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.     

Multiresolution HVS and statistically based image coding scheme

In this paper a novel multiresolution human visual system and statistically based image coding scheme is presented. It decorrelates the input image into a number of subbands using a lifting based wavelet transform. The codec employs a novel statistical encoding algorithm to code the coefficients in the detail subbands. Perceptual weights are applied to regulate the threshold value of each detail subband that is required in the statistical encoding process. The baseband coefficients are losslessly coded. An extension of the codec to the progressive transmission of images is also developed. To evaluate the performance of the coding scheme, it was applied to a number of test images and its performance with and without perceptual weights is evaluated. The results indicate significant improvement in both subjective and objective quality of the reconstructed images when perceptual weights are employed. The performance of the proposed technique was also compared to JPEG and JPEG2000. The results show that the proposed coding scheme outperforms both coding standards at low compression ratios, while offering satisfactory performance at higher compression ratios.     

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.     

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.     

A new optimized uncertainty evaluation applied to the Monte-Carlo simulation in platinum resistance thermometer calibration

The basic steps for evaluating the measurement uncertainty according to ISO approach, propagation of uncertainties and Monte-Carlo simulation are investigated. These methods during a case study in a temperature secondary laboratory for uncertainty assessment of a platinum resistance thermometer calibration are illustrated. For considering some sources of variability in the measurement which may not be appropriately treated and the computational efficiency in simulation model, a simulation optimization and a Genetic algorithm are proposed to establish lower and upper bounds as limit standards for simulation results.     

Correlation between nanoindentation response and wear characteristics of CrN-based coatings deposited by an Arc-PVD method

The examination of the existing relationships between nanoindentation responses and tribological properties of the nanostructured CrN, Cr(CN), and (CrTi)N coatings was the matters to be considered in this research. A cathodic arc physical vapor deposition machine was therefore implemented to apply the chosen coatings on the DIN 1.2510 tool steel substrate. Moreover, an X-ray diffraction and a field emission scanning electron microscope were utilized in order to show the features regarding microstructure and morphology of these very coatings. The mechanical and tribological behavior of the coatings was expected to be assessed with the use of a nanoindentation and pin-on-disc wear tests. According to the obtained result, the wear resistance and hardness value of the (CrTi)N coating were proved to be much better than those of the CrN and Cr(CN). Linear equations were proposed between wear rate/hardness and friction coefficient/hardness to evaluate the correlation between mechanical and tribological properties. The presence of a quadratic equation between the friction coefficient and the plastic deformation index was also discovered.     

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.     

Overcoming endogenous constraints on neuronal regeneration

One of the grand challenges in neuroengineering is to stimulate regeneration after central nervous system (CNS) or peripheral nervous system (PNS) injury to restore function. The state of the art today is that PNS injuries heal to a limited extent, whereas CNS injuries are largely intractable to regeneration. In this context, we examine the underlying biochemical and cellular constraints on endogenous healing of neural tissues. Identification and characterization of endogenous "rate-limiting" processes that constrain regeneration would allow one to craft solutions to overcome critical impediments for accelerated healing. It is increasingly evident that biochemical pathways triggered by the nature and duration of injury-triggered inflammatory response may determine the endogenous constraints and subsequently determine regenerative fate. In this paper, critical endogenous constraints of PNS and CNS regeneration are identified, and the effects of modulating the phenotypes of immune cells on neuronal regeneration are discussed.