An Overview on SARS‑CoV‑2(COVID‑19)and Other Human Coronaviruses and Their Detection Capability via Amplification Assay,Chemical Sensing,Biosensing,Immunosensing,and Clinical Assays

A novel coronavirus of zoonotic origin(SARSCoV-2)has recently been recognized in patients with acute respiratory disease.COVID-19 causative agent is structurally and genetically similar to SARS and bat SARS-like coronaviruses.The drastic increase in the number of coronavirus and its genome sequence have given us an unprecedented opportunity to perform bioinformatics and genomics analysis on this class of viruses.Clinical tests like PCR and ELISA for rapid detection of this virus are urgently needed for early identification of infected patients.However,these techniques are expensive and not readily available for point-of-care(POC)applications.Currently,lack of any rapid,available,and reliable POC detection method gives rise to the progression of COVID-19 as a horrible global problem.To solve the negative features of clinical investigation,we provide a brief introduction of the general features of coronaviruses and describe various amplification assays,sensing,biosensing,immunosensing,and aptasensing for the determination of various groups of coronaviruses applied as a template for the detection of SARS-CoV-2.All sensing and biosensing techniques developed for the determination of various classes of coronaviruses are useful to recognize the newly immerged coronavirus,i.e.,SARS-CoV-2.Also,the introduction of sensing and biosensing methods sheds light on the way of designing a proper screening system to detect the virus at the early stage of infection to tranquilize the speed and vastity of spreading.Among other approaches investigated among molecular approaches and PCR or recognition of viral diseases,LAMP-based methods and LFAs are of great importance for their numerous benefits,which can be helpful to design a universal platform for detection of future emerging pathogenic viruses.     

Effect of light intensity and frequency of flashing light from blue light emitting diodes on astaxanthin production by Haematococcus pluvialis

Flashing light from blue light emitting diodes is an effective method for the reduction of energy consumption in the bioproduction of astaxanthin by Haematococcus pluvialis. We investigated the effects of light intensity and frequency on the final astaxanthin concentration in bioproduction by H. pluvialis grown mixotrophically. The final astaxanthin concentration under illumination with flashing light, with frequencies ranging from 25 to 200 Hz, was dependent on the light intensity and on the duty cycle and was equivalent, or higher, in comparison with that under illumination with continuous light at the same incident intensity. The light intensity determined the maximum attainable concentration of astaxanthin under continuous illumination. Under illumination with flashing light, the ratio of the final astaxanthin concentration to the maximum concentration at a specific light intensity was correlated to the duty cycle in the frequency range from 25 to 200 Hz. The effect of lower frequencies on enhanced astaxanthin production under flashing light was also studied; at levels as low as 1 Hz, higher final astaxanthin concentrations were observed under flashing light compared to concentrations attained under continuous light.     

Comparing the Effects of Microwave and Conventional Heating Methods on the Evaporation Rate and Quality Attributes of Pomegranate (<Emphasis Type="Italic">Punica granatum</Emphasis> L.) Juice Concentrate

Pomegranate juice was concentrated by conventional heating and microwave heating at different operational pressures (12, 38.5, and 100 kPa), and their effects on evaporation rate and quality attributes of concentrated juice were investigated. The final juice concentration of 40° Brix was achieved in 140, 127, and 109 min at 100, 38.5, and 12 kPa, respectively, by using conventional heating. Applying microwave energy decreased required times to 118, 95, and 75 min. The changes in color, anthocyanin content, and antioxidant capacity during concentration processes were investigated. L*, a*, and b* parameters were measured to estimate the intensity of color loss. All Hunter color parameters decreased with time. Results showed that the degradation of color, anthocyanins, and antioxidant activity were more important in conventional heating compared to microwave heating method. Degradation rates increases by increasing process pressure. A first-order kinetics model was applied to modeling changes in total solid content, anthocyanin content, and antioxidant capacity.     

An improved mechanism for capacity payment based on system dynamics modeling for investment planning in competitive electricity environment

Many countries have experienced restructuring in their electric utilities. This restructuring has presented the power industries with new challenges, the most important of which is long-term investment planning under uncertain conditions. This paper presents an improved mechanism for capacity payment. The mechanism has been investigated based on system dynamic modeling. In our proposed mechanism, generators will recover a part of their investment through capacity payment. While the payment for any plant remains constant during the operation period, it depends on the investment needed to build it. The main factors affecting long-term planning have been considered in our model. The approach can be used to investigate the effects of fixed as well as variable capacity payment in market investment. We used the probability density function of load as a new concept to calculate average market price. Delays in unit constructions, estimation of demand, and market capacity growth during construction periods have been included in the proposed algorithm as parameters, which affect the regulator's decision for changing capacity payment. The model can be used by regulators to investigate strategies that may affect the fluctuations in the market.     

Synthesis of kappa-carrageenan-g-poly(acrylamide)/sepiolite nanocomposite hydrogels and adsorption of cationic dye

In this study, nanocomposite hydrogels from grafting of acrylamide onto kappa-carrageenan biopolymer were prepared in the presence of sepiolite clay. Methylenebisacrylamide and ammonium persulfate were used as cross-linker and initiator, respectively. The sepiolite nanoclay was introduced into hydrogel matrix without any chemical treatment. The structure of nanocomposites was investigated by FTIR, SEM, TEM, and TGA techniques. The TEM image showed that sepiolite exists as individual needle’s shape. The swelling of hydrogels were studied in distilled water, salt solutions, and various pHs. The obtained nanocomposites were evaluated to remove of cationic crystal violet (CV) dye from water. The kinetic and isotherm of adsorption of dye onto nanocomposites were studied and analyzed according to kinetic and isotherm models. The results showed that the pseudo-second-order adsorption kinetic was predominated for the adsorption of CV onto nanocomposites. The experimental equilibrated adsorption capacity of nanocomposites was analyzed using Freundlich and Langmuir isotherm models. The results corroborated that the experimental data fit the Langmuir isotherm the best. By varying the pH of initial dye solution, while the clay-free hydrogel showed relatively pH-independent adsorption behavior, the nanocomposites depicted pH-dependent adsorption.     

Multi-objective modelling of day ahead scheduling of MMG-based distribution networks accompanied by DEA considering economics,emissions and power quality

ABSTRACT

This paper presents the state of the art relating to multi-objective modelling for day ahead scheduling of multi micro grid-based distribution networks, using optimal power flow (OPF) accompanied by data envelopment analysis (DEA). In this paper eco-reliability cost function, power quality enhancement and emission reduction are treated as the objective functions and the uncertainties of renewable distributed generations (DGs), load demand and market price are incorporated into the problem. This method is able to find the optimum operation of DGs in grid-connected or isolated MGs, power transaction between each MG and upstream networks/other MGs and hourly reconfiguration instants. For this purpose, firstly OPF is applied to the problem, then the obtained optimal solutions are prioritised by DEA and ranking is done, based on the efficiencies of the optimal solutions. Finally, the provided results validate the practicability of the proposed method and accuracy of the outcomes.     

Radiosynthesis and biodistribution of [^18F]-tetracosactide using a semi-automated [^18F]SFB production module

In order to prepare a specific melanocortin type 2 receptor (MC2R) ligand, b1-24-corticotrophin was pre-pared in one-step reaction with [18F] SFB and b-1-24-corticotrophin pharmaceutical solution (1 mg/mL, pH=6.5). [18F]SFB was prepared in a semi-automated module in two steps with an overall radiochemical yield of 47% to EOB (not-decay corrected) in 90 min. The 18F-labeled intermediates and 18F-labeled peptide was checked by RTLC and HPLC. The results show that the radiochemical purity is >95% and the yield to EOB (not-decay corrected) is 29% for final 18F-labeled peptide at optimized conditions. Preliminary in vivo studies in normal mice were performed to deter-mine biodistribution of the 18F-labeled peptide for 150 min. The results show that the major tracer uptake is consistent with the natural distribution of MC2R receptors in mammals. Testes/blood and testes/muscle ratios for 18F-labeled peptide at 150 min were 184 and 1.56, respectively, and adipocyte/blood and adipocyte/muscle ratios at 120 min were 221 and 142, respectively. The data support the specific receptor binding of the radiolabeled peptide as reported for MC2R receptor accumulation in adipocytes and testes and demonstrates the retention of biological activity of the pep-tide. This tracer can be used in detection of MC2R distribution in malignancies and sex organ diseases.     

Solving the stochastic support vector regression with probabilistic constraints by a high-performance neural network model

This paper offers a recurrent neural network to support vector machine (SVM) learning in stochastic support vector regression with probabilistic constraints. The SVM is first converted into an equivalent quadratic programming (QP) formulation in linear and nonlinear cases. An artificial neural network for SVM learning is then proposed. The presented neural network framework guarantees obtaining the optimal solution of the SVM problem. The existence and convergence of the trajectories of the network are studied. The Lyapunov stability for the considered neural network is also shown. The efficiency of the proposed method is shown by three illustrative examples.

     

Enhanced oil recovery from carbonate reservoirs by spontaneous imbibition of low salinity water

An experimental study was performed to investigate the impact of low salinity water on wettability alteration in carbonate core samples from southern Iranian reservoirs by spontaneous imbibition. In this paper, the effect of temperature, salinity, permeability and connate water were investigated by comparing the produced hydrocarbon curves. Contact angle measurements were taken to confirm the alteration of surface wettability of porous media. Oil recovery was enhanced by increasing the dilution ratio of sea water, and there existed an optimum dilution ratio at which the highest oil recovery was achieved. In addition, temperature had a very significant impact on oil recovery from carbonate rocks. Furthermore, oil recovery from a spontaneous imbibition process was directly proportional to the permeability of the core samples. The presence of connate water saturation inside the porous media facilitated oil production significantly. Also, the oil recovery from porous media was highly dependent on ion repulsion/attraction activity of the rock surface which directly impacts on the wettability conditions. Finally, the highest ion attraction percentage was measured for sodium while there was no significant change in pH for all experiments.     

Computer simulation of the optical properties of high-temperature cermet solar selective coatings

A computer simulation is developed to calculate the solar absorptance and thermal emittance of various configurations of cermet solar selective coatings. Special attention has been paid to those material combinations, which are commonly used in high-temperature solar thermal applications. Moreover, other material combinations such as two-, three- and four-cermet-layer structures as solar selective coatings have been theoretically analyzed by computer simulation using three distinct physical models of Ping Sheng, Maxwell–Garnett and Bruggeman. The novel case of two-cermet-layer structure with different cermet components has also been investigated. The results were optimized by allowing the program to manipulate the metal volume fraction and thickness of each layer and the results compared to choose the best possible configuration. The calculated results are within the range of 0.91–0.97 for solar absorptance and 0.02–0.07 for thermal emittance at room temperature.