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Xiaoyan Qiu

Publications and source records attributed to Xiaoyan Qiu.

6 recordsLinked to original sources

Dynamic Modeling and Control of Multi-Stack Alkaline Water Electrolysis Systems with Shared Gas Separators and Lye Circulation:Industrial Data-Based Validation and Simulation

An emerging approach for large-scale renewable hydrogen production is integrating multiple alkaline water electrolysis (AWE) stacks into one balance-of-plant (BoP) system, sharing gas-lye separation and lye circulation components. While this configuration, termed $N$-in-1, reduces cost and complexity, its dynamic performance under fluctuating power remains unclear compared with conventional 1-in-1 systems. This paper develops a state-space model of the multi-stack AWE system, capturing lye circulation, temperature, and hydrogen-to-oxygen (HTO) dynamics, calibrated via experiments on a 4,000 Nm$^3$/h-rated 4-in-1 system. A mixed-integer quadratic programming (MIQP)-based predictive controller is then designed to coordinate inter-stack current distribution, lye flow, and cooling for load tracking and operational stability. Simulations on the experimentally validated model show that a $4$-in-1 system achieves similar performance compared to four parallel 1-in-1 systems under continuous operation. Differences in load-tracking, temperature stabilization errors, and specific energy consumption remain below 0.015 MW, 0.346 K, and 0.001 kWh/Nm$^3$ under wind power supply when all stacks remain online.

math.OC

Online Dynamic Parameter Estimation of an Alkaline Electrolysis System Based on Bayesian Inference

When directly coupled with fluctuating energy sources such as wind and photovoltage power, the alkaline electrolysis (AEL) in a power-to-hydrogen (P2H) system is required to operate flexibly by dynamically adjusting its hydrogen production rate. The flex-ibility characteristics, e.g., loading range and ramping rate, of an AEL system are significantly influenced by some parameters re-lated to the dynamic processes of the AEL system. These parame-ters are usually difficult to measure directly and may even change with time. To accurately evaluate the flexibility of an AEL system in online operation, this paper presents a Bayesian Inference-based Markov Chain Monte Carlo (MCMC) method to estimate these parameters. Meanwhile, posterior joint probability distribu-tions of the estimated parameters are obtained as a byproduct, which provides valuable physical insight into the AEL systems. Experiments on a 25 kW electrolyzer validate the proposed pa-rameter estimation method.

eess.SY

Time-dependent Clearance of Cyclosporine in Adult Renal Transplant Recipients: A Population Pharmacokinetic Perspective

Aim The pharmacokinetic (PK) properties of cyclosporine (CsA) in renal transplant recipients are patient- and time-dependent. Knowledge of this time-related variability is necessary to maintain or achieve CsA target exposure. Here, we aimed to identify factors explaining variabilities in CsA PK properties and characterise time-dependent clearance (CL/F) by performing a comprehensive analysis of CsA PK factors using population PK (popPK) modelling of long-term follow-up data from our institution. Methods In total, 3,674 whole-blood CsA concentrations from 183 patients who underwent initial renal transplantation were analysed using nonlinear mixed-effects modelling. The effects of potential covariates were selected according to a previous report and well-accepted theoretical mechanisms. Model-informed individualised therapeutic regimens were also conducted. Results A two-compartment model adequately described the data and the estimated mean CsA CL/F was 32.6 L h-1 (5%). Allometrically scaled body size, haematocrit (HCT) level, CGC haplotype carrier status, and postoperative time may contribute to CsA PK variability. The CsA bioavailability in patients receiving a prednisolone dose (PD) of 80 mg was 20.6% lower than that in patients receiving 20 mg. A significant decrease (52.6%) in CL/F was observed as the HCT increased from 10.5% to 60.5%. The CL/F of the non-CGC haplotype carrier was 14.4% lower than that of the CGC haplotype carrier at 3 months post operation. CsA dose adjustments should be considered in different postoperative periods. Conclusions By monitoring body size, HCT, PD, and CGC haplotype, changes in CsA CL/F over time could be predicted. Such information could be used to optimise CsA therapy.

q-bio.TO

Effect of protein binding on exposure of unbound and total mycophenolic acid: a population pharmacokinetic analysis in Chinese adult kidney transplant recipients

AIMS A population pharmacokinetic (PK) analysis was performed to: (1) characterise the PK of unbound and total mycophenolic acid (MPA) and its 7-O-mycophenolic acid glucuronide (MPAG) metabolite, and (2) identify the clinically significant covariates that cause variability in the dose-exposure relationship to facilitate dose optimisation. METHODS A total of 740 unbound MPA (uMPA), 741 total MPA (tMPA) and 734 total MPAG (tMPAG) concentration-time data from 58 Chinese kidney transplant patients were analysed using a nonlinear mixed-effect model. The influence of covariates was tested using a stepwise procedure. RESULTS The PK of unbound MPA and MPAG were characterised by a two- and one-compartment model with first-order elimination, respectively. Apparent clearance of uMPA (CLuMPA/F) was estimated to be 852 L/h with a relative standard error (RSE) of 7.1%. The tMPA and uMPA were connected using a linear protein binding model, in which the protein binding rate constant (kB) increased non-linearly with the serum albumin (ALB) concentration. The estimated kB was 53.4 /h (RSE, 2.3%) for patients with ALB of 40 g/L. In addition, model-based simulation showed that changes in ALB substantially affected tMPA but not uMPA exposure. CONCLUSIONS The established model adequately described the population PK characteristics of the uMPA, tMPA, and MPAG. The estimated CLuMPA/F and unbound fraction of MPA (FUMPA) in Chinese kidney transplant recipients were comparable to those published previously in Caucasians. We recommend monitoring uMPA instead of tMPA to optimise mycophenolate mofetil (MMF) dosing for patients with lower ALB levels.

q-bio.TO

Systematic external evaluation of published population pharmacokinetic models for tacrolimus in adult liver transplant recipients

Background:Diverse tacrolimus population pharmacokinetic models in adult liver transplant recipients have been established to describe the PK characteristics of tacrolimus in the last two decades. However, their extrapolated predictive performance remains unclear.Therefore,in this study,we aimed to evaluate their external predictability and identify their potential influencing factors. Methods:The external predictability of each selected popPK model was evaluated using an independent dataset of 84 patients with 572 trough concentrations prospectively collected from Huashan Hospital. Prediction and simulation based diagnostics and Bayesian forecasting were conducted to evaluate model predictability. Furthermore, the effect of model structure on the predictive performance was investigated.Results:Sixteen published popPK models were assessed. In prediction-based diagnostics,the prediction error within 30% was below 50% in all the published models. The simulation based normalised prediction distribution error test and visual predictive check indicated large discrepancies between the observations and simulations in most of the models. Bayesian forecasting showed improvement in model predictability with two to three prior observations. Additionally, the predictive performance of the nonlinear Michaelis Menten model was superior to that of linear compartment models,indicating the underlying nonlinear kinetics of tacrolimus in liver transplant recipients.Conclusions:The published models performed inadequately in prediction and simulation based diagnostics. Bayesian forecasting may improve the predictive performance of the models. Furthermore, nonlinear kinetics of tacrolimus may be mainly caused by the properties of the drug itself, and incorporating nonlinear kinetics may be considered to improve model predictability.

q-bio.QM

Limited individual attention and online virality of low-quality information

Social media are massive marketplaces where ideas and news compete for our attention. Previous studies have shown that quality is not a necessary condition for online virality and that knowledge about peer choices can distort the relationship between quality and popularity. However, these results do not explain the viral spread of low-quality information, such as the digital misinformation that threatens our democracy. We investigate quality discrimination in a stylized model of online social network, where individual agents prefer quality information, but have behavioral limitations in managing a heavy flow of information. We measure the relationship between the quality of an idea and its likelihood to become prevalent at the system level. We find that both information overload and limited attention contribute to a degradation in the market's discriminative power. A good tradeoff between discriminative power and diversity of information is possible according to the model. However, calibration with empirical data characterizing information load and finite attention in real social media reveals a weak correlation between quality and popularity of information. In these realistic conditions, the model predicts that high-quality information has little advantage over low-quality information.

cs.SI