Muscle: Their Role in Ocular Lens Function and Intraocular Pressure Reduction.

Background: Bradykinin is an endogenously produced nonapeptide with many physiological and pathological functions that are mediated by two pharmacologically defined receptor subtypes, B1- and B2-receptors. Current studies sought to characterize the functional bradykinin (BK) receptors present in freshly isolated bovine ciliary muscle (BCM) using an organ-bath tissue contraction system. Methods: Cumulative longitudinal isometric tension responses of BCM strips (4-5 mm) were recorded before and after the addition of test compounds to BCM strips hooked up to an isometric strain gauge transducer system. Results: BK and its analogs (7-11 concentrations) contracted BCM in a biphasic concentration-dependent manner. The first high affinity/potency phase accounted for 40-60% of the maximal contraction by each of BK (potency, EC50 = 0.9 ± 0.3 nM), Lys-BK (EC50 = 0.7 ± 0.1 nM), Met-Lys-BK (EC50 = 1 ± 0.1 nM), Hyp3-BK (EC50 = 1 ± 0.2 nM), RMP-7 (EC50 = 3.5 ± 0.5 nM), and Des-Arg9-BK (EC50 = 10 ± 0.4nM) (mean ± SEM, n = 3-8). The second lower activity phase of contraction potency values for these peptides ranged between 100 nM and 3 µM. In the presence of a selective B1-receptor antagonist (R715; 0.1-10 µM), the concentration-response curves to Des-Arg9-BK (B1-receptor agonist) were still observed, indicating activation of B2-receptors by this kinin. Likewise, when B2-receptors were completely blocked by using a B2-selective antagonist (WIN-64338; 1-10 µM), BK still induced BCM contraction, now by stimulating B1-receptors. Conclusions: This agonist/antagonist profile of BCM receptors indicated the presence of both B1- and B2-receptor subtypes, both being responsible for contracting this smooth muscle. The BCM kinin receptors may be involved in changing the shape of the ocular lens to influence accommodation, and since the ciliary muscle is attached to the trabecular meshwork through which aqueous humor drains, endogenously released kinins may regulate intraocular pressure.

Joint modelling of longitudinal ordinal and multi-state data.

Joint modeling of longitudinal and survival data is increasingly used in biomedical studies. However, existing joint models are not applicable to model the longitudinal ordinal responses with non-ignorable missing values caused by the occurrence of events in a multi-state process. In this article, we introduce a joint model for longitudinal ordinal measurements and multi-state data. Our proposed joint model consists of two sub-models: a proportional odds sub-model for longitudinal ordinal measurements and a multi-state sub-model with transition-specific proportional hazards for times of transitions between different health states, both linked by shared random effects. The model parameters were estimated employing the maximum likelihood method for a piecewise constant baseline hazard function. The proposed joint model is evaluated in a simulation study and, as an illustration, it is fitted to real data from people with human immunodeficiency virus.

Modeling inclusive electron-nucleus scattering with Bayesian artificial neural networks

We introduce a Bayesian protocol based on artificial neural networks that is suitable for modeling inclusive electron-nucleus scattering on a variety of nuclear targets with quantified uncertainties. Unlike previous applications in the field, which directly parameterize the cross sections, our approach employs artificial neural networks to represent the longitudinal and transverse response functions. In contrast to cross sections, which depend on the incoming energy, scattering angle, and energy transfer, the response functions are determined solely by the energy and momentum transfer to the system, allowing the angular component to be treated analytically. We assess the accuracy and predictive power of our framework against the extensive data in the quasielastic inclusive electron-scattering database. Additionally, we present novel extractions of the longitudinal and transverse response functions and compare them with previous experimental analysis and nuclear ab-initio calculations.

Cooperative Nernst effect of multilayer systems: Parallel circuit model study

Transverse thermoelectric power generation has emerged as a topic of immense interest in recent years owing to the orthogonal geometry which enables better scalability and fabrication of devices. Here, we investigate the thickness dependence of longitudinal and transverse responses in film-substrate systems, i.e., the Seebeck coefficient, the Hall coefficient, the Nernst coefficient, and the anomalous Nernst coefficient in a unified and general manner based on the circuit model, which describes the system as the parallel setup. By solving the parallel circuit model, we show that the transverse responses exhibit a significant peak, indicating the importance of a cooperative effect between the film and the substrate, arising from circulating currents that occur in these multilayer systems in the presence of a temperature gradient. Finally, on the basis of realistic material parameters, we predict that the Nernst effect in bismuth thin films on doped silicon substrates is boosted to unprecedented values if the thickness ratio is tuned accordingly, motivating experimental validation. Published by the American Physical Society 2024

Nonlinear seismic response analysis of long-span railway cable-stayed bridges crossing strike-slip faults

Active faults along railways in the mountainous regions of western China pose significant challenges to bridge safety. To ensure the safe operation of long-span railway bridges under complex geological conditions, this study investigates the synthesis of artificial ground motions for bridges crossing strike-slip faults and analyzes their nonlinear seismic response. First, we develop a theoretical method for simulating high- and low-frequency seismic motions using a finite fault and an equivalent velocity pulse model. Next, using a specific long-span railway cable-stayed bridge as a case study, we construct a nonlinear finite element model with OpenSees software. Finally, we assess the seismic response of key bridge components considering various crossing angles, seismic amplitudes, fault rupture directivity, and fling-step effects. The results show that the crossing angle significantly influences the seismic response, with longitudinal and transverse responses exhibiting opposite patterns. Additionally, the scaling factor of seismic motion significantly affects bridge response. For bridges crossing strike-slip faults, the longitudinal response exhibits a sudden increase in displacement due to instantaneous velocity pulses, while the transverse response shows notable residual displacement influenced by the fling-step effect. However, the critical section curvatures of bridge towers and piers remain within the elastic range across all crossing angles, indicating that controlling large displacement deformations is crucial for the seismic design of bridges crossing strike-slip faults.

Force-extension and longitudinal response of wormlike chains with single cross-link

Certain important biopolymers, such as actin filaments, are known to have cross-links at their interfaces, which significantly influence their mechanical properties. To explore these effects, the force-extension and longitudinal response of wormlike chains (WLCs) with a single cross-link under tension in two-dimension are examined using both analytical methods and Brownian dynamics simulations. The cross-link is modeled as a spring in the analytical method, and mode analysis is used to calculate the path integrals associated with the partition function. These theoretical results are then validated through Brownian dynamics simulations. Final results indicate that the simulation results are consistent with the theoretical predictions, particularly for situations involving large tensile force and short chain, which are prerequisites for the application of the weak bending approximation.

Multi-Objective Optimization Design of a Mooring System Based on the Surrogate Model

As the development of floating offshore wind turbines (FOWTs) progresses from offshore to deeper sea, the demands on mooring systems to ensure the safety of the structure have become increasingly stringent, leading to a concomitant rise in costs. A parameter optimization method for the mooring system of FOWTs is proposed, with the mooring line length and anchor radial spacing as the optimization variables, and the minimization of surge, yaw, and nacelle acceleration as the objectives. A series of mooring system configuration samples are generated by the fully analytical factorial design method, and the open source program OpenFAST is employed to simulate the global responses in the time domain. To enhance the efficiency of the optimization process, a multi-objective evolutionary algorithm, Non-dominated Sorting Genetic Algorithm II (NSGA-II), is utilized to find the Pareto-optimal solutions, alongside a Kriging model, which serves as a surrogate model for the FOWTs. This approach was applied to an IEC 15MW FOWT to demonstrate the optimization procedure. The results indicate that the integration of the genetic algorithm and the surrogate model achieved rapid convergence and high accuracy. Through this optimization process, the longitudinal motion response of FOWTs is reduced by a maximum of 6.46%, the yaw motion by 2.87%, and the nacelle acceleration by 11.55%.

Vibration control of a longitudinally vibrating rod connected through an elastic coupler by installing a nonlinear vibration reduction coupler

To study the potential application of the longitudinal vibration control of a rod coupling system by employing NESs, this study proposes a nonlinear vibration reduction coupler (NVRC), where the NVRC can be regarded as the NES which is installed between the two elastic structures. The introduction of NVRC is aimed at controlling the longitudinal vibration of the rod system. Based on the Lagrange method (LM), the longitudinal vibration analysis model of a rod system connected through a linear elastic coupler and an NVRC is established, in which the longitudinal vibration responses of the rod system with an NVRC are predicted. In the numerical analysis, the correctness and stability of LM in calculating longitudinal vibration responses of the rod system with an NVRC are verified, where the chosen reasons for observation points are explained. It can be concluded that the introduction of NVRC can reduce the vibration of each resonance area of the rod system at the same time. Under certain parameters, the vibration characteristics of the rod system are changed by employing NVRC. Furthermore, nonlinear stiffness and viscous damping of NVRC can be chosen as the adjustable parameters that strengthen the vibration reduction ratio of the rod system. Overall, the longitudinal vibration of the rod system can be effectively controlled by choosing reasonable parameters of NVRC. The introduction of NVRC provides an effective way to control the longitudinal vibration of the rod system.

The QIBA Profile for Diffusion-Weighted MRI: Apparent Diffusion Coefficient as a Quantitative Imaging Biomarker.

The apparent diffusion coefficient (ADC) provides a quantitative measure of water mobility that can be used to probe alterations in tissue microstructure due to disease or treatment. Establishment of the accepted level of variance in ADC measurements for each clinical application is critical for its successful implementation. The Diffusion-Weighted Imaging Biomarker Committee of the Quantitative Imaging Biomarkers Alliance (QIBA) has recently advanced the ADC Profile from the consensus to clinically feasible stage for the brain, liver, prostate, and breast. This profile distills multiple studies on ADC repeatability and describes detailed procedures to achieve stated performance claims on an observed ADC change within acceptable confidence limits. In addition to reviewing the current ADC Profile claims, this report has used recent literature to develop proposed updates for establishing metrology benchmarks for mean lesion ADC change that account for measurement variance. Specifically, changes in mean ADC exceeding 8% for brain lesions, 27% for liver lesions, 27% for prostate lesions, and 15% for breast lesions are claimed to represent true changes with 95% confidence. This report also discusses the development of the ADC Profile, highlighting its various stages, and describes the workflow essential to achieving a standardized implementation of advanced quantitative diffusion-weighted MRI in the clinic. The presented QIBA ADC Profile guidelines should enable successful clinical application of ADC as a quantitative imaging biomarker and ensure reproducible ADC measurements that can be used to confidently evaluate longitudinal changes and treatment response for individual patients.

Enhanced vertical railway track quality index with dynamic responses from moving trains

The conventional vertical track quality index (TQI) based on the standard deviation of longitudinal levels yields standardized railway track condition assessment. Nevertheless, its capability to identify problems is limited, particularly in the ballast and substructure layers when abrupt changes affect train-track interaction. Previous research shows that dynamic responses from moving trains via axle box acceleration (ABA) measurements can quantify abrupt changes in the vertical dynamic responses. Thus, this paper proposes a framework to design an enhanced vertical TQI, called EnVTQI, by integrating track longitudinal levels and dynamic responses from ABA measurements. First, measured ABA signals are processed to mitigate the influence of variation in measurement speed. Then, substructure and ballast-related features are extracted, including scale average wavelet power (SAWP) in the ranges 0.04 m-1 to 0.33 m-1 (substructure) and 1.25 m-1 to 2.50 m-1 (ballast). This enables identifying track conditions at different track layers. Finally, EnVTQI is determined by weight averaging between the conventional vertical TQI and the ABA features from moving trains. The performance of EnVTQI is evaluated based on 48 segments of a 200-m track on a Dutch railway line. The results indicate that EnVTQI helps to distinguish track segments that cause poor train-track interaction, which the conventional TQI does not indicate. EnVTQI can supplement the conventional TQI, improving the effectiveness of track maintenance decision-making.

Analytical Solution for Longitudinal Seismic Responses of Circular Tunnel Crossing Fault Zone

ABSTRACTThis paper proposes a simplified analytical solution for longitudinal seismic responses of a circular tunnel crossing a fault zone under longitudinally propagating shear waves. The transmissions and reflections of shear waves at two geological interfaces between the fault zone and intact rock are considered when calculating the free‐field displacement. An improved elastic foundation beam model considering different tangential contact conditions at the tunnel‒rock interface is also adopted. According to the continuous conditions at the two geological interfaces, explicit expressions for the tunnel displacement, bending moment, and shearing force are given. The effectiveness of the proposed analytical solution is validated via numerical simulations, and the importance of accounting for tangential contact conditions at the tunnel‒rock interface is emphasized. Moreover, parametric studies are performed to investigate the effects of the fault zone width, rock conditions, tunnel lining stiffness, tangential contact conditions, and earthquake frequency on the deformation and internal forces of tunnels subjected to seismic waves. This novel analytical solution can be utilized to quickly estimate the longitudinal seismic responses of circular tunnels crossing fault zones subjected to longitudinally propagating shear waves, particularly in the preliminary engineering design, and can be extended to geological conditions with multiple interfaces.

Longitudinal (α33) and transverse(α31) dynamic magnetoelectric hysteretic response for CoFe1.88Dy0.12O4–K0.5Na0.5NbO3 lead-free multiferroic laminates

The magnetoelectric (ME) laminate structures of CoFe1.88Dy0.12O4 (CFDO, ferrite) and K0.50Na0.50NbO3 (KNN, ferroelectric/piezoelectric) phases were fabricated by silver epoxy bonding technique and tested the ME response in longitudinal (α33) and transverse (α31) mode. The CFDO reveals the cubic spinel structure while KNN reveals the perovskite orthorhombic crystal structures having dense microstructure. The CFDO confirms the phase segregation of the DyFeO3ortho-ferrite phase, while the KNN lead-free ceramic showed the Curie temperature of 416 °C, 13µC/cm2 maximum polarization, 25,296 × 10-15 m2/N figure of merit, piezoelectric charge coefficient d33 of 47 pC/N. The longitudinal (α33) and transverse (α31) dynamic magnetoelectric response is studied to figure out the effective magnetic field direction to get better values of magnetoelectric voltage sensitivity i.e. αME. Both modes revealed the hysteretic behavior i.e. lagging of ME voltage response to an applied magnetic field which evidences a true multiferroic character of CFDO/KNN laminates. Remarkably, the (CFDO /KNN/ CFDO) structure demonstrated a substantial magnetoelectric coefficient in LT (α31) mode of approximately 38.5 mV/cm·Oe at a magnetic field of 400 Oe and −37.55 mV/cm·Oe at a magnetic field of −400 Oe. Thus, here we present the magnetoelectric laminate structure of CFDO /KNN/ CFDO phases beneficial for magnetic field sensors.

Robust model averaging prediction of longitudinal response with ultrahigh-dimensional covariates

Robust model averaging prediction of longitudinal response with ultrahigh-dimensional covariates

Joint modeling of mixed skewed longitudinal responses using convolution of normal and log-normal distributions: a Bayesian approach

This paper investigates the joint modeling of mixed ordinal and continuous longitudinal responses using a random effects model and applying a conditional approach. For the ordinal responses, a latent variable model with a logistic distribution is employed. To address skewness in the data, the model incorporates normal and log-normal convolution (NLNC) for both the error term and the random effects in the longitudinal model. Parameter estimation is carried out within a Bayesian framework using Gibbs sampling. The performance of the proposed model is evaluated through simulation studies, comparing it to joint models of mixed ordinal and continuous longitudinal responses assuming skew-normal or normal distributions. The results indicate that joint models using skew-normal or normal distributions can lead to biased parameter estimates, whereas the NLNC joint model performs better overall. Additionally, the proposed method is applied to analyze data from the British Household Panel Survey (BHPS), using life satisfaction and annual income as the correlated ordinal and continuous longitudinal responses, respectively, with annual income showing significant skewness. The results demonstrate that the proposed model provides the best fit for capturing the substantial skewness in the data.