ISI‐mitigating modulation scheme using ion reaction for molecular communications

Here, according to the type‐based modulation technique, the authors develop a novel modulation scheme by utilising ion collision and reaction to mitigate inter‐symbol interference (ISI) in diffusive molecular communication (MC) systems. Two types of ions are employed as messenger molecules that cause a chemical reaction in the medium. According to the residual molecules and chemical reaction, the proposed modulation scheme adaptively adjusts the number of emitted molecules, thereby guaranteeing that the number of molecules that arrived at the receiver remains at a stable level. The authors evaluate the performance of the proposed scheme by comparing it with the conventional binary molecule shift keying (BMoSK), BMoSK with power adjustment (BMoSK‐PA), and ideal BMoSK (without ISI) modulation techniques via diffusion. Numerical results show that the bit error probability and channel capacity of the proposed modulation scheme are much closer to the ideal BMoSK modulation scheme compared to the conventional BMoSK and the BMoSK‐PA modulation schemes.Inspec keywords: channel capacity, intersymbol interference, error statisticsOther keywords: ISI‐mitigating modulation scheme, ion reaction, molecular communications, type‐based modulation technique, novel modulation scheme, ion collision, inter‐symbol interference, diffusive molecular communication systems, messenger molecules, chemical reaction, residual molecules, emitted molecules, conventional binary molecule shift, ideal BMoSK modulation scheme, conventional BMoSK, BMoSK‐PA modulation schemes

Nomenclature

Nc

number of molecules received in the current bit interval

Np

number of molecules received in current bit interval due to the molecules released in the previous bit interval

Nn

the Additive White Gaussian Noise

τ1

the detection thresholds of bit 1

τ2

the detection thresholds of bit 0

     

Control strategy design for the anti‐HBV mathematical model

Currently, the anti‐viral therapy has been extensively utilised to reduce the viral burden and switch off certain infectious sources for hepatitis B virus (HBV) infected patients in clinical treatment. Several pieces of existing evidence have demonstrated that large‐scale coverage with anti‐viral therapy has obtained a certain great contribution in hygiene and disease control. In this study, an anti‐HBV mathematical model is considered and its control strategy of the drug treatment is designed. Based on the Lyapunov theory, this study derives three main theorems to propose three different control strategies, respectively, for drug treatments m(t) and n(t), such that all states of the anti‐HBV model can finally converge to the infection‐free equilibrium point E1 asymptotically. Especially, the designed drug treatment m(t) or n(t) is not a fixed value, but it is time‐varying and dependent on states. In Theorem 1, the single drug treatment m(t) without n(t) is synthesised. Theorem 2 considers the single drug treatment n(t) without m(t). In Theorem 3, the combination therapy of m(t) and n(t) is designed. Finally, there are several simulations to show that the proposed combination therapy is much more effective to cure HBV infected patients than the drug treatment with solely single m(t) or single n(t).Inspec keywords: microorganisms, patient treatment, drugs, physiological models, diseasesOther keywords: combination therapy, HBV infected patients, control strategy design, clinical treatment, disease control, drug treatment, antiviral therapy, antiHBV mathematical model, hepatitis B virus infected patients, infection‐free equilibrium point     

Drug repositioning via matrix completion with multi‐view side information

In the process of drug discovery and disease treatment, drug repositioning is broadly studied to identify biological targets for existing drugs. Many methods have been proposed for drug–target interaction prediction by taking into account different kinds of data sources. However, most of the existing methods only use one side information for drugs or targets to predict new targets for drugs. Some recent works have improved the prediction accuracy by jointly considering multiple representations of drugs and targets. In this work, the authors propose a drug–target prediction approach by matrix completion with multi‐view side information (MCM) of drugs and proteins from both structural view and chemical view. Different from existing studies for drug–target prediction, they predict drug–target interaction by directly completing the interaction matrix between them. The experimental results show that the MCM method could obtain significantly higher accuracies than the comparison methods. They finally report new drug–target interactions for 26 FDA‐approved drugs, and biologically discuss these targets using existing references.Inspec keywords: proteins, diseases, medical computing, drugs, genetics, molecular biophysicsOther keywords: drug–target interaction prediction, prediction accuracy, matrix completion, multiview side information, structural view, chemical view, drug repositioning, drug discovery, biological targets, FDA‐approved drugs

Nomenclature

P

md×mt known drug–target interaction matrix

As

kd×kt complete low‐rank matrix in the structural view

Ac

kd×kt complete low‐rank matrix in the chemical view

Wds

md×md drug–drug similarity matrix in the structural view

Wts

mt×mt target–target similarity matrix in the structural view

Wdt

md×md drug–drug similarity matrix in the chemical view

Wtt

mt×mt target–target similarity matrix in the chemical view

Ds

md×kd drugs feature matrix in the structural view

Gs

mt×kt protein targets feature matrix in the structural view

Dc

md×kd drugs feature matrix in the chemical view

Gc

mt×kt protein targets feature matrix in the chemical view

Q

md×mt the common complete drug–target interaction matrix

Z

kd×kt any given matrix

⟨⋅,⋅⟩

inner product for matrices

∇

gradient operator

λ1, λ2

trade‐off parameters

     

Modelling and analysing biological oscillations in quorum sensing networks

Recent experiments have shown that the biological oscillation of quorum sensing (QS) system play a vital role not only in the process of bacterial synthesis but also in the treatment of cancer by releasing drugs. As known, these five substances TetR, CI, LacI, AiiA and AI are the core components of the QS system. However, the effects of AiiA and protein synthesis time delay on QS system are often ignored in the theoretical model, which is taken as a priority in the proposed research. Therefore, the authors developed a new mathematical model to explore the effects of AiiA and time delay on the dynamical behaviour of QS system theoretically and numerically. The results show that time delay can induce oscillation of QS system. Concretely, there exists a time delay threshold τ0. When time delay is less than τ0, the system is stable. With the increasing of time delay and once it passes τ0, oscillation behaviour occurs. Moreover, the length of time delay determines the amplitude and period of the QS oscillation. In addition, the value of τ0 is sensitive to AiiA. These results may enhance the understanding of QS oscillations and provide new insights for bacterial release drugs to treat cancer.Inspec keywords: cellular biophysics, delays, cancer, microorganisms, molecular biophysics, proteinsOther keywords: quorum sensing networks, biological oscillation, protein synthesis time delay, time delay threshold, QS oscillation, cancer treatment, bacterial synthesis     

Petri Net modelling approach for analysing the behaviour of Wnt/ β ‐catenin and Wnt/ Ca2+ signalling pathways in arrhythmogenic right ventricular cardiomyopathy

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is an inherited heart muscle disease that may result in arrhythmia, heart failure and sudden death. The hallmark pathological findings are progressive myocyte loss and fibro fatty replacement, with a predilection for the right ventricle. This study focuses on the adipose tissue formation in cardiomyocyte by considering the signal transduction pathways including Wnt/ β ‐catenin and Wnt/Ca²⁺ regulation system. These pathways are modelled and analysed using stochastic petri nets (SPN) in order to increase our comprehension of ARVC and in turn its treatment regimen. The Wnt/ β ‐catenin model predicts that the dysregulation or absence of Wnt signalling, inhibition of dishevelled and elevation of glycogen synthase kinase 3 along with casein kinase I are key cytotoxic events resulting in apoptosis. Moreover, the Wnt/Ca²⁺ SPN model demonstrates that the Bcl2 gene inhibited by c‐Jun N‐terminal kinase protein in the event of endoplasmic reticulum stress due to action potential and increased amount of intracellular Ca²⁺ which recovers the Ca²⁺ homeostasis by phospholipase C, this event positively regulates the Bcl2 to suppress the mitochondrial apoptosis which causes ARVC.Inspec keywords: molecular biophysics, enzymes, cancer, muscle, Petri nets, cellular biophysics, bioelectric potentials, biomembranes, tumours, cardiology, genetics, biochemistry, calciumOther keywords: heart failure, sudden death, hallmark pathological findings, progressive myocyte loss, fibro fatty replacement, adipose tissue formation, signal transduction pathways, Ca²⁺ regulation system, stochastic petri nets, ARVC, $β‐catenin model, Wnt signalling, glycogen synthase kinase 3, Bcl2 gene, c‐Jun N‐terminal kinase protein, petri Net modelling approach, Ca²⁺ signalling pathways, arrhythmogenic right ventricular cardiomyopathy, inherited heart muscle disease, Ca²⁺ SPN model, Ca     

Improvement in prediction of antigenic epitopes using stacked generalisation: an ensemble approach

The major intent of peptide vaccine designs, immunodiagnosis and antibody productions is to accurately identify linear B‐cell epitopes. The determination of epitopes through experimental analysis is highly expensive. Therefore, it is desirable to develop a reliable model with significant improvement in prediction models. In this study, a hybrid model has been designed by using stacked generalisation ensemble technique for prediction of linear B‐cell epitopes. The goal of using stacked generalisation ensemble approach is to refine predictions of base classifiers and to get rid of the worse predictions. In this study, six machine learning models are fused to predict variable length epitopes (6–49 mers). The proposed ensemble model achieves 76.6% accuracy and average accuracy of repeated 10‐fold cross‐validation is 73.14%. The trained ensemble model has been tested on the benchmark dataset and compared with existing sequential B‐cell epitope prediction techniques including APCpred, ABCpred, BCpred and AAPBCPred.Inspec keywords: generalisation (artificial intelligence), support vector machines, cellular biophysics, pattern classification, proteins, learning (artificial intelligence), bioinformaticsOther keywords: antigenic epitopes, stacked generalisation, peptide vaccine designs, immunodiagnosis, antibody productions, linear B‐cell epitopes, generalisation ensemble technique, generalisation ensemble approach, machine learning models, base classifiers     

Bifurcation and oscillatory dynamics of delayed CDK1‐APC feedback loop

Extensive experimental evidence has been demonstrated that the dynamics of CDK1‐APC feedback loop play crucial roles in regulating cell cycle processes, but the dynamical mechanisms underlying the regulation of this loop are still not completely understood. Here, the authors systematically investigated the stability and bifurcation criteria for a delayed CDK1‐APC feedback loop. They showed that the maximum reaction rate of CDK1 inactivation by APC can drive sustained oscillations of CDK1 activity (CDK1∗ ) and APC activity (APC∗ ), and the amplitude of these oscillations is increasing with the increase of the reaction rate over a wide range; a certain range of the self‐activation rate for CDK1 is also significant for generating these oscillations, for too high or too low rates the oscillations cannot be generated. Moreover, they derived the sufficient conditions to determine the stability and Hopf bifurcations, and found that the sum of time delays required for activating CDK1 and APC can induce CDK1∗ and APC∗ to be oscillatory, even when the CDK1∗ and APC∗ settle in a definite stable steady state. Furthermore, they presented an explicit algorithm for the properties of periodic oscillations. Finally, numerical simulations have been presented to justify the validity of theoretical analysis.Inspec keywords: feedback, numerical analysis, cellular biophysics, bifurcation, delaysOther keywords: $APC^\ast $APC, activating CDK1, $CDK1^\ast $CDK1, delayed CDK1‐APC feedback loop, CDK1‐APC feedback loop play crucial roles, CDK1 inactivation, CDK1 activity     

Facile nano‐free electrochemiluminescence biosensor for detection of sulphamethoxazole via tris(2,2′‐bipyridyl)ruthenium(II) and N ‐methyl pyrrolidone recognition

The electrochemiluminescence (ECL) system based on the ruthenium complex has become a powerful tool in the field of analytical chemistry. However, the non‐aqueous ECL luminescence system, which does not involve complex nano‐modification, has not been widely used for the determination of analytes. In this study, N ‐methyl pyrrolidone was selected as the solvent, and it could also act as a co‐reactant of Rubpy32+. Based on this, a simple ECL system without nanomaterials was established. Strong ECL was generated. Furthermore, a quenching effect between the excited state of Rubpy32+ and sulphamethoxazole (SMZ) was observed. Based on this, a sensitive ECL sensor for detecting SMZ is constructed. A linear relationship between ECL signal quenching intensity (ΔI) and the logarithm of SMZ concentration (log C) in the concentration range of 1 × 10⁻⁷ –1 × 10⁻⁵ mol/l is obtained. The limit of detection is as low as 3.33 × 10⁻⁹ mol/l. The method has been applied to the detection of SMZ in tap water samples with different concentration levels with satisfactory results, and the recovery was 95.3–102.6%.Inspec keywords: biosensors, electrochemical sensors, electroluminescence, chemiluminescence, organic compounds, electrochemistryOther keywords: ruthenium complex, analytical chemistry, nonaqueous ECL luminescence system, complex nanomodification, quenching effect, ECL signal quenching intensity, ECL sensor system, nanofree electrochemiluminescence biosensor system, sulphamethoxazole detection, tris(2,2′‐bipyridyl)ruthenium(II), N‐methyl pyrrolidone recognition, analyte determination, nanomaterials, SMZ concentration detection     

Engineering molecular communications integrated with carbon nanotubes in neural sensor nanonetworks

There have been recent advances in the engineering of molecular communication (MC)‐based networks for nanomedical applications. However, the integration of MC with biomaterials such as carbon nanotubes (CNTs) presents various critical research challenges. In this study, the authors envisaged integrating MC‐based nanonetwork with CNTs to optimise nanonetwork performance. In neural networks, a chronic reduction in the concentration of the neurotransmitter acetylcholine (ACh) eventually leads to the development of neurodegenerative diseases; therefore, they used CNTs as a molecular switch to optimise ACh conductivity supported by artificial MC. Furthermore, MC enables communication between transmitter neurons and receiver neurons for fine‐tuning the ACh release rate according to the feedback concentration of ACh. Subsequently, they proposed a min/max feedback scheme to fine‐tune the expected throughput and ACh transmission efficiency. For demonstration purposes, they deduced analytical forms for the proposed schemes in terms of throughput, incurred traffic rates, and average packet delay.Inspec keywords: carbon nanotubes, cellular biophysics, diseases, feedback, nanomedicine, nanosensors, neural nets, neurophysiologyOther keywords: carbon nanotubes, neural sensor nanonetworks, nanomedical applications, biomaterials, molecular communication‐based nanonetwork, neural networks, neurotransmitter acetylcholine, neurodegenerative diseases, transmitter neurons, receiver neurons     

Improving adaptive receivers performance in molecular communication via diffusion

Forthcoming applications for molecular communications (MC) such as drug‐delivery and health monitoring will require robust receiver capabilities to mitigate channel memory and inter symbol interference caused by previous transmitted symbols. Here, the authors introduce an adaptive weighted algorithm to reduce the influence of these factors. This novel signal detection is deployed on to a concentration‐based MC system with absorbing receiver which is based on the so‐called first passage time concept. The proposed detector has low complexity and does not require explicit channel knowledge. To evaluate authors’ proposed algorithm, a theoretical approach is developed to derive the bit error rate (BER). Numerical results also carried out to verify the accuracy of these formulations and establish that the new detector will achieve better performance in comparison with other common low‐complex detectors under certain scenarios. Additionally, the authors propose a simple pre‐coding technique to combat the sequence of consecutive ones in low ISI scenarios. Also a comparison between detectors is given, which is based on the variation of distance, symbol period, signal‐to‐noise ratio (SNR), and number of molecules.Inspec keywords: radio receivers, error statistics, signal detection, intersymbol interferenceOther keywords: low‐complex detectors, low ISI scenarios, symbol period, signal‐to‐noise ratio, adaptive receivers performance, molecular communication, drug‐delivery, health monitoring, robust receiver capabilities, channel memory, inter symbol interference, previous transmitted symbols, adaptive weighted algorithm, novel signal detection, concentration‐based MC system, absorbing receiver, passage time concept, low complexity, explicit channel knowledge, authors, theoretical approach, bit error rate, numerical results     

Enhancing data rate of molecular communication system using Brownian motion

Inter‐symbol and co‐channel interferences restrict the capacity of molecular communication (MC) systems. In this study, the effect of these interferences on the data rate of MC systems is investigated to design an efficient MC system. To this end, the authors propose an analytical model for a diffusion‐based MC system comprised of two nanomachines when they exploit On/Off keying modulation. They model the Brownian motion of molecules in a one‐dimensional environment as a wiener process and the life expectancy of diffused molecules as an exponential process. First, they consider the inter‐symbol interference to derive the data rate of the MC system as a function of the receiver decision threshold and the symbol time duration. Hence, they propose an algorithm to obtain the optimal values of MC system parameters. Then, the effect of co‐channel interference is considered by assuming parallel MC systems. They propose a minimum distance between adjacent MC systems that their co‐channel interferences effect to be negligible. Moreover, they verify the accuracy of the analytical results by Monte–Carlo simulations. Results show a remarkable improvement in the data rate of MC systems. The derived results may find application in nanonetworks where nanomachines connect together to perform complex tasks.Inspec keywords: channel capacity, Monte Carlo methods, intersymbol interference, stochastic processes, Brownian motion, cochannel interferenceOther keywords: enhancing data rate, molecular communication system, Brownian motion, co‐channel interference, efficient MC system, diffusion‐based MC system, inter‐symbol interference, MC system parameters, parallel MC systems, adjacent MC systems, co‐channel interferences effect     

Distributional and inferential properties of some new multivariate process capability indices for symmetric specification region

Statistical quality control is used to improve performance of processes. Since most of the processes are multivariate in nature, multivariate process capability indices (MPCIs) have been developed by many researchers depending on the context. However, it is generally difficult to understand and calculate MPCIs, compared to their univariate counterparts like $C_p$, $C_{pk}$, and so on. This paper discusses a relatively new development in MPCIs, namely, $C_G(u,v)$, which is a multivariate analogue of $C_p(u,v)$—the celebrated superstructure of univariate process capability indices . Some statistical properties of $C_G(u,v)$ are studied, particularly of $C_G(0,0)$, a member MPCI of the superstructure, which measures potential capability of a multivariate process. A threshold value of $C_G(0,0)$ is computed, and this can be considered as a logical cut-off for other member indices of $C_G(u,v)$ as well. The expression for the upper limit of the proportion of nonconformance is derived as a function of $C_G(0,0)$. Density plots of asymptotic distributions of four major member indices of $C_G(u,v)$, namely, $C_G(0,0)$, $C_G(1,0)$, $C_G(0,1)$, and $C_G(1,1)$, are made. Finally, a numerical example is discussed to supplement the theory developed in this paper.     

Tip‐mould microcontact printing for functionalisation of optical microring resonator

We present an approach to functionalise optical microring resonators as hybridisation platforms, using tip‐mould reactive microcontact printing process. Derived from reactive microcontact printing using an ad hoc mould of polydimethylsiloxane (PDMS), the method functionalises single microring resonator with a target‐specific capture agent. The authors report the functionalisation of silicon nitride (SiN) 200μm diameter microring resonator with single‐strand DNA and the hybridisation detection of 100 nM target analyte, while concurrently monitoring not‐functionalised microring as a control sensor. Results show that the functionalisation approach permits to address single microring resonators with mutual distance lower than 100μm with high precision, enabling a better integration of multiple spotting zones on the chip concerning traditional functionalisation procedures.Inspec keywords: DNA, molecular biophysics, biosensors, microsensors, optical resonators, microcavities, soft lithography, polymers, silicon compounds, integrated optics, optical sensors, micro‐opticsOther keywords: tip‐mould reactive microcontact printing, optical microring resonator, hybridisation platforms, polydimethylsiloxane, PDMS, target‐specific capture agent, single‐strand DNA, hybridisation detection, multiple spotting zones, chip, size 200 mum, SiN     

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      

Optimized identification of earlywood and latewood stiffnesses in loblolly pine in simulated experiments

Knowledge of local mechanical behaviour of wood is especially important as silvicultural practices are modified to allow wood to compete as a relevant material in high technology applications. Challenges associated with identification of local mechanical behaviour have resulted in simplified test geometries designed to determine one or two constitutive parameters. The objective of this work was to design and simulate an entire experiment developed to simultaneously identify the earlywood and latewood orthotropic stiffnesses in loblolly pine in a single specimen and load geometry. The virtual experiment was capable of evaluating optimal orthotropy orientation for reduced identification errors and indicating most favourable choices for data smoothing filters and identification methodology. Additionally, certain ring spacing and latewood percentages were shown to produce large errors, but those combinations are unlikely to occur naturally. The simulation was able to identify $Q_{11},Q_{22}$, and $Q_{66}$ with approximately $\pm 10\%$ error; the $Q_{12}$ error was larger with more scatter. The methodology presented here contributes to the best practices available for heterogeneous stiffness identification.     

Isolation,characterisation and enzymatic activity of Streptomyces sp. and its pH control during fermentation process

Streptomyces sp. with grey white mycelium was isolated from Kodiyakkarai marine segment of east coastal of India. The isolate produced spiny spores and did not produce any diffusible pigments. Various biochemical tests were carried out to confirm the isolate classification. The amylolytic enzyme activity was estimated using the isolated strain which was confirmed by golden yellowish zone formation after using the Gram''s iodine stain. The amount of amylase produced by the isolate was 6.15 U/ml. Higher living cells always produce better enzymes, so that the process parameters especially pH was maintained in fermentation chamber for higher growth and also for large‐scale growth. For maintaining the pH a mathematical process model was developed using the data obtained during the process. The addition of Kalman''s filter along with proportional–integral–derivative controller gave better stability in pH. By maintaining of pH 7, growth rate was significantly increased from 0.51to 0.59 gm/l on day 5 which are discussed in the results and discussions.Inspec keywords: enzymes, pH control, fermentation, biochemistry, biological techniquesOther keywords: isolation, enzymatic activity, Streptomyces sp, pH control, fermentation process, grey white mycelium, Kodiyakkarai marine segment, east coastal India, diffusible pigments, biochemical tests, isolate classification, amylolytic enzyme activity, isolated strain, golden yellowish zone formation, Gram''s iodine stain, fermentation chamber, mathematical process model, Kalman''s filter, proportional–integral–derivative controller, pH 7

Nomenclature

V

culture volume (l)

F

feed flow rate of substrate (l/h)

F(a/b)

acid/base flow rate (ml/h)

Fl

evaporative loss (l)

X

biomass concentration (g/l/lg)

Xi

biomass inlet flow (l)

μ

specific growth rate of biomass (h⁻¹)

kd

Arrhenius constant for cell death

H+

hydrogen ion concentration (mol/l)

γ

proportionality constant (mol H⁺/g biomass)

T

time (s)

     

Efficient monitoring of coefficient of variation with an application to chemical reactor process

Control chart is a useful tool to monitor the performance of the industrial or production processes. Control charts are mostly adopted to detect unfavorable variations in process location (mean) and dispersion (standard deviation) parameters. In the literature, many control charts are designed for the monitoring of process variability under the assumption that the process mean is constant over time and the standard deviation is independent of the mean. However, for many real-life processes, the standard deviation may be proportional to mean, and hence it is more appropriate to monitor the process coefficient of variation (CV). In this study, we are proposing a design structure of the Shewhart type CV control chart under neoteric ranked set sampling with an aim to improve the detection ability of the usual CV chart. A comprehensive simulation study is conducted to evaluate the performance of the proposed $C{V}_{[\mathrm{NRSS}]}$ chart in terms of $ARL$, $MDRL,$ and $SDRL$ measures. Moreover, the comparison of $C{V}_{[\mathrm{NRSS}]}$ chart is made with the existing competitive charts, based on simple random sampling, ranked set sampling (RSS), median RSS, and extreme RSS schemes. The results revealed that the proposed chart has better detection ability as compared to all existing competitive charts. Finally, a real-life example is presented to illustrate the working of the newly proposed CV chart.     

Mesh‐Like Carbon Nanosheets with High‐Level Nitrogen Doping for High‐Energy Dual‐Carbon Lithium‐Ion Capacitors

Li‐ion capacitors (LICs) have demonstrated great potential for bridging the gap between lithium‐ion batteries and supercapacitors in electrochemical energy storage area. The main challenge for current LICs (contain a battery‐type anode as well as a capacitor‐type cathode) lies in circumventing the mismatched electrode kinetics and cycle degradation. Herein, a mesh‐like nitrogen (N)‐doped carbon nanosheets with multiscale pore structure is adopted as both cathode and anode for a dual‐carbon type of symmetric LICs to alleviate the above mentioned problems via a facile and green synthesis approach. With rational design, this dual‐carbon LICs exhibits a broad high working voltage window (0–4.5 V), an ultrahigh energy density of $218.4\mathrm{Wh}{\mathrm{kg}}^{–1}{}_{\mathrm{electrodes}}$ ( $229.8\mathrm{Wh}{\mathrm{L}}^{–1}{}_{\mathrm{electrodes}}$), the highest power density of $22.5\mathrm{kW}{\mathrm{kg}}^{–1}{}_{\mathrm{electrodes}}$ ( $23.7\mathrm{kW}{\mathrm{L}}^{–1}{}_{\mathrm{electrodes}}$) even under an ultrahigh energy density of $97.5\mathrm{Wh}{\mathrm{kg}}^{–1}{}_{\mathrm{electrodes}}$ ( $102.6\mathrm{Wh}{\mathrm{L}}^{–1}{}_{\mathrm{electrodes}}$), as well as reasonably good cycling stability with capacity retention of 84.5% (only 0.0016% capacity loss per cycle) within 10 000 cycles under a high current density of 5 A g^?1. This study provides an efficient method and option for the development of high performance LIC devices.     

Robust observer based control for plasma glucose regulation in type 1 diabetes patient using attractive ellipsoid method

This paper deals with the design of robust observer based output feedback control law for the stabilisation of an uncertain nonlinear system and subsequently apply the developed method for the regulation of plasma glucose concentration in Type 1 diabetes (T1D) patients. The principal objective behind the proposed design is to deal with the issues of intra‐patient parametric variation and non‐availability of all state variables for measurement. The proposed control technique for the T1D patient model is based on the attractive ellipsoid method (AEM). The observer and controller conditions are obtained in terms of linear matrix inequality (LMI), thus allowing to compute easily both the observer and controller gains. The closed‐loop response obtained using the designed controller avoids adverse situations of hypoglycemia and post‐prandial hyperglycemia under uncertain conditions. Further to validate the robustness of the design, closed‐loop simulations of random 200 virtual T1D patients considering parameters within the considered ranges are presented. The results indicate that hypoglycemia and post‐prandial hyperglycemia are significantly reduced in the presence of bounded (±30% ) parametric variability and uncertain exogenous meal disturbance.Inspec keywords: medical control systems, observers, uncertain systems, nonlinear control systems, robust control, control system synthesis, linear matrix inequalities, feedback, sugar, closed loop systems, diseasesOther keywords: virtual T1D patients, type 1 diabetes patients, closed‐loop simulations, uncertain conditions, post‐prandial hyperglycemia, designed controller, closed‐loop response, controller gains, linear matrix inequality, controller conditions, T1D patient model, control technique, intra‐patient parametric variation, principal objective, plasma glucose concentration, uncertain nonlinear system, robust observer based output feedback control law, attractive ellipsoid method, plasma glucose regulation