scholarly journals A Short Review on Various Engineering Applications of Electrospun One-Dimensional Metal Oxides

Materials ◽  
2021 ◽  
Vol 14 (18) ◽  
pp. 5139
Author(s):  
Weronika Smok ◽  
Tomasz Tański
Keyword(s):  
Research Work ◽  
Short Review ◽  
Oxide Semiconductors ◽  
Global Trends ◽  
One Dimensional ◽  
University Of Technology ◽  
Engineering And Technology ◽  
Subsequent Calcination ◽  
Low Dimensional ◽  
High Level

The growing scientific interest in one-dimensional (1D) nanostructures based on metal-oxide semiconductors (MOS) resulted in the analysis of their structure, properties and fabrication methods being the subject of many research projects and publications all over the world, including in Poland. The application of the method of electrospinning with subsequent calcination for the production of these materials is currently very popular, which results from its simplicity and the possibility to control the properties of the obtained materials. The growing trend of industrial application of electrospun 1D MOS and the progress in modern technologies of nanomaterials properties investigations indicate the necessity to maintain the high level of research and development activities related to the structure and properties analysis of low-dimensional nanomaterials. Therefore, this review perfectly fits both the global trends and is a summary of many years of research work in the field of electrospinning carried out in many research units, especially in the Department of Engineering Materials and Biomaterials of the Faculty of Mechanical Engineering and Technology of Silesian University of Technology, as well as an announcement of further activities in this field.

scholarly journals Event Prediction in Complex Social Graphs using One-Dimensional Convolutional Neural Network

2019 ◽  
Author(s):  
Bonaventure Molokwu
Keyword(s):  
Social Networks ◽  
Complex Structure ◽  
Research Work ◽  
Social Graph ◽  
One Dimensional ◽  
Social Actors ◽  
Event Prediction ◽  
Social Graphs ◽  
Unique Approach ◽  
Low Dimensional

Social network graphs possess apparent and latent knowledge about their respective actors and links which may be exploited, using effective and efficient techniques, for predicting events within the social graphs. Understanding the intrinsic relationship patterns among spatial social actors and their respective properties are crucial factors to be taken into consideration in event prediction within social networks. My research work proposes a unique approach for predicting events in social networks by learning the context of each actor/vertex using neighboring actors in a given social graph with the goal of generating vector-space embeddings for each vertex. Our methodology introduces a pre-convolution layer which is essentially a set of feature-extraction operations aimed at reducing the graph's dimensionality to aid knowledge extraction from its complex structure. Consequently, the low-dimensional node embeddings are introduced as input features to a one-dimensional ConvNet model for event prediction about the given social graph. Training and evaluation of this proposed approach have been done on datasets (compiled: November, 2017) extracted from real world social networks with respect to 3 European countries. Each dataset comprises an average of 280,000 links and 48,000 actors.

Structure of the exudate gum from Meryta sinclairii

2020 ◽  
Author(s):  
Ian Sims ◽  
Richard Furneaux
Keyword(s):  
Average Molecular Weight ◽  
Gum Arabic ◽  
Arabinogalactan Protein ◽  
Weight Average Molecular Weight ◽  
1H And 13C Nmr ◽  
One Dimensional ◽  
Linkage Analyses ◽  
Yariv Reagent ◽  
Native Tree ◽  
High Level

A gum that exudes from the wounded trunk of the New Zealand native tree Meryta sinclairii has been isolated. The gum was completely precipitated by the β-glucosyl Yariv reagent and was thus determined to be an arabinogalactan-protein (AGP). It contained >95% w/w carbohydrate and only 2% w/w protein with a high level of hydroxyproline. SEC-MALLS showed that the gum had a weight-average molecular weight of 4.45×106Da compared with 6.02×105Da for gum arabic. Constituent sugar and linkage analyses were consistent with polymers comprised of a highly branched backbone of 1,3-linked galactopyranosyl (Galp) residues, with side-chains made up of arabinofuranose- (Araf) containing oligosaccharides, terminated variously by rhamnopyranosyl (Rhap), arabinopyranosyl (Arap), Galp and glucuronopyranosyl (GlcpA) residues. Analysis by one-dimensional and two-dimensional 1H and 13C NMR experiments confirmed the linkage analyses. The structure of the gum is discussed in comparison with the structure of gum arabic and other AGPs. © 2003 Elsevier Science Ltd. All rights reserved.

Development and Achievements of SSM Processes for High Performance Components

2016 ◽  
Vol 256 ◽  
pp. 319-327 ◽  
Author(s):  
Mario Rosso ◽  
Ildiko Peter ◽  
Ivano Gattelli
Keyword(s):  
Industrial Development ◽  
High Performance ◽  
Rear Axle ◽  
Research Work ◽  
Industrial Applications ◽  
Alternative Methods ◽  
Front Suspension ◽  
Large Numbers ◽  
Automotive Parts ◽  
High Level

During the last decades under the enthusiastic and competent guidance of Mr Chiarmetta SSM processes attained in Italy at Stampal Spa (Torino) an unquestionable high level of industrial development with the production of large numbers of high performance automotive parts, like variety of suspension support, engine suspension mounts, steering knuckle, front suspension wheel, arm and rear axle. Among the most highlighted findings SSM processes demonstrated their capability to reduce the existing gap between casting and forging, moreover during such a processes there are the opportunity to better control the defect level.Purpose of this paper is to highlight the research work and the SSM industrial production attained and developed by Mr G.L. Chiarmetta, as well as to give an overview concerning some alternative methods for the production of enhanced performance light alloys components for critical industrial applications and to present an analysis of a new rheocasting process suitable for the manufacturing of high performance industrial components.

Oscillatory Behaviors of Delayed p53 Regulatory Network with microRNA 192 in DNA Damage Response

2021 ◽  
Vol 31 (02) ◽  
pp. 2150020
Author(s):  
Chunyan Gao ◽  
Fangqi Chen
Keyword(s):  
Dna Damage ◽  
Time Delay ◽  
Dna Damage Response ◽  
Positive Feedback ◽  
Regulatory Network ◽  
Feedback Loop ◽  
Research Work ◽  
Positive Feedback Loop ◽  
Damage Response ◽  
High Level

This study develops a general model of delayed p53 regulatory network in the DNA damage response by introducing microRNA 192-mediated positive feedback loop based on the existing research work. Through theoretical analysis and numerical simulation, we find that the delay as a bifurcation parameter can drive the p53-Mdm2 module to undergo a supercritical Hopf bifurcation, thereby producing oscillation behavior. Moreover, we demonstrate how the positive feedback loop formed by p53* and microRNA 192 (miR-192) with the feature of double-negative regulation produces oscillations. Further, a comparison is given to demonstrate that microRNA 192-mediated positive feedback loop affects the robustness of system oscillations. In addition, we show that ataxia telangiectasia mutated kinase (ATM), once activated by DNA damage, makes p53* undergo two Hopf bifurcations. These results reveal that both time delay and miR-192 play tumor suppressing roles by promoting p53 oscillation or high level expression, which will provide a perspective for promoting the development of anti-cancer drugs by targeting miR-192 and time delay.

scholarly journals A Novel Density-based Technique for Outlier Detection of High Dimensional Data Utilizing Full Feature Space

2021 ◽  
Vol 50 (1) ◽  
pp. 138-152
Author(s):  
Mujeeb Ur Rehman ◽  
Dost Muhammad Khan
Keyword(s):  
Data Mining ◽  
Outlier Detection ◽  
High Dimensional Data ◽  
Research Work ◽  
Feature Space ◽  
High Dimensional ◽  
Data Set ◽  
Data Points ◽  
Low Dimensional ◽  
Intrinsic Feature

Recently, anomaly detection has acquired a realistic response from data mining scientists as a graph of its reputation has increased smoothly in various practical domains like product marketing, fraud detection, medical diagnosis, fault detection and so many other fields. High dimensional data subjected to outlier detection poses exceptional challenges for data mining experts and it is because of natural problems of the curse of dimensionality and resemblance of distant and adjoining points. Traditional algorithms and techniques were experimented on full feature space regarding outlier detection. Customary methodologies concentrate largely on low dimensional data and hence show ineffectiveness while discovering anomalies in a data set comprised of a high number of dimensions. It becomes a very difficult and tiresome job to dig out anomalies present in high dimensional data set when all subsets of projections need to be explored. All data points in high dimensional data behave like similar observations because of its intrinsic feature i.e., the distance between observations approaches to zero as the number of dimensions extends towards infinity. This research work proposes a novel technique that explores deviation among all data points and embeds its findings inside well established density-based techniques. This is a state of art technique as it gives a new breadth of research towards resolving inherent problems of high dimensional data where outliers reside within clusters having different densities. A high dimensional dataset from UCI Machine Learning Repository is chosen to test the proposed technique and then its results are compared with that of density-based techniques to evaluate its efficiency.

scholarly journals Solution of Parabolic Partial Differential Equations by Non-Polynomial Cubic Spline Technique

2021 ◽  
Vol 5 (3) ◽  
Author(s):  
Bilal Ahmad ◽  
Anjum Perviz ◽  
Muhammad Ozair Ahmad ◽  
Fazal Dayan
Keyword(s):  
Research Work ◽  
Numerical Test ◽  
Parabolic Partial Differential Equation ◽  
Parabolic Partial Differential Equations ◽  
The Novel ◽  
Parabolic Pdes ◽  
Partial Differential ◽  
Novel Technique ◽  
Engineering And Technology ◽  
Scientific Engineering

Parabolic partial differential equation having a great impact on our scientific, engineering and technology. Enormous research have been conducted for the solution of parabolic PDEs. . In this research work, we introduced a novel technique for the numerical solution of fourth order PDEs.  The novel technique is based upon the polynomial cubic cutting method (PCSM) was used with Adomian breakdown technique (ADM).The constraint for the alternative variables was decomposed by Edomian decomposition for the successive approximation. A numerical test problem of parabolic PDEs solved by purposed technique

scholarly journals A Short Review on One Dimensional Wigner Crystallization

2020 ◽  
Author(s):  
Niccolo Traverso Ziani ◽  
Fabio Cavaliere ◽  
Karina Guerrero Becerra ◽  
Maura Sassetti
Keyword(s):  
Carbon Nanotubes ◽  
Structural Transition ◽  
Luttinger Liquid ◽  
Electronic System ◽  
Short Review ◽  
One Dimensional ◽  
Basic Properties ◽  
Wigner Crystallization ◽  
Liquid Theory ◽  
The One

The simplest possible structural transition that an electronic system can undergo is Wigner crystallization. The aim of this short review is to discuss the main aspects of three recent experimets on the one dimensional Wigner molecule, starting from scratch. To achieve this task, the Luttinger liquid theory of weakly and strongly interacting fermions will be shortly addressed, together with the basic properties of carbon nanotubes that are require. Then, the most relevant properties of Wigner molecules will be addressed, and finally the experiments will be described.

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