Development of a Mortality Prediction Model in Hospitalised SARS-CoV-2 Positive Patients Based on Routine Kidney Biomarkers

Acute kidney injury (AKI) is a prevalent complication in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positive inpatients, which is linked to an increased mortality rate compared to patients without AKI. Here we analysed the difference in kidney blood biomarkers in SARS-CoV-2 positive patients with non-fatal or fatal outcome, in order to develop a mortality prediction model for hospitalised SARS-CoV-2 positive patients. A retrospective cohort study including data from suspected SARS-CoV-2 positive patients admitted to a large National Health Service (NHS) Foundation Trust hospital in the Yorkshire and Humber regions, United Kingdom, between 1 March 2020 and 30 August 2020. Hospitalised adult patients (aged ≥ 18 years) with at least one confirmed positive RT-PCR test for SARS-CoV-2 and blood tests of kidney biomarkers within 36 h of the RT-PCR test were included. The main outcome measure was 90-day in-hospital mortality in SARS-CoV-2 infected patients. The logistic regression and random forest (RF) models incorporated six predictors including three routine kidney function tests (sodium, urea; creatinine only in RF), along with age, sex, and ethnicity. The mortality prediction performance of the logistic regression model achieved an area under receiver operating characteristic (AUROC) curve of 0.772 in the test dataset (95% CI: 0.694–0.823), while the RF model attained the AUROC of 0.820 in the same test cohort (95% CI: 0.740–0.870). The resulting validated prediction model is the first to focus on kidney biomarkers specifically on in-hospital mortality over a 90-day period.     

Numerical and sensitivity analysis of MHD bioconvective slip flow of nanomaterial with binary chemical reaction and Newtonian heating

The impact of Stefan blowing on the MHD bioconvective slip flow of a nanofluid towards a sheet is explored using numerical and statistical tools. The governing partial differential equations are nondimensionalized and converted to similarity equations using apposite transformations. These transformed equations are solved using the Runge–Kutta–Fehlberg method with the shooting technique. Graphical visualizations are used to scrutinize the effect of the controlling parameters on the flow profiles, skin friction coefficient, local Nusselt, and Sherwood number. Moreover, the sensitivities of the reduced Sherwood and Nusselt number to the input variables of interest are explored by adopting the response surface methodology. The outcomes of the limiting cases are emphatically in corroboration with the outcomes from preceding research. It is found that the heat transfer rate has a positive sensitivity towards the haphazard motion of the nanoparticles and a negative sensitivity towards the thermomigration. The thermal field is enhanced by the Stefan blowing aspect. Moreover, the fluid velocity can be controlled by the applied magnetic field.     

Pyrolysis conditions and ozone oxidation effects on ammonia adsorption in biomass generated chars

Ammonia adsorbents were generated via pyrolysis of biomass (peanut hulls and palm oil shells) over a range of temperatures and compared to a commercially available activated carbon (AC) and solid biomass residuals (wood and poultry litter fly ash). Dynamic ammonia adsorption studies (i.e., breakthrough curves) were performed using these adsorbents at 23 degrees C from 6 to 17 ppmv NH(3). Of the biomass chars, palm oil char generated at 500 degrees C had the highest NH(3) adsorption capacity (0.70 mg/g, 6 ppmv, 10% relative humidity (RH)), was similar to the AC, and contrasted to the other adsorbents (including the AC), the NH(3) adsorption capacity significantly increased if the relative humidity was increased (4 mg/g, 7 ppmv, 73% RH). Room temperature ozone treatment of the chars and activated carbon significantly increased the NH(3) adsorption capacity (10% RH); resultant adsorption capacity, q (mg/g) increased by approximately 2, 6, and 10 times for palm oil char, peanut hull char (pyrolysis only), and activated carbon, respectively. However, water vapor (73% RH at 23 degrees C) significantly reduced NH(3) adsorption capacity in the steam and ozone treated biomass, yet had no effect on the palm shell char generated at 500 degrees C. These results indicate the feasibility of using a low temperature (and thus low energy input) pyrolysis and activation process for the generation of NH(3) adsorbents from biomass residuals.     

Fault estimation and tolerant control for discrete‐time switched systems with sojourn probabilities

This paper addresses the issue of fault estimation and accommodation for a discrete‐time switched system with actuator faults. Here, we assume that the sojourn probabilities are known a priori. By using the reduced‐order observer method, the sojourn probability approach, and the Lyapunov technique, a fault estimation algorithm is obtained for the considered system. The main objective of this work is to design a dynamic output feedback fault‐tolerant controller based on the obtained fault estimation information such that the closed‐loop discrete‐time switched system with available sojourn probabilities is robustly mean‐square stable and satisfies a prescribed mixed and passivity disturbance attenuation level in the presence of actuator faults. More precisely, a dynamic output feedback fault‐tolerant controller is established in terms of linear matrix inequalities. Finally, numerical examples are provided to illustrate the usefulness and effectiveness of the proposed design technique.     

Observer‐based resilient finite‐time control of blood gases model during extra‐corporeal circulation

This study aims at designing an observer‐based resilient controller to regulate the amount of oxygen and carbon dioxide in the blood of patients during the extra‐corporeal blood circulation process. More precisely, in this study, a suitable observer‐based resilient controller is constructed to regulate the levels of patient blood gases in a finite interval of time. The finite‐time boundedness with the prescribed H∞ performance index of the considered blood gases control system against modelling uncertainty and external disturbances is ensured by using Lyapunov stability analysis. Moreover, a set of sufficient conditions for obtaining the controller gain is developed in the form of linear matrix inequalities (LMIs). Finally, the effectiveness of the proposed robust finite‐time control scheme is verified through simulation results. The result reveals that the blood gases are maintained in their physiological ranges during a stable extra‐corporeal circulation process via the proposed observer‐based resilient controller.Inspec keywords: blood, haemodynamics, oxygen, carbon compounds, controllers, medical control systems, biomedical equipment, Lyapunov methods, linear matrix inequalitiesOther keywords: observer‐based resilient finite‐time control, observer‐based resilient controller, oxygen amount, carbon dioxide amount, extracorporeal blood circulation process, patient blood gas levels, finite time interval, finite‐time boundedness, H_∞ performance index, blood gases control system, Lyapunov stability analysis, controller gain, linear matrix inequalities, physiological ranges, LMIs, CO₂ , O₂      

Effect of Strong Pump Depletion on Two-beam Coupling in Photorefractive BaTiO3 at 442 nm

Abstract

Photorefractive BaTiO₃ crystal illuminated at 442 nm gives a large initial scattering level, which leads to strong pump depletion into beam fanning. Studies on the time development of beam fanning show a temporal shift of the fanned beam maximum towards the c-axis direction. The effect on the signal beam amplification of the strong pump depletion into beam fanning has been investigated, revealing different temporal development of the amplified signal for various cross-angles. Our observations on beam fanning in the presence and in the absence of a signal reveal that there is appreciable coupling between the fanned beam and the signal.     

Formation of all fourteen Bravais lattices of three-dimensional photonic crystal structures by a dual beam multiple-exposure holographic technique

We make use of a dual beam multiple-exposure (DBME) holographic technique for the formation of all 14 Bravais lattices of three-dimensional photonic crystal microstructures. For simplicity of experimental implementation, the DBME method has been modified such that, prior to each exposure, once the proper angle between the wave vectors of the interfering beams is chosen, a single axis rotation of the recording medium gives the desired results. The parameters required for the generation of the lattice structures have been derived by appropriate modification of interference of four noncoplanar beams (IFNB) analysis for corresponding implementation in the DBME technique, and the results have been verified by computer simulations. After giving a comparative study of the results with the IFNB method, recording geometries for the DBME approach are also proposed in order to realize all 14 Bravais lattices experimentally.     

Optimization of pulsed current GTAW process parameters for sintered hot forged AISI 4135 P/M steel welds by simulated annealing and genetic algorithm

Abundant improvements have occurred in materials handling, especially in metal joining. Pulsed current gas tungsten arc welding (PCGTAW) is one of the consequential fusion techniques. In this work, PCGTAW of AISI 4135 steel engendered through powder metallurgy (P/M) has been executed, and the process parameters have been highlighted applying Taguchi’s L9 orthogonal array. The results show that the peak current (Ip), gas flow rate (GFR), welding speed (WS) and base current (Ib) are the critical constraints in strong determinant of the Tensile strength (TS) as well as percentage of elongation (% Elong) of the joint. The practical impact of applying Genetic algorithm (GA) and Simulated annealing (SA) to PCGTAW process has been authenticated by means of calculating the deviation between predicted and experimental welding process parameters.     

Robust reliable sampled-data control for switched systems with application to flight control

This paper addresses the robust reliable stabilisation problem for a class of uncertain switched systems with random delays and norm bounded uncertainties. The main aim of this paper is to obtain the reliable robust sampled-data control design which involves random time delay with an appropriate gain control matrix for achieving the robust exponential stabilisation for uncertain switched system against actuator failures. In particular, the involved delays are assumed to be randomly time-varying which obeys certain mutually uncorrelated Bernoulli distributed white noise sequences. By constructing an appropriate Lyapunov–Krasovskii functional (LKF) and employing an average-dwell time approach, a new set of criteria is derived for ensuring the robust exponential stability of the closed-loop switched system. More precisely, the Schur complement and Jensen's integral inequality are used in derivation of stabilisation criteria. By considering the relationship among the random time-varying delay and its lower and upper bounds, a new set of sufficient condition is established for the existence of reliable robust sampled-data control in terms of solution to linear matrix inequalities (LMIs). Finally, an illustrative example based on the F-18 aircraft model is provided to show the effectiveness of the proposed design procedures.