scholarly journals Rapid and accurate detection of SARS-CoV-2 mutations using a Cas12a-based sensing platform

2021 ◽  
pp. 113857
Author(s):  
Changsheng He ◽  
Cailing Lin ◽  
Guosheng Mo ◽  
Binbin Xi ◽  
An′an Li ◽  
...  
Keyword(s):  
Accurate Detection ◽  
Sensing Platform

Accurate Detection and Quantization of Leaf- Diseases through Soft Computing

2018 ◽  
Vol 1 (1) ◽  
pp. 236-247
Author(s):  
Divya Srivastava ◽  
Rajitha B. ◽  
Suneeta Agarwal
Keyword(s):  
Machine Learning ◽  
Image Processing ◽  
Agricultural Production ◽  
Bacterial Blight ◽  
Early Stage ◽  
Second Phase ◽  
Computationally Efficient ◽  
Stage Of Disease ◽  
Accurate Detection ◽  
Two Phases

Diseases in leaves can cause the significant reduction in both quality and quantity of agricultural production. If early and accurate detection of disease/diseases in leaves can be automated, then the proper remedy can be taken timely. A simple and computationally efficient approach is presented in this paper for disease/diseases detection on leaves. Only detecting the disease is not beneficial without knowing the stage of disease thus the paper also determine the stage of disease/diseases by quantizing the affected of the leaves by using digital image processing and machine learning. Though there exists a variety of diseases on leaves, but the bacterial and fungal spots (Early Scorch, Late Scorch, and Leaf Spot) are the most prominent diseases found on leaves. Keeping this in mind the paper deals with the detection of Bacterial Blight and Fungal Spot both at an early stage (Early Scorch) and late stage (Late Scorch) on the variety of leaves. The proposed approach is divided into two phases, in the first phase, it identifies one or more disease/diseases existing on leaves. In the second phase, amount of area affected by the disease/diseases is calculated. The experimental results obtained showed 97% accuracy using the proposed approach.

Precise Localization of 28 nm via Chain Resistive Defect Using EBAC and Nanoprobing

2012 ◽  
Author(s):  
P. Larré ◽  
H. Tupin ◽  
C. Charles ◽  
R.H. Newton ◽  
A. Reverdy
Keyword(s):  
Electron Beam ◽  
Failure Analysis ◽  
Test Structure ◽  
Precise Localization ◽  
Isolation Method ◽  
Accurate Detection ◽  
Conventional Methods ◽  
Technology Nodes ◽  
Tem Lamella

Abstract As technology nodes continue to shrink, resistive opens have become increasingly difficult to detect using conventional methods such as AVC and PVC. The failure isolation method, Electron Beam Absorbed Current (EBAC) Imaging has recently become the preferred method in failure analysis labs for fast and highly accurate detection of resistive opens and shorts on a number of structures. This paper presents a case study using a two nanoprobe EBAC technique on a 28nm node test structure. This technique pinpointed the fail and allowed direct TEM lamella.

Optical Sensors for Detection of Amino Acids

2018 ◽  
Vol 25 (19) ◽  
pp. 2272-2290 ◽  
Author(s):  
Aafrin M. Pettiwala ◽  
Prabhat K. Singh
Keyword(s):  
Amino Acids ◽  
Optical Sensors ◽  
Supramolecular Assemblies ◽  
Significant Activity ◽  
Physiological Level ◽  
Biological Scaffolds ◽  
Detection Systems ◽  
Sensing Platform ◽  
Neurological Conditions ◽  
Detailed Search

Background: Amino acids are crucially involved in a myriad of biological processes. Any aberrant changes in physiological level of amino acids often manifest in common metabolic disorders, serious neurological conditions and cardiovascular diseases. Thus, devising methods for detection of trace amounts of amino acids becomes highly elemental to their efficient clinical diagnosis. Recently, the domain of developing optical sensors for detection of amino acids has witnessed significant activity which is the focus of the current review article. Methods: We undertook a detailed search of the peer-reviewed literature that primarily deals with optical sensors for amino acids and focuses on the use of different type of materials as a sensing platform. Results: Ninety-five papers have been included in the review, majority of which deal with optical sensors. We attempt to systematically classify these contributions based on the applications of various chemical and biological scaffolds such as polymers, supramolecular assemblies, nanoparticles, DNA, heparin etc for the sensing of amino acids. This review identifies that supramolecular assemblies and nanomaterial continue to be commonly used platforms to devise sensors for amino acids followed by surfactant assemblies. Conclusion: The broad implications of amino acids in human health and diagnosis have stirred a lot of interest to develop optimized optical detection systems for amino acids in recent years, using different materials based on chemical and biological scaffolds. We have also attempted to highlight the merits and demerits of some of the noteworthy sensor systems to instigate further efforts for constructing amino acids sensor based on unconventional concepts.

Selective Sensing Platform Utilizing Graphitized Multi-Walled Carbon Nanotubes for Monitoring of Ondansetron and Paracetamol

2020 ◽  
Vol 16 ◽  
Author(s):  
Biljana Nigović ◽  
Iva Šimunić ◽  
Ana Mornar
Keyword(s):  
Carbon Nanotubes ◽  
Cation Exchange ◽  
Supporting Electrolyte ◽  
Polymer Concentration ◽  
Fixed Dose ◽  
Sensing Platform ◽  
Multi Walled Carbon Nanotubes ◽  
Electroanalytical Method ◽  
Walled Carbon Nanotubes

Background: Ondansetron and paracetamol are often co-administrated to prevent and treat nausea and vomiting caused by anaesthesia and to control of postoperative pain. In addition, ondansetron is used as the first-line antiemetic in paracetamol overdose. Therefore, selective and sensitive method for their simultaneous analysis is of a great importance. The electroanalytical methods are highly sensitive and offer many possibilities for new sensor platform design. However, at present, no electroanalytical method for simultaneous determination of these drugs has been proposed. Objective: The aim of this study was to develop a novel nanosensor for selective monitoring of ondansetron and paracetamol in pharmaceutical and biological samples without expensive and time-consuming pretreatments. Methods: The graphitized multi-walled carbon nanotubes embedded in a cation exchange polymer matrix was selected, among various surface functionalizations evaluated, to design novel sensor. Based on its excellent sensing performance, the first electroanalytical method was developed for rapid concurrent determination of investigated drugs. Results: The scanning electron microscopy study showed interlinked nanoporous network structure and highly enlarged active surface. The developed sensor facilitated electron transfer in the oxidation of both drugs and tremendously enhanced the adsorption capacity for ondasetron, thus exhibiting significant increase of drug responses and sensitivity. To obtain much sensitive response of investigated drugs the effect of pH values of supporting electrolyte, dispersed nanomaterial amount, the cation exchange polymer concentration, drop-casting volume of nanocomposite suspension, accumulation potential and deposition time on the peak current was evaluated. The developed electroanalytical method was validated and practical utility of the proposed nanosensor was tested. Conclusion: The developed sensor is promising sensing platform with a fast response time for analysis of ondansetron and paracetamol at very different concentration levels found in their fixed-dose combination and human serum sample after recommended daily doses showing its potential usage in pharmaceutical quality control and clinical research.

Colorimetric Dye-Loaded Nanofiber Yarn: Eye-Readable and Weavable Gas Sensing Platform

ACS Nano ◽  
2020 ◽  
Vol 14 (12) ◽  
pp. 16907-16918
Author(s):  
Dong-Ha Kim ◽  
Jun-Hwe Cha ◽  
Jee Young Lim ◽  
Jaehyeong Bae ◽  
Woosung Lee ◽  
...  
Keyword(s):  
Gas Sensing ◽  
Nanofiber Yarn ◽  
Sensing Platform

Rapid colorimetric sensing platform for the detection of Listeria monocytogenes foodborne pathogen

2016 ◽  
Vol 86 ◽  
pp. 1061-1066 ◽  
Author(s):  
Sahar Alhogail ◽  
Ghadeer A.R.Y. Suaifan ◽  
Mohammed Zourob
Keyword(s):  
Listeria Monocytogenes ◽  
Foodborne Pathogen ◽  
Colorimetric Sensing ◽  
Sensing Platform

scholarly journals A Novel Stacking Approach for Accurate Detection of Fake News

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 22626-22639
Author(s):  
Tao Jiang ◽  
Jian Ping Li ◽  
Amin Ul Haq ◽  
Abdus Saboor ◽  
Amjad Ali
Keyword(s):  
Fake News ◽  
Accurate Detection
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