Visual performance of a new bi-aspheric, segmented, asymmetric multifocal IOL

PURPOSE: To assess the visual performance and subjective experience of eyes implanted with a new bi-aspheric, segmented, multifocal intraocular lens: the Mplus X (Topcon Europe Medical, Capelle aan den IJssel, Netherlands). METHODS: Seventeen patients (mean age: 64.0 ± 12.8 years) had binocular implantation (34 eyes) with the Mplus X. Three months after the implantation, assessment was made of: manifest refraction; uncorrected and corrected distance visual acuity; uncorrected and distance corrected near visual acuity; defocus curves in photopic conditions; contrast sensitivity; halometry as an objective measure of glare; and patient satisfaction with unaided near vision using the Near Acuity Visual Questionnaire. RESULTS: Mean residual manifest refraction was -0.13 ± 0.51 diopters (D). Twenty-five eyes (74%) were within a mean spherical equivalent of ±0.50 D. Mean uncorrected distance visual acuity was +0.10 ± 0.12 logMAR monocularly and 0.02 ± 0.09 logMAR binocularly. Thirty-two eyes (94%) could read 0.3 or better without any reading correction and all patients could read 0.3 or better with a reading correction. Mean monocular uncorrected near visual acuity was 0.18 ± 0.16 logMAR, improving to 0.15 ± 0.15 logMAR with distance correction. Mean binocular uncorrected near visual acuity was 0.11 ± 0.11 logMAR, improving to 0.09 ± 0.12 logMAR with distance correction. Mean binocular contrast sensitivity was 1.75 ± 0.14 log units at 3 cycles per degree, 1.88 ± 0.20 log units at 6 cycles per degree, 1.66 ± 0.19 log units at 12 cycles per degree, and 1.11 ± 0.20 log units at 18 cycles per degree. Mean binocular and monocular halometry showed a glare profile of less than 1° of debilitating light scatter. Mean Near Acuity Visual Questionnaire Rasch score (0 = no difficulty, 100 = extreme difficulty) for satisfaction for near vision was 20.43 ± 14.64 log-odd units. CONCLUSIONS: The Mplus X provides a good visual outcome at distance and near with minimal dysphotopsia. Patients were very satisfied with their uncorrected near vision. © SLACK Incorporated.

A laser induced breakdown spectroscopy quantitative analysis method based on the robust least squares support vector machine regression model

Data fluctuation in multiple measurements of Laser Induced Breakdown Spectroscopy (LIBS) greatly affects the accuracy of quantitative analysis. A new LIBS quantitative analysis method based on the Robust Least Squares Support Vector Machine (RLS-SVM) regression model is proposed. The usual way to enhance the analysis accuracy is to improve the quality and consistency of the emission signal, such as by averaging the spectral signals or spectrum standardization over a number of laser shots. The proposed method focuses more on how to enhance the robustness of the quantitative analysis regression model. The proposed RLS-SVM regression model originates from the Weighted Least Squares Support Vector Machine (WLS-SVM) but has an improved segmented weighting function and residual error calculation according to the statistical distribution of measured spectral data. Through the improved segmented weighting function, the information on the spectral data in the normal distribution will be retained in the regression model while the information on the outliers will be restrained or removed. Copper elemental concentration analysis experiments of 16 certified standard brass samples were carried out. The average value of relative standard deviation obtained from the RLS-SVM model was 3.06% and the root mean square error was 1.537%. The experimental results showed that the proposed method achieved better prediction accuracy and better modeling robustness compared with the quantitative analysis methods based on Partial Least Squares (PLS) regression, standard Support Vector Machine (SVM) and WLS-SVM. It was also demonstrated that the improved weighting function had better comprehensive performance in model robustness and convergence speed, compared with the four known weighting functions.