Performance analysis of multi-antenna relay networks with imperfect channel estimation

In this paper, we present the performance of multi-antenna selective combining decode-and-forward (SC-DF) relay networks over independent but non-identical Nakagami-m fading channels with imperfect channel estimation. The outage probability, moment generating function (MGF) and symbol error probability (SEP) will be derived in closed-form using the SNR statistical characteristics. To make the analysis trackable, we have derived the MGF and SEP for integer values of fading severity, m. Also, to make the relations more simple, we develop high signal to noise ratio (SNR) analysis for the performance metrics of our system. Subsequently, we propose optimal and adaptive power allocation algorithms along with the equal power allocation method. Finally, for comparison with analytical formulas, we perform some Monte-Carlo simulations.     

A Flat Polymeric Membrane Sensor for Carbon Dioxide/Nitrogen Gas Mixture

A gas sensor was developed to measure the concentration of binary gas mixtures. This sensor works based on the permeability change of different gas mixtures across the polymeric membranes. Although high values of permeability and selectivity are needed for an ideal separation, the performance of this sensor mainly depends on the permeability factor. Polysulfone and silicone rubber were applied as the membrane base and coat, respectively. Moreover, in contrast to existing polymeric sensors that use hollow fibers, the present sensor is made of flat membranes. This new design is cheaper, smaller, and easier to use in comparison to the hollow fiber polymeric sensors. In order to test the sensor applicability, nitrogen and carbon dioxide were used as model gases. The effect of pressure on the response time and sensor accuracy was studied for the aforementioned gases. The response time (T_95%) of this low price sensor was 50?s, and the tolerance of measuring concentration was approximately 1.4% at 2?bar feed pressure. Also, increasing the feed pressure can improve the response time or accuracy of the sensor.     

A Multi-Criteria Group Decision Making Methodology Using Interval Type-2 Fuzzy Sets: Application to Water Resources Management

In this paper, a new fuzzy group decision-making methodology which determines and incorporates negotiation powers of decision makers is developed. The proposed method is based on a combination of interval type-2 fuzzy sets and a multi-criteria decision making (MCDM) model, namely TOPSIS. To examine the applicability of the proposed methodology, it is used for finding the best scenario of allocating water and reclaimed wastewater to domestic, agricultural, and industrial water sectors and restoring groundwater quantity and quality in the Varamin region located in Tehran metropolitan area in Iran. The results show that the selected scenario leads to an acceptable groundwater conservation level during a long-term planning horizon. Although the capital cost of this scenario is high, which leads to groundwater restoration during the 34-year planning horizon, it is determined as the best allocation scenario. This scenario also entails the second least pumping cost, due to less water allocation from the groundwater. To evaluate the results of the proposed methodology, they are compared with those obtained using some well-known interval type-2 decision-making approaches including arithmetic-based, TOPSIS-based, and likelihood-based comparison methods. The Spearman correlation coefficient shows that the obtained results generally concur with those of the other methods. It is also concluded that the proposed methodology gives more reasonable results by calculating and considering the negotiation powers of decision makers in an extended TOPSIS-based group decision-making model.

     

Nigella arvensis leaf extract mediated green synthesis of silver nanoparticles: Their characteristic properties and biological efficacy

In the present study, the potential of aqueous leaf extract of Nigella arevensis for biosynthesis of silver nanoparticles (AgNPs) was evaluated. The formation of AgNPs was confirmed by color changes and UV–visible spectroscopy, which showed absorbance maxima peak at 416?nm. The transmission electron microscope (TEM) image showed the AgNPs to be anisotropic and mostly spherical with sizes in the range of 5–100?nm. Fourier transform infrared (FTIR) analysis indicated that the flavonoids, alkaloids and phenolic groups present in leaf extract were involved in the reduction and capping of phytogenic AgNPs. These nanoparticles showed the cytotoxic effects against H1229 and MCF-7 cancer cell lines with an IC₅₀ value of 10?μg/mL. AgNPs showed insignificant antioxidant properties compared to the crude extract, and it was effective against clinical isolated bacterial strains. Furthermore, the bioderived AgNPs displayed significant catalytic activity against methylene blue. These results confirmed the advantages and applications of these phytogenic AgNPs using the green method in various fields.     

Adsorption of BSA onto hexagonal mesoporous silicate loaded by APTES and tannin: Isotherm,thermodynamic and kinetic studies

In the present study, hexagonal mesoporous silica (HMS) was synthesized and modified by tannic acid as a natural poly-phenol and amine (TA-A-HMS) and was applied for the adsorption of bovine serum albumin (BSA) from aqueous media. To investigate the structure of HMS and TA-A-HMS, SEM, TEM, XRD, BET and FTIR analysis were applied. The effects of pH, adsorbent dosage, contact time and temperature on the BSA adsorption were studied. After modification, BET surface area of HMS was reduced from 885?m²/g to 51?m²/g which confirms the presence of tannin and amine groups that inhibit the adsorption of nitrogen molecules. According to the results of equilibrium data, it is shown that Langmuir isotherm with maximum adsorption capacity of 1000?mg/g is the predominant model and adsorption is mono-layer. Kinetic and thermodynamic studies also reveal that adsorption kinetic followed by pseudo-second order model and the adsorption process is exothermic.     

Selective toxicity of hydroxyl-rich carbon nanodots for cancer research

Nano Research - The toxicity of nanoparticles in a biological system is an integration of effects arising from surface functionality, particle size, ionic dissolution, etc. This complexity suggests...     

Review: the latest advances in biomedical applications of chitosan hydrogel as a powerful natural structure with eye-catching biological properties

Journal of Materials Science - Chitosan is one of the natural cationic polymers with unique properties such as non-toxicity, biodegradability, biocompatibility, environmentally friendly that has...     

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.