Plasmonic vortices for tunable manipulation of target particles, using arrays of elliptical holes in a gold layer.

Here, we numerically prove that light with linear polarization can be coupled to surface plasmon polaritons at an elliptical hole perforated in a gold layer to generate plasmonic vortex (PV). Benefiting from the smooth variation of the minor to major ellipse axes, a gradual variation in the phase profile of the generated PV is achieved. Regarding this, three types of independent arrays of elliptical holes are presented, which can produce uniform and high quality PVs with different topological charges at the center of the arrays. The first array can produce PV with topological charges of + 1 and - 1, depending on the polarization orientation of the incident light. In the second one, the topological charge of the PV can be switched between 0 and + 2, by switching the polarization direction of the incident light. In the third array, a robust PV with topological charge of + 1 is generated independent of possible tolerances in the polarization orientation. In order to use the generated PVs for plasmonic tweezing application, there are side fringes around the central vortex of the arrays that should be eliminated. To produce a single vortex, we propose metal-insulator-metal (MIM) structures, screening excessive fringes and allowing the central PVs to leak out. It is also demonstrated by simulation that target particles, such as gold and polystyrene spheres of subwavelength dimensions, can be efficiently manipulated by our MIM designs, suitable for different applications including local mixing, and applying switchable torque or force to target particles to explore their complete elastic characteristics.

Diagnostic Accuracy of Multiple MRI Parameters in Dealing with Incidental Thyroid Nodules.

Background: Different MRI parameters have been studied for evaluating thyroid nodules. Diffusion-weighted imaging (DWI) and T2 imaging sequences with considerable efficacy in evaluating soft tissue tumors merit further assessment for thyroid nodule investigation. Method: We evaluated incidental thyroid nodules (ITNs) reported on head and neck MRI studies. The T2 signal intensity (SI), T2 signal intensity ratio (SIR), Z value, and apparent diffusion coefficient (ADC) values of the thyroid nodule were obtained for every patient. The patients were referred to the radiology department for the thyroid nodule ultrasound study. Finally, 33 participants (37 thyroid nodules) who were scheduled for fine needle aspiration and cytology (FNAC) were enrolled. Regarding the FNAC results, the nodules were divided into malignant and benign groups. The two groups' MRI parameters were compared using a two samples independent t test, and the cutoff values were estimated by analyzing the receiver operating characteristics plot. Results: The T2 signal intensities, SIR, Z values, and ADC values were significantly higher in the benign group than malignant. The cutoff points of 230 (AUC = 0.759), 3.38 (AUC = 0.754), 37 (AUC = 0.759), and 1.73 (AUC = .690) were obtained for T2 values, SIR, Z values, and ADC values, respectively. Conclusion: T2, SIR, Z, and ADC values are reliable for discriminating benign from malignant ITNs. However, further studies with a larger sample size are needed to provide more accurate mean values, identify outliers, and reduce confounding factors and bias.

Correction: Ghanei et al. Effect of Nano-CuO on Engineering and Microstructure Properties of Fibre-Reinforced Mortars Incorporating Metakaolin: Experimental and Numerical Studies. Materials 2017, 10, 1215.

The authors regret that Figures 6 and 11b in [...].

Prediction of thyroid nodule malignancy using thyroid imaging reporting and data system (TIRADS) and nodule size.

OBJECTIVES: Thyroid imaging reporting and data system (TIRADS) is a combination of ultrasonographic features developed to help physicians in predicting the malignancy risk of thyroid nodules based on sonographic characteristics. Thyroid nodule size is another factor in determining whether a nodule is malignant. The aim of this study was detecting the predictive value of TIRADS and nodule size based on Bethesda classification in prognostication of malignancy. METHODS: This was a cross-sectional study of 239 patients with thyroid nodules. The patients underwent ultrasonography using TIRADS classification and FNA biopsy based on Bethesda categorization. The results were analyzed using SPSS with the cut off points and predictive values measured. RESULTS: TIRADS ≥4 could detect malignant nodules with a sensitivity of 91.67% and specificity of 52.8%. An inverse relationship was observed between nodule size and malignancy risk and cutoff point of 12 mm was found for detecting malignant nodules. CONCLUSIONS: Thyroid nodules with TIRADS 4 and 5 and diameter lower than 12 mm, are highly suspicious for malignancy and should be considered as indications for fine needle aspiration biopsy. ADVANCES IN KNOWLEDGE: The study suggests TIRADS and thyroid nodule size as sensitive predictors of malignancy.

Effect of Nano-CuO on Engineering and Microstructure Properties of Fibre-Reinforced Mortars Incorporating Metakaolin: Experimental and Numerical Studies.

In this study, the effects of nano-CuO (NC) on engineering properties of fibre-reinforced mortars incorporating metakaolin (MK) were investigated. The effects of polypropylene fibre (PP) were also examined. A total of twenty-six mixtures were prepared. The experimental results were compared with numerical results obtained by adaptive neuro-fuzzy inference system (ANFIS) and Primal Estimated sub-GrAdient Solver for SVM (Pegasos) algorithm. Scanning Electron Microscope (SEM) was also employed to investigate the microstructure of the cement matrix. The mechanical test results showed that both compressive and flexural strengths of cement mortars decreased with the increase of MK content, however the strength values increased significantly with increasing NC content in the mixture. The water absorption of samples decreased remarkably with increasing NC particles in the mixture. When PP fibres were added, the strengths of cement mortars were further enhanced accompanied with lower water absorption values. The addition of 2 wt % and 3 wt % nanoparticles in cement mortar led to a positive contribution to strength and resistance to water absorption. Mixture of PP-MK10NC3 indicated the best results for both compressive and flexural strengths at 28 and 90 days. SEM images illustrated that the morphology of cement matrix became more porous with increasing MK content, but the porosity reduced with the inclusion of NC. In addition, it is evident from the SEM images that more cement hydration products adhered onto the surface of fibres, which would improve the fibre-matrix interface. The numerical results obtained by ANFIS and Pegasos were close to the experimental results. The value of R² obtained for each data set (validate, test and train) was higher than 0.90 and the values of mean absolute percentage error (MAPE) and the relative root mean squared error (PRMSE) were near zero. The ANFIS and Pegasos models can be used to predict the mechanical properties and water absorptions of fibre-reinforced mortars with MK and NC.

A discrete curvature-based deformable surface model with application to segmentation of volumetric images.

In this paper, we present a new curvature-based three-dimensional (3-D) deformable surface model. The model deforms under defined force terms. Internal forces are calculated from local model curvature, using a robust method by a least-squares error (LSE) approximation to the Dupin indicatrix. External forces are calculated by applying a step expansion and restoration filter (SEF) to the image data. A solution for one of the most common problems associated with deformable models, self-cutting, has been proposed in this work. We use a principal axis analysis and reslicing of the deformable model, followed by triangulation of the slices, to remedy self-cutting. We use vertex resampling, multiresolution deformation, and refinement of the mesh grid to improve the quality of the model deformation, which leads to better results. Examples of the model application to different cases (simulation, magnetic resonance imaging (MRI), computerized tomography (CT), and ultrasound images) are presented, showing diversity and flexibility of the model.