Carbon nanotube decorated magnetic microspheres as an affinity matrix for biomolecules

Carbon nanotube (CNT) decorated magnetic microspheres were fabricated to develop a multimodal platform that utilizes non-covalent molecular interactions of CNTs to magnetically separate biomolecules. Hybrid CNT-microspheres prepared by a feasible method reported herein had a well-defined structure as characterized by Raman spectroscopy and scanning electron microscopy. Binding interactions of resulting magnetic CNT-microspheres with DNA oligonucleotides were studied to demonstrate that single stranded DNA (ssDNA) in a solution can be effectively recovered by magnetic CNT-microspheres through strong physical wrapping of DNA around CNTs' walls. The magnetic character of these CNT-microspheres combined with their capability to bind other molecules including DNA allows their use as an affinity matrix that can be utilized in affinity separation of biomolecules, and also as a platform to monitor non-covalent binding interactions of CNTs with other biomolecules. As a proof of concept, we report on the use of these CNT-microspheres in in vitro selection of ssDNA aptamers against carcinoembryonic antigen (CEA), a cancer biomarker, by Systematic Evolution of Ligands by Exponential Enrichment (SELEX). ssDNA aptamer candidates that have strong affinity towards CEA were successfully separated magnetically from a pool of ssDNA (1014 molecules). Our results demonstrate that CNT-microspheres can serve as strong tools for affinity separation methodologies and can be utilized for various affinity pairs in solution

Extraction of Projection Profile, Run-Histogram and Entropy Features Straight from Run-Length Compressed Text-Documents

Document Image Analysis, like any Digital Image Analysis requires identification and extraction of proper features, which are generally extracted from uncompressed images, though in reality images are made available in compressed form for the reasons such as transmission and storage efficiency. However, this implies that the compressed image should be decompressed, which indents additional computing resources. This limitation induces the motivation to research in extracting features directly from the compressed image. In this research, we propose to extract essential features such as projection profile, run-histogram and entropy for text document analysis directly from run-length compressed text-documents. The experimentation illustrates that features are extracted directly from the compressed image without going through the stage of decompression, because of which the computing time is reduced. The feature values so extracted are exactly identical to those extracted from uncompressed images.Comment: Published by IEEE in Proceedings of ACPR-2013. arXiv admin note: text overlap with arXiv:1403.778

A Study of a Wind Tunnel Measurement System for Unsteady Pressures Using Pneumatic Transmission Lines

The application of pneumatic transmission lines theory to a tube-scanning valve system for unsteady pressure measurements in the AFIT 5-foot wind tunnel is investigated. Transfer gains of various tube-scanning valve configurations were experimentally measured and the validity of a theoretical model verified for a frequency range of 20 Hz to 140 Hz. The selected system having a 0.0625-in. ID flexible tube of 84 in. length connected to a scanning valve was installed in the wind tunnel. Unsteady pressures introduced over an 18 percent airfoil at zero angle of attack were measured with this system. Data were collected for 0, 40, 60, 80, 100, and 150 mph for a frequency range of 30 Hz to 55 Hz. Comparison of theoretical and experimental results for one data point revealed the dependence of the verification of the system measurement accuracy on the wind tunnel speeds and flow perturbation characteristics. Theoretical predictions were verified for 30, 35, and 40 hz only

OCR for TIFF Compressed Document Images Directly in Compressed Domain Using Text segmentation and Hidden Markov Model

In today's technological era, document images play an important and integral part in our day to day life, and specifically with the surge of Covid-19, digitally scanned documents have become key source of communication, thus avoiding any sort of infection through physical contact. Storage and transmission of scanned document images is a very memory intensive task, hence compression techniques are being used to reduce the image size before archival and transmission. To extract information or to operate on the compressed images, we have two ways of doing it. The first way is to decompress the image and operate on it and subsequently compress it again for the efficiency of storage and transmission. The other way is to use the characteristics of the underlying compression algorithm to directly process the images in their compressed form without involving decompression and re-compression. In this paper, we propose a novel idea of developing an OCR for CCITT (The International Telegraph and Telephone Consultative Committee) compressed machine printed TIFF document images directly in the compressed domain. After segmenting text regions into lines and words, HMM is applied for recognition using three coding modes of CCITT- horizontal, vertical and the pass mode. Experimental results show that OCR on pass modes give a promising results.Comment: The paper has 14 figures and 1 tabl

E. coli-quantum dot bioconjugates as whole-cell fluorescent reporters for probing cellular damage

A quantum dot (QD) conjugated whole-cell E. coli biosensor (E. coli–QD bioconjugates) was developed as a new molecular tool for probing cellular damage. The E. coli–QD bioconjugates were viable and exhibited fluorescence emission at 585 nm. Scanning electron microscopy (SEM) analysis of E. coli–QD bioconjugates revealed that the QDs were immobilized on the cell-surfaces and the fluorescence emission from QDs present on cell-surfaces was visualized by confocal microscopic examination. The E. coli–QD bioconjugates were employed as whole-cell fluorescent reporters that were designed to function as fluorescence switches that turn-off when cellular damage occurs. In this study, multi-walled carbon nanotubes (CNTs) were utilized as a model nanomaterial to probe cellular damage. Fluorescence spectra were recorded after the exposure of E. coli–QD bioconjugates with CNTs. We observed a strong correlation between fluorescence emission spectra, SEM and confocal microscopic analysis demonstrating that CNTs induced a dose and exposure time-dependent cellular toxicity. This toxicity mainly occurred by the physical interaction and cellular trafficking mechanisms that led to the collapse of the cellular structure and thus loss of fluorescence. The responses of E. coli–QD bioconjugates against CNTs were also visualized by simply exposing the cells to UV light and therefore rapid toxicity analysis and screening can be made. Our study demonstrated an easy and simple method to determine an important mechanistic perspective for the biological toxicity of chemicals or nanomaterials (NMs)

Defect Tracking System

The main purpose of this project is it is an online Bug Hawker system and which is used for providing the solutions to correct the errors. This application is a totally web based tool and any user can access this tool by registering into the software. This software works once we login into the software and we can choose the error what kind of error it is etc. from the dropdown list. This software also has the extra facilities like email notifications, generating the reports, user access control etc

Biosensors for cardiac biomarkers detection: a review

The cardiovascular disease (CVD) is considered as a major threat to global health. Therefore, there is a growing demand for a range of portable, rapid and low cost biosensing devices for the detection of CVD. Biosensors can play an important role in the early diagnosis of CVD without having to rely on hospital visits where expensive and time-consuming laboratory tests are recommended. Over the last decade, many biosensors have been developed to detect a wide range of cardiac marker to reduce the costs for healthcare. One of the major challenges is to find a way of predicting the risk that an individual can suffer from CVD. There has been considerable interest in finding diagnostic and prognostic biomarkers that can be detected in blood and predict CVD risk. Of these, C-reactive protein (CRP) is the best known biomarker followed by cardiac troponin I or T (cTnI/T), myoglobin, lipoprotein-associated phospholipase A(2), interlukin-6 (IL-6), interlukin-1 (IL-1), low-density lipoprotein (LDL), myeloperoxidase (MPO) and tumor necrosis factor alpha (TNF-α) has been used to predict cardiovascular events. This review provides an overview of the available biosensor platforms for the detection of various CVD markers and considerations of future prospects for the technology are addressed