Changes In Model Parameters Research Articles

Comment on “On the Functional Annotation of Open-Channel Structures in the Glycine Receptor”

Recently, we reported the simulation of a stable open state of the glycine receptor. Central to the stability of the simulations was the behavior of the highly conserved leucine residues at the 9' gate, which were found to rotate into adjacent pockets, thus providing a structural rationale for decades of biochemical observations. In contrast, a previously reported model from Cerdan etal. (2018) resembled a more collapsed state. However, in support of their model, they draw attention to the agreement between calculated and experimental conductance measurements and argue that our model tends to overestimate ion flow. Here, we argue that there are many pitfalls with this approach and that the apparent agreement most likely reflects a fortuitous cancellation of errors. The computed values are highly sensitive to very small changes in model parameters. It is also likely that polarization effects will be very significant, and these have not yet been considered.

A LUTI microsimulation framework to evaluate long-term impacts of automated mobility on the choice of housing-mobility bundles

Land use–transportation interaction models can be useful planning support systems to assess the long-term implications of emerging transportation technologies like mobility-on-demand and automated vehicles. We propose an agent-based simulation framework ( SimMobility Long-Term) that uses econometrically robust behavioral models to model the potential impacts of accessibility changes in “car-lite” communities on the choice of housing-mobility bundles. Residential relocation and private mobility holding decisions are jointly considered in a sequential simulation modeling approach. Different types of market responses to the car-lite pilot are modeled through various scenarios via assumptions of changes in model parameters, and compared to a baseline where the car-lite pilot is never implemented. A comparatively vehicle-free study area with a low vacancy rate is chosen to obtain conservative estimates of policy impacts. Our findings indicate that initial awareness of the pilot is quite effective in making the study area more vehicle-free relative to the baseline. However, as market effects start impacting housing prices and bidding results, the vehicle-free gains are significantly reduced due to neighborhood gentrification. In conclusion, we highlight how land use–transportation interaction models can be used to explore market dynamics to see where market pressures matter, along with the need to align car-lite policies with market conditions regarding vacancy and car ownership rates.

Response of the parameters of excess infiltration and excess storage model to land use cover change

Abstract The Loess Plateau is the main source of water in Yellow River, China. After 1980s, the Yellow river water presented a significant reduction, what caused the decrease of the Yellow river discharge had been debated in academic circles. We proceeded with runoff generation mechanisms to explain this phenomenon. We built saturation excess runoff and infiltration excess runoff generation mechanisms for rainfall–runoff simulation in Jingle sub-basin of Fen River basin on the Loess Plateau, to reveal the influence of land use change on flood processes and studied the changes of model parameters under different underlying conditions. The results showed that the runoff generation mechanism was mainly infiltration-excess overland flow, but the flood events of saturation-excess overland flow had an increasing trend because of land use cover change (the increase of forestland and grassland areas and the reduction of cultivated land). Some of the model parameters had physical significances，such as water storage capacity (WM), infiltration capacity (f), evapotranspiration (CKE), soil permeability coefficient (k) and index of storage capacity distribution curve (n) showed increasing trends, and index of infiltration capacity distribution curve (m) showed a decreasing trend. The above results proved the changes of runoff generation mechanism from the perspective of model parameters in Jingle sub-basin, which can provide a new perspective for understanding the discharge reduction in the Yellow River basin.

Simple Analytical Models of an Electromagnetically Thin Nonmagnetic Conducting Cylindrical Shell Rotating in External, Static, and Slowly Time-Varying Magnetic Fields

This letter presents very simple analytical models for calculating the effectiveness of static and low frequency magnetic fields shielding by means of rotating electromagnetically thin nonmagnetic conducting cylindrical shells. In fact, “thin” means that the shells may be of any thickness, but must be thinner or at most comparable to the diffusion skin depth, which is not a particularly high requirement in practical constructions of this type. Useful expressions for the shielding factors that contain only elementary functions are given. The new formulas, which can be called “engineering formulas for quick evaluation,” are much simpler than those published earlier and work correctly in a wide range of changes in model parameters. The scope of applicability of the proposed analytical models has been analyzed.

Effect of the measurement errors on two one‐sided Shewhart control charts for monitoring the ratio of two normal variables

AbstractMonitoring the ratio between two random normal variables plays an important role in many industrial manufacturing processes. In this paper, we suggest designing two one‐sided Shewhart control charts monitoring this ratio. The numerical results show that the one‐sided charts have more advantages compared with the two‐sided Shewhart chart proposed previously in the literature. Moreover, we investigate the effect of measurement error on the performance of these control charts where the measurement error is supposed to follow a linear covariate error model. The change of model parameters from an in‐control condition to an out‐of‐control is presented without using a strict assumption about the independence of the shift size from measurement errors. A valuable finding from this study is that taking multiple measurements per item is not an effective way to reduce the negative effect of measurement error on the Shewhart charts' performance.

ІДЕНТИФІКАЦІЯ НАПРУЖЕНОГО СТАНУ ЛЮДИНИ-ОПЕРАТОРА

В статті розглядається можливість ідентифікації напруженого стану людини шляхом визначення параметрів математичної моделі, яка отримується на основі аналізу біофізичних показників, що фіксуються за результатами вимірів. Приведено приклад розрахунку.

Simulating and predicting the flux change of reverse osmosis membranes over time during wastewater reclamation caused by organic fouling

During the operation of the RO system, it’s significant to predict the flux change over time. Previous research conducted detailed exploration on the dynamics of RO membrane fouling, and provided a solid database for modelling. In this study, a modified intermediate blocking model with two parameters was proposed to describe the flux change of RO membranes under a huge variety of conditions. Raw data reported by over 20 research groups from 11 different countries was used to validate the feasibility of this model. It proved applicable to describe the flux change of RO membranes fouled by pure organic matter or mixture and tertiary treated wastewater. In order to reveal the relationship between model parameters and foulant concentrations, RO membrane fouling behaviors of typical foulants (sodium alginate (SA), bovine serum albumin (BSA) and mixture) were further investigated. We found that the change of model parameters with SA concentrations was in accordance with Langmuir adsorption isotherm model. Therefore, the model parameters could be calculated by SA concentrations under certain optional conditions, and then the flux change could be predicted by this model. In this way, a novel time-course model was established, which could predict the flux change of RO membranes over time only with SA concentrations. Besides, the synergic effect between SA and BSA on RO membrane fouling was directly quantified.

Road network link prediction model based on subgraph pattern

Urban road network (referred to as the road network) is a complex and highly sparse network. Link prediction of the urban road network can reasonably predict urban structural changes and assist urban designers in decision-making. In this paper, a new link prediction model ASFC is proposed for the characteristics of the road network. The model first performs network embedding on the road network through road2vec algorithm, and then organically combines the subgraph pattern with the network embedding results and the Katz index together, and then we construct the all-order subgraph feature that includes low-order, medium-order and high-order subgraph features and finally to train the logistic regression classification model for road network link prediction. The experiment compares the performance of the ASFC model and other link prediction models in different countries and different types of urban road networks and the influence of changes in model parameters on prediction accuracy. The results show that ASFC performs well in terms of prediction accuracy and stability.

SPARC: Found in translation: quantitative predictors of cardiac myocyte responses to β‐adrenergic stimulation across species

BackgroundDespite strong evidence of the fundamental connection between the brain and the heart, there is still a poor quantitative and functional understanding of the role of autonomic regulation in normal cardiac excitation‐contraction coupling and pathophysiology, including arrhythmias or contractile dysfunction. The intrinsic electrophysiologic differences across various animal models and species upon which our knowledge is based might be a contributing factor to this limited understanding. Indeed, by simulating our multi‐species computational framework for simulation of excitation‐contraction coupling and β‐adrenergic signaling in mouse, rabbit and human ventricular myocytes, we have shown that the well‐conserved fight‐or‐flight response is mediated by different sub‐cellular processes in rodents vs. larger mammals.AimWe sought to construct a suite of tools, based on statistical regression, for “translating” findings from animal models into human physiologic responses. To this aim, we also extended our multi‐species framework by developing a new porcine model, informed by ad‐hoc experimental recordings.Methods & ResultsOptical maps of transmembrane potentials and intracellular calcium transients (CaTs) from pig right and left ventricular wedge preparations were utilized for model parameter identification via an optimization algorithm that minimizes the error between simulated and experimental outputs, both with and without β‐adrenergic stimulation. By randomly varying parameters in our baseline multi‐species models, we generated populations of mouse, rabbit, pig and human virtual cells, and then applied multivariable linear regression to the population data to quantify inter‐species differences in the sensitivity of action potential (AP) and CaT properties (at both baseline and upon β‐adrenergic activation) to changes in model parameters. A regression model was used to develop quantitative predictors of human response from different subsets of simulated AP and CaT data (mimicking variable composition of experimental datasets). We found that predictors built upon calibrated AP and CaT signals can well reconstruct human response from mouse, rabbit or pig measurements. However, predictors devoid of calibrated (absolute) measures performed more poorly. In the absence of calibrated data, prediction of human response could be improved by combining data from two of the other species.ConclusionWe developed a robust and predictive framework that is well grounded and validated with a broad experimental data set and that will help to (1) understand inter‐species difference in the response to sympathetic stimulation, and (2) map experimental or simulated data in one species onto another species, most importantly human. We expect our model to provide a powerful tool to study the interaction between β‐adrenergic activation and the functional cardiac substrate and translate these findings across multiple species.Support or Funding InformationThis work is supported by the National Institutes of Health (NIH) Stimulating Peripheral Activity to Relieve Conditions grant OT2OD026580.

Control of the Vessel Course using of PID-Regulator under Parametric Uncertainty

The work is devoted to the problem of ensuring the safe movement of vessels in maritime waters. A special place within the framework of this problem is occupied by the task of planning the shipping route: the trajectory of the vessel’s movement in the local sea waters area and shipping route from the port of sailing out to the port of destination. The purpose of planning the vessel’s trajectory in the local sea waters area is to ensure navigation safety in the conditions of collective movement and geographical features of the waters area. In the present work the task of controlling the vessel when she is proceeding by the program trajectory is considered. The article notes that the inaccuracy of a preconceived ideas about the model of vessel movement can significantly affect the behavior of the vessel in the control processing, accuracy of control may become insufficient in circumstances of high traffic intensity, which can lead to dangerous approach of vessels. To solve this problem, it is proposed to include in the ship’s control system the PID - regulator operating on a deviation from the course, integral from this deviation and its derivative, and also, the function of identifying the model of motion of an object by the method of speed gradient, realizing a closed system. As a model of the vessel’s movement adopted well known model Nomoto of second order. The article is accompanied by the results of modeling the proposed ship control system. It is shown that it is able to operates within a single process in real time and respond adequately to changes of motion model parameters.

Can increased accessibility from emerging mobility services create a car-lite future? Evidence from Singapore using LUTI microsimulation

ABSTRACT Emerging mobility services are being increasingly regulated, with several cities testing car-lite policy interventions in pilot study areas before a metro-wide implementation. This study uses an agent-based LUTI microsimulation model to examine the effect of accessibility improvements on private mobility holdings, both directly and through the mediating effect of housing choice. Different market responses to acar-lite pilot are modeled through various assumptions of changes in model parameters. Three study areas with different characteristics are chosen to explore the spatial variation in policy effects. Our findings indicate that in-movers are more likely to be higher-income households with a comparatively higher car ownership rate. Unintended negative consequences like gentrification can significantly undermine the potential boosts to vehicle-free behavior inside the study area. As a possible step to mitigate such consequences, we suggest that emerging mobility regulation strategies anticipate and address the likely response of the housing market and urban redevelopment opportunities.

Lifetime cost-effectiveness analysis of first-line dialysis modalities for patients with end-stage renal disease under peritoneal dialysis first policy

BackgroundThis study aimed to determine the lifetime cost-effectiveness of first-line dialysis modalities for end-stage renal disease (ESRD) patients under the “Peritoneal Dialysis First” policy.MethodsLifetime cost-effectiveness analyses from both healthcare provider and societal perspectives were performed using Markov modelling by simulating at age 60. Empirical data on costs and health utility scores collected from our studies were combined with published data on health state transitions and survival data to estimate the lifetime cost, quality-adjusted life-years (QALYs) and cost-effectiveness of three competing dialysis modalities: peritoneal dialysis (PD), hospital-based haemodialysis (HD) and nocturnal home HD.ResultsFor cost-effectiveness analysis over a lifetime horizon from the perspective of healthcare provider, hospital-based HD group (lifetime cost USD$142,389; 6.58 QALYs) was dominated by the PD group (USD$76,915; 7.13 QALYs). Home-based HD had the highest effectiveness (8.37 QALYs) but with higher cost (USD$97,917) than the PD group. The incremental cost-effectiveness ratio (ICER) was USD$16,934 per QALY gained for home-based HD over PD. From the societal perspective, the results were similar and the ICER was USD$1195 per QALY gained for home-based HD over PD. Both ICERs fell within the acceptable thresholds. Changes in model parameters via sensitivity analyses had a minimal impact on ICER values.ConclusionsThis study assessed the cost-effectiveness of dialysis modalities and service delivery models for ESRD patients under “Peritoneal Dialysis First” policy. For both healthcare provider and societal perspectives, PD as first-line dialysis modality was cost-saving relative to hospital-based HD, supporting the existing PD First or favoured policy. When compared with PD, Nocturnal home Home-based HD was considered a cost-effective first-line dialysis modality for ESRD patients.

COST-EFFECTIVENESS ANALYSIS FOR HPV MITIGATION STRATEGIES IN THE REPUBLIC OF MOLDOVA BASED ON INFECTIOUS DISEASE MODELLING

Human papillomavirus (HPV) is a sexually transmittable virus infection, which is a necessary risk factor for developing cervical cancer, first killer for working women in Moldova. Since 2018 Moldova has modified the screening program and the vaccination program (mainly funded externally). To assess the performance of the mitigation policy we propose the cost-effectiveness analysis according to 2 already implemented strategies. (1) Vaccination of a single age-cohort, although vaccinating a single cohort may not have a substantial effect in other countries with distinct socio-economic situation. (2) Transition to more technologically advance screening ecosystem (changing from Romanowski to Pap smear), which might not necessary be cost-efficient in low resource settings (if GDP per capita doesn’t grow substantially at the same time). (1) We verified that single cohort vaccination is both cost-beneficial (total costs reduction will balance intervention costs around the year 2040) and cost-efficient (with incremental impact in 20 years perspective on the level of 2300 EUR/QALY). Moreover, we found out that single year cohort is more beneficial than 5-years cohort vaccination scenarios in our mathematical model. This behaviour could be explained by a transitional situation in Moldova (HPV epidemic is near outbreak threshold), still small changes of model parameters and initial conditions could cause strong effect in the epidemiology. However, a definitive answer cannot be given with the chosen methodology. (2) Transition between Romanowski -> Pap smear cytology in screening benefits unquestionably in epidemiology e.g. due to a higher specificity. However, further maintenance and higher procedure costs could exceed treatment costs, hence intervention costs would gather an unacceptable share of national resources that are limited and that are dedicated to public health.

In-silico study of age-related ionic remodeling in human ventricular cardiomyocytes

Ageing is one of the dominant risk factors for cardiovascular diseases. A large number of experimental data is collected on the cellular remodeling in the ageing myocardium from mammals, but very little is known about the human cardiomyocytes. We used a combined electro-mechanical model of human ventricular cardiomyocytes and a population of models approach to investigate the variability in the response of cardiomyocytes to age-related changes in model parameters of the ionic currents. To generate a control model population, we varied 9 ionic parameters and excluded model samples with biomarkers of cellular action potential (AP) and Ca2+ transient (CT) falling outside the physiological ranges. Using the control population of models, we evaluated the response to age-related reduction in the K+ transient outward current, SERCA pump, and an increase in the Na+Ca2+ exchange current and L-type Ca2+ current. Then, we randomly generated 60 age-related sets of the 4 parameters and applied each set to every model in the control population. We showed an increase in the frequency of repolarization anomalies (RA) and critical AP prolongation in the ageing model populations suggesting arrhythmogenic effects of the ionic remodeling. The population based approach allowed us to assess the pro-arrhythmic contribution of the ionic parameters in ageing cardiomyocytes.

Study of Hydrocephalus Using Poroelastic Models

The filtration of arterial, venous, and capillary blood, and liquor is investigated using a multiphase poroelastic model for brain matter based on medical data. The model can be used to describe the healthy brain, the brain with hydrocephalus, and the transition between them due to a change in model parameters.

Assessing the predictability of nonlinear dynamics under smooth parameter changes.

Short-term forecasts of nonlinear dynamics are important for risk-assessment studies and to inform sustainable decision-making for physical, biological and financial problems, among others. Generally, the accuracy of short-term forecasts depends upon two main factors: the capacity of learning algorithms to generalize well on unseen data and the intrinsic predictability of the dynamics. While generalization skills of learning algorithms can be assessed with well-established methods, estimating the predictability of the underlying nonlinear generating process from empirical time series remains a big challenge. Here, we show that, in changing environments, the predictability of nonlinear dynamics can be associated with the time-varying stability of the system with respect to smooth changes in model parameters, i.e. its local structural stability. Using synthetic data, we demonstrate that forecasts from locally structurally unstable states in smoothly changing environments can produce significantly large prediction errors, and we provide a systematic methodology to identify these states from data. Finally, we illustrate the practical applicability of our results using an empirical dataset. Overall, this study provides a framework to associate an uncertainty level with short-term forecasts made in smoothly changing environments.

Quasi-static modeling of a novel growing soft-continuum robot

Soft-continuum robots attract researchers owing to their advantages over rigid-bodied robots such as adaptation of the flexible structure to tortuous environments, and compliant contact mechanics. The need for new modeling methods to attain precise control for such systems has emerged from the recent rapid progress in soft robotics. This article presents a quasi-static model for a growing soft-continuum robot that is propelled via thin-walled inflated tubes, and steered by the difference between tube lengths. Therefore, the robot shaft is modeled as a series of inflated beams under deformation. A quasi-static model coupled with a kinematic model is developed to accurately position the end effector while accounting for the inflated beam stiffness and end-effector loads. The proposed model calculates control parameters, namely tube lengths and tendon tensions required to maintain the end effector at a certain position. Tip deflection due to end-effector loading is calculated and kinematic model inputs are updated to correct positioning error caused by shaft deformation. The model is simulated for the soft-continuum robot moving on a path to show the change in model parameters for various end-effector positions. Results demonstrate the significance of including pressurized tube stiffness in the model for growing robots of similar type. Second, the need for tendons in addition to pneumatic actuation is emphasized for accurate positioning of the end effector under loading. The proposed model offers a potential method for simulation and control of similar growing soft-continuum robots presented in the literature.

Economic implications of localization strategies for cerebrospinal fluid rhinorrhea.

The direct costs associated with different diagnostic algorithms to localize cerebrospinal fluid (CSF) rhinorrhea have not been described. A decision-tree analysis of imaging modalities used to localize CSF rhinorrhea was performed to compare associated direct costs. The primary outcome was cost, which was determined based on reimbursement data published by the Centers for Medicare and Medicaid Services in 2018. The model was parameterized after a literature review of published studies was performed from 1990 to 2018 to estimate the sensitivity CSF rhinorrhea localization of the following radiographic modalities: high-resolution computed tomography (HRCT), magnetic resonance cisternography (MRC), and CT cisternography (CTC). In addition to base case analysis, 1-way sensitivity analyses were also performed to evaluate the robustness of results to changes in model parameters. Among patients with a high suspicion for CSF rhinorrhea, use of HRCT followed by exploration in the operating room if preliminary HRCT was negative was found to be the optimal localization modality from a cost perspective ($172.25). The next least costly algorithm was HRCT followed by MRC ($294.10). Imaging algorithms beginning with CTC were the next least costly modality ($727.37). Sensitivity analyses generally supported HRCT to be the optimal initial radiographic strategy over a wide range of parameter values. This work advocates HRCT as first-line modality to localize CSF rhinorrhea from a cost perspective. Although algorithms beginning with MRC were on average $35 more expensive than those starting with CTC, associated risks of CTC were not modeled and may play a role in decision making.

Diffusion Kurtosis Imaging maps neural damage in the EAE model of multiple sclerosis

Diffusion kurtosis imaging (DKI) is an imaging modality that yields novel disease biomarkers and in combination with nervous tissue modeling, provides access to microstructural parameters. Recently, DKI and subsequent estimation of microstructural model parameters has been used for assessment of tissue changes in neurodegenerative diseases and associated animal models. In this study, mouse spinal cords from the experimental autoimmune encephalomyelitis (EAE) model of multiple sclerosis (MS) were investigated for the first time using DKI in combination with biophysical modeling to study the relationship between microstructural metrics and degree of animal dysfunction. Thirteen spinal cords were extracted from animals with varied grades of disability and scanned in a high-field MRI scanner along with five control specimen. Diffusion weighted data were acquired together with high resolution T2* images. Diffusion data were fit to estimate diffusion and kurtosis tensors and white matter modeling parameters, which were all used for subsequent statistical analysis using a linear mixed effects model. T2* images were used to delineate focal demyelination/inflammation. Our results reveal a strong relationship between disability and measured microstructural parameters in normal appearing white matter and gray matter. Relationships between disability and mean of the kurtosis tensor, radial kurtosis, radial diffusivity were similar to what has been found in other hypomyelinating MS models, and in patients. However, the changes in biophysical modeling parameters and in particular in extra-axonal axial diffusivity were clearly different from previous studies employing other animal models of MS. In conclusion, our data suggest that DKI and microstructural modeling can provide a unique contrast capable of detecting EAE-specific changes correlating with clinical disability.

Capturing the Sparsity and Tracking the Channels for Massive MIMO Networks

Due to its enhanced capacity and energy efficiency, massive MIMO has become a critical technology for the 5 G and beyond mobile networks. However, fully achieving its benefits requires the accurate estimation of channel. In this article, we propose a low-overhead characteristic learning, tracking, and monitoring mechanism for the time-varying massive MIMO channels. Specially, we exploit the common spatial sparsity and temporal correlation of the channels. Firstly, using the virtual channel representation and modeling the temporal correlation as an autoregressive process, we formulate the time-varying massive MIMO channel as a sparse signal model. Then, a sparse Bayesian learning (SBL) scheme based on the expectation maximization (EM) is proposed to determine the model parameters of the channel. To achieve the posteriors of different model parameters, the approximate message passing (AMP) is used in the expectation step. Furthermore, the Kalman filtering (KF) with a reduced dimension is used to track the downlink (DL) channel. To observe the change of model parameters and start the relearning process, a monitoring scheme based on the Bayesian Cramer-Rao bound (BCRB) is also developed. Finally, numerical results are provided to demonstrate the performance of our proposed scheme.