Silane-functionalized Al2O3-modified polyurethane powder coatings: Nonisothermal degradation kinetics and mechanistic insights

This work reports on nonisothermal degradation kinetics of polyurethane (PU)-based powder coatings containing 1, 3, and 5%wt% vinyltrimethoxysilane functionalized Al₂O₃ (V-Al₂O₃) nanoparticles. Thermogravimetric analysis of PU/V-Al₂O₃ powder coatings with different V-Al₂O₃ contents has been performed at different heating rates. Variation of activation energy (E_a) of PU/V-Al₂O₃ powder coatings was modeled as a function of partial mass loss by using Kissinger–Akahira–Sunose, Ozawa–Wall–Flynn and modified Coats–Redfern isoconversional approaches. The results revealed hindered decomposition process of PU/V-Al₂O₃ nanocomposite powder coatings, featured by an increase in activation energy of degradation from ∼158 for blank PU to 225, 183, and 229 kJ/mol for nanocomposites filled with 1, 3, and 5 wt% of V-Al₂O₃, respectively. Likewise, pre-exponential factor values increased for samples containing V-Al₂O₃ nanoparticles compared to that of blank sample. Sestak–Berggren kinetic model appropriately captured thermal degradation behavior of PU/V-Al₂O₃ nanocomposites than that of nth order decomposition kinetic reaction models.     

Hidden Two-Stream Collaborative Learning Network for Action Recognition

The two-stream convolutional neural network exhibits excellent performance in the video action recognition. The crux of the matter is to use the frames already clipped by the videos and the optical flow images pre-extracted by the frames, to train a model each, and to finally integrate the outputs of the two models. Nevertheless, the reliance on the pre-extraction of the optical flow impedes the efficiency of action recognition, and the temporal and the spatial streams are just simply fused at the ends, with one stream failing and the other stream succeeding. We propose a novel hidden twostream collaborative (HTSC) learning network that masks the steps of extracting the optical flow in the network and greatly speeds up the action recognition. Based on the two-stream method, the two-stream collaborative learning model captures the interaction of the temporal and spatial features to greatly enhance the accuracy of recognition. Our proposed method is highly capable of achieving the balance of efficiency and precision on large-scale video action recognition datasets.     

Eco‐friendly synthesis of silver and gold nanoparticles with enhanced antimicrobial,antioxidant, and catalytic activities

The present work is emphasised on the bio‐fabrication of silver and gold nanoparticles in a single step by a microwave‐assisted method using the leaf extract of Synedrella nodiflora as both reducing and stabilising agent. The synthesised nanoparticles are highly stable and show surface plasmon resonance peak at 413 and 535 nm, respectively, for silver and gold nanoparticles in UV–Vis spectrum. The functional group responsible for the reduction of metal ions were obtained from Fourier transform infrared spectroscopy. The crystalline nature of nanoparticles with face‐centred cubic geometry was confirmed by the X‐ray diffraction and selected area electron diffraction patterns. The morphology and sizes of the silver and gold nanoparticles were obtained from transmission electron microscopy images. The nanoparticles exhibit effective antimicrobial activities against various pathogenic strains. These antimicrobial properties were analysed by employing agar well diffusion method. The nanoparticles show significant antioxidant properties, and it was determined using 2, 2‐diphenyl‐1‐picrylhydrazyl assay. The nanoparticles also show potent catalytic activity in the degradation of anthropogenic pollutant dyes Congo red and eosin Y by excess NaBH₄. Thus, the current study demonstrates the potential use of S. nodiflora as a reducing and stabilising agent for the synthesis of silver and gold nanoparticles and their relevance in the field of biomedicine and catalysis.Inspec keywords: transmission electron microscopy, visible spectra, surface plasmon resonance, nanofabrication, ultraviolet spectra, field emission electron microscopy, reduction (chemical), nanocomposites, microorganisms, nanoparticles, dyes, silver, X‐ray diffraction, nanomedicine, gold, antibacterial activity, electron diffraction, infrared spectra, particle size, Fourier transform spectra, scanning electron microscopy, catalysis, crystal growth from solutionOther keywords: synthesised nanoparticles, gold nanoparticles, catalytic activities, electron diffraction patterns, antimicrobial activities, antioxidant activities, transmission electron microscopy images, X‐ray diffraction, 2,2‐diphenyl‐1‐picrylhydrazyl assay, Synedrella nodiflora, UV–Vis spectrum, silver nanoparticles, biofabrication, surface plasmon resonance, Fourier transform infrared spectroscopy, face‐centred cubic geometry, area electron diffraction patterns, pathogenic strains, agar well diffusion method, anthropogenic pollutant dyes, Congo red, eosin Y, wavelength 413.0 nm, wavelength 535.0 nm, Au, Ag     

A knowledge-based framework for extracting components in agile systems development

Considerable strides have been made in the use of components in software development. Many proprietary enterprise resource planning (ERP) software environments use modular components to develop and customize “best practices” to meet a specific organizational need. In agile application development, many developers and users are asked to design systems in a short period of time. These applications may use components that are embedded in software repositories. The challenge then is how to select the right software components (data and procedures) to meet an application requirement. Although experienced developers may select and customize components to meet the needs of an application, such expertise may not be available to other applications. This paper presents a knowledge-based framework to select and customize software components and demonstrates its value in deriving quality specifications, even when the developers are relatively inexperienced.     

Neural Free-Viewpoint Relighting for Glossy Indirect Illumination

Precomputed Radiance Transfer (PRT) remains an attractive solution for real-time rendering of complex light transport effects such as glossy global illumination. After precomputation, we can relight the scene with new environment maps while changing viewpoint in real-time. However, practical PRT methods are usually limited to low-frequency spherical harmonic lighting. All-frequency techniques using wavelets are promising but have so far had little practical impact. The curse of dimensionality and much higher data requirements have typically limited them to relighting with fixed view or only direct lighting with triple product integrals. In this paper, we demonstrate a hybrid neural-wavelet PRT solution to high-frequency indirect illumination, including glossy reflection, for relighting with changing view. Specifically, we seek to represent the light transport function in the Haar wavelet basis. For global illumination, we learn the wavelet transport using a small multi-layer perceptron (MLP) applied to a feature field as a function of spatial location and wavelet index, with reflected direction and material parameters being other MLP inputs. We optimize/learn the feature field (compactly represented by a tensor decomposition) and MLP parameters from multiple images of the scene under different lighting and viewing conditions. We demonstrate real-time (512 x 512 at 24 FPS, 800 x 600 at 13 FPS) precomputed rendering of challenging scenes involving view-dependent reflections and even caustics.     

Statistical exploratory analysis of genetic algorithms

Genetic algorithms have been extensively used and studied in computer science, yet there is no generally accepted methodology for exploring which parameters significantly affect performance, whether there is any interaction between parameters, and how performance varies with respect to changes in parameters. This paper presents a rigorous yet practical statistical methodology for the exploratory study of genetic and other adaptive algorithms. This methodology addresses the issues of experimental design, blocking, power calculations, and response curve analysis. It details how statistical analysis may assist the investigator along the exploratory pathway. As a demonstration of our methodology, we describe case studies using four well-known test functions. We find that the effect upon performance of crossover is pre-dominantly linear, while the effect of mutation is predominantly quadratic. Higher order effects are noted but contribute less to overall behavior. In the case of crossover, both positive and negative gradients are found suggesting the use of a maximum crossover rate for some problems and its exclusion for others. For mutation, optimal rates appear higher compared with earlier recommendations in the literature, while supporting more recent work. The significance of interaction and the best values for crossover and mutation are problem specific.     

CFD simulation for steam distribution in header and tube assemblies

The study of the flow characteristics in manifolds (dividing, combining, parallel or Z-manifold and reverse or U-manifold) is a classic subject of engineering fluid dynamics and hydrodynamics. These manifolds are widely used in chemical processes, electronic cooling equipment, solar collectors, spargers, microchannels, fuel cells, heat exchangers and refrigerant distribution in multi-split type of air conditioner, etc. In the literature extensive work has been done for finding out flow distribution in plate-fin heat exchanger, microchannels and spargers. Present work focuses on the flow and pressure distribution in piping networks, which has gained importance in many areas such as air distribution in diffuser system of aerobic biological treatment, steam distribution in passive decay heat removal systems, etc.     

Physical and electrical properties of combustion synthesized NASICON type Na3Cr2(PO4)3 crystallites: Effect of glycine molar ratios

Thermally stable Na₃Cr₂(PO₄)₃ nano-crystallites are synthesized through novel solution combustion technique using glycine fuel in three molar ratios. Effects of fuel molar ratio on structural and electrical properties are investigated. Reaction parameters like fuel molar ratio, flame temperature and number of moles of gases evolved, play a major role in deciding physical and electrical properties. Out of the synthesized samples, one which contains fuel in 1:1 molar ratio shows highest grain conductivity of 2.35 × 10⁻⁶ S cm⁻¹. Improved conductivity is elucidated by least size and highest density of the crystallites, which in turn is decided by the flame temperature. Ac electrical properties are investigated using complex impedance spectroscopy. Activation energies for dc conduction and relaxation are determined and the results are reported.     

Optical properties of corn oil during frying

Optical absorption characteristics of corn oil were investigated in the visible and near infrared regions between 400 and 2500 nm as the oil degraded during potato frying. The visible wavelength of maximum absorption between 400 and 600 nm shifted towards longer wavelengths as the frying operation progressed. The results showed that light absorption in the visible range of the electromagnetic spectrum between 400 and 600nm correlated well with viscosity.     

Combustion synthesis and subsequent sintering of titanium-matrix composites

Titanium-matrix composites containing up to 50 wt% TiC particles were prepared by combustion synthesis using elemental powders. The products were subsequently sintered at 1160°C for various periods of time. SEM and X-ray diffraction were used to assess the changes that took place during the two stages of processing. Products of combustion synthesis containing in excess of 25%TiC contained large cracks as well as agglomerates of carbide particles that were undesirable from the point of view of reinforcing the metal. The carbide obtained by combustion synthesis had a higher carbon content than that expected according to the Ti-C equilibrium phase diagram, due to the non-equilibrium nature of the reaction. During the sintering stage, the carbide of non-equilibrium composition reacted with titanium to yield the carbide of equilibrium composition. The composition changes were investigated and their significance on the sintering process is discussed.