The influence of substrate temperature on the structural and optical properties of ZnS thin films

Thin films of ZnS were deposited on soda lime glass substrates by a modified close-space sublimation technique. The change in optical and structural properties of the films deposited at various substrate temperatures (150–450°C) was investigated. X-ray diffraction spectra showed that films were polycrystalline in nature having cubic structure oriented only along (111) plan. The crystallinity of films increased with the substrate temperature up to 250°C. However, crystallinity decreased with further increase of substrate temperature and films became amorphous at 450°C. The atomic force microscopy data revealed that the films become more uniform and dense with the increase of substrate temperature. Optical properties of the films were determined from the transmittance data using Swanepoel model. It was observed that the energy band gap is increased from 3.52 to 3.65 eV and refractive index of the films are decreased with the increase of substrate temperature. Moreover, considerable improvement in blue response of the films was noticed with increasing substrate temperature.     

Design formulations for non-welded and welded aluminium columns using Continuous Strength Method

Aluminium members are used in structural applications due to their high strength-to-weight ratio, corrosion resistance, attractive appearance, recyclability, ease of production and availability. Thin aluminium sections are susceptible to buckling at a relatively low stress and welding makes it even worse; the design stress i.e. 0.2% proof stress is almost halved in the vicinity of the heat affected zones (HAZs). Currently available design codes have their guidelines both for welded and non-welded aluminium columns, but the predictions for welded aluminium columns are often quite inconsistent. The current research exploits a newly developed strain based design approach the ‘Continuous Strength Method’ (CSM) to predict the behaviour of aluminium members with SHS and RHS cross-sections subjected to compression. A new design curve is proposed herein to predict the cross-sectional resistance in compression; this concept is further extended to propose a new Perry type buckling curve to predict the flexural buckling resistance of aluminium columns. A simplified technique is proposed to include the effect of heat affected zone (HAZ) in CSM formulations. The CSM predictions for aluminium columns are compared against those obtained using available guidelines proposed by the European, American and Australian/ New Zealand standards of aluminium structures. The CSM predictions for non-welded columns are in line with the code predictions, whilst the proposed simple technique for transversely welded columns seems to produce significantly improved predictions.     

A robust neural network model for fault detection in the presence of mislabelled data

Several data-driven methodologies for process monitoring and detection of faults or abnormalities have been developed for the safety of processing systems. The effectiveness of data-based models, however, is impacted by the volume and quality of training data. This work presents a robust neural network model for addressing the mislabelled and low-quality data in detecting faults and process abnormalities. The approach is based on harnessing data quality features along with supervisory labels in the network training. The data quality has been computed using the Mahalanobis distances and trusted centres of each class of data such as normal and faulty data. The method has been examined for detecting abnormalities in two case studies; a continuous stirred tank heater problem for detecting leaks and the Tennessee Eastman chemical process for detecting step and sticking faults. The performance of the proposed robust artificial neural networks (ANN) model is evaluated in terms of accuracy, fault detection rate, false alarm rate, and classification index at varying extents of mislabelling, namely, 1%, 5%, and 10% mislabelled data. The proposed model demonstrates higher detection performance, especially at increased labels of mislabelled data where the performance of the conventional ANN is severely impacted. The proposed methodology can be advantageous in handling mislabelled and low-quality data issues which are crucial in the data-driven modelling of processing systems.     

A comprehensive study on the size-dependent hygrothermal analysis of exponentially graded microplates on elastic foundations

Abstract

In this paper, the effects of hygrothermal conditions on various behaviors, such as bending, free vibration, mechanical and thermal buckling, of exponentially graded microplates lying on two-parameter elastic foundations are investigated. The trigonometric four-variable plate theory incorporated to the modified couple stress theory (MCST) is employed to derive the equations of motion. The present MCST contains an internal material length scale parameter, thus it can capture the size effect. The microplate is assumed to be subjected to a temperature rise and moisture concentration which are varied linearly through the thickness of the plate. Based on an exponential law, the material properties of the microplate are graded only in z direction. The equations of motion are solved analytically to obtain the displacements, stresses, eigenfrequencies and critical buckling load and temperature of the microplates. The present results are validated by comparing them with those previously published. The numerical examples reveal that considering the size effect and/or the elastic foundations leads to an increment in plate stiffness and thereby leads to a decrement in the deflection and an increment in eigenfrequency and buckling loads. It is also shown that the size effect is negligible for the thicker plate.     

Carbon nanotubes play an important role in the spatial arrangement of calcium deposits in hydrogels for bone regeneration

Age related bone diseases such as osteoporosis are considered among the main causes of reduced bone mechanical stability and bone fractures. In order to restore both biological and mechanical function of diseased/fractured bones, novel bioactive scaffolds that mimic the bone structure are constantly under development in tissue engineering applications. Among the possible candidates, chitosan-based thermosensitive hydrogel scaffolds represent ideal systems due to their biocompatibility, biodegradability, enhanced antibacterial properties, promotion of osteoblast formation and ease of injection, which makes them suitable for less invasive surgical procedures. As a main drawback, these chitosan systems present poor mechanical performance that could not support load-bearing applications. In order to produce more mechanically-competent biomaterials, the combined addition of hydroxyapatite and carbon nanotubes (CNTs) is proposed in this study. Specifically, the aim of this work is to develop thermosensitive chitosan hydrogels containing stabilised single-walled and multi-walled CNTs, where their effect on the mechanical/physiochemical properties, calcium deposition patterns and ability to provide a platform for the controlled release of protein drugs was investigated. It was found that the addition of CNTs had a significant effect on the sol–gel transition time and significantly increased the resistance to compression for the hydrogels. Moreover, in vitro calcification studies revealed that CNTs played a major role in the spatial arrangements of newly formed calcium deposits in the composite materials studied, suggesting that they may have a role in the way the repair of fragile and/or fractured bones occurs in vivo.     

Estimation of missing observations in two‐level split‐plot designs

Inserting estimates for the missing observations from split‐plot designs restores their balanced or orthogonal structure and alleviates the difficulties in the statistical analysis. In this article, we extend a method due to Draper and Stoneman to estimate the missing observations from unreplicated two‐level factorial and fractional factorial split‐plot (FSP and FFSP) designs. The missing observations, which can either be from the same whole plot, from different whole plots, or comprise entire whole plots, are estimated by equating to zero a number of specific contrast columns equal to the number of the missing observations. These estimates are inserted into the design table and the estimates for the remaining effects (or alias chains of effects as the case with FFSP designs) are plotted on two half‐normal plots: one for the whole‐plot effects and the other for the subplot effects. If the smaller effects do not point at the origin, then different contrast columns to some or all of the initial ones should be discarded and the plots re‐examined for bias. Using examples, we show how the method provides estimates for the missing observations that are very close to their actual values. Copyright © 2007 John Wiley & Sons, Ltd.     

Generation and Selection of Specific Aptamers Targeting Brucella Species through an Enhanced Cell-SELEX Methodology

Brucellae are Gram-negative, aerobic, non-motile coccobacilli causing brucellosis in man and animals. The disease is one of the most significant yet neglected global zoonoses. Especially in developing countries, brucellosis is causing public health problems and economic losses to private animal owners and national revenues. Composed of oligonucleotides, aptamers are chemical analogues of antibodies that are promising components for developing aptamer-based rapid, sensitive, and specific tests to identify the Brucella group of bacteria. For this purpose, aptamers were generated and selected by an enhanced protocol of cell systematic evolution of ligands by exponential enrichment (cell-SELEX). This enhanced cell-SELEX procedure involved the combination of both conventional and toggle cell-SELEX to boost the specificity and binding affinity to whole Brucella cells. This procedure, combined with high-throughput sequencing of the resulting aptamer pools, comprehensive bioinformatics analysis, and wet lab validation assays, led to the selection of a highly sensitive and specific aptamer for those Brucella species known to circulate in Egypt. The isolated candidate aptamer showed dissociation constant (K_D) values of 43.5 ± 11, 61.5 ± 8, and 56 ± 10.8 nM for B. melitensis, B. abortus, and B. suis, respectively. This is the first development of a Brucella-specific aptamer using an enhanced combination of conventional and toggle cell-SELEX to the authors’ best knowledge.     

Hydrogen production by methane cracking using Ni-supported catalysts in a fluidized bed

Nickel, supported on porous alumina (γAl₂O₃), non-porous alumina (αAl₂O₃), and porous silica, was used to catalyze methane cracking in a fluidized bed reactor for hydrogen production. The effects of temperature, PCH₄${\text{P}}_{{\text{CH}}_4}$, and particle diameter, and their interactions, on methane conversion were studied with each catalyst. Temperature was the dominant parameter affecting the hydrogen production rate for all catalysts and particle diameter had the strongest effect on the total amount of carbon deposited. Maximum methane conversion as a function of support type followed the order Ni/SiO₂ > Ni/αAl₂O₃ > Ni/γAl₂O₃. Nonetheless, better fluidization quality was obtained with Ni/γAl₂O₃. Methane conversion was increased by increasing temperature and particle size from 108 to 275 μm due to better fluidization achieved with 275 μm particles. Increasing the flow rate and methane partial pressure (PCH₄${\text{P}}_{{\text{CH}}_4}$) caused a drop in methane conversion. Tests were also run in a fixed bed reactor, and at constant weight hourly space velocity (WHSV), higher conversion was achieved in the fixed bed, but at the same time faster deactivation occurred since a higher methane conversion led to increase in carbon filament and encapsulating carbon formation rates. A critical problem with the fixed bed was the pressure build-up inside the reactor due to carbon accumulation. Finally, a series of cracking/regeneration cycle experiments were carried out in the fluidized bed reactor. The regeneration was performed through product carbon gasification in air. Ni/αAl₂O₃ and Ni/γAl₂O₃ activity decreased significantly with the first regeneration, which is attributed to Ni sintering during exothermic regeneration/carbon oxidation. However, Ni/SiO₂ was thermally stable over at least three cracking/regeneration cycles, but mechanical attrition was observed.     

Detection of Abnormal Activities from Various Signals Based on Statistical Analysis

We perceive big data with massive datasets of complex and variegated structures in the modern era. Such attributes formulate hindrances while analyzing and storing the data to generate apt aftermaths. Privacy and security are the colossal perturb in the domain space of extensive data analysis. In this paper, our foremost priority is the computing technologies that focus on big data, IoT (Internet of Things), Cloud Computing, Blockchain, and fog computing. Among these, Cloud Computing follows the role of providing on-demand services to their customers by optimizing the cost factor. AWS, Azure, Google Cloud are the major cloud providers today. Fog computing offers new insights into the extension of cloud computing systems by procuring services to the edges of the network. In collaboration with multiple technologies, the Internet of Things takes this into effect, which solves the labyrinth of dealing with advanced services considering its significance in varied application domains. The Blockchain is a dataset that entertains many applications ranging from the fields of crypto-currency to smart contracts. The prospect of this research paper is to present the critical analysis and review it under the umbrella of existing extensive data systems. In this paper, we attend to critics' reviews and address the existing threats to the security of extensive data systems. Moreover, we scrutinize the security attacks on computing systems based upon Cloud, Blockchain, IoT, and fog. This paper lucidly illustrates the different threat behaviour and their impacts on complementary computational technologies. The authors have mooted a precise analysis of cloud-based technologies and discussed their defense mechanism and the security issues of mobile healthcare.