Nanoparticles are increasingly being recognized for their potential utility in biological applications including nanomedicine.Here,we have synthesized zinc oxide(ZnO)nanorods using zinc acetate and hexamethylenetetram...Nanoparticles are increasingly being recognized for their potential utility in biological applications including nanomedicine.Here,we have synthesized zinc oxide(ZnO)nanorods using zinc acetate and hexamethylenetetramine as precursors followed by characterizing using X-ray diffraction,fourier transform infrared spectroscopy,scanning electron microscopy and transmission electron microscopy.The growth of synthesized zinc oxide nanorods was found to be very close to its hexagonal nature,which is confirmed by X-ray diffraction.The nanorod was grown perpendicular to the long-axis and grew along the[001]direction,which is the nature of ZnO growth.The morphology of synthesized ZnO nanorods from the individual crystalline nucleus was confirmed by scanning and transmission electron microscopy.The length of the nanorod was estimated to be around 21 nm in diameter and 50 nm in length.Our toxicology studies showed that synthesized ZnO nanorods exposure on hela cells has no significant induction of oxidative stress or cell death even in higher concentration(10μg/ml).The results suggest that ZnO nanorods might be a safer nanomaterial for biological applications.展开更多
The present progress of visual-based detection of the diseased area of a malady plays an essential part in the medicalfield.In that case,the image proces-sing is performed to improve the image data,wherein it inhibits ...The present progress of visual-based detection of the diseased area of a malady plays an essential part in the medicalfield.In that case,the image proces-sing is performed to improve the image data,wherein it inhibits unintended dis-tortion of image features or it enhances further processing in various applications andfields.This helps to show better results especially for diagnosing diseases.Of late the early prediction of cancer is necessary to prevent disease-causing pro-blems.This work is proposed to identify lung cancer using lung computed tomo-graphy(CT)scan images.It helps to identify cancer cells’affected areas.In the present work,the original input image from Lung Image Database Consortium(LIDC)typically suffers from noise problems.To overcome this,the Gaborfilter used for image processing is highly enhanced.In the next stage,the Spherical Iterative Refinement Clustering(SIRC)algorithm identifies cancer-suspected areas on the CT scan image.This approach can help radiologists and medical experts recognize cancer diseases and syndromes so that serious progress can be avoided in the early stages.These new methods help to remove unwanted por-tions of the CT image and better utilization the image.The subspace extraction of features approach is beneficial for evaluating lung cancer.This paper introduces a novel approach called Contiguous Cross Propagation Neural Network that tends to locate regions afflicted by lung cancer using CT scan pictures(CCPNN).By using the feature values from the fourth step of the procedure,the proposed CCPNN tends to categorize the lesion in the lung nodular site.The efficiency of the suggested CCPNN approach is evaluated using classification metrics such as recall(%),precision(%),F-measure(percent),and accuracy(%).Finally,the incorrect classification ratios are determined to compare the trained networks’effectiveness,through these parameters of CCPNN,it obtains the outstanding per-formance of 98.06%and it has provided the lowest false ratio of 1.8%.展开更多
Our aim is to study the Hopf bifurcation and synchronisation of a fractional-order butterfly-fishchaotic system. First, we derived the existence of a chaotic attractor in the fractional-order systemand also synchronis...Our aim is to study the Hopf bifurcation and synchronisation of a fractional-order butterfly-fishchaotic system. First, we derived the existence of a chaotic attractor in the fractional-order systemand also synchronisation problem between two identical fractional-order chaotic systems isstudied. Also, control design for the synchronisation with a suitable linear controller is tested inthe response system. Finally, numerical simulation results are provided to confirm the theoreticalanalysis.展开更多
基金supported by NASA funding NNX08BA47ANCC-1-02038+1 种基金NIH-1P20MD001822-1NSF(RISE)HRD-0734846
文摘Nanoparticles are increasingly being recognized for their potential utility in biological applications including nanomedicine.Here,we have synthesized zinc oxide(ZnO)nanorods using zinc acetate and hexamethylenetetramine as precursors followed by characterizing using X-ray diffraction,fourier transform infrared spectroscopy,scanning electron microscopy and transmission electron microscopy.The growth of synthesized zinc oxide nanorods was found to be very close to its hexagonal nature,which is confirmed by X-ray diffraction.The nanorod was grown perpendicular to the long-axis and grew along the[001]direction,which is the nature of ZnO growth.The morphology of synthesized ZnO nanorods from the individual crystalline nucleus was confirmed by scanning and transmission electron microscopy.The length of the nanorod was estimated to be around 21 nm in diameter and 50 nm in length.Our toxicology studies showed that synthesized ZnO nanorods exposure on hela cells has no significant induction of oxidative stress or cell death even in higher concentration(10μg/ml).The results suggest that ZnO nanorods might be a safer nanomaterial for biological applications.
文摘The present progress of visual-based detection of the diseased area of a malady plays an essential part in the medicalfield.In that case,the image proces-sing is performed to improve the image data,wherein it inhibits unintended dis-tortion of image features or it enhances further processing in various applications andfields.This helps to show better results especially for diagnosing diseases.Of late the early prediction of cancer is necessary to prevent disease-causing pro-blems.This work is proposed to identify lung cancer using lung computed tomo-graphy(CT)scan images.It helps to identify cancer cells’affected areas.In the present work,the original input image from Lung Image Database Consortium(LIDC)typically suffers from noise problems.To overcome this,the Gaborfilter used for image processing is highly enhanced.In the next stage,the Spherical Iterative Refinement Clustering(SIRC)algorithm identifies cancer-suspected areas on the CT scan image.This approach can help radiologists and medical experts recognize cancer diseases and syndromes so that serious progress can be avoided in the early stages.These new methods help to remove unwanted por-tions of the CT image and better utilization the image.The subspace extraction of features approach is beneficial for evaluating lung cancer.This paper introduces a novel approach called Contiguous Cross Propagation Neural Network that tends to locate regions afflicted by lung cancer using CT scan pictures(CCPNN).By using the feature values from the fourth step of the procedure,the proposed CCPNN tends to categorize the lesion in the lung nodular site.The efficiency of the suggested CCPNN approach is evaluated using classification metrics such as recall(%),precision(%),F-measure(percent),and accuracy(%).Finally,the incorrect classification ratios are determined to compare the trained networks’effectiveness,through these parameters of CCPNN,it obtains the outstanding per-formance of 98.06%and it has provided the lowest false ratio of 1.8%.
文摘Our aim is to study the Hopf bifurcation and synchronisation of a fractional-order butterfly-fishchaotic system. First, we derived the existence of a chaotic attractor in the fractional-order systemand also synchronisation problem between two identical fractional-order chaotic systems isstudied. Also, control design for the synchronisation with a suitable linear controller is tested inthe response system. Finally, numerical simulation results are provided to confirm the theoreticalanalysis.
