Enhancement of electromechanical properties of natural rubber by adding barium titanate filler: An electro-mechanical study

Natural rubber is one of the most potential electro-active polymers for sensors, actuators, and energy harvesting applications. Enhancing the characteristic properties of polymers by reinforcing with fillers that possess multifunctional attributes have attracted considerable attention. In the present study, barium titanate reinforced natural rubber composite is prepared by using two-roll mill mixing. Afterwards, mechanical, electrical, and electromechanical properties of the composites are extensively analyzed by reinforcing different amounts of barium titanate into the matrix of natural rubber. The fabricated dielectric composite shows excellent properties such as high dielectric constant, low dielectric losses, high dielectric breakdown strength, and extreme stretchability. It is observed that as the filler loading reaches the value of 11 parts per hundred rubber (phr), maximum agglomeration of the particles occurs. Maximum stretchability and highest ratio of dielectric constant to elastic modulus are obtained at 8 phr of barium titanate fillers and at the loading, a maximum actuation strain of 11.24% is achieved. This study provides a simple, economical, and effective method for preparing enhanced mechanical, electrical, and electromechanical properties of natural rubber composites, facilitating the wide applications of dielectric materials as actuators and generators.     

Fractional-order adaptive backstepping control of a class of uncertain systems with external disturbances

Fractional control schemes are powerful tools for fulfilling robust tracking performance of different systems. This paper is the pioneering one in developing a fractional-order adaptive backstepping controller (FOABC) for a general class of integer-order and fractional-order (FO) systems. Model uncertainties and external disturbances can perturb system response and the controller is designed such that it can suppress the performance degradation caused by these factors. Moreover, rigorous mathematical analyses are carried out based on fractional Lyapunov theorems to ensure stability of the controlled systems. To justify the claims, worked-out examples including integer-order and FO systems are simulated. Good tracking performance of the proposed controller as well as robustness against uncertainties and insensitivity to external disturbances make it a good candidate for a broad range of systems. The results of implementing the proposed controller on different systems are compared with some newly proposed control approaches which highlight the outperformance of the FOABC.     

Experimental and numerical investigation of bridge pier scour estimation using ANFIS and teaching–learning-based optimization methods

Studies have shown that the major cause of the bridge failures is the local scour around the pier foundations or their abutments. The local scour around the bridge pier is occurred by changing the flow pattern and creating secondary vortices in the front and rear of the bridge piers. Until now, many researchers have proposed empirical equations to estimate the bridge pier scour based on laboratory and field datasets. However, scale impact, laboratory simplification, natural complexity of rivers and the personal judgement are among the main causes of inaccuracy in the empirical equations. Therefore, due to the deficiencies and disadvantages of existing equations and the complex nature of the local scour phenomenon, in this study, the adaptive network-based fuzzy inference system (ANFIS) and teaching–learning-based optimization (TLBO) method were combined and used. The parameters of the ANFIS were optimized by using TLBO optimization method. To develop the model and validate its performance, two datasets were used including laboratory dataset that consisted of experimental results from the current study and previous ones and the field dataset. In total, 27 scaled experiments of different types of pier groups with different cross sections and side slopes were carried out. To evaluate the model ability in prediction of scour depth, results were compared to the standard ANFIS and empirical equations using evaluation functions including Hec-18, Froehlich and Laursen and Toch equations. The results showed that adding TLBO to the standard ANFIS was efficient and can increase the model capability and reliability. Proposed model achieved better results than Laursen and Toch equation which had the best results among empirical relationships. For instance, proposed model in comparison with the Laursen and Toch equation, based on the RMSE function, yielded 50.4% and 71.8% better results in laboratory and field datasets, respectively.

     

Triple-layer proton exchange membranes based on chitosan biopolymer with reduced methanol crossover for high-performance direct methanol fuel cells application

A novel triple-layer proton exchange membrane comprising two thin layers of structurally modified chitosan, as methanol barrier layers, both sides coated with Nafion^®105 is prepared and tested for high-performance direct methanol fuel cell applications. A tight adherence is detected between layers from SEM and EDX data for the cross-sectional area of the newly designed membrane, which are attributed to high affinity of opposite charged polyelectrolyte layers. Proton conductivity and methanol permeability measurements show improved transport properties for the multi-layer membrane compared to Nafion^®117 with approximately the same thickness. Moreover, direct methanol fuel cell tests reveal higher open circuit voltage, power density output, and overall fuel cell efficiency for the triple-layer membrane than Nafion^®117, especially at concentrated methanol solutions. A power output of 68.10 mW cm^?2 at 5 M methanol feed is supplied using multi-layer membrane, which is found to be about 72% more than that of for Nafion^®117. In addition, fuel cell efficiency for multi-layer membrane is measured about 19.55% and 18.45% at 1 and 5 M methanol concentrations, respectively. Owing to the ability to provide high power output, significantly reduced methanol crossover, ease of preparation and low cost, the triple-layer membrane under study could be considered as a promising polyelectrolyte for high-performance direct methanol fuel cell applications.     

Oxidative Damage in Sporadic Colorectal Cancer: Molecular Mapping of Base Excision Repair Glycosylases MUTYH and hOGG1 in Colorectal Cancer Patients

Oxidative stress, oxidative DNA damage and resulting mutations play a role in colorectal carcinogenesis. Impaired equilibrium between DNA damage formation, antioxidant status, and DNA repair capacity is responsible for the accumulation of genetic mutations and genomic instability. The lesion-specific DNA glycosylases, e.g., hOGG1 and MUTYH, initiate the repair of oxidative DNA damage. Hereditary syndromes (MUTYH-associated polyposis, NTHL1-associated tumor syndrome) with germline mutations causing a loss-of-function in base excision repair glycosylases, serve as straight forward evidence on the role of oxidative DNA damage and its repair. Altered or inhibited function of above glycosylases result in an accumulation of oxidative DNA damage and contribute to the adenoma-adenocarcinoma transition. Oxidative DNA damage, unless repaired, often gives rise G:C > T:A mutations in tumor suppressor genes and proto-oncogenes with subsequent occurrence of chromosomal copy-neutral loss of heterozygosity. For instance, G>T transversions in position c.34 of a KRAS gene serves as a pre-screening tool for MUTYH-associated polyposis diagnosis. Since sporadic colorectal cancer represents more complex and heterogenous disease, the situation is more complicated. In the present study we focused on the roles of base excision repair glycosylases (hOGG1, MUTYH) in colorectal cancer patients by investigating tumor and adjacent mucosa tissues. Although we found downregulation of both glycosylases and significantly lower expression of hOGG1 in tumor tissues, accompanied with G>T mutations in KRAS gene, oxidative DNA damage and its repair cannot solely explain the onset of sporadic colorectal cancer. In this respect, other factors (especially microenvironment) per se or in combination with oxidative DNA damage warrant further attention. Base excision repair characteristics determined in colorectal cancer tissues and their association with disease prognosis have been discussed as well.     

A metadata model for collaborative experiments and simulations in earthquake engineering

Research projects in earthquake engineering yield a very large amount of complex data from experiments and computer simulations. Understanding and exchanging these complicated and voluminous data sets prompted the development of metadata models that document the processes of data generation, and facilitate the collaboration and exchange of information between researchers. The present metadata model was designed to document and exchange a large number of large data files in earthquake engineering, but is applicable to other fields of engineering and science. The model was conceived based on a series of former data models, which were unduly complicated and limited to few types of experiments. Simpler than its predecessors, the present metadata model applies to all kinds of earthquake engineering experiments. It was developed in the object-oriented framework using Protégé. Its applications are illustrated with examples from centrifuge experiments.     

Autophagy,Unfolded Protein Response,and Neuropilin-1 Cross-Talk in SARS-CoV-2 Infection: What Can Be Learned from Other Coronaviruses

The COVID-19 pandemic is caused by the 2019–nCoV/SARS-CoV-2 virus. This severe acute respiratory syndrome is currently a global health emergency and needs much effort to generate an urgent practical treatment to reduce COVID-19 complications and mortality in humans. Viral infection activates various cellular responses in infected cells, including cellular stress responses such as unfolded protein response (UPR) and autophagy, following the inhibition of mTOR. Both UPR and autophagy mechanisms are involved in cellular and tissue homeostasis, apoptosis, innate immunity modulation, and clearance of pathogens such as viral particles. However, during an evolutionary arms race, viruses gain the ability to subvert autophagy and UPR for their benefit. SARS-CoV-2 can enter host cells through binding to cell surface receptors, including angiotensin-converting enzyme 2 (ACE2) and neuropilin-1 (NRP1). ACE2 blockage increases autophagy through mTOR inhibition, leading to gastrointestinal complications during SARS-CoV-2 virus infection. NRP1 is also regulated by the mTOR pathway. An increased NRP1 can enhance the susceptibility of immune system dendritic cells (DCs) to SARS-CoV-2 and induce cytokine storm, which is related to high COVID-19 mortality. Therefore, signaling pathways such as mTOR, UPR, and autophagy may be potential therapeutic targets for COVID-19. Hence, extensive investigations are required to confirm these potentials. Since there is currently no specific treatment for COVID-19 infection, we sought to review and discuss the important roles of autophagy, UPR, and mTOR mechanisms in the regulation of cellular responses to coronavirus infection to help identify new antiviral modalities against SARS-CoV-2 virus.