Antigenic properties of the SARS-CoV-2 nucleoprotein are altered by the RNA admixture

Determining the presence of antibodies to the SARS-CoV-2 antigens is the best way to identify infected people, regardless of the development of symptoms of COVID-19. The nucleoprotein (NP) of the SARS-CoV-2 is an immunodominant antigen of the virus; anti-NP antibodies are detected in persons previously infected with the virus with the highest titers. Many test systems for detecting antibodies to SARS-CoV-2 contain NP or its fragments as antigen. The sensitivity and specificity of such test systems differ significantly, which can be explained by variations in the antigenic properties of NP caused by differences in the methods of its cultivation, isolation and purification. We investigated this effect for the Escherichia coli-derived SARS-CoV-2 NP, obtained from the cytoplasm in the soluble form. We hypothesized that co-purified nucleic acids that form a strong complex with NP might negatively affect NP’s antigenic properties. Therefore, we have established the NP purification method, which completely eliminates the RNA in the NP preparation. Two stages of RNA removal were used: treatment of the crude lysate of E. coli with RNase A and subsequent selective RNA elution with 2 M NaCl solution. The resulting NP without RNA has a significantly better signal-to-noise ratio when used as an ELISA antigen and tested with a control panel of serum samples with antibodies to SARS-CoV-2; therefore, it is preferable for in vitro diagnostic use. The same increase of the signal-to-noise ratio was detected for the free N-terminal domain of the NP. Complete removal of RNA complexed with NP during purification will significantly improve its antigenic properties, and the absence of RNA in NP preparations should be controlled during the production of this antigen.

An Interaction Less Duo Control Strategy for Bi-polar Voltage Source Converter in Renewables Integrated Multi-Terminal HVDC (MTDC) Grids

The PVF or PV²Fdouble droop control is commended for its ability to regulate both the dc voltage and frequency in a decentralized approach. However, a convincing response is not achieved due to an interaction between the droop characteristics of dc voltage and frequency. This interaction affects the dc voltage and frequency support of the AC system surrounded Multi-Terminal HVDC (AC-MTDC) grid. To overcome this effect, a Duo control strategy is proposed in this paper, which takes advantage of a Bi-polar Voltage Source Converter (B-VSC) topology in the MTDC grid. The virtue of proposed control technique is emphasized by comparing it with the existing $ PV²F double droop control along with three case studies and two test systems. The validation of interaction less Duo control strategy is carried out on five terminal CIGRE DC grid benchmark model integrated into two area power system (AC-MTDC grid-1) and New England IEEE 39 bus system (AC-MTDC grid-2). These test systems are simulated in PSCAD/EMTDC software.

An Interaction Less Duo Control Strategy for Bi-polar Voltage Source Converter in Renewables Integrated Multi-Terminal HVDC (MTDC) Grids

The PVF or PV²Fdouble droop control is commended for its ability to regulate both the dc voltage and frequency in a decentralized approach. However, a convincing response is not achieved due to an interaction between the droop characteristics of dc voltage and frequency. This interaction affects the dc voltage and frequency support of the AC system surrounded Multi-Terminal HVDC (AC-MTDC) grid. To overcome this effect, a Duo control strategy is proposed in this paper, which takes advantage of a Bi-polar Voltage Source Converter (B-VSC) topology in the MTDC grid. The virtue of proposed control technique is emphasized by comparing it with the existing $ PV²F double droop control along with three case studies and two test systems. The validation of interaction less Duo control strategy is carried out on five terminal CIGRE DC grid benchmark model integrated into two area power system (AC-MTDC grid-1) and New England IEEE 39 bus system (AC-MTDC grid-2). These test systems are simulated in PSCAD/EMTDC software.

A Heuristic Methods-Based Power Distribution System Optimization Toolbox

This paper proposes a toolbox for simulating the effective integration of renewable energy sources into distribution systems. The toolbox uses four heuristic methods: the particle swarm optimization (PSO) method, and three recently developed methods, namely Gray Wolf Optimization (GWO), Ant Lion Optimization (ALO), and Whale Optimization Algorithm (WOA), for the efficient operation of power distribution systems. The toolbox consists of two main functionalities. The first one allows the user to select the test system to be solved (33-, 69-, or 141-bus test systems), the locations of the distributed generators (DGs), and the voltage regulators. In addition, the user selects the daily active power output profiles of the DGs, and the tool solves the voltage deviation problem for the specified time of day. The second functionality involves the simulation of energy storage systems and provides the optimal daily power output of the resources. With this program, a graphical user interface (GUI) allows users to select the test system, the optimization method to be used, the number of DGs and locations, the locations and number of battery energy storage systems (BESSs), and the tap changer locations. With the simple user interface, the user can manage the distribution system simulation and see the results by making appropriate changes to the test systems.

Performance of six SARS-CoV-2 RNA detection systems in symptomatic and asymptomatic pediatric and maternal patients

Aim: This study evaluated the real-world performance of six test systems for detection of SARS-CoV-2 in 138 pediatric and 110 adult maternal patients. Materials & methods: Nasopharyngeal swabs were tested directly using the Aptima™ SARS-CoV-2 (Aptima) and Simplexa™ COVID-19 Direct (Simplexa), and with Altona RealStar® RT-PCR and CDC RT-PCR with nucleic acid extracted on the Roche® MagNA Pure 96 (Altona-MP96) or bioMérieux EMAG® (Altona-EMAG). Results/Conclusion: Overall percent-positive and percent-negative agreements among the six test systems were, respectively: Aptima: 94.8 and 100%; Altona-MP96: 96.5 and 99.3%; CDC-MP96: 100 and 99.3%; Altona-EMAG: 86.1 and 100%; CDC-EMAG: 98.2 and 100%; Simplexa: 87 and 99.2%. The six test systems showed agreement ranging from 92.7 (κ = 0.85) to 98.8% (κ = 0.98).

Comparative techno-economic analysis of power system with and without renewable energy sources

<p>The primary aim of this work is to feature the advantages of integrating natural source of energy from the solar and wind to the prevailing electric power systems. Two types of analysis are carried out in two test systems (standard and modified test systems) and the outcome of the test systems are compared. The two analyses are technical analysis and economic analysis. The stability of the voltage is analyzed under technical analysis and the price of energy consumed from the electric grid is calculated and analyzed under the economic analysis. Dynamic hourly load data, hourly solar radiation, hourly wind velocity, and dynamic electricity prices are considered for the standard IEEE system and modified test system (with the integration of RES). Voltage stability index (L-Index) and price of the electricity consumed from electric grid are found for standard test system and the outcome is compared with the outcome of modified test systems. MATLAB coding is done for techno-economic analysis for both test systems. It is inferred from the outcome that the integration of renewable energy sources fairly contributes to the economic benefit of the system by lowering the power purchased from the grid and enhance the stability of the system.</p>