An optical tool for quantitative assessment of phycocyanin pigment concentration in cyanobacterial blooms within inland and marine environments

Quantitative assessment of the pigment phycocyanin (PC) in cyanobacterial blooms is essential to assess their abundance and distribution and consequently aid their management in many recreational waters within inland and coastal environments. In contrast to the open-ocean waters, these water bodies are very complex with a pronounced heterogeneity of their optical properties, and hence accurate retrieval of the water-leaving radiances and PC concentration from satellite observations is notoriously difficult with existing algorithms. In the present study, a new inversion algorithm is developed as a rapid cyanobacteria bloom assessment method and its retrievals of PC are compared with in-situ and satellite observations and those from a previously reported inversion algorithm. The new algorithm estimates PC concentration on the basis of the unique absorption feature of phycocyanin at 620 nm which is isolated from the total pigment absorption by taking advantage of the well-recognized absorption and reflectance features in the red and near-infrared (NIR) wavelengths (less impacted by the influences of the overlapping absorption signatures of the mixture constituents and pigment packaging). The by-products of this work include chl-a concentration and predictions from reflectance data to monitor the cyanobacterial component and non-cyanobacterial component of the phytoplankton assemblage and to evaluate PC:Chl-a pigment weight ratios for specific water types. Initial validation of the algorithm was performed using in-situ field data in turbid productive waters dominated by phycocyanin and other pigments, yielding coefficients of determination and slope close to unity and mean errors less than a few percent. These results suggest that the algorithm could be used as a rapid assessment tool for the remote-sensing assessment of the spatial distribution and relative abundance of cyanobacterial blooms in many regional water bodies.     

Syzygium aqueum leaf extract and its bioactive compounds enhances pre-adipocyte differentiation and 2-NBDG uptake in 3T3-L1 cells

The insulin-like and/or insulin-sensitising effects of Syzygium aqueum leaf extract and its six bioactive compounds; 4-hydroxybenzaldehyde, myricetin-3-O-rhamnoside, europetin-3-O-rhamnoside, phloretin, myrigalone-G and myrigalone-B were investigated in 3T3-L1 adipocytes. We observed that, S. aqueum leaf extract (0.04–5 μg/ml) and its six bioactive compounds (0.08–10 μM) at non-cytotoxic concentrations were effectively enhance adipogenesis, stimulate glucose uptake and increase adiponectin secretion in 3T3-L1 adipocytes. Clearly, the compounds myricetin-3-O-rhamnoside and europetin-3-O-rhamnoside showed insulin-like and insulin-sensitising effects on adipocytes from a concentration of 0.08 μM. These compounds were far better than rosiglitazone and the other isolated compounds in enhancing adipogenesis, stimulating 2-NBDG uptake and increasing adiponectin secretion at all the concentrations tested. These suggest the antidiabetic potential of S. aqueum leaf extract and its six bioactive compounds. However, further molecular interaction studies to explain the mechanisms of action are highly warranted.     

Photocuring and thermomechanical properties of multifunctional amide acrylate compositions derived from castor oil

The photopolymerization of multifunctional acrylate monomers synthesized from castor oil was investigated by photo-DSC. These studies revealed that the extent of photopolymerization depended on the double bond concentration and a greater degree of crosslinking occurred in monomer mixtures with higher difunctional content. The monomer mixtures displayed significantly higher maximum rate of polymerization (R_p^max) and shorter time to reach peak maximum than the pure monomers. DMTA studies of films showed good storage modulus and broad tan δ transitions indicating heterogeneity in the crosslinked networks. The films displayed sub-T_g transitions in the loss modulus curves were possibly due to the side chain motions of the monomer acrylates which increased with increasing triacrylate concentration. Glass transition temperature (T_g) of these networks depended on composition and shifted to higher values with increasing amount of triacrylate.     

Active bearing estimation from a mobile two-dimensional array of sensors

A new approach for active-sonar target detection and bearing estimation from a mobile two-dimensional array of sensors operating in a predominantly noisy environment is presented. Sensor-level adaptive noise cancellation featuring an unconventional method for reference-noise estimation is the key preprocessing step in the proposed approach. A signal-subspace algorithm resulting from two-stage optimisation based on a generalised eigendecomposition of the signal plus (residual) noise covariance matrix is employed to estimate the bearing of the detected target. Simulation results conclusively demonstrate that the proposed scheme is capable of performing target detection and the subsequent two-dimensional bearing estimation with a high degree of reliability at signal-to-noise power ratios as low as -70 and -40-dB, respectively.     

Chemical constituents and antimicrobial and antioxidant potentials of essential oil and acetone extract of Nigella sativa seeds

The antifungal, antibacterial and antioxidant potentials of essential oil and acetone extract of black cumin were investigated by different techniques. In the inverted petriplate method, the essential oil showed complete zones of inhibition against Penicillium citrinum at a 6 µl dose. Essential oil showed complete growth inhibition against Bacillus cereus, Bacillus subtilis and Staphylococcus aureus, Pseudomonas aeruginosa at 2000 and 3000 ppm, respectively, by the agar well diffusion method. The antioxidant activity was evaluated by measuring peroxide, TBA and total carbonyl values of rapeseed oil at fixed time intervals. Both the extract and essential oil showed strong antioxidant activity in comparison with butylated hydroxyanisole (BHA) and butylated hydroxytoluene (BHT). In addition, their inhibitory action in the linoleic acid system was studied by monitoring the accumulation of peroxide concentration. Their radical scavenging capacity was carried out on 2,2′‐diphenyl‐1‐picrylhydrazyl (DPPH) radical and they showed excellent scavenging activity in comparison with synthetic antioxidants. Their reducing power was also determined, demonstrating strong antioxidant capacity of both the essential oil and extract. Gas chromatographic and gas chromatographic–mass spectrometric studies on the essential oil resulted in the identification of 38 components representing 84.65% of the total amount. The major component was p‐cymene (36.2%) followed by thymoquinone (11.27%), α‐thujene (10.03%), longifolene (6.32%), β‐pinene (3.78%), α‐pinene (3.33%) and carvacrol (2.12%), whereas extract showed the presence of 16 components representing 97.9% of the total amount. The major components were linoleic acid (53.6%), thymoquinone (11.8%), palmitic acid (10%), p‐cymene (8.6%), longifolene (5.8%) and carvacrol (3.7%). Copyright © 2005 Society of Chemical Industry     

FPGA Implementation of Deep Leaning Model for Video Analytics

In recent years, deep neural networks have become a fascinating and influential research subject, and they play a critical role in video processing and analytics. Since, video analytics are predominantly hardware centric, exploration of implementing the deep neural networks in the hardware needs its brighter light of research. However, the computational complexity and resource constraints of deep neural networks are increasing exponentially by time. Convolutional neural networks are one of the most popular deep learning architecture especially for image classification and video analytics. But these algorithms need an efficient implement strategy for incorporating more real time computations in terms of handling the videos in the hardware. Field programmable Gate arrays (FPGA) is thought to be more advantageous in implementing the convolutional neural networks when compared to Graphics Processing Unit (GPU) in terms of energy efficient and low computational complexity. But still, an intelligent architecture is required for implementing the CNN in FPGA for processing the videos. This paper introduces a modern high-performance, energy-efficient Bat Pruned Ensembled Convolutional networks (BPEC-CNN) for processing the video in the hardware. The system integrates the Bat Evolutionary Pruned layers for CNN and implements the new shared Distributed Filtering Structures (DFS) for handing the filter layers in CNN with pipelined data-path in FPGA. In addition, the proposed system adopts the hardware-software co-design methodology for an energy efficiency and less computational complexity. The extensive experimentations are carried out using CASIA video datasets with ARTIX-7 FPGA boards (number) and various algorithms centric parameters such as accuracy, sensitivity, specificity and architecture centric parameters such as the power, area and throughput are analyzed. These results are then compared with the existing pruned CNN architectures such as CNN-Prunner in which the proposed architecture has been shown 25% better performance than the existing architectures.     

Screening the UV‐blocking and antimicrobial properties of herbal nanoparticles prepared from Aloe vera leaves for textile applications

Nanomaterials play a vital role in textile industries due to their unique properties and applications. There is an increase in the use of nanoscale phyto products in textiles to control the bacterial infection in fabrics. Here, natural herbal nanoparticles of different sizes were prepared from shade‐dried Aloe vera plant leaves using ball milling technique without any additives. The amorphous herbal A. vera nanoparticles possess an average particle size of 40 ± 2 nm and UV‐absorption maximum at 269 nm. A. vera nanopowders–chitosan nanocomposites were prepared and coated on cotton fabrics using pad‐dry cure method. The evaluation of antibacterial activity against Escherichia coli (22.05 ± 0.06 mm) and Staphylococcus aureus (27.17 ± 0.02 mm), UV‐protection properties (UV‐protection factor = 57.2 ± 0.1), and superhydrophobic nature (155 ± 3°) of the prepared herbal nanoparticles and their composites were analysed by disc diffusion, UV–visible spectral analysis, and contact angle analysis. Understanding the functional properties of herbal nanoparticles, coated particles on fabrics highlights their potential applications in protective clothing with better antimicrobial properties, hydrophobicity, and UV‐protection properties. This study of using A. vera herbal nanoparticles in textiles significantly enhances the fabric performance to develop protective textile fabrics in defence and biomedical fields.Inspec keywords: nanoparticles, particle size, nanofabrication, nanomedicine, antibacterial activity, biomedical materials, hydrophobicity, ultraviolet spectra, visible spectra, radiation protection, textile fibres, cotton fabrics, ball milling, X‐ray diffraction, light scattering, scanning electron microscopy, X‐ray fluorescence analysis, fluorescence, amorphous state, nanocomposites, filled polymers, protective coatings, curing, microorganisms, biodiffusion, contact angle, surface morphology, protective clothingOther keywords: UV‐blocking, antimicrobial properties, disc diffusion, UV‐visible spectral analysis, contact angle analysis, morphological characteristics, protective clothing, protective textile fabrics, biomedical fields, superhydrophobic nature, UV‐protection factor, UV‐protection properties, Staphylococcus aureus, Escherichia coli, pad‐dry cure method, cotton fabrics, A. vera nanopowders‐chitosan nanocomposites, UV‐absorption maximum, average particle size, amorphous herbal A. vera nanoparticles, X‐ray fluorescence spectrometry, scanning electron microscopy, dynamic light scattering, UV‐visible spectrophotometry, X‐ray diffraction, ball milling, shade‐dried Aloe vera plant leaves, natural herbal nanoparticle size, bacterial infection, nanoscale phyto products, textile industries, nanomaterials, textile applications     

Fringe Formation in an In-Plane Displacement Measurement Configuration with Twofold Increase in Sensitivity: Theory and experiment

A fringe-formation theory for a dual-beam illumination configuration that leads to a twofold increase in sensitivity for the measurement of in-plane displacement is described. Here we have taken into account all four beams simultaneously that are generated at the image plane owing to two-beam illumination and their cross-interference terms for fringe formation. We show that the sensitivity obtainable is the usual interferometric sensitivity when we take into account all four beams simultaneously and doubles only when the retroreflected beams are observed. A detailed theory and an experimental demonstration of the method are presented.     

A vector radiative transfer model for sea-surface salinity retrieval from space: a non-raining case

ABSTRACT

Sea-surface salinity (SSS) can be measured from space using a microwave sensor. However, achieving the desired accuracy in SSS retrieval is challenging due to the lower sensitivity of the brightness temperature to SSS especially at low sea-surface temperature conditions. The retrieval accuracy can be further degraded due to the atmospheric and sea-surface effects (including emission and reflection), which require more accurate correction methods based on the radiative transfer model. In this article, a vector radiative transfer model (VRTM) was developed based on a matrix operator method that considers the ocean–atmosphere system under non-raining conditions. The results from this model were compared with measurement data provided by the Soil Moisture and Ocean Salinity (SMOS) satellite sensor and the results from two other RT models (RT4 model and a forward model of the European Space Agency, ESA). Statistical evaluation of these results revealed that estimation errors of top of atmosphere (TOA) radiance by the VRTM model was less than 0.3% as compared to the RT4 model results. The difference of the brightness temperatures predicted by the VRTM model and measured by the SMOS was within 1.5 K which was better than the ESA’s forward model predictions. These results suggest that the VRTM is relatively more accurate and has high computational efficiency for simulating the TOA brightness temperature for various scientific research and remote-sensing applications.