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Abstract Background Healthcare policy implemented during the COVID-19 pandemic may have impacted the health of patients with heart failure. Australian data provide a unique opportunity to examine service disruption independent of significant COVID-19 burden. This study aimed to examine heart failure care during the pandemic in New South Wales (NSW). Methods Analysis of hospital utilisation among patients aged ≥ 18 years with a primary diagnosis of heart failure conducted using linked administrative health records from hospital admission, emergency department, non-admitted services, and mortality data collections. Health service utilisation and outcomes were compared “Pre-pandemic” (PP): 16th March 2018 – 28th August 2019 and “During pandemic” (DP): 16th March 2020 – 28th August 2021. Mortality data were available until December 2021. Results Heart failure-related ED presentations and hospital admissions were similar between the periods (PP = 15,324 vs DP = 15,023 ED presentations, PP = 24,072 vs DP = 23,145 hospital admissions), though rates of admission from ED were lower DP (PP = 12,783/15,324 (83.4% [95% CI 82.8-84.0]) vs DP = 12,230/15,023 (81.4% [95% CI 80.8-82.0%]). There was no difference according to age, sex, rurality, or socioeconomic status. Outpatient volume reduced DP (PP = 44,447 vs DP = 35,801 occasions of service), but telehealth visits increased nearly threefold (PP = 5,978/44,447 (13.4% [95% CI 13.1-13.8%]) vs DP = 15,901/35,801 (44.4% [95% CI 43.9-44.9%]) with highest uptake among the wealthy and those in major cities. Time to heart failure-related ED presentation, hospitalisation or all-cause mortality following index admission was longer DP (PP = 273 [IQR 259, 290] days, DP = 323 [IQR 300, 342] days, HR 0.91 [95% CI 0.88, 0.95]). Conclusions Policies implemented DP had minimal impact on volumes of inpatient heart failure care in NSW hospitals, but there were fewer admissions from ED and reduced volumes of publicly funded outpatient care. A rapid shift from patient-facing to remotely delivered care enabled compliance with restrictions and was associated with increased time to heart failure-related adverse events, but access was not afforded equally across the socio-demographic spectrum.

In this article, we manage the energy consumption of numerous intelligent homes and charging stations including several electric vehicles in real-time using a computationally efficient predictive controller. The studied scenario is made up of a couple of primary layers. At the low level of the hierarchical framework, users are clustered into different groups based on their vehicles' departure times. Meanwhile, the energy consumption of subordinate users is controlled by multiple aggregators, interaction among which is modeled as an aggregative game. The high-level interactive and distributed control problem can be solved by a predictive controller, wherein the terminal constraints related to the reference energy of each cluster's storage capacity are transferred to the end of the prediction horizon. Additionally, each aggregator can only exchange local data with some neighboring aggregators through an untrustable communication network. As a result of denial of service attacks on the aggregators' network, the strong connectivity of the communication graph may be directly destroyed, leading to performance degradation. To address such an issue, each aggregator reconstructs the attacked information of its neighbors using a linear combination of received data in the last two iterations. Furthermore, a time-ofuse pricing tariff whose value is small for faithful households is investigated so that convergence time remains unaltered. Practical examples are simulated to assess the usefulness of the proposed iterative algorithm. [ABSTRACT FROM AUTHOR]

In distribution networks, failure to smooth the load curve leads to voltage drop and power quality loss. In this regard, electric vehicle batteries can be used to smooth the load curve. However, to persuade vehicle owners to share their vehicle batteries, we must also consider the owners' profits. A challenging problem is that existing methods do not take into account the vehicle owner demands including initial and final states of charge and arrival and departure times of vehicles. Another problem is that battery capacity of each vehicle varies depending on the type of vehicle; which leads to uncertainties in the charging and discharging dynamics of batteries. In this paper, we propose a modified mean-field method so that the load curve is smoothed, vehicle owner demands are met, and different capacities of electric vehicle batteries are considered. The simulation results show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Objective and Aim. Atorvastatin inhibits cholesterol synthesis which is critically important in the formation of the viral envelope and secretion. The efficacy and safety of giving atorvastatin (40 mg/day) as an adjunct to tenofovir in the treatment of hepatitis B (HBV) were assessed. Method. In this single-blind clinical trial, 40 patients with active chronic hepatitis B were randomly allocated to treatment or control groups. The treatment group received the standard treatment for chronic HBV (300 mg tenofovir twice a day) along with 40 mg/day atorvastatin for 12 months, while the control group received a placebo once daily in addition to the standard tenofovir regimen. Serum aspartate aminotransferase (AST), alanine aminotransferase (ALT), and HBV DNA copy numbers were measured at the beginning of the treatment and 1, 3, 6, 9, 12 months later. Results. One month after starting the treatment, the HBV copy number in the atorvastatin + tenofovir-treated group was significantly lower, by 200×, compared with the control group. After three months of the treatment, there was no detectable HBV DNA in 50% of the atorvastatin + tenofovir-treated group compared with 30% in the control group. The half-life of plasma viral load was 2.03 and 3.32 months in the atorvastatin + tenofovir-treated and control groups, respectively. No adverse events due to taking atorvastatin were observed. Conclusions. The combination of atorvastatin with tenofovir increased antiviral activity and led to a faster recovery from viral infection. Therefore, this modality can be recommended as a safe combination therapy for chronic hepatitis B patients. [ABSTRACT FROM AUTHOR]

Background Hypertensive disorders of pregnancy, gestational diabetes, and having a small‐for‐gestational‐age baby are known to substantially increase a woman's risk of cardiovascular disease. Despite this, evidence for models of care that mitigate cardiovascular disease risk in women with these pregnancy‐related conditions is lacking. Methods and Results A 6‐month prospective cohort study assessed the effectiveness of a multidisciplinary Women's Heart Clinic on blood pressure and lipid control in women aged 30 to 55 years with a past pregnancy diagnosis of hypertensive disorders of pregnancy, gestational diabetes, or a small‐for‐gestational age baby in Melbourne, Australia. The co‐primary end points were (1) blood pressure

This paper investigates the problem of unknown input estimation such as acceleration, target class, and maneuvering target tracking using a hybrid algorithm. One of the challenges of unknown input estimation is that no effective method has been presented so far that could be applied to general cases. The available methods are ineffective when the range of variation of the unknown input parameter is large. Also, the issue of determining the system class could improve the performance of the tracking algorithms in many applications. Using the Bayesian theory, the posterior distribution functions of state and parameter could be obtained concurrently. In the proposed algorithm, Liu and West and multimode filters are used for unknown parameters' estimation, and particle filter is used to estimate the posterior density function. Parameter estimation and mode determination could be used in the resampling phase to weight the particles in accordance with the target mode. The main advantage of the adaptive parameter estimation approach is its ability to provide a quick estimation of the abruptly changing parameters from noninformative prior knowledge and to do this for multiple unknown parameters. Simulation results show that the proposed algorithm performs better than the other input estimation and tracking methods. [ABSTRACT FROM AUTHOR]

This paper investigates maneuvering-target tracking problem based on a multisensor system and interacting multiple model (IMM). The estimation is performed by a novel particle filter (PF) with a capability to deal with the state-dependent noises and interference of the sensors' coverage environment. An adaptive sensor selection algorithm, where some sensors are selected in each stage based on the signal-to-interference pulse noise ratio (SINR) and participate in the state estimation, is proposed. To deal with the effect of interference, we focus on designing and implementing the sensor selection algorithm, where a multisensor system with nonuniform arrays is derived by solving a convex optimization problem. On this basis, a nonuniform array of sensors is selected in each time interval aiming at maximizing the SINR of the received information from the undercoverage area. This would allow tracking in practical environments experiences interference. This method also is able to reduce the tracking error rate. [ABSTRACT FROM AUTHOR]

The article describes the experience of the state of Maryland with the COVID-19 surge. Topics discussed include provision of the state's Health Care Decisions Act (HCDA), the formation of a COVID-19 Working Group by Maryland Healthcare Ethics Committee Network (MHECN) in mid-March 2019, and benefit of a regional ethics network.

The paper develops finite-time consensus control for multi-agent systems by considering disturbances and input saturation. A new adaptive-terminal sliding mode control is suggested to solve consensus control within a finite time. Two cases are solved in the paper. In the first case, it is assumed that disturbances are with known upper. To achieve the consensus purpose within the finite time, in this case, the control inputs are designed based on terminal sliding mode technique by considering the input signal saturation. Also, the control inputs are modified to reduce the high dependency of reaching times to initial speeds. In the second case, the agents are subjected to disturbances with unknown upper bounds. To handle the problem, the control signals are acquired by combining the adaptive and terminal sliding mode methods. By considering saturation boundary and disturbances with unknown upper band, a new adaptive-terminal sliding mode method is designed to control the multi-agent system in reduced settling and reaching times. The proposed techniques efficiency is confirmed by numerical simulations. [ABSTRACT FROM AUTHOR]

This paper presents some computationally efficient algorithms for online tracking of set points in robust model predictive control context subject to state and input constraints. The nonlinear systems are represented by a linear model along with an additive nonlinear term which is locally Lipschitz. As an unstructured uncertainty, this term is replaced in the robust stability constraint by its Lipschitz coefficient. A scheduled control technique is employed to transfer the system to desired set points, given online, by designing local robust model predictive controllers. This scheme includes estimating the regions of feasibility and stability of the related equilibriums and online switching among the local controllers. The proposed optimisation problems for calculating the regions of feasibility and stability are defined as linear matrix inequalities that can be solved in polynomial time. The effectiveness of the proposed algorithms is illustrated by an example. [ABSTRACT FROM AUTHOR]

In this paper, by introducing a new general state-space form for uncertain linear time-invariant fractional-order systems subjected to interval and polytopic uncertainties, two problems including robust stability analysis and robust stabilization of the presented systems are investigated. Subsequently, two sufficient conditions in terms of several linear matrix inequalities for the problems mentioned are concluded as two separate theorems. It is assumed that the fractional order α is a known constant belonging to 0 < α < 1 . Simulation results of two different numerical examples demonstrate that the provided sufficient conditions are applicable and effective for tackling robust stability and stabilization problems. [ABSTRACT FROM AUTHOR]

This paper presents a new analytical method to design fractional-order proportional–integral–derivative (PID) controllers. The control parameters are calculated so that the closed-loop system approximates a desired transfer function with transient response requirements. This function is determined based on the characteristic ratio assignment method. The control parameters are calculated by matching the first three moments of the closed-loop transfer function with the corresponding values of the desired system. Furthermore, to ensure closed-loop stability the proposed method is improved by using the shifted moments around the crossover frequency. Illustrative examples are given to show the performance of the proposed method. [ABSTRACT FROM AUTHOR]