Interaction of the properties of individual cotton fibres in a blend

Yarn engineering plays an important role in producing fabric for particular use. It is a common practice that yarn properties are predicted from constituent fibre properties. Cotton properties being highly variable in nature attracted various scientists from all over the world to derive prediction equations. More than 200 articles have been published in this area. Most of these predictions are based on single cotton, whereas in practice, more than one cotton is mixed together to optimise cost and quality. This study reports the accuracy of using weighted average method to determine the properties of blended cottons. Also, a set of prediction equations, derived for single cotton, tried to predict the properties of blended cotton yarns. To increase the accuracy of predictions, a new set of equations have been derived for binary cotton-blended yarns.     

Preparation and characterization of CdS–Bi2S3 nanocomposite thin film by successive ionic layer adsorption and reaction (SILAR) method

CdS, Bi₂S₃ and CdS–Bi₂S₃ nanocomposite thin films were grown by successive ionic layer adsorption and reaction method (SILAR) onto the glass substrates at room temperature. These films were characterized by X-ray diffraction (XRD), scanning electron microscope (SEM) and electrical measurement systems. A comparative study was made between CdS, Bi₂S₃ and CdS–Bi₂S₃ nanocomposite thin films. The XRD patterns reveal that CdS, Bi₂S₃ and CdS–Bi₂S₃ nanocomposite thin film have hexagonal, orthorhombic and mixed phase of hexagonal CdS and orthorhombic Bi₂S₃ crystal structure, respectively. SEM images showed uniform deposition of the material over the entire glass substrate. The energy band gap for CdS, Bi₂S₃ and CdS–Bi₂S₃ thin films were revealed from the optical studies and were found to be 2.4, 1.6 and 1.69 eV, respectively. The thermoemf measurements of CdS–Bi₂S₃ nanocomposite thin film revealed n-type electrical conductivity, while the I–V measurement of CdS, Bi₂S₃ and CdS–Bi₂S₃ nanocomposite thin film under dark and illumination condition (100 mW/cm²) exhibited photoconductivity phenomena suggesting its applicability in photosensors devices.     

In vitro assessment of antimicrobial efficacy of the D-tagatose and lactobacilli-based synbiotic preparations against the pathogenic Escherichia coli and Salmonella typhimurium

The study aimed to investigate the utilisation of prebiotic D-tagatose by probiotic lactobacilli (L. rhamnosus GG, L. casei, L. acidophilus and L. fermentum) and enteric pathogens (E. coli and S. typhimurium) to determine synbiotic potential of D-tagatose and lactobacilli combination. The antimicrobial efficacy of the synbiotic preparations (D-tagatose with lactobacillus) was assessed against selected pathogens in co-culture assays. Evidently, D-tagatose supported growth of selected lactobacilli, especially the L. rhamnosus GG and L. casei, but not the enteric pathogens. The tested synbiotic preparations completely inhibited growth of both the pathogens, even in the presence of D-glucose in co-cultures. The well-diffusion assay demonstrated the presence of antimicrobial activity as recorded by drop of culture pH. The study substantiated that D-tagatose could be an effective prebiotic component for formulation of potential synbiotic combinations with L. rhamnosus GG or L. casei that can be used as an alternative to antibiotics against enteric pathogens.     

Musically Modified Substitution-Box for Clinical Signals Ciphering in Wireless Telecare Medical Communicating Systems

Telecare medical communication system (TMCS) is an essential component in today’s fast moving era. Patients are privileged to have wireless online medical facilities from their remote locations. Probability of noscomial infections is absolutely zero in such wireless TMCS. Data Security of heterogeneous patients during the wireless communication is a big challenge. Patients’ data privacy is highly confidential and need enhanced encryption measures. Intruding leads to the medical data adulterations in such telecare systems. This paper proposes a modified Advanced Encryption Standards (AES) based on the biometric generated key. Binary biometric key were generated from the patients’ fingerprints. S-box of AES has been enhanced by the musical involvement of metaheuristic harmony search algorithm. Clinical electrocardiogram (ECG) signals were carried out to enhance the security mechanism of the TMCS. Different tests were carried on the proposed technique, which in turn gets wise bench-mark outcomes. Statistical analyses were conducted to counterfeit the intruding. This proposed technique is suitable for wireless TCMS with higher degree of patients’ privacy.

     

Deep Learning Guided Double Hidden Layer Neural Synchronization Through Mutual Learning

Neural Processing Letters - In this paper, a Double Hidden Layer Neural Networks synchronization mechanism using Generative Adversarial Network (GAN) and mutual learning is used for the development...     

Non-linear weight adjustment in adaptive gamma correction for image contrast enhancement

Multimedia Tools and Applications - Image enhancement remains an intricate problem, crucial for image analysis. Several algorithms exist for the same. A few among these algorithms categorize images...     

Faster Synchronization of Triple Layer Neural Network Using Nature Inspired Whale Optimization: A Key Exchange Protocol

Wireless Personal Communications - The secret key swap over protocol is developed using a Whale Optimization-guided Three Layer Neural Networks coordination mechanism in this article. An adversary...     

Behavior of alginate–gelatin blended gel with embedded macrovoids: Stress-induced changes and the solute release characteristics

Blending of gelatin to alginate promote cell–material interaction. However, the changes in diffusive and mechanical properties need to be ascertained. This study shows that the presence of two superposed polymer networks, where gelatin is not additionally crosslinked resulted in higher uptake and slower release of vitamin B₁₂. In the presence of gelatin, the stress is found higher for the same level of compressive deformation, and the permeability of the pore fluid during expulsion under compressive stress is found significantly lower. Also, a large residual strain at the end of each cycle in case of cyclic compression is observed, when gelatin is present. A microfluidic device is used to introduce voids uniformly across the blended gel with an objective to increase compressibility, permeability (for faster equilibration of pore pressure), and uptake of bioactive species. The results showing lower permeability and higher uptake in the presence of gelatin are discussed.     

Using hyperspectral vegetation indices to estimate the fraction of photosynthetically active radiation absorbed by corn canopies

The fraction of photosynthetically active radiation (FPAR) absorbed by vegetation – a key parameter in crop biomass and yields as well as net primary productivity models – is critical to guiding crop management activities. However, accurate and reliable estimation of FPAR is often hindered by a paucity of good field-based spectral data, especially for corn crops. Here, we investigate the relationships between the FPAR of corn (Zea mays L.) canopies and vegetation indices (VIs) derived from concurrent in situ hyperspectral measurements in order to develop accurate FPAR estimates. FPAR is most strongly (positively) correlated to the green normalized difference vegetation index (GNDVI) and the scaled normalized difference vegetation index (NDVI*). Both GNDVI and NDVI* increase with FPAR, but GNDVI values stagnate as FPAR values increase beyond 0.75, as previously reported according to the saturation of VIs – such as NDVI – in high biomass areas, which is a major limitation of FPAR-VI models. However, NDVI* shows a declining trend when FPAR values are greater than 0.75. This peculiar VI–FPAR relationship is used to create a piecewise FPAR regression model – the regressor variable is GNDVI for FPAR values less than 0.75, and NDVI* for FPAR values greater than 0.75. Our analysis of model performance shows that the estimation accuracy is higher, by as much as 14%, compared with FPAR prediction models using a single VI. In conclusion, this study highlights the feasibility of utilizing VIs (GNDVI and NDVI*) derived from ground-based spectral data to estimate corn canopy FPAR, using an FPAR estimation model that overcomes limitations imposed by VI saturation at high FPAR values (i.e. in dense vegetation).