Deposition of alumina films by inverted cylindrical magnetron sputtering assisted by optical emission spectroscopy

Alumina coatings have been deposited on glass substrates by reactive ac (41 kHz) magnetron sputtering of two hollow aluminum targets in argon-oxygen plasma at 5 kW sputtering power in the poisoned mode and in the unstable region of hysteresis loop of reactive sputtering. The poisoned mode produces nanocrystalline films of and alumina at a low deposition rate of 0.06 nm·s-1. Amorphous alumina films have been grown at a higher deposition rate of 0.2 nm·s-1 with the aid of optical emission spectroscopy in which the feedback signal of Al emission spectral line at 396 nm monitored Al concentration in the plasma discharge and accomplished the controlled oxidation of targets during reactive sputtering. Dynamic secondary ion mass spectroscopy studies confirm that alumina films grown in the unstable region of the hysteresis loop of reactive sputtering are highly stoichiometric and of uniform composition with film thickness. Our study demonstrates the successful coupling of optical emission spectroscopy with hollow cylindrical magnetrons for deposition of alumina films

Machine Learning enabled models for YouTube Ranking Mechanism and Views Prediction

With the continuous increase of internet usage in todays time, everyone is influenced by this source of the power of technology. Due to this, the rise of applications and games Is unstoppable. A major percentage of our population uses these applications for multiple purposes. These range from education, communication, news, entertainment, and many more. Out of this, the application that is making sure that the world stays in touch with each other and with current affairs is social media. Social media applications have seen a boom in the last 10 years with the introduction of smartphones and the internet being available at affordable prices. Applications like Twitch and Youtube are some of the best platforms for producing content and expressing their talent as well. It is the goal of every content creator to post the best and most reliable content so that they can gain recognition. It is important to know the methods of achieving popularity easily, which is what this paper proposes to bring to the spotlight. There should be certain parameters based on which the reach of content could be multiplied by a good factor. The proposed research work aims to identify and estimate the reach, popularity, and views of a YouTube video by using certain features using machine learning and AI techniques. A ranking system would also be used keeping the trending videos in consideration. This would eventually help the content creator know how authentic their content is and healthy competition to make better content before uploading the video on the platform will be ensured.Comment: The Paper has been ACCEPTED at the "2nd International Conference on Computing and Communication Networks(ICCCN-2022)". This paper will be published by AIP publishing and DOI will be issued later o

Quantum-Inspired Evolutionary Algorithms for Neural Network Weight Distribution: A Classification Model for Parkinson\u27s Disease

Parkinson’s Disease is a degenerative neurological disorder with unknown origins, making it impossible to be cured or even diagnosed. The following article presents a Three-Layered Perceptron Neural Network model that is trained using a variety of evolutionary as well as quantum-inspired evolutionary algorithms for the classification of Parkinson\u27s Disease. Optimization algorithms such as Particle Swarm Optimization, Artificial Bee Colony Algorithm and Bat Algorithm are studied along with their quantum-inspired counter-parts in order to identify the best suited algorithm for Neural Network Weight Distribution. The results show that the quantum-inspired evolutionary algorithms perform better under the given circumstances, with qABC offering the highest accuracy of about 92.3%. The presented model can be used not only for disease diagnosis but is also likely to find its applications in various other fields as well

Design of Integrated Artificial Intelligence Techniques for Video Surveillance on IoT Enabled Wireless Multimedia Sensor Networks

The recent advancements in the Internet of Things (IoT) and Wireless Multimedia Sensor Networks (WMSN) made high-speed multimedia streaming, data processing, and essential analytics processes with minimal delay. Multimedia sensors used in WMSN-based surveillance applications are beneficial helpful in attaining accurate and elaborate details. However, it has become essential to design an effective and lightweight solution for data traffic management in WMSN owing to the massive quantities of data, generated by multimedia sensors. The development of Artificial Intelligence (AI) and Machine Learning (ML) techniques can be leveraged to investigate, collect, store, and process multimedia streaming data for decision-making in real-time scenarios. In this aspect, the current study develops an Integrated AI technique for Video Surveillance in IoT-enabled WMSN, called IAIVS-WMSN. The proposed IAIVS-WMSN technique aims to design a practical scheme for object detection and data transmission in WMSN. The proposed IAIVS-WMSN approach encompasses three stages: object detection, image compression, and clustering. The Mask Regional Convolutional Neural Network (Mask RCNN) technique is primarily utilized for object detection in the target region. Besides, Neighbourhood Correlation Sequence-based Image Compression (NCSIC) technique is applied to reduce data transmission. Finally, Artificial Flora Algorithm (AFA)-based clustering technique is designed for the election of Cluster Heads (CHs) and construction clusters. The design of object detection with compression and clustering techniques for WMSN shows the novelty of the work. These three processes’ designs enable one to accomplish effective data transmission in IoT-enabled WMSN. The researchers conducted multiple simulations to highlight the supreme performance of the IAIVS-WMSN approach. The simulation outcomes inferred the enhanced performance of the IAIVS-WMSN algorithm to the existing approaches

Casamino acids facilitate the secretion of recombinant dengue virus serotype-3 envelope domain III in Pichia pastoris

Background: Dengue is a viral disease spread to humans by mosquitoes. Notably, there are four serotypes of Dengue Viruses (DENV) that places ∼40% of the global population at risk of infection. However, lack of a suitable drug or a preventive vaccine exacerbates the matter further. Envelope Domain-III (EDIII) antigen of Dengue Virus (DENV) has garnered much attention as a promising vaccine candidate for dengue, in addition to its use as a diagnostic intermediate. Hence developing a method for efficient production of high quality recombinant EDIII is important for research and industrial purpose. Results: In this work, a Pichia pastoris system was optimized for the secretory over-expression of DENV serotype-3 EDIII under the control of methanol inducible AOX1 promoter. Temperature alone had a significant impact upon the amount of secretory EDIII, with 2.5-fold increase upon reducing the induction temperature from 30 to 20 °C. However surprisingly, supplementation of culture media with Casamino Acids (CA), further augmented secretory EDIII titer, with a concomitant drop of intracellular EDIII levels at both temperatures. Though, reduction in intracellular retention of EDIII was more prominent at 20°C than 30°C. This suggests that CA supplementation facilitates overexpressing P. pastoris cells to secrete more EDIII by reducing the proportion retained intracellularly. Moreover, a bell-shaped correlation was observed between CA concentration and secretory EDIII titer. The maximum EDIII expression level of 187 mg/L was achieved under shake flask conditions with induction at 20°C in the presence of 1% CA. The overall increase in EDIII titer was ∼9-fold compared to un-optimized conditions. Notably, mouse immune-sera, generated using this purified EDIII antigen, efficiently neutralized the DENV. Conclusions: The strategy described herein could enable fulfilling the mounting demand for recombinant EDIII as well as lay direction to future studies on secretory expression of recombinant proteins in P. pastoris with CA as a media supplement