Data mining and machine learning approaches for prediction modelling of schistosomiasis disease vectors: Epidemic disease prediction modelling

This research presents viable solutions for prediction modelling of schistosomiasis disease based on vector density. Novel training models proposed in this work aim to address various aspects of interest in the artificial intelligence applications domain. Topics discussed include data imputation, semi-supervised labelling and synthetic instance simulation when using sparse training data. Innovative semi-supervised ensemble learning paradigms are proposed focusing on labelling threshold selection and stringency of classification confidence levels. A regression-correlation combination (RCC) data imputation method is also introduced for handling of partially complete training data. Results presented in this work show data imputation precision improvement over benchmark value replacement using proposed RCC on 70% of test cases. Proposed novel incremental transductive models such as ITSVM have provided interesting findings based on threshold constraints outperforming standard SVM application on 21% of test cases and can be applied with alternative environment-based epidemic disease domains. The proposed incremental transductive ensemble approach model enables the combination of complimentary algorithms to provide labelling for unlabelled vector density instances. Liberal (LTA) and strict training approaches provided varied results with LTA outperforming Stacking ensemble on 29.1% of test cases. Proposed novel synthetic minority over-sampling technique (SMOTE) equilibrium approach has yielded subtle classification performance increases which can be further interrogated to assess classification performance and efficiency relationships with synthetic instance generation.

Revisiting the comparison between the Shack-Hartmann and the pyramid wavefront sensors via the Fisher information matrix

Exoplanet direct imaging with large ground based telescopes requires eXtreme Adaptive Optics that couples high-order adaptive optics and coronagraphy. A key element of such systems is the high-order wavefront sensor. We study here several high-order wavefront sensing approaches, and more precisely compare their sensitivity to noise. Three techniques are considered: the classical Shack-Hartmann sensor, the pyramid sensor and the recently proposed LIFTed Shack-Hartmann sensor. They are compared in a unified framework based on precise diffractive models and on the Fisher information matrix, which conveys the information present in the data whatever the estimation method. The diagonal elements of the inverse of the Fisher information matrix, which we use as a figure of merit, are similar to noise propagation coefficients. With these diagonal elements, so called "Fisher coefficients", we show that the LIFTed Shack-Hartmann and pyramid sensors outperform the classical Shack-Hartmann sensor. In photon noise regime, the LIFTed Shack-Hartmann and modulated pyramid sensors obtain a similar overall noise propagation. The LIFTed Shack-Hartmann sensor however provides attractive noise properties on high orders.

Experimental validation of LIFT for estimation of low-order modes in low-flux wavefront sensing

Laser Tomographic and Multi-Conjugate Adaptive Optics systems rely on natural guide stars to sense low order aberrations (tip/tilt and focus). LIFT is a novel focal plane wavefront sensor (WFS), performing a maximum likelihood phase retrieval on a single image, with better sensitivity than a 2 × 2 Hartmann-Shack WFS. Its performance for the estimation of tip/tilt and focus is similar to a pyramid WFS without modulation, but with a simpler set-up. We present here the LIFT concept and associated data processing, as well as experimental results. We validate the estimation of tip/tilt and focus, with monochromatic and large bandwidth light, and verify the low noise sensitivity predicted by theory.

Analytical expression of long-exposure adaptive-optics-corrected coronagraphic image. First application to exoplanet detection

In this paper we derive an analytical model of a long-exposure star image for an adaptive-optics(AO)-corrected coronagraphic imaging system. This expression accounts for static aberrations upstream and downstream of the coronagraphic mask as well as turbulence residuals. It is based on the perfect coronagraph model. The analytical model is validated by means of simulations using the design and parameters of the SPHERE instrument. The analytical model is also compared to a simulated four-quadrant phase-mask coronagraph. Then, its sensitivity to a miscalibration of structure function and upstream static aberrations is studied, and the impact on exoplanet detectability is quantified. Last, a first inversion method is presented for a simulation case using a single monochromatic image with no reference. The obtained result shows a planet detectability increase by two orders of magnitude with respect to the raw image. This analytical model presents numerous potential applications in coronographic imaging, such as exoplanet direct detection, and circumstellar disk observation.

On-line long-exposure phase diversity: a powerful tool for sensing quasi-static aberrations of extreme adaptive optics imaging systems

The phase diversity technique is a useful tool to measure and pre-compensate for quasi-static aberrations, in particular non-common path aberrations, in an adaptive optics corrected imaging system. In this paper, we propose and validate by simulations an extension of the phase diversity technique that uses long exposure adaptive optics corrected images for sensing quasi-static aberrations during the scientific observation, in particular for high-contrast imaging. The principle of the method is that, for a sufficiently long exposure time, the residual turbulence is averaged into a convolutive component of the image and that phase diversity estimates the sole static aberrations of interest. The advantages of such a procedure, compared to the processing of shortexposure image pairs, are that the separation between static aberrations and turbulence-induced ones is performed by the long-exposure itself and not numerically, that only one image pair must be processed, that the estimation benefits from the high SNR of long-exposure images, and that only the static aberrations of interest are to be estimated. Long-exposure phase diversity can also be used as a phasing sensor for a segmented aperture telescope. Thus, it may be particularly useful for future planet finder projects such as EPICS on the European ELT.

High-order adaptive optics requirements for direct detection of extrasolar planets: Application to the SPHERE instrument

The detection of extrasolar planets implies an extremely high-contrast, long-exposure imaging capability at near infrared and probably visible wavelengths. We present here the core of any Planet Finder instrument, that is, the extreme adaptive optics (XAO) subsystem. The level of AO correction directly impacts the exposure time required for planet detection. In addition, the capacity of the AO system to calibrate all the instrument static defects ultimately limits detectivity. Hence, the extreme AO system has to adjust for the perturbations induced by the atmospheric turbulence, as well as for the internal aberrations of the instrument itself. We propose a feasibility study for an extreme AO system in the frame of the SPHERE (Spectro-Polarimetry High-contrast Exoplanet Research) instrument, which is currently under design and should equip one of the four VLT 8-m telescopes in 2010.

The effect of adding two target-controlled concentrations (1–3 ng mL−1) of remifentanil on MACBAR of desflurane*

BACKGROUND AND OBJECTIVES

The aim of this prospective, randomized, double-blind study was to determine the effects of adding two different target-controlled concentrations of remifentanil (1 and 3 ng mL(-1)) on the desflurane requirement for blunting sympathetic responses after surgical incision (minimum anaesthetic concentration (MAC(BAR)).

METHODS

67 patients, aged 20-50 yr, ASA I, undergoing general anaesthesia for elective abdominal surgery were enrolled and randomly allocated to receive no remifentanil infusion (n = 21) or a target-controlled effect-site concentration of 1 ng mL(-1) (n = 24) or 3 ng mL(-1) remifentanil (n = 22). All patients were anaesthetized with propofol, cisatracurium and desflurane with a mixture of 60% nitrous oxide in oxygen. Sympathetic responses to surgical incision were determined after a 20-min period of stable end-tidal desflurane and target-controlled remifentanil concentrations. Predetermined end-tidal desflurane concentrations and the MAC(BAR) for each group were determined using an up-and-down sequential-allocation technique.

RESULTS

The MAC(BAR) of desflurane was higher in the group receiving no remifentanil (6.25% [95% confidence interval: 5.9-6.5%]) as compared with patients of the groups receiving 1 ng mL(-1) (2.7% [2.6-2.8%]; P < 0.001) and 3 ng mL(-1) remifentanil (2% [1.9-2.2%]; P < 0.01). When considering a MAC value in this age population and the contribution of 60% nitrous oxide (0.55 MAC), the combined MAC(BAR) values, expressed as multiples of the MAC, were 1.9, 0.8 and 0.6 MAC, in the three groups, respectively.

CONCLUSION

A target-controlled concentration of 1 ng mL(-1) remifentanil results in a 57% decrease in the MAC(BAR) of desflurane combined with 60% nitrous oxide. Increasing the target concentration of remifentanil to 3 ng mL(-1) produces a further 26% decrease in the MAC(BAR) values of desflurane.

Closed-loop experimental validation of the spatially filtered Shack-Hartmann concept

An experimental validation of the spatially filtered Shack-Hartmann concept (F-SH) is presented that allows aliasing effects to be decreased. This effect is studied by use of an adaptive optical testbed with a focal plane pinhole in front of the wave-front sensor. First, the ability to close the loop on turbulence is demonstrated. Then the performance gain conferred by the device is quantified and compared with end-to-end simulation results. Another property of the F-SH concept, i.e., the reduction of the waffle modes, is highlighted.

Improvement of Shack-Hartmann wave-front sensor measurement for extreme adaptive optics

The development of high-performance adaptive optics systems requires the optimization of wave-front sensors (WFSs) working in the high-order correction regime. We propose a new method to improve the wave-front slope estimation of a Shack-Hartmann WFS in such a regime. Based on a detailed analysis of the different errors in the slope estimation with a classical centroid and with the new method, the gain in terms of wave-front-sensing accuracy in both the detector and the photon noise regimes is stressed. This improvement is proposed without major system disruption.

Optimal wave-front reconstruction strategies for multiconjugate adaptive optics

We propose an optimal approach for the phase reconstruction in a large field of view (FOV) for multiconjugate adaptive optics. This optimal approach is based on a minimum-mean-square-error estimator that minimizes the mean residual phase variance in the FOV of interest. It accounts for the C2n profile in order to optimally estimate the correction wave front to be applied to each deformable mirror (DM). This optimal approach also accounts for the fact that the number of DMs will always be smaller than the number of turbulent layers, since the C2n profile is a continuous function of the altitude h. Links between this optimal approach and a tomographic reconstruction of the turbulence volume are established. In particular, it is shown that the optimal approach consists of a full tomographic reconstruction of the turbulence volume followed by a projection onto the DMs accounting for the considered FOV of interest. The case where the turbulent layers are assumed to match the mirror positions [model-approximation (MA) approach], which might be a crude approximation, is also considered for comparison. This MA approach will rely on the notion of equivalent turbulent layers. A comparison between the optimal and MA approaches is proposed. It is shown that the optimal approach provides very good performance even with a small number of DMs (typically, one or two). For instance, good Strehl ratios (greater than 20%) are obtained for a 4-m telescope on a 150-arc sec x 150-arc sec FOV by using only three guide stars and two DMs.

Efficient phase estimation for large-field-of-view adaptive optics

We propose a maximum a posteriori-based estimation of the turbulent phase in a large field of view (FOV) to overcome the anisoplanatism limitation in adaptive optics. We show that, whatever the true atmospheric profile, a small number of equivalent layers (two or three) is required for accurate restoration of the phase in the whole FOV. The implications for multiconjugate adaptive optics are discussed in terms of the number and conjugated heights of the deformable mirrors. The number of guide stars required for wave-front measurements in the field is also discussed: three (or even two) guide stars are sufficient to produce good performance.

Treatment of hypopituitarism in infancy. Effect on head circumference growth

BACKGROUND

Head circumference of children with multiple pituitary-hormone deficiency (MPHD) may be subnormal for age. Moreover it is known that linear growth in infancy is growth-hormone (GH) dependent. Therefore, aim of the study has been to compare head circumference measurements in children with hypopituitarism after L-thyroxine (L-T4) therapy alone, before therapy with GH, and after GH was added to the therapy.

METHODS

Five infants (2 girls, 3 boys) with MPHD, diagnosed and treated before the age of 2 years and whose auxological parameters records during L-T4 therapy alone were available, were retrospectively studied. Head circumference and length measurements were expressed as standard deviation score (SDS). Weight measurements were expressed as weight for length ratio percentage.

RESULTS

Initially treated with L-T4 alone for a mean period of 4, 5 months, there were neither positive effects on head circumference nor on linear growth. A significant catch-up growth was observed only employing GH therapy in addition to L-T4: mean head circumference SDS and length SDS increased respectively from -2.20 to -0.89 SDS and from -4.16 to -0.87 SDS after a mean period of 18 months of combined GH and L-T4 therapy.

CONCLUSIONS

Therefore, head circumference growth, in infancy, is growth hormone dependent as well as linear growth, and during GH treatment, monitoring head circumference growth is important as much as monitoring linear growth.

Treatment of hypopituitarism in infancy. Effect on head circumference growth

BACKGROUND

Head circumference of children with multiple pituitary-hormone deficiency (MPHD) may be subnormal for age. Moreover it is known that linear growth in infancy is growth-hormone (GH) dependent. Therefore, aim of the study has been to compare head circumference measurements in children with hypopituitarism after L-thyroxine (L-T4) therapy alone, before therapy with GH, and after GH was added to the therapy.

METHODS

Five infants (2 girls, 3 boys) with MPHD, diagnosed and treated before the age of 2 years and whose auxological parameters records during L-T4 therapy alone were available, were retrospectively studied. Head circumference and length measurements were expressed as standard deviation score (SDS). Weight measurements were expressed as weight for length ratio percentage.

RESULTS

Initially treated with L-T4 alone for a mean period of 4, 5 months, there were neither positive effects on head circumference nor on linear growth. A significant catch-up growth was observed only employing GH therapy in addition to L-T4: mean head circumference SDS and length SDS increased respectively from -2.20 to -0.89 SDS and from -4.16 to -0.87 SDS after a mean period of 18 months of combined GH and L-T4 therapy.

CONCLUSIONS

Therefore, head circumference growth, in infancy, is growth hormone dependent as well as linear growth, and during GH treatment, monitoring head circumference growth is important as much as monitoring linear growth.

Myopic deconvolution of adaptive optics images by use of object and point-spread function power spectra

Adaptive optics systems provide a real-time compensation for atmospheric turbulence. However, the correction is often only partial, and a deconvolution is required for reaching the diffraction limit. The need for a regularized deconvolution is discussed, and such a deconvolution technique is presented. This technique incorporates a positivity constraint and some a priori knowledge of the object (an estimate of its local mean and a model for its power spectral density). This method is then extended to the case of an unknown point-spread function, still taking advantage of similar a priori information on the point-spread function. Deconvolution results are presented for both simulated and experimental data.