Pilot study of hyperopic LASIK using the solid-state laser technology

Background To evaluate and report the visual, refractive, and aberrometric outcomes of LASIK for the correction of low to moderate hyperopia in a pilot group using a commercially available solid-state laser. Methods Prospective pilot study including 11 consecutive eyes with low to moderate hyperopia of six patients undergoing LASIK surgery using the Pulzar Z1 solid-state laser (CustomVis Laser Pty Ltd., currently CV Laser). Visual, refractive, and aberrometric changes were evaluated. Potential complications were evaluated as well. Mean follow-up time was 6.6 months (range, 3 to 11 months). Results A significant improvement in LogMAR uncorrected distance visual acuity (UDVA) was observed postoperatively (p = 0.01). No significant change was detected in LogMAR corrected distance visual acuity (CDVA) (p = 0.21). Postoperative LogMAR UDVA was 0.1 (about 20/25) or better in ten eyes (90.9 %). Mean overall efficacy and safety indices were 1.03 and 1.12. Postoperatively, no losses of lines of CDVA were observed. Postoperative spherical equivalent was within ±1.00 D in ten eyes (90.9 %). With regard to aberrations, no statistically significant changes were found in higher order and primary coma RMS postoperatively (p ≥ 0.21), and only minimal but statistically significant negativization of primary spherical aberration (p = 0.02) was observed. No severe complications were observed. Conclusion LASIK surgery using the solid-state laser technology seems to be a useful procedure for the correction of low to moderate hyperopia, with minimal induction of higher order aberrations.

Crop Phenology Estimation Using a Multitemporal Model and a Kalman Filtering Strategy

In this letter, a new approach for crop phenology estimation with remote sensing is presented. The proposed methodology is aimed to exploit tools from a dynamical system context. From a temporal sequence of images, a geometrical model is derived, which allows us to translate this temporal domain into the estimation problem. The evolution model in state space is obtained through dimensional reduction by a principal component analysis, defining the state variables, of the observations. Then, estimation is achieved by combining the generated model with actual samples in an optimal way using a Kalman filter. As a proof of concept, an example with results obtained with this approach over rice fields by exploiting stacks of TerraSAR-X dual polarization images is shown.

Dynamical Approach for Real-Time Monitoring of Agricultural Crops

In this paper, a novel approach for exploiting multitemporal remote sensing data focused on real-time monitoring of agricultural crops is presented. The methodology is defined in a dynamical system context using state-space techniques, which enables the possibility of merging past temporal information with an update for each new acquisition. The dynamic system context allows us to exploit classical tools in this domain to perform the estimation of relevant variables. A general methodology is proposed, and a particular instance is defined in this study based on polarimetric radar data to track the phenological stages of a set of crops. A model generation from empirical data through principal component analysis is presented, and an extended Kalman filter is adapted to perform phenological stage estimation. Results employing quad-pol Radarsat-2 data over three different cereals are analyzed. The potential of this methodology to retrieve vegetation variables in real time is shown.

Contribution to Real-Time Estimation of Crop Phenological States in a Dynamical Framework Based on NDVI Time Series: Data Fusion With SAR and Temperature

In this study, a methodology based in a dynamical framework is proposed to incorporate additional sources of information to normalized difference vegetation index (NDVI) time series of agricultural observations for a phenological state estimation application. The proposed implementation is based on the particle filter (PF) scheme that is able to integrate multiple sources of data. Moreover, the dynamics-led design is able to conduct real-time (online) estimations, i.e., without requiring to wait until the end of the campaign. The evaluation of the algorithm is performed by estimating the phenological states over a set of rice fields in Seville (SW, Spain). A Landsat-5/7 NDVI series of images is complemented with two distinct sources of information: SAR images from the TerraSAR-X satellite and air temperature information from a ground-based station. An improvement in the overall estimation accuracy is obtained, especially when the time series of NDVI data is incomplete. Evaluations on the sensitivity to different development intervals and on the mitigation of discontinuities of the time series are also addressed in this work, demonstrating the benefits of this data fusion approach based on the dynamic systems.

Ideological Complex Systems: Mathematical Theory

The goal of this article is to build an abstract mathematical theory rather than a computational one of the process of transmission of ideology. The basis of much of the argument is Patten's Environment Theory that characterizes a system with its double environment (input or stimulus and output or response) and the existing interactions among them. Ideological processes are semiotic processes, and if in Patten's theory, the two environments are physical, in this theory ideological processes are physical and semiotic, as are stimulus and response.