Cotton linter nano-fibers as the potential reinforcing agent for guar gum

Cotton linter nano-fibers (CLNFs) were prepared from cotton linters by a refining process. The prepared CLNFs were characterized for morphology, crystallinity and degree of polymerization. CLNF was used as a reinforcing agent in guar gum to improve its performance properties. Guar gum/CLNF nanocomposite films were prepared by a solution-casting process. CLNF was added in concentrations of 0.1, 0.25, 0.5 and 1.0 % (w/w) in guar gum. The prepared guar gum/CLNF nano-composite films were characterized for mechanical, thermal, rheological, crystallinity, water vapor transmission rate (WVTR) and light transparency properties. The enthalpy of melting and melting temperature of guar gum increased with increased concentration of CLNF; but up to 0.25 % (w/w) concentration, above which they started decreasing. Tensile strength and Young’s modulus of guar gum increased by 32 and 35 %, respectively, by 0.25 % (w/w) addition of CLNF; however, it decreased on further increase in the concentration of CLNF. The percentage elongation at break and WVTR decreased by 58 and 57 % for 0.25 % (w/w) CLNF-added guar gum. The observed improvements in the properties were due to better interaction between CLNF and guar gum. CLNF was found to have uniformly dispersed in guar gum on addition up to 0.25 % concentration; however, it started forming aggregates at higher concentration, as evident from scanning electron microscopy. Viscosity increased, whereas transparency decreased with increased concentration of CLNF in guar gum.     

Magnetically Guided Self‐Assembly and Coding of 3D Living Architectures

In nature, cells self‐assemble at the microscale into complex functional configurations. This mechanism is increasingly exploited to assemble biofidelic biological systems in vitro. However, precise coding of 3D multicellular living materials is challenging due to their architectural complexity and spatiotemporal heterogeneity. Therefore, there is an unmet need for an effective assembly method with deterministic control on the biomanufacturing of functional living systems, which can be used to model physiological and pathological behavior. Here, a universal system is presented for 3D assembly and coding of cells into complex living architectures. In this system, a gadolinium‐based nonionic paramagnetic agent is used in conjunction with magnetic fields to levitate and assemble cells. Thus, living materials are fabricated with controlled geometry and organization and imaged in situ in real time, preserving viability and functional properties. The developed method provides an innovative direction to monitor and guide the reconfigurability of living materials temporally and spatially in 3D, which can enable the study of transient biological mechanisms. This platform offers broad applications in numerous fields, such as 3D bioprinting and bottom‐up tissue engineering, as well as drug discovery, developmental biology, neuroscience, and cancer research.     

Unsupervised learning-based clustering approach for smart identification of pathologies and segmentation of tissues in brain magnetic resonance imaging

Human-made/developed algorithms provide automatic identification and segmentation of the tissues, lesions and tumor regions available in brain magnetic resonance scan images, which invocates predicaments such as high computational cost and low accuracy rate. Such hassles are reconciled with the utilization of an unsupervised approach in combination with clustering techniques. Initially, static features are chosen from the input image, which is fed to the self-organizing map (SOM), where the algorithm employs the dimensionality reduction of input images. Consecutively, the reduced SOM prototype of data is clustered by the modified fuzzy K-means (MFKM) algorithm. The MFKM algorithm can be modified in terms of membership variables because it operates with spatial information and converges quickly, and this would be of greater benefit to radiologists as they reduce the wrong predictions and voluminous time that normally occur owing to human involvement. The proposed algorithm provides 98.77% sensitivity and 97.5% specificity, which are better than any other traditional algorithms mentioned in this article.     

Analysis of Stress Control on 33-kV Non-ceramic Insulators Using Finite-element Method

In this article, analysis of electric field stress and electric potential distributions of a 33-kV composite insulator and factors that affect the electric field are discussed. Accordingly, the article is classified into two parts. In the first part, the designs of three different configurations of non-ceramic (composite) insulator based on their geometry modification in end fittings and water shed are discussed. The electrical performances are analyzed using electric field and electrical potential distribution. In the second part, a reduction of the electric field near the end fittings is done to control the electric field stress intended for long-term performance. For that, the grading material is placed between the core and housing materials by fitting the arcing horn near the end fittings. A 33-kV composite insulator is modeled in two dimensions by the finite-element method to investigate the electric field and electric potential distribution under normal and polluted conditions. The results reveal that an optimum installation of an arcing horn at the high-voltage end in the composite insulator with silicone rubber overlapping the edges of metal end fittings made a significant reduction in electric field stress on 33-kV non-ceramic insulators.     

Ionic liquid mediated application of nano zinc oxide on cotton fabric for multi-functional properties

In this work, nano zinc oxide (nano-ZnO) was applied onto cotton fabric by exhaustion method using an ionic liquid (IL), 1-butyl 3-methyl imidazolium chloride [BMIM][Cl], to improve its uptake and fixation. Effect of temperature on the exhaustion of nano-ZnO in the presence of ionic liquid was investigated. A spectrophotometric method was established to determine the concentration of nano-ZnO in the exhausted bath. Treated cotton fabrics were characterized using Fourier transform infrared, scanning electron microscope, atomic absorption spectroscopy, X-ray diffraction, Thermo gravimetric analysis and UV spectrophotometry. Washing durability test using the AATCC 61-2003 method demonstrated that the amount of nano-ZnO retained in the cotton substrate was sufficient enough to exhibit 50+ UV protection and 99% inhibition against the tested pathogenic micro-organisms. A plausible mechanism for better exhaustion of nano-ZnO on cotton fabric has been proposed on the basis of ionic liquid driven swelling property of the cotton polymer.     

Functional finishing in cotton fabrics using zinc oxide nanoparticles

Nanotechnology, according to the National Nanotechnology Initiative (NNI), is defined as utilization of structure with at least one dimension of nanometer size for the construction of materials, devices or systems with novel or significantly improved properties due to their nano-size. The nanostructures are capable of enhancing the physical properties of conventional textiles, in areas such as anti-microbial properties, water repellence, soil-resistance, anti-static, anti-infrared and flame-retardant properties, dyeability, colour fastness and strength of textile materials. In the present work, zinc oxide nanoparticles were prepared by wet chemical method using zinc nitrate and sodium hydroxide as precursors and soluble starch as stabilizing agent. These nanoparticles, which have an average size of 40 nm, were coated on the bleached cotton fabrics (plain weave, 30 s count) using acrylic binder and functional properties of coated fabrics were studied. On an average of 75%, UV blocking was recorded for the cotton fabrics treated with 2% ZnO nanoparticles. Air permeability of the nano-ZnO coated fabrics was significantly higher than the control, hence the increased breathability. In case of nano-ZnO coated fabric, due to its nano-size and uniform distribution, friction was significantly lower than the bulk-ZnO coated fabric as studied by Instron® Automated Materials Testing System. Further studies are under way to evaluate wash fastness, antimicrobial properties, abrasion properties and fabric handle properties.     

DravidianCodeMix: sentiment analysis and offensive language identification dataset for Dravidian languages in code-mixed text

Language Resources and Evaluation - This paper describes the development of a multilingual, manually annotated dataset for three under-resourced Dravidian languages generated from social media...     

Functional finishing of cotton fabrics using silver nanoparticles

We have reported a novel in situ synthesis protocol for silver nanoparticles onto cotton fabrics. Here, cotton fabric immersed in silver nitrate solution is autoclaved at 15 psi, 121 degrees C for 15 min. At this temperature and pressure, the aldehyde terminal of starch (residual size material on cotton fabric) reduced the silver nitrate to silver metal and simultaneously stabilized the nanoparticles on fabric itself. The UV-visible absorption spectrum of both cotton fabrics and bath solution showed a typical absorption peak at 420 nm corresponding to the surface plasmon resonance of silver nanoparticles. With the help of transmission electron micrographs, the average size of the dislodged silver nanoparticles in water is calculated to be 20.9 +/- 13.7 nm. This silver nanoparticles impregnated cotton fabrics showed excellent antibacterial activity against Staphylococcus aureus and bacteriostasis activity against Klebsiella pneumoniae. Also, silver nanoparticles impregnated fabrics expressed significant UV-protection capability in comparison with the untreated fabrics.     

Functional behaviour of paper coated with zinc oxide–soluble starch nanocomposites

Zinc oxide (ZnO) is a potential pigment material for paper coating to impart brightness and better printing properties. Nano-ZnO, due to its extremely small size, gives paper coating pigment a high covering power apart from anti-fungal and UV-protecting properties. In this work, zinc oxide–soluble starch nanocomposites (nano-ZnO) was prepared by a simple and novel wet chemical method using zinc nitrate and sodium hydroxide as precursors and soluble starch as stabilizing agent. Primary particle size distribution was extracted from small angle X-ray scattering (SAXS) measurements by the hard sphere model and calculated to have an average size of 4.1 nm. This nano-ZnO was coated on the surface of base paper (59 GSM) in a laboratory paper coater and their properties were studied. The brightness, whiteness, paper smoothness, print density, print uniformity, picking velocity and oil absorbency of nano-ZnO coated paper showed significant improvement than that of bulk-ZnO coated paper. In addition, the nano-ZnO coated paper showed excellent anti-fungal and UV-protecting properties that are much essential to enhance the life of a paper.     

Support Vector Machine-based Denoising Technique for Removal of White Noise in Partial Discharge Signal

Abstract—Partial discharge (PD) measurement has emerged as a dominant investigative tool for condition monitoring of insulation in high voltage equipment. In general, PD signals are severely polluted by several noises like white noise, random noise, discrete spectral interferences (DSI). The challenge lies with removing these noises from PD signal effectively by preserving the signal features. In this article, support vector machine (SVM) based denoising technique has been proposed for the removal of white noise from PD signal. The proposed SVM technique retains the edge of the original signal efficiently and also pseudo Gibbs phenomenon does not exist with SVM technique. In order to evaluate the effectiveness of the proposed method, artificially simulated PD signal mixed with white noise and the measured PD readings are considered. For the purpose of comparison, other denoising techniques such as fast Fourier transform (FFT), discrete wavelet transform (DWT), and translation invariant wavelet transform (TIWT) are also considered. The results reveal that, SVM based denoising technique shows better performance in terms of higher signal to noise ratio, signal reconstruction error ratio, cross correlation coefficient and reduction in noise level, mean square error, and waveform distortion.