Encapsulated filtering blebs after trabeculectomy with mitomycin-C

BACKGROUND AND OBJECTIVE: To determine the frequency of encapsulated blebs after guarded filtration procedures with mitomycin-C. PATIENTS AND METHODS: The authors reviewed the charts of all patients who had undergone a guarded filtration procedure with mitomycin-C. There were 235 patients (283 cases) who had more than 1 month of follow-up. RESULTS: An encapsulated bleb developed in 7 eyes (2.47%) of 6 patients. Identification of bleb encapsulation occurred at a mean follow-up time of 29.7 ± 14.6 days after surgery. The mean intraocular pressure at that point was 24.2 ± 13.5 mm Hg in the affected eyes. Three eyes were treated medically, and needling was performed in 4 eyes. CONCLUSION: There is a low frequency of encapsulated bleb formation after guarded filtration procedures with adjunctive mitomycin- C.

A 75-81 GHz, 14.3 dBm Peak Output Power, 21 dB Peak Gain, SiGe Power-Combining Amplifier Operating from a Single 3.3 V Supply

A compact differential 4-way power combiner with 2.3 dB loss and high common-mode rejection characteristic for use in mm-wave PAs is presented. A complete circuit comprised of a power splitter, two-stage cascode PA array, and a power combiner was implemented in SiGe technology. Measured small-signal gain of at least 17 dB was obtained from 74.5 GHz to 80.5 GHz with a peak 21 dB at 79 GHz. The prototype delivered 13.2 dBm P1dB and 14.3 dBm Psat when operated from a single 3.3 V supply at 75 GHz.

Anticipatory Planning Reveals Segmentation of Cortical Motor Output During Action Observation

It has been argued that the variation in brain activity that occurs when observing another person reflects a representation of actions that is indivisible, and which plays out in full once the intent of the actor can be discerned. We used transcranial magnetic stimulation to probe the excitability of corticospinal projections to 2 intrinsic hand muscles while motions to reach and grasp an object were observed. A symbolic cue either faithfully indicated the required final orientation of the object and thus the nature of the grasp that was required, or was in conflict with the movement subsequently displayed. When the cue was veridical, modulation of excitability was in accordance with the functional role of the muscles in the action observed. If however the cue had indicated that the alternative grasp would be required, modulation of output to first dorsal interosseus was consistent with the action specified, rather than the action observed-until the terminal phase of the motion sequence during which the object was seen lifted. Modulation of corticospinal output during observation is thus segmented-it progresses initially in accordance with the action anticipated, and if discrepancies are revealed by visual input, coincides thereafter with that of the action seen.

Implementation of phantom-less IMRT delivery verification using Varian DynaLog files and R/V output

This study aims to evaluate the use of Varian radiotherapy dynamic treatment log (DynaLog) files to verify IMRT plan delivery as part of a routine quality assurance procedure. Delivery accuracy in terms of machine performance was quantified by multileaf collimator (MLC) position errors and fluence delivery accuracy for patients receiving intensity modulated radiation therapy (IMRT) treatment. The relationship between machine performance and plan complexity, quantified by the modulation complexity score (MCS) was also investigated. Actual MLC positions and delivered fraction of monitor units (MU), recorded every 50 ms during IMRT delivery, were extracted from the DynaLog files. The planned MLC positions and fractional MU were taken from the record and verify system MLC control file. Planned and delivered beam data were compared to determine leaf position errors with and without the overshoot effect. Analysis was also performed on planned and actual fluence maps reconstructed from the MLC control file and delivered treatment log files respectively. This analysis was performed for all treatment fractions for 5 prostate, 5 prostate and pelvic node (PPN) and 5 head and neck (H&N) IMRT plans, totalling 82 IMRT fields in ∼5500 DynaLog files. The root mean square (RMS) leaf position errors without the overshoot effect were 0.09, 0.26, 0.19 mm for the prostate, PPN and H&N plans respectively, which increased to 0.30, 0.39 and 0.30 mm when the overshoot effect was considered. Average errors were not affected by the overshoot effect and were 0.05, 0.13 and 0.17 mm for prostate, PPN and H&N plans respectively. The percentage of pixels passing fluence map gamma analysis at 3%/3 mm was 99.94 ± 0.25%, which reduced to 91.62 ± 11.39% at 1%/1 mm criterion. Leaf position errors, but not gamma passing rate, were directly related to plan complexity as determined by the MCS. Site specific confidence intervals for average leaf position errors were set at -0.03-0.12 mm for prostate and -0.02-0.28 mm for more complex PPN and H&N plans. For all treatment sites confidence intervals for RMS errors with the overshoot was set at 0-0.50 mm and for the percentage of pixels passing a gamma analysis at 1%/1 mm a confidence interval of 68.83% was set also for all treatment sites. This work demonstrates the successful implementation of treatment log files to validate IMRT deliveries and how dynamic log files can diagnose delivery errors not possible with phantom based QC. Machine performance was found to be directly related to plan complexity but this is not the dominant determinant of delivery accuracy.

A multi-output two-stage locally regularized model construction method using the extreme learning machine

This paper investigates the construction of linear-in-the-parameters (LITP) models for multi-output regression problems. Most existing stepwise forward algorithms choose the regressor terms one by one, each time maximizing the model error reduction ratio. The drawback is that such procedures cannot guarantee a sparse model, especially under highly noisy learning conditions. The main objective of this paper is to improve the sparsity and generalization capability of a model for multi-output regression problems, while reducing the computational complexity. This is achieved by proposing a novel multi-output two-stage locally regularized model construction (MTLRMC) method using the extreme learning machine (ELM). In this new algorithm, the nonlinear parameters in each term, such as the width of the Gaussian function and the power of a polynomial term, are firstly determined by the ELM. An initial multi-output LITP model is then generated according to the termination criteria in the first stage. The significance of each selected regressor is checked and the insignificant ones are replaced at the second stage. The proposed method can produce an optimized compact model by using the regularized parameters. Further, to reduce the computational complexity, a proper regression context is used to allow fast implementation of the proposed method. Simulation results confirm the effectiveness of the proposed technique. © 2013 Elsevier B.V.

Adaptive Fusion Of Particle Filtering And Spatio-Temporal Motion Energy For Human Tracking

Object tracking is an active research area nowadays due to its importance in human computer interface, teleconferencing and video surveillance. However, reliable tracking of objects in the presence of occlusions, pose and illumination changes is still a challenging topic. In this paper, we introduce a novel tracking approach that fuses two cues namely colour and spatio-temporal motion energy within a particle filter based framework. We conduct a measure of coherent motion over two image frames, which reveals the spatio-temporal dynamics of the target. At the same time, the importance of both colour and motion energy cues is determined in the stage of reliability evaluation. This determination helps maintain the performance of the tracking system against abrupt appearance changes. Experimental results demonstrate that the proposed method outperforms the other state of the art techniques in the used test datasets.

Frequency Filtering of Torsional Alfvén Waves by Chromospheric Magnetic Field

In this Letter, we demonstrate how the observation of broadband frequency propagating torsional Alfvén waves in chromospheric magnetic flux tubes can provide valuable insight into their magnetic field structure. By implementing a full nonlinear three-dimensional magnetohydrodynamic numerical simulation with a realistic vortex driver, we demonstrate how the plasma structure of chromospheric magnetic flux tubes can act as a spatially dependent frequency filter for torsional Alfvén waves. Importantly, for solar magnetoseismology applications, this frequency filtering is found to be strongly dependent on magnetic field structure. With reference to an observational case study of propagating torsional Alfvén waves using spectroscopic data from the Swedish Solar Telescope, we demonstrate how the observed two-dimensional spatial distribution of maximum power Fourier frequency shows a strong correlation with our forward model. This opens the possibility of beginning an era of chromospheric magnetoseismology, to complement the more traditional methods of mapping the magnetic field structure of the solar chromosphere.

Systolic two-port adaptor for high performance wave digital filtering

The authors present a VLSI circuit for implementing wave digital filter (WDF) two-port adaptors. Considerable speedups over conventional designs have been obtained using fine grained pipelining. This has been achieved through the use of most significant bit (MSB) first carry-save arithmetic, which allows systems to be designed in which latency L is small and independent of either coefficient or input data wordlength. L is determined by the online delay associated with the computation required at each node in the circuit (in this case a multiply/add plus two separate additions). This in turn means that pipelining can be used to considerably enhance the sampling rate of a recursive digital filter. The level of pipelining which will offer enhancement is determined by L and is fine-grained rather than bit level. In the case of the circuit considered, L = 3. For this reason pipeline delays (half latches) have been introduced between every two rows of cells to produce a system with a once every cycle sample rate.

DEPENDENCE OF LIGHT OUTPUT FROM NOMINALLY SMOOTH AL-OX-AU TUNNEL-JUNCTIONS ON ELECTRODE MORPHOLOGY

The light output from nominally smooth Al-Ox-Au tunnel junctions is observed to be substantially independent of the deposition rate of the Au film electrode. Films deposited quickly (2 nm s-1) and those deposited slowly (0.16 nm s-1) have similar spectral dependences and intensities. (This is in contrast to roughened films where those deposited quickly give out less light, especially towards the blue end of the spectrum.) The behaviour can be interpreted in terms of the ratio l(ph)/l(em) where l(ph) and l(em) are the mean free paths of surface plasmons between external photon emissions and internal electromagnetic absorptions respectively. Once l(ph)/l(em) exceeds 100, as it does on smooth films, grain size has little further effect on the spectral shape of the light output. In fast-deposited films there are two compensating effects on the output intensity: grain boundary scattering decreases it and greater surface roughness increases it.

DFIG Machine Design for Maximizing Power Output Based on Surrogate Optimization Algorithm

This paper presents a surrogate-model based optimization of a doubly-fed induction generator (DFIG) machine winding design for maximizing power yield. Based on site-specific wind profile data and the machine’s previous operational performance, the DFIG’s stator and rotor windings are optimized to match the maximum efficiency with operating conditions for rewinding purposes. The particle swarm optimization (PSO)-based surrogate optimization techniques are used in conjunction with the finite element method (FEM) to optimize the machine design utilizing the limited available information for the site-specific wind profile and generator operating conditions. A response surface method in the surrogate model is developed to formulate the design objectives and constraints. Besides, the machine tests and efficiency calculations follow IEEE standard 112-B. Numerical and experimental results validate the effectiveness of the proposed technologies.