A study on the effect of polishing fluid volume in ball end magnetorheological finishing process

Ball end magnetorheological finishing is a unique process that utilizes a magnetically controlled ball of polishing fluid at the tip of the rotating tool to finish workpiece of different materials and shapes. The aim of this research is to study the effect of polishing fluid volume on finishing spot size and the surface finish associated with it. A magnetostatic simulation is done to find the variation of flux density in the working gap and on the workpiece surface. The maximum limit of the polishing fluid volume is selected on the basis of area of threshold magnetic flux density (minimum value required for finishing) region on the workpiece surface. The surface characteristics and the diameter of the finished spot are analyzed by varying the fluid volume. The surface obtained with high fluid volume is poorly finished and has scratch marks as the excess fluid flows out from the working gap and forms a thick ring at the periphery of the tool tip. Contrary to this, if the fluid volume is too less, then it merely rotates over the workpiece surface without causing any finishing action. An optimum range of fluid volume produces a good quality surface finish with constant finished spot size.     

Piezoelectric properties in two-dimensional materials: Simulations and experiments

The piezoelectric effect, discovered in 1880 by Jacques and Pierre Curie, effectively allows to transduce signals from the mechanical domain to the electrical domain and vice versa. For this reason, piezoelectric devices are already ubiquitous, including, for instance, quartz oscillators, mechanical actuators with sub-atomic resolution and microbalances. However, the ability to synthesize two-dimensional (2D) materials may enable the fabrication of innovative devices with unprecedented performance. For instance, many materials which are not piezoelectric in their bulk form become piezoelectric when reduced to a single atomic layer; moreover, since all the atoms belong to the surface, piezoelectricity can be effectively engineered by proper surface modifications. As additional advantages, 2D materials are strong, flexible, easy to be co-integrated with conventional integrated circuits or micro-electromechanical systems and, in comparison with bulk or quasi-1D materials, easier to be simulated at the atomistic level. Here, we review the state of the art on 2D piezoelectricity, with reference to both computational predictions and experimental characterization. Because of their unique advantages, we believe 2D piezoelectric materials will substantially expand the applications of piezoelectricity.     

Bilayer SiO2 Nanorod Arrays as Omnidirectional and Thermally Stable Antireflective Coating

Nature instigates researchers significantly in imitating to engender comparable properties using artificial methods, which unlocks developing trend in material science and engineering progress. Fabricating graded‐index nanostructures is an effective approach to tune and generate similar properties artificially such as the moth's eye antireflectance (AR) or lotus like superhydrophobicity. Herein, Bilayer AR coatings with periodically arranged SiO₂ hierarchical nanostructures resembling moth eyes are fabricated on dense SiO₂ matrix base layer using the versatile route of glancing angle deposition technique (GLAD). The refractive indices of monolayer SiO₂ are tuned from 1.46 to 1.08 by changing the deposition angle (α) from 0 to 88°. The fabricated bilayer SiO₂ AR (BSAR) film possess high optical omnidirectional broadband transparency and tunability at a desired wavelength range showing <1% reflectance. The present AR design is flexible and practically applicable to various supporting substrate materials (η varies from 1.45 to 1.9). Furthermore, the omnidirectional BSAR films show multiple functions including enhanced mechanical strength, the thermal stability (up to 300 °C), and hydrophobic capability with a water contact angle (CA) of 147° to withstand under humid environment. This multipurpose coating provides an intriguing route in optics field for imminent research.

     

Template‐Free Fabrication of Mesoporous Alumina Nanospheres Using Post‐Synthesis Water‐Ethanol Treatment of Monodispersed Aluminium Glycerate Nanospheres for Molybdenum Adsorption

This work reports the template‐free fabrication of mesoporous Al₂O₃ nanospheres with greatly enhanced textural characteristics through a newly developed post‐synthesis “water‐ethanol” treatment of aluminium glycerate nanospheres followed by high temperature calcination. The proposed “water‐ethanol” treatment is highly advantageous as the resulting mesoporous Al₂O₃ nanospheres exhibit 2–4 times higher surface area (up to 251 m² g^?1), narrower pore size distribution, and significantly lower crystallization temperature than those obtained without any post‐synthesis treatment. To demonstrate the generality of the proposed strategy, a nearly identical post‐synthesis “water treatment” method is successfully used to prepare mesoporous monometallic (e.g., manganese oxide (MnO₂)) and bimetallic oxide (e.g., CuCo₂O₄ and MnCo₂O₄) nanospheres assembled of nanosheets or nanoplates with highly enhanced textural characteristics from the corresponding monometallic and bimetallic glycerate nanospheres, respectively. When evaluated as molybdenum (Mo) adsorbents for potential use in molybdenum‐99/technetium‐99m (⁹⁹Mo/^99mTc) generators, the treated mesoporous Al₂O₃ nanospheres display higher molybdenum adsorption performance than non‐treated Al₂O₃ nanospheres and commercial Al₂O₃, thereby suggesting the effectiveness of the proposed strategy for improving the functional performance of oxide materials. It is expected that the proposed method can be utilized to prepare other mesoporous metal oxides with enhanced textural characteristics and functional performance.     

Silver Nanoflower Decorated Graphene Oxide Sponges for Highly Sensitive Variable Stiffness Stress Sensors

Soft conductive materials should enable large deformation while keeping high electrical conductivity and elasticity. The graphene oxide (GO)‐based sponge is a potential candidate to endow large deformation. However, it typically exhibits low conductivity and elasticity. Here, the highly conductive and elastic sponge composed of GO, flower‐shaped silver nanoparticles (AgNFs), and polyimide (GO‐AgNF‐PI sponge) are demonstrated. The average pore size and porosity are 114 µm and 94.7%, respectively. Ag NFs have thin petals (8–20 nm) protruding out of the surface of a spherical bud (300–350 nm) significantly enhancing the specific surface area (2.83 m² g^?1). The electrical conductivity (0.306 S m^?1 at 0% strain) of the GO‐AgNF‐PI sponge is increased by more than an order of magnitude with the addition of Ag NFs. A nearly perfect elasticity is obtained over a wide compressive strain range (0–90%). The strain‐dependent, nonlinear variation of Young's modulus of the sponge provides a unique opportunity as a variable stiffness stress sensor that operates over a wide stress range (0–10 kPa) with a high maximum sensitivity (0.572 kPa^?1). It allows grasping of a soft rose and a hard bottle, with the minimal object deformation, when attached on the finger of a robot gripper.     

Nutratherapeutics approach against cancer: tomato‐mediated synthesised gold nanoparticles

In this study, an eco‐friendly biosynthesis of stable gold nanoparticles (T‐GNPs) was carried out using different concentrations of tomato juice (nutraceuticals) as a reducing agent and tetrachloroauric acid as a metal precursor to explore their potential application in cancer therapeutics. The synthesis of T‐GNPs was monitored by UV‐visible absorption spectroscopy, which unveiled their formation by exhibiting the typical surface plasmon absorption maxima at 522 nm. The size of T‐GNPs was found to be 10.86 ± 0.6 nm. T‐GNPs were characterised by dynamic light scattering, zeta potential, transmission electron microscopy analysis and Fourier transform infrared spectroscopy. T‐GNPs were further investigated for their anti‐cancer activity against human lung carcinoma cell line (A ₅₄₉) and human cervical cancer cell line wherein the IC₅₀ values were found to be 0.286 and 0.200 mM, respectively. T‐GNPs inhibited the growth of cancer cells by generating ROS and inducing apoptosis. T‐GNPs were found highly effective by virtue of their size, metallic property and capping molecules. Thus, this study opens up the prospects of using nutraceutical (tomato juice) as nutratherapeutic agent (T‐GNPs) against critical diseases like lung cancer and cervical cancer.Inspec keywords: gold, nanoparticles, particle size, cancer, ultraviolet spectra, visible spectra, electrokinetic effects, transmission electron microscopy, Fourier transform infrared spectra, cellular biophysics, spectrochemical analysis, nanomedicine, nanofabricationOther keywords: tomato‐mediated synthesised gold nanoparticles, tomato juice, reducing agent, tetrachloroauric acid, cancer therapeutics, UV‐visible absorption spectroscopy, surface plasmon absorption, dynamic light scattering, zeta potential, transmission electron microscopy analysis, Fourier transform infrared spectroscopy, human lung carcinoma cell line, anticancer activity, human cervical cancer cell line, nutratherapeutic agent, lung cancer, Au     

An Improved Hybrid Indoor Positioning Algorithm via QPSO and MLP Signal Weighting

Accurate location or positioning of people and self-driven devices in large indoor environments has become an important necessity The application of increasingly automated self-operating moving transportation units, in large indoor spaces demands a precise knowledge of their positions. Technologies like WiFi and Bluetooth, despite their low-cost and availability, are sensitive to signal noise and fading effects. For these reasons, a hybrid approach, which uses two different signal sources, has proven to be more resilient and accurate for the positioning determination in indoor environments. Hence, this paper proposes an improved hybrid technique to implement a fingerprinting based indoor positioning, using Received Signal Strength information from available Wireless Local Area Network access points, together with the Wireless Sensor Networks technology. Six signals were recorded on a regular grid of anchor points, covering the research space. An optimization was performed by relative signal weighting, to minimize the average positioning error over the research space. The optimization process was conducted using a standard Quantum Particle Swarm Optimization, while the position error estimate for all given sets of weighted signals was performed using a Multilayer Perceptron (MLP) neural network. Compared to our previous research works, the MLP architecture was improved to three hidden layers and its learning parameters were finely tuned. These experimental results led to the 20% reduction of the positioning error when a suitable set of signal weights was calculated in the optimization process. Our final achieved value of 0.725 m of the location incertitude shows a sensible improvement compared to our previous results.     

A Framework of Deep Optimal Features Selection for Apple Leaf Diseases Recognition

Identifying fruit disease manually is time-consuming, expert-required, and expensive; thus, a computer-based automated system is widely required. Fruit diseases affect not only the quality but also the quantity. As a result, it is possible to detect the disease early on and cure the fruits using computer-based techniques. However, computer-based methods face several challenges, including low contrast, a lack of dataset for training a model, and inappropriate feature extraction for final classification. In this paper, we proposed an automated framework for detecting apple fruit leaf diseases using CNN and a hybrid optimization algorithm. Data augmentation is performed initially to balance the selected apple dataset. After that, two pre-trained deep models are fine-tuning and trained using transfer learning. Then, a fusion technique is proposed named Parallel Correlation Threshold (PCT). The fused feature vector is optimized in the next step using a hybrid optimization algorithm. The selected features are finally classified using machine learning algorithms. Four different experiments have been carried out on the augmented Plant Village dataset and yielded the best accuracy of 99.8%. The accuracy of the proposed framework is also compared to that of several neural nets, and it outperforms them all.     

WiMA: Towards a Multi-Criterion Association in Software Defined Wi-Fi Networks

Despite the planned installation and operations of the traditional IEEE 802.11 networks, they still experience degraded performance due to the number of inefficiencies. One of the main reasons is the received signal strength indicator (RSSI) association problem, in which the user remains connected to the access point (AP) unless the RSSI becomes too weak. In this paper, we propose a multi-criterion association (WiMA) scheme based on software defined networking (SDN) in Wi-Fi networks. An association solution based on multi-criterion such as AP load, RSSI, and channel occupancy is proposed to satisfy the quality of service (QoS). SDN having an overall view of the network takes the association and reassociation decisions making the handoffs smooth in throughput performance. To implement WiMA extensive simulations runs are carried out on Mininet-NS3-Wi-Fi network simulator. The performance evaluation shows that the WiMA significantly reduces the average number of retransmissions by 5%–30% and enhances the throughput by 20%–50%, hence maintaining user fairness and accommodating more wireless devices and traffic load in the network, when compared to traditional client-driven (CD) approach and state of the art Wi-Balance approach.     

Localization of nervonic acid beta-oxidation in human and rodent peroxisomes: impaired oxidation in Zellweger syndrome and X-linked adrenoleukodystrophy

Studies with purified subcellular organelles from rat liver indicate that nervonic acid (C24:1) is beta-oxidized preferentially in peroxisomes. Lack of effect by etomoxir, inhibitor of mitochondrial beta-oxidation, on beta-oxidation of lignoceric acid (C24:0), a peroxisomal function, and that of nervonic acid (24:1) compared to the inhibition of palmitic acid (16:0) oxidation, a mitochondrial function, supports the conclusion that nervonic acid is oxidized in peroxisomes. Moreover, the oxidation of nervonic and lignoceric acids was deficient in fibroblasts from patients with defects in peroxisomal beta-oxidation [Zellweger syndrome (ZS) and X-linked adrenoleukodystrophy (X-ALD)]. Similar to lignoceric acid, the activation and beta-oxidation of nervonic acid was deficient in peroxisomes isolated from X-ALD fibroblasts. Transfection of X-ALD fibroblasts with human cDNA encoding for ALDP (X-ALD gene product) restored the oxidation of both nervonic and lignoceric acids, demonstrating that the same molecular defect may be responsible for the abnormality in the oxidation of nervonic as well as lignoceric acid. Moreover, immunoprecipitation of activities for acyl-CoA ligase for both lignoceric acid and nervonic acid indicate that saturated and monoenoic very long chain (VLC) fatty acids may be activated by the same enzyme. These results clearly demonstrate that similar to saturated VLC fatty acids (e.g., lignoceric acid), VLC monounsaturated fatty acids (e.g., nervonic acid) are oxidized preferentially in peroxisomes and that this activity is impaired in X-ALD. In view of the fact that the oxidation of unsaturated VLC fatty acids is defective in X-ALD patients, the efficacy of dietary monoene therapy, "Lorenzo's oil," in X-ALD needs to be evaluated.