65 resultados para cyclotron resonance


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This paper describes a multilayer localized surface plasmon resonance (LSPR) graphene biosensor that includes a layer of graphene sheet on top of the gold layer, and the use of different coupled configuration of a laser beam. The study also investigates the enhancement of the sensitivity and detection accuracy of the biosensor through monitoring biomolecular interactions of biotin-streptavidin with the graphene layer on the gold thin film. Additionally, the role of thin films of gold, silver, copper and aluminum in the performance of the biosensor is separately investigated for monitoring the binding of streptavidin to the biotin groups. The performance of the LSPR graphene biosensor is theoretically and numerically assessed in terms of sensitivity, adsorption efficiency, and detection accuracy under varying conditions, including the thickness of biomolecule layer, number of graphene layers and operating wavelength. Enhanced sensitivity and improved adsorption efficiency are obtained for the LSPR graphene biosensor in comparison with its conventional counterpart; however, detection accuracy under the same resonance condition is reduced by 5.2% with a single graphene sheet. This reduction in detection accuracy (signal to noise ratio) can be compensated for by introducing an additional layer of silica doped B2O3 (sdB2O3) placed under the graphene layer. The role of prism configuration, prism angle and the interface medium (air and water) is also analyzed and it is found that the LSPR graphene biosensor has better sensitivity with triangular prism, higher prism angle, lower operating wavelength and larger number of graphene layers. The approach involves a plot of a reflectivity curve as a function of the incidence angle. The outcomes of this investigation highlight the ideal functioning condition corresponding to the best design parameters.

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Localized surface plasmon resonance (LSPR) is a promising detection method for label-free sensing of biomolecules. In this paper, a multilayer design for a LSPR biosensor is presented. In the proposed design, a periodic array of dielectric grating is incorporated on top of a graphene layer in the biosensor. The aim is to improve sensitivity of the LSPR biosensor through monitoring biomolecular interactions of biotin-streptavidin. Sensitivity improvement is obtained for the proposed LSPR biosensor compared with conventional SPR counterparts. In addition, to optimize the design, we have investigated grating geometry including volume factor and grating depth. The outcome of this investigation identifies ideal functioning conditions corresponding to the best design parameters.

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Magnetic resonance imaging (MRI) of the brain is used to detect depression disorder. However, a large number of MRI scans needs to be analyzed for such detection. Manual segmentation of the biomarkers in MRI scans by clinical experts can become time consuming and sometimes erroneous. This paper presents a study on computer-aided detection of depression from MRI scans. These systems have not yet been identified, categorized and compared in the literature. The paper covers fully automated to semi-automated detection systems. It also presents performance comparison for the considered systems.

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Localized surface plasmon resonance (LSPR) biosensors are employed to detect target biomolecules which have particular resonance wavelengths. Accordingly, tunability of the LSPR wavelength is essential in designing LSPR devices. LSPR devices employing silver nano-particles present better efficiencies than those using other noble metals such as gold; however, silver nano-particles are easily oxidized when they come in contact with liquids, which is inevitable in biosensing applications. To attain both durability and tunabilty in a LSPR biosensor, this paper proposes alumina (AL2O3) capped silver nano-disks. It is shown that through controlling the thickness of the cap, the LSPR resonance frequency can be finely tuned over a wide range; and moreover, the cap protects silver nano-particles from oxidation and high temperature.

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This paper proposes a novel sinusoidal shape nano-particle employed in localized surface plasmon resonance (LSPR) devices. Numerical modeling demonstrates advantages offered by the proposed nano-sinusoid on LSPR enhancement against other nano-particles including noble nano-triangles and nano-diamonds. Although nano-triangles exhibit high concentration of the electric field near their tips, when illuminated with a light polarized along the tip axis, they present only one hot spot at the vertex along the polarization direction. To create a structure with two hot spots, which is desired in bio-sensing applications, two nano-triangles can be put back-to-back. Therefore, a nano-diamond particle is obtained which exhibits two hot spots and presents higher enhancements than nano-triangles for the same resonant wavelength. The main drawback of the nano-diamonds is the fluctuation in their physical size-plasmon spectrum relationships, due to a high level of singularity as the result for their four sharp tip points. The proposed nano-sinusoid overcomes this disadvantage while maintaining the benefits of having two hot spots and high enhancements.

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Introduction : Depression is a major issue worldwide and is seen as a significant health problem. Stigma and patient denial, clinical experience, time limitations, and reliability of psychometrics are barriers to the clinical diagnoses of depression. Thus, the establishment of an automated system that could detect such abnormalities would assist medical experts in their decision-making process. This paper reviews existing methods for the automated detection of depression from brain structural magnetic resonance images (sMRI).Methods : Relevant sources were identified from various databases and online sites using a combination of keywords and terms including depression, major depressive disorder, detection, classification, and MRI databases. Reference lists of chosen articles were further reviewed for associated publications.Results : The paper introduces a generic structure for representing and describing the methods developed for the detection of depression from sMRI of the brain. It consists of a number of components including acquisition and preprocessing, feature extraction, feature selection, and classification.Conclusion : Automated sMRI-based detection methods have the potential to provide an objective measure of depression, hence improving the confidence level in the diagnosis and prognosis of depression.

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A new nano-sinusoid shape has recently been proposed, which offers the advantage of more resonance wavelength tunability than that offered by other sharp-tip nano-particles. In this paper, a one-dimensional (1D) chain of the nano-sinusoids is modelled, and results are compared with those describing chains of nano-triangles and nano-diamonds. It is demonstrated that the chain of nano-sinusoids provides more enhancement at hot spots than other examined nano-particle shapes. This enhancement is analytically quantified using the coupling constant values used in the electrostatic eigenmode method for analytically solving Maxwell's equations for the nano-plasmonic devices. In addition, investigating LSPR spectrum of two-dimensional (2D) arrays of NPs demonstrates existence of enhanced surface electric fields on hot spots of the outer rows of the array.

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Designed a multilayer SPR biosensor to improve the detection sensitivity and accuracy simultaneously. Developed a design procedure to identify optimum design parameters for SPR biosensing. Devised a new detection measurement technique based on S-parameters for SPR biosensing.

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This paper presents a subwavelength grating based multilayer surface plasmon resonance biosensor (SPRB) which includes a periodic array of subwavelength grating on top of a layer of graphene sheet in the biosensor. The proposed biosensor is named grating-graphene SPRB (GG-SPRB). The aim of the proposed multilayer structure is to improve the sensitivity of the SPRB through monitoring of the biomolecular interactions of DNA hybridization. Significant sensitivity improvement is obtained for the GG-SPRB compared with the conventional SPRB. The result of the numerical investigation of the GG-SPRB is presented and compared with a theoretically developed multilayer matrix formalism, and a good agreement has been observed. In addition, an optimization of the grating dimensions including volume factor, grating depth, grating angle, grating period, and grating geometry (e.g., rectangular, sinusoidal and triangular) is presented. The outcome of the investigation presented in this paper identifies desired functioning conditions corresponding to the best design parameters for the GG-SPRB.