Assessing the effects of time-dependent restrictions and control actions to flatten the curve of COVID-19 in Kazakhstan.

This article presents the assessment of time-dependent national-level restrictions and control actions and their effects in fighting the COVID-19 pandemic. By analysing the transmission dynamics during the first wave of COVID-19 in the country, the effectiveness of the various levels of control actions taken to flatten the curve can be better quantified and understood. This in turn can help the relevant authorities to better plan for and control the subsequent waves of the pandemic. To achieve this, a deterministic population model for the pandemic is firstly developed to take into consideration the time-dependent characteristics of the model parameters, especially on the ever-evolving value of the reproduction number, which is one of the critical measures used to describe the transmission dynamics of this pandemic. The reproduction number alongside other key parameters of the model can then be estimated by fitting the model to real-world data using numerical optimisation techniques or by inducing ad-hoc control actions as recorded in the news platforms. In this article, the model is verified using a case study based on the data from the first wave of COVID-19 in the Republic of Kazakhstan. The model is fitted to provide estimates for two settings in simulations; time-invariant and time-varying (with bounded constraints) parameters. Finally, some forecasts are made using four scenarios with time-dependent control measures so as to determine which would reflect on the actual situations better.

Robust Position Control of an Over-actuated Underwater Vehicle under Model Uncertainties and Ocean Current Effects Using Dynamic Sliding Mode Surface and Optimal Allocation Control.

Underwater vehicles (UVs) are subjected to various environmental disturbances due to ocean currents, propulsion systems, and un-modeled disturbances. In practice, it is very challenging to design a control system to maintain UVs stayed at the desired static position permanently under these conditions. Therefore, in this study, a nonlinear dynamics and robust positioning control of the over-actuated autonomous underwater vehicle (AUV) under the effects of ocean current and model uncertainties are presented. First, a motion equation of the over-actuated AUV under the effects of ocean current disturbances is established, and a trajectory generation of the over-actuated AUV heading angle is constructed based on the line of sight (LOS) algorithm. Second, a dynamic positioning (DP) control system based on motion control and an allocation control is proposed. For this, motion control of the over-actuated AUV based on the dynamic sliding mode control (DSMC) theory is adopted to improve the system robustness under the effects of the ocean current and model uncertainties. In addition, the stability of the system is proved based on Lyapunov criteria. Then, using the generalized forces generated from the motion control module, two different methods for optimal allocation control module: the least square (LS) method and quadratic programming (QP) method are developed to distribute a proper thrust to each thruster of the over-actuated AUV. Simulation studies are conducted to examine the effectiveness and robustness of the proposed DP controller. The results show that the proposed DP controller using the QP algorithm provides higher stability with smaller steady-state error and stronger robustness.

Osmotin-loaded magnetic nanoparticles with electromagnetic guidance for the treatment of Alzheimer's disease.

Alzheimer's disease (AD) is the most prevalent age-related neurodegenerative disease, pathologically characterized by the accumulation of aggregated amyloid beta (Aß) in the brain. Here, we describe for the first time the development of a new, pioneering nanotechnology-based drug delivery approach for potential therapies for neurodegenerative diseases, particularly AD. We demonstrated the delivery of fluorescent carboxyl magnetic Nile Red particles (FMNPs) to the brains of normal mice using a functionalized magnetic field (FMF) composed of positive- and negative-pulsed magnetic fields generated by electromagnetic coils. The FMNPs successfully reached the brain in a few minutes and showed evidence of blood-brain barrier (BBB) crossing. Moreover, the best FMF conditions were found for inducing the FMNPs to reach the cortex and hippocampus regions. Under the same FMF conditions, dextran-coated Fe3O4 magnetic nanoparticles (MNPs) loaded with osmotin (OMNP) were transported to the brains of Aß1-42-treated mice. Compared with native osmotin, the OMNP potently attenuates Aß1-42-induced synaptic deficits, Aß accumulation, BACE-1 expression and tau hyperphosphorylation. This magnetic drug delivery approach can be extended to preclinical and clinical use and may advance the chances of success in the treatment of neurological disorders like AD in the future.

In Silico Magnetic Nanocontainers Navigation in Blood Vessels: A Feedback Control Approach.

Magnetic nanoparticles (MNPs) are recently used in a drug delivery system to pass the blood brain barrier. However, because the magnetic force acting on particles is proportional to their volumes, as the size of particles is small, the large magnetic field is required to produce enough magnetic force for overcoming the hydrodynamic drag force as well as other forces in blood vessels. Other difficulties for controlling MNPs are the complicated behavior of hydrodynamic drag force and uncertain factors in their dynamics. Therefore, open-loop control methods cannot guarantee guiding every MNP to the correct location. Considering these challenges, this paper introduces a feedback control approach for magnetic nanoparticles (MNPs) in blood vessels. To the best of our knowledge, this is the first time feedback controller that is designed for MNPs without aggregation. Simulation studies in MATLAB and real-time verifications on a physical model in COMSOL-MATLAB interface are performed to prove the feasibility of the proposed approach. It is shown that the proposed control scheme can accurately and effectively navigate the MNP to the correct path with feasible hardware supports.

Guidance of Magnetic Nanocontainers for Treating Alzheimer's Disease Using an Electromagnetic, Targeted Drug-Delivery Actuator.

The "impermeability" of the blood-brain barrier (BBB) has hindered effective treatment of central nervous system (CNS) disorders such as Alzheimer's disease (AD), which is one of the most common neurodegenerative disorders. A drug can be delivered to a targeted disease site effectively by applying a strong electromagnetic force to the conjugate of a drug and magnetic nanocontainers. This study developed a novel nanotechnology-based strategy to deliver therapeutic agents to the brain via the BBB as a possible therapeutic approach for AD. First, a novel approach for an electromagnetic actuator for guiding nanocontainers is introduced. Then, we analyzed the in vivo uptake in mice experimentally to evaluate the capacity of the nanocontainers. In the mouse model, we demonstrated that magnetic particles can cross the normal BBB when subjected to external electromagnetic fields of 28 mT (0.43 T/m) and 79.8 mT (1.39 T/m). Our study also assessed the differential effects of pulsed (0.25, 0.5, and 1 Hz) and constant magnetic fields on the transport of particles across the BBB in mice injected with magnetic nanoparticles (MNPs) via a tail vein. The applied magnetic field was either kept constant or pulsed on and off. Relative to a constant magnetic field, the rate of MNP uptake and transport across the BBB was enhanced significantly by a pulsed magnetic field. Localization inside the brain was established using fluorescent MNPs. These results using 770-nm fluorescent carboxyl magnetic nanocontainers demonstrated the feasibility of the proposed electromagnetic targeted drug delivery actuator. These results establish an effective strategy for regulating the biodistribution of MNPs in the brain through the application of an external electromagnetic field. This might be a valuable targeting system for AD diagnosis and therapy.