Protein/Polymer‐Based Dual‐Responsive Gold Nanoparticles with pH‐Dependent Thermal Sensitivity

This article presents the synthesis and physicochemical behavior of dual‐responsive plasmonic nanoparticles with reversible optical properties based on protein‐coated gold nanoparticles grafted with thermosensitive polymer brushes by means of surface‐initiated atom transfer radical polymerization (SI‐ATRP) that exhibit pH‐dependent thermo‐responsive behavior. Spherical gold NPs of two different sizes (15 nm and 60 nm) and with different stabilizing agents (citrate and cetyltrimethylammonium bromide (CTAB), respectively) were first capped with bovine serum albumin (BSA). The resulting BSA‐capped NPs (Au@BSA NPs) exhibited not only extremely high colloidal stability under physiological conditions, but also a reversible U‐shaped pH‐responsive behavior, similar to pure BSA. The ?‐amine of the L‐lysine in the protein coating was then used to covalently bind an ATRP‐initiator, allowing for the SI‐ATRP of thermosensitive polymer brushes of oligo(ethylene glycol) methacrylates with an LCST of 42 °C in pure water and around 37 °C under physiological conditions. Such protein coated nanoparticles grafted with thermosensitive polymers exhibit a smart pH‐dependent thermosensitive behavior.     

Buccal Bioadhesive Delivery System of 5-Fluorouracil: Optimization and Characterization

The objective of this work was to apply the response surface approach in the development of buccal bioadhesive tablets of 5-fluorouracil (5-FU). Experiments were performed according to a 3² factorial design to evaluate the effects of two polymers, Gantrez MS-955 (X₁) and hydroxypropylmethyl cellulose (HPMC) K15M (X₂) on the bioadhesive force, percentage drug release in 8 h (Rel_{8 h}), time taken for 50% drug release (t_50%), and diffusion coefficient (n). The effect of the two independent variables on the response variables was studied by response surface plots and contour plots generated by the Design Expert® software. The compatibility between 5-FU and the tablet excipients was confirmed by differential scanning calorimetry (DSC) and Fourier transform infrared (FTIR) studies. Both the polymers were found to have synergistic effect on bioadhesion but the effect of Gantrez was more pronounced. A nonlinear twisted relationship was obtained for Rel_{8 h} at the intermediate and high levels of the polymers, which indicated an interaction between them at the corresponding factor levels. Kinetic treatment to the dissolution profiles revealed that the drug release ranged from Fickian to anomalous transport, which was mainly dependent on both the independent variables. The desirability function was used to optimize the response variables, and the observed responses were in agreement with the experimental values.     

Interaction of polyelectrolytes and their composites with living cells

Since the layer-wise polyelectrolyte deposition offers the opportunity to modify surfaces for biomedical applications, interactions and toxicity between polyelectrolytes and living cells become interesting. The aim of the present work is to determine the different factors such as contact area, charge, and transplantation site that influence the cell reaction to a specific polymer. We found that toxicity is influenced by all these factors and cannot be tested easily in a model.     

Face mask detection using YOLOv3 and faster R-CNN models: COVID-19 environment

There are many solutions to prevent the spread of the COVID-19 virus and one of the most effective solutions is wearing a face mask. Almost everyone is wearing face masks at all times in public places during the coronavirus pandemic. This encourages us to explore face mask detection technology to monitor people wearing masks in public places. Most recent and advanced face mask detection approaches are designed using deep learning. In this article, two state-of-the-art object detection models, namely, YOLOv3 and faster R-CNN are used to achieve this task. The authors have trained both the models on a dataset that consists of images of people of two categories that are with and without face masks. This work proposes a technique that will draw bounding boxes (red or green) around the faces of people, based on whether a person is wearing a mask or not, and keeps the record of the ratio of people wearing face masks on the daily basis. The authors have also compared the performance of both the models i.e., their precision rate and inference time.

     

Machining Parameters Optimization of Titanium Alloy using Response Surface Methodology and Particle Swarm Optimization under Minimum-Quantity Lubrication Environment

The present paper depicts an application of response surface methodology (RSM) and particle swarm optimization (PSO) technique for optimizing the machining factors in turning of titanium (Grade-II) alloy using cubic boron nitride insert tool under minimum quantity lubricant (MQL) environment. The three machining factors, i.e., cutting speed (V_c), feed rate (f) and side cutting edge angle (approach angle π), are designed as three factors by using RSM design, which is withal subject to several constraints including tangential force (F_c), tool wear (V_Bmax), surface roughness (R_a) and tool-chip contact length (L). The multiple regression technique was used to establish the interaction between input parameters and given responses. Moreover, the results have been presented and optimized process parameters are acquired through multi-response optimization via desirability function as well as the PSO technique. The lower values of V_c (200 m/min), f (0.10 mm/rev) and higher values of ? (90°) are the optimum machining factors for minimizing the aforementioned responses. It was also observed that the selected responses predicated on PSO are much closer as that of the values acquired in view of the desirability function approach. Henceforth, PSO has the potential to cull appropriate machining factors while turning titanium (Grade-II) alloys under MQL conditions.     

Effect of deposition time on sputtered ZnO thin films and their gas sensing application

Nowadays, advanced industrialization and population growth have led to increasing the environmental related issues. This paper reports the effect of deposition time on ZnO films deposited on to the glass substrate by using rf magnetron sputtering technique and their further use for gas sensing applications. Herein, deposition time is considered to be changed from 300 s, 800 s (S1, S2). The thickness of deposited films lies in the range of 130–180 nm. The synthesized films were characterized by various techniques in terms of structural, morphological, optical and gas sensing properties. The typical crystal size of ZnO films was found to be in the range of 15–27 nm. FESEM analysis revealed the growth of nanospheres was lies in the range of 80–120 nm. Fourier transform infrared spectroscopy confirmed the ZnO bonding located at a wavelength of 430 cm^?1. The average optical transmittance of the film was about 90–95% in the visible range. The optical band gap of ZnO films was decreased from 3.31 to 3.29 eV. The detailed characterization study showed 800 s is an optimum deposition time for good optoelectronic properties. For gas sensing application, highest sensitivity was obtained at operating temperature of 205 °C. Prepared films have a quick response and fast recovery time in the range of 128 s and 163 s respectively. These response and recovery time characteristics were explained by valence ion mechanism.     

Characterization of heavy metal trace elements in the fly ash from a thermal power plant

The disposal of fly ash in the thermal power plant is a challenging task. With the increase in the demand of the coal as fuel in thermal power plants, combustion products, such as coal ash, become a serious environmental problem due to their leaching characteristics. The objective of the present study was to investigate the leaching characteristics of the fly ash disposed in ash pond of thermal power plants. A series of leaching tests have been performed with different liquid-to-solid (L/S) ratio. The L/S ratio varies from 20:1 to 60:1. It is observed that the elements, such as Mn, Mg, Cr, Zn, Ni, Pb, Fe, and Cu, are most abundant elements, while Mo and Co are the least abundant elements. It is also observed that the leaching characteristics of the fly ash are affected by the pH of extraction solution and liquid-to-solid (L/S) ratio.     

Change profile analysis of open-source software systems to understand their evolutionary behavior

Source code management systems (such as git) record changes to code repositories of Open-Source Software (OSS) projects. The metadata about a change includes a change message to record the intention of the change. Classification of changes, based on change messages, into different change types has been explored in the past to understand the evolution of software systems from the perspective of change size and change density only. However, software evolution analysis based on change classification with a focus on change evolution patterns is still an open research problem. This study examines change messages of 106 OSS projects, as recorded in the git repository, to explore their evolutionary patterns with respect to the types of changes performed over time. An automated keyword-based classifier technique is applied to the change messages to categorize the changes into various types (corrective, adaptive, perfective, preventive, and enhancement). Cluster analysis helps to uncover distinct change patterns that each change type follows. We identify three categories of 106 projects for each change type: high activity, moderate activity, and low activity. Evolutionary behavior is different for projects of different categories. The projects with high and moderate activity receive maximum changes during 76–81 months of the project lifetime. The project attributes such as the number of committers, number of files changed, and total number of commits seem to contribute the most to the change activity of the projects. The statistical findings show that the change activity of a project is related to the number of contributors, amount of work done, and total commits of the projects irrespective of the change type. Further, we explored languages and domains of projects to correlate change types with domains and languages of the projects. The statistical analysis indicates that there is no significant and strong relation of change types with domains and languages of the 106 projects.     

FEMT: a computational approach for fog elimination using multiple thresholds

Multimedia Tools and Applications - Refining visibility through haze removal from image becomes an inevitable chore and essential to recognize and track vehicles, traffic signal, and signs clearly...     

Scientometric analysis of literature on distributed vehicular networks : VOSViewer visualization techniques

Artificial Intelligence Review - The idea of vehicular communication has evolved dramatically over the past two decades apparently with technological advancements that accord low power and memory...