Electrochemical corrosion parameters for active and passive reinforcing steel in carbonated and sound concrete

The electrochemical corrosion parameters, such as corrosion potential, corrosion current density, and the Tafel constants are necessary inputs for the corrosion modeling in reinforced concrete. Literature shows large variability in their values, whereas the data are scarce for the carbonated concrete. This paper presents a range of corrosion parameters for the active steel in carbonated and the passive steel in noncarbonated concrete. Forty-eight singly reinforced concrete cylinders were cast, of which 24 were carbonated and the others were sound samples. Potentiodynamic polarization curves were obtained at three different scan rates and extrapolated to extract the corrosion parameters. To validate these parameters, a macrocell corrosion system was simulated using FEM-based Comsol multiphysics® software. The numerical results were compared to two experimental studies. A natural dispersion in the values of corrosion parameters for both active and passive steels was observed. The average Stern–Geary constant was 54 and 47 mV for active and passive steels, respectively. Numerical simulations with the obtained parameters predicted the macrocell corrosion in partially carbonated concrete with a high accuracy. The presented values of corrosion parameters in this study could help researchers and engineers to simulate the corrosion phenomena in concrete accurately.     

Interbilayer-crosslinked multilamellar vesicles as synthetic vaccines for potent humoral and cellular immune responses

Vaccines based on recombinant proteins avoid the toxicity and antivector immunity associated with live vaccine (for example, viral) vectors, but their immunogenicity is poor, particularly for CD8(+) T-cell responses. Synthetic particles carrying antigens and adjuvant molecules have been developed to enhance subunit vaccines, but in general these materials have failed to elicit CD8(+) T-cell responses comparable to those for live vectors in preclinical animal models. Here, we describe interbilayer-crosslinked multilamellar vesicles formed by crosslinking headgroups of adjacent lipid bilayers within multilamellar vesicles. Interbilayer-crosslinked vesicles stably entrapped protein antigens in the vesicle core and lipid-based immunostimulatory molecules in the vesicle walls under extracellular conditions, but exhibited rapid release in the presence of endolysosomal lipases. We found that these antigen/adjuvant-carrying vesicles form an extremely potent whole-protein vaccine, eliciting endogenous T-cell and antibody responses comparable to those for the strongest vaccine vectors. These materials should enable a range of subunit vaccines and provide new possibilities for therapeutic protein delivery.     

Inactivation of Shiga toxin-producing Escherichia coli in single-strength lemon and lime juices containing preservatives

The objective of this study was to determine the inactivation of non-O157 Shiga toxin-producing Escherichia coli (STEC) serotypes in comparison with O157 STEC in commercially produced, shelf-stable lemon and lime juices. The present validation tests confirmed that storage of the juices containing preservatives at room temperatures (22°C) for 3 days (72 h) ensures a >6-log reduction of O26, O45, O103, O111, O121, O145, and O157 STEC. These results demonstrate that non-O157 STEC had survival abilities comparable to those of E. coli O157:H7 strains in acidic food products such as lemon and lime juices (pH 2.5 ± 0.1); therefore, the storage conditions deemed to inactivate E. coli O157:H7 similarly inactivate the non-O157 serotypes.     

Towards efficient human–machine interaction for home energy management with seasonal scheduling using deep fuzzy neural optimizer

Cognition, Technology & Work - Maintaining the records of domestic consumers’ electricity consumption patterns is very complex task for the utilities, especially for extracting the...     

De-Noising Brain MRI Images by Mixing Concatenation and Residual Learning (MCR)

Brain magnetic resonance images (MRI) are used to diagnose the different diseases of the brain, such as swelling and tumor detection. The quality of the brain MR images is degraded by different noises, usually salt & pepper and Gaussian noises, which are added to the MR images during the acquisition process. In the presence of these noises, medical experts are facing problems in diagnosing diseases from noisy brain MR images. Therefore, we have proposed a de-noising method by mixing concatenation, and residual deep learning techniques called the MCR de-noising method. Our proposed MCR method is to eliminate salt & pepper and gaussian noises as much as possible from the brain MRI images. The MCR method has been trained and tested on the noise quantity levels 2% to 20% for both salt & pepper and gaussian noise. The experiments have been done on publically available brain MRI image datasets, which can easily be accessible in the experiments and result section. The Structure Similarity Index Measure (SSIM) and Peak Signal-to-Noise Ratio (PSNR) calculate the similarity score between the denoised images by the proposed MCR method and the original clean images. Also, the Mean Squared Error (MSE) measures the error or difference between generated denoised and the original images. The proposed MCR de-noising method has a 0.9763 SSIM score, 84.3182 PSNR, and 0.0004 MSE for salt & pepper noise; similarly, 0.7402 SSIM score, 72.7601 PSNR, and 0.0041 MSE for Gaussian noise at the highest level of 20% noise. In the end, we have compared the MCR method with the state-of-the-art de-noising filters such as median and wiener de-noising filters.     

Exploring the Potential of Wire Fed Direct Energy Deposition of Aluminum–Boron Nitride Nanotube Composite: Microstructural Evolution and Mechanical Properties

Recent advancements have shown great promise in utilizing wire-fed direct energy deposition (DED) for building aluminum alloy structures. However, utilizing the wire-fed DED approach for fabricating metal matrix composite structures remains a significant challenge. Herein, a wire-based additive manufacturing process is used to successfully produce a 1D boron nitride nanotube (BNNT)-reinforced aluminum composite with high strength. Al-BNNT electrode is developed in house. The microstructural changes that occur during layer-by-layer deposition are investigated. The grain morphology changes from equiaxed grains in the bottom layer to columnar grains in the top layer. BNNTs act as nuclei to promote the formation of equiaxed grains and interfacial compounds (AlN and AlB₂) during solidification. This results in improved strength, with Al-BNNT composite exhibiting a tensile strength of 47 MPa, 2.3 times higher than its pure Al. Higher strength is attributed to the retention and uniform distribution of BNNT reinforcement in the melt pool, leading to effective load transfer. This study demonstrates the potential of additive manufacturing for producing high-performance metal matrix composites with novel 1D reinforcements and improved multifunctional properties.