STR-944: EFFECTS OF FINITE ELEMENT MODELLING APPROACH FOR PRESTRESSING SYSTEM ON THE PRESSURE CAPACITY OF A CANDU CONTAINMENT STRUCTURE

The primary objective of this article is to investigate the response of a CANDU®1 nuclear power plant containment structure to a much higher internal pressure that could be encountered during a severe accident. In this study, for the prestressed containment structure, a detailed model is obtained by a full 3D model. Nonlinear finite element method is employed to predict the response of the structure using ANSYS software. The major challenges for modelling prestressing tendon elements are to accommodate parameters affecting prestressing forces. In previous research studies, the prestressing system is modelled using an equivalent pressure and tendon end forces, and tendons are modelled as smeared reinforcement in the concrete elements. In this study, the prestressing tendons are modelled using discrete elements. This method enables the capability of the model to update the prestressing forces accommodating the non-uniform losses. The difference in the response of the structure using the discrete model for the prestressing tendons and the smeared approach is 15 percent. It is observed that the containment structure, meets the design requirements of the current standards as it behaves linearly up to 1.5 times the design pressure, and the ultimate pressure capacity is estimated as 2.7 times the design pressure. The ultimate pressure capacity is reached when the prestressing tendon rupture at the dome

Improved prosthetic hand control with concurrent use of myoelectric and inertial measurements

Abstract Background Myoelectric pattern recognition systems can decode movement intention to drive upper-limb prostheses. Despite recent advances in academic research, the commercial adoption of such systems remains low. This limitation is mainly due to the lack of classification robustness and a simultaneous requirement for a large number of electromyogram (EMG) electrodes. We propose to address these two issues by using a multi-modal approach which combines surface electromyography (sEMG) with inertial measurements (IMs) and an appropriate training data collection paradigm. We demonstrate that this can significantly improve classification performance as compared to conventional techniques exclusively based on sEMG signals. Methods We collected and analyzed a large dataset comprising recordings with 20 able-bodied and two amputee participants executing 40 movements. Additionally, we conducted a novel real-time prosthetic hand control experiment with 11 able-bodied subjects and an amputee by using a state-of-the-art commercial prosthetic hand. A systematic performance comparison was carried out to investigate the potential benefit of incorporating IMs in prosthetic hand control. Results The inclusion of IM data improved performance significantly, by increasing classification accuracy (CA) in the offline analysis and improving completion rates (CRs) in the real-time experiment. Our findings were consistent across able-bodied and amputee subjects. Integrating the sEMG electrodes and IM sensors within a single sensor package enabled us to achieve high-level performance by using on average 4-6 sensors. Conclusions The results from our experiments suggest that IMs can form an excellent complimentary source signal for upper-limb myoelectric prostheses. We trust that multi-modal control solutions have the potential of improving the usability of upper-extremity prostheses in real-life applications

Controversies in acute kidney injury: conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) conference

In 2012, Kidney Disease: Improving Global Outcomes (KDIGO) published a guideline on the classification and management of acute kidney injury (AKI). The guideline was derived from evidence available through February 2011. Since then, new evidence has emerged that has important implications for clinical practice in diagnosing and managing AKI. In April of 2019, KDIGO held a controversies conference entitled Acute Kidney Injury with the following goals: determine best practices and areas of uncertainty in treating AKI; review key relevant literature published since the 2012 KDIGO AKI guideline; address ongoing controversial issues; identify new topics or issues to be revisited for the next iteration of the KDIGO AKI guideline; and outline research needed to improve AKI management. Here, we present the findings of this conference and describe key areas that future guidelines may address

Chemical Stability of Bioglass in Simulated Oral Environment

Statement of Problem: Bioglasses are a series of biocompatible dental materials, which are considered as light conducting inserts in resin composite restorations. Consequently, their chemical stability is more essential when they are used in conjunction with resin composite. Objectives: The aim of this study was to evaluate and compare the chemical stability of Bioglass with dental porcelain and resin composite by determining the amount of released K+, Na+, Ca2+ ions and silicone elements from these materials as a result of exposure to tested solutions with different pH levels including: Sodium Bicarbonate [SB, (pH=9.2)], Sodium Buffer Lactate [SBL, (pH=2.4)], Acetic Acid [AA, (pH=2.4)], and Distilled Water [DW, (pH=6.2)]. Materials and Methods: In this experimental study, forty 2.0 × 4.0 cylindrical rods for each tested material group (Dental porcelain, Resin composite and Bioglass) were prepared. They were divided into four subgroups of 10 rods each, which immersed in one of the four testing solutions in a designated container. The containers were stored at 50°C and 100% humidity for one week. The released ions were measured by using a spectrophotometer (µg/cm2/ml). The data were statistically analyzed by nonparametric Kruskal-Wallis H test. Results: It was observed that the tested materials released ions at different levels of concentration. The significant amounts of Sodium, Calcium, and Silicon ions release were measured in Bioglass subgroups in all the tested solutions (p < 0.001). Potassium ion release from dental porcelain was the largest in all solutions except for AA in which Bioglass had the greatest potassium ion release (p < 0.001). Conclusions: A greater structural instability was observed for Biogalss group than dental porcelain and resin composite in testing solutions with different pH .level

EMG prediction from motor cortical recordings via a nonnegative point-process filter

A constrained point process filtering mechanism for prediction of electromyogram (EMG) signals from multi-channel neural spike recordings is proposed here. Filters from the Kalman family are inherently sub-optimal in dealing with non-Gaussian observations, or a state evolution that deviates from the Gaussianity assumption. To address these limitations, we modeled the non-Gaussian neural spike train observations by using a generalized linear model (GLM) that encapsulates covariates of neural activity, including the neurons’ own spiking history, concurrent ensemble activity, and extrinsic covariates (EMG signals). In order to predict the envelopes of EMGs, we reformulated the Kalman filter (KF) in an optimization framework and utilized a non-negativity constraint. This structure characterizes the non-linear correspondence between neural activity and EMG signals reasonably. The EMGs were recorded from twelve forearm and hand muscles of a behaving monkey during a grip-force task. For the case of limited training data, the constrained point process filter improved the prediction accuracy when compared to a conventional Wiener cascade filter (a linear causal filter followed by a static non-linearity) for different bin sizes and delays between input spikes and EMG output. For longer training data sets, results of the proposed filter and that of the Wiener cascade filter were comparable

Techno-economic Assessment of a Hydrogen-based Islanded Microgrid in North-east

Currently, renewable energy-based generators are considered worldwide to achieve net zero targets. However, the stochastic nature of renewable energy systems leads to regulation and control challenges for power system operators, especially in remote and regional grids with smaller footprints. A hybrid system (i.e., solar, wind, biomass, energy storage) could minimise this issue. Nevertheless, the hybrid system is not possible to develop in many islands due to the limited land area, geographical conditions, and others. Hydrogen as a carrier of clean energy can be used in locations where the installation of extensive or medium-scale renewable energy facilities is not permissible due to population density, geographical constraints, government policies, and regulatory issues. This paper presents a techno-economic assessment of designing a green hydrogen-based microgrid for a remote island in North-east Australia. This research work determines the optimal sizing of microgrid components using green hydrogen technology. Due to the abovementioned constraints, the green hydrogen production system and the microgrid proposed in this paper are located on two separate islands. The paper demonstrates three cost-effective scenarios for green hydrogen production, transportation, and electricity generation. This work has been done using Hybrid Optimisation Model for Multiple Energy Resources or HOMER Pro simulation platform. Simulation results show that the Levelized Cost of Energy using hydrogen technology can vary from AU$0.37/kWh to AU$1.08/kWh depending on the scenarios and the variation of key parameters. This offers the potential to provide lower-cost electricity to the remote community. Furthermore, the CO2 emission could be reduced by 17,607,77 kg/year if the renewable energy system meets 100% of the electricity demand. Additionally, the sensitivity analysis in this paper shows that the size of solar PV and wind used for green hydrogen production can further be reduced by 50%. The sensitivity analysis shows that the system could experience AU$0.03/kWh lower levelized cost if the undersea cable is used to transfer the generated electricity between islands instead of hydrogen transportation. However, it would require environmental approval and policy changes as the islands are located in the Great Barrier Reef

Epidemiology of cardiogenic shock and cardiac arrest complicating non‐ST‐segment elevation myocardial infarction: 18‐year US study

Abstract Aims This study aims to evaluate the impact of the combination of cardiogenic shock (CS) and cardiac arrest (CA) complicating non‐ST‐segment elevation myocardial infarction (NSTEMI). Methods and results Adult (>18 years) NSTEMI admissions using the National Inpatient Sample database (2000 to 2017) were stratified by the presence of CA and/or CS. Outcomes of interest included in‐hospital mortality, early coronary angiography, hospitalization costs, and length of stay. Of the 7 302 447 hospitalizations due to NSTEMI, 147 795 (2.0%) had CS only, 155 522 (2.1%) had CA only, and 41 360 (0.6%) had both CS and CA. Compared with 2000, the adjusted odds ratios (ORs) and 95% confidence interval (CIs) for CS, CA, and both CS and CA in 2017 were 3.75 (3.58–3.92), 1.46 (1.42–1.50), and 4.52 (4.16–4.87), respectively (all P < 0.001). The CS + CA (61.2%) cohort had higher multiorgan failure than CS (42.3%) and CA only (32.0%) cohorts, P < 0.001. The CA only cohort had lower rates of overall (52% vs. 59–60%) and early (17% vs. 18–27%) angiography compared with the other groups (all P < 0.001). CS + CA admissions had higher in‐hospital mortality compared with those with CS alone (aOR 4.12 [95% CI 4.00–4.24]), CA alone (aOR 1.69 [95% CI 1.65–1.74]), or without CS/CA (aOR 22.66 [95% CI 22.06–23.27]). The presence of CS, either alone or with CA, was associated with higher hospitalization costs and longer hospital length of stay. Conclusions The combination of CS and CA is associated with higher rates of acute non‐cardiac organ failure and in‐hospital mortality in NSTEMI admissions as compared with those with either CS or CA alone