In silico modelling of neuron signal impact of cytokine storm-induced demyelination

In this study, we develop an in silico model of a neuron's behaviour under demyelination caused by a cytokine storm to investigate the effects of viral infections in the brain. We use a comprehensive model to measure how cytokine-induced demyelination affects the propagation of action potential (AP) signals within a neuron. We analysed the effects of neuron-neuron communications by applying information and communication theory at different levels of demyelination. Our simulations demonstrate that virus-induced degeneration can play a role in the signal power and spiking rate, which compromise the propagation and processing of information between neurons. We propose a transfer function to model the weakening effects on the AP. Our results show that demyelination induced by a cytokine storm not only degrades the signal but also impairs its propagation within the axon. Our proposed in silico model can analyse virus-induced neurodegeneration and enhance our understanding of virus-induced demyelination.

Optimal tuning of PID controllers with derivative filter for stable processes using three points from the step response

This paper proposes a novel approach for tuning Proportional Integral Derivative (PID) controllers, utilizing experimental data obtained from an open-loop step input. We propose to use the measurements of the times taken to reach 5%, 35.3% and 85.3% of the final output, as well as the process static gain, to tune the controller. The tuning equations are applicable for a wide range of stable and over damped systems. Starting from an approximate model with three real poles and time delay (obtained from the measurements), the tuning equations approximate the controller that minimizes the Integral of Absolute Error (IAE) of the disturbance response. The designer can freely decide the Sensitivity Margin (Ms) to fix a desired robustness, as a difference with respect to other known methods where the user chooses among few predefined robustness values. The user can also select freely the derivative filter parameter, N, to find the required compromise between speed response and measurement noise amplification. For N=0 a PI controller is chosen. As N increases, a faster PID controller is selected, with higher noise amplification. We have also developed a web-based application and an Android application, downloadable for free, that implement the tuning equations as well as the whole required procedure.

Probing Surface Photovoltage Effect Using Photoassisted Secondary Electron Emission

While the properties of surfaces and interfaces are crucial to modern devices, they are commonly difficult to explore since the signal from the bulk often masks the surface contribution. Here we introduce a methodology based on scanning electron microscopy (SEM) coupled with a pulsed laser source, which offers the capability to sense the topmost layer of materials, to study the surface photovoltage (SPV) related effects. This method relies on a pulsed optical laser to transiently induce an SPV and a continuous primary electron beam to produce secondary electron (SE) emission and monitor the change of the SE yield under laser illumination. We observe contrasting behaviors of the SPV-induced SE yield change on n-type and p-type semiconductors. We further study the dependence of the SPV-induced SE yield on the primary electron beam energy, the optical fluence, and the modulation frequency of the optical excitation, which reveal the details of the dynamics of the photocarriers in the presence of the surface built-in potential. This fast, contactless, and bias-free technique offers a convenient and robust platform to probe surface electronic phenomena, with great promise to probe nanoscale effects with a high spatial resolution. Our result further provides a basis to understand the contrast mechanisms of emerging time-resolved electron microscopic techniques, such as the scanning ultrafast electron microscopy.

Designing of IMC-PID Controller for Higher-order Process Based on Model Reduction Method and Fractional Coefficient Filter with Real-time Verification

An improved model reduction scheme is proposed here for higher-order processes and subsequently an enhanced IMC-PID controller is designed based on the obtained reduced model. In the proposed scheme, higher-order processes are estimated as first-order-plus-dead-time (FOPDT) model. Designed IMC controller includes a filter having two separate time constants with fractional order coefficients. Efficacy of the proposed model reduction scheme is verified in terms of closed loop performance evaluation for higher-order minimum and non-minimum phase process models in comparison with improved SIMC (iSIMC) controller (Grimholt. Optimal PI and PID control of first-order plus delay processes and evaluation of the original and improved SIMC rules. J Process Control. 2018;70:36–46). Overall performance enhancement for the proposed method is demonstrated through simulation study as well as real-time experimentation on a level control loop.

Fractional Order PID Controller Design for Supply Manifold Pressure Control of Proton Exchange Membrane Fuel Cell

In this work, fractional order PIλDµ (FOPID) controller designed to enhance the dynamic performance of the Proton Exchange Membrane (PEM) fuel cell. The control objective is to regulate the supply manifold pressure on cathode side to maintain oxygen excess ratio of the PEM fuel cell. The higher order PEM fuel cell model is approximated to First order plus time delay (FOPTD) model for controller design and analysis. The proposed FOPID controller is designed based on minimization of Integral Absolute Error (IAE) with pre specified maximum sensitivity (Ms) as a constraint. Uncertainty and measurement noise analysis is carried out to verify the robustness of the designed controller. The simulation results of proposed FOPID controller is compared with other designing methods. Based on minimization of IAE value, the SP 1.4 FOPID controller produces IAE value of 0.255 where as AMIGO 1.4 tuning method and ZN based FOPID tuning methods produces 0.263 and 3.817 respectively for perfect case. Based on maximum sensitivity Ms is 1.4, the SP 1.4 FOPID controller produces Ms of 1.4 where as AMIGO 1.4 PID and ZN based FOPID tuning methods produces Ms of 1.5 and 1.25 respectively for perfect case, which indicates that the proposed SP 1.4 FOPID controller is robust. The proposed SP 1.4 FOPID provides better values (rise time of 0.331 sec, settling time of 0.692 sec and percentage of peak overshoot of 0.797 for perfect case) when compared with other methods. From simulation results, for the control of supply manifold pressure of PEM fuel cell, the proposed fractional-order PID controllers improves the closed loop performance in terms of rise time, settling time and percentage of peak overshoot when compared to the integer-order PID controllers.

Synthesis of N-Protected Staurosporinones

We report a method for the synthesis of N-protected staurosporinones, which are useful for the synthesis of indolo[2,3-a]pyrrolo[3,4-c]carbazole alkaloids and related compounds. An interaction of gramine methiodide (2) with 3-(N-benzyl)indolylacetonitrile (3) in the presence of t-BuLi, followed by a CF3COOH-catalyzed intramolecular indole-indole coupling and dehydrogenation with DDQ, produced 5-cyanoindolo[2,3-a]carbazole 6 almost quantitatively. Reduction of its cyano group followed by N-benzylation produced N-benzylaminomethylindolo[2,3-a]carbazole 8b, which was subjected to Pd(OAc)2-catalyzed direct aromatic carbonylation to give N-protected staurosporinone 9b. Treatment with AlCl3 in anisole removed N-benzyl groups to afford staurosporinone quantitatively.