Generalized fuzzy clustering for segmentation of multi-spectral magnetic resonance images.

An integrated approach for multi-spectral segmentation of MR images is presented. This method is based on the fuzzy c-means (FCM) and includes bias field correction and contextual constraints over spatial intensity distribution and accounts for the non-spherical cluster's shape in the feature space. The bias field is modeled as a linear combination of smooth polynomial basis functions for fast computation in the clustering iterations. Regularization terms for the neighborhood continuity of intensity are added into the FCM cost functions. To reduce the computational complexity, the contextual regularizations are separated from the clustering iterations. Since the feature space is not isotropic, distance measure adopted in Gustafson-Kessel (G-K) algorithm is used instead of the Euclidean distance, to account for the non-spherical shape of the clusters in the feature space. These algorithms are quantitatively evaluated on MR brain images using the similarity measures.

Climatic drivers of hourly to yearly tree radius variations along a 6°C natural warming gradient

Climate affects the timing, rate and dynamics of tree growth, over time scales ranging from seconds to centuries. Monitoring how a tree's stem radius varies over these time scales can provide insight into intra-annual stem dynamics and improve our understanding of climate impacts on tree physiology and growth processes. Here, we quantify the response of radial conifer stem size to environmental fluctuations via a novel assessment of tree circadian cycles. We analyze four years of sub-hourly data collected from 56 larch and spruce trees growing along a natural temperature gradient of ∼6 °C in the central Swiss Alps. During the growing season, tree stem diameters were greatest at mid-morning and smallest in the late evening, reflecting the daily cycle of water uptake and loss. Along the gradient, amplitudes calculated from the stem radius cycle were ∼50% smaller at the upper site (∼2200 m a.s.l.) relative to the lower site (∼800 m a.s.l.). We show changes in precipitation, temperature and cloud cover have a substantial effect on typical growing season diurnal cycles; amplitudes were nine times smaller on rainy days (>10 mm), and daily amplitudes are approximately 40% larger when the mean daily temperature is 15–20 °C than when it is 5–10 °C. We find that over the growing season in the sub-alpine forests, spruce show greater daily stem water movement than larch. However, under projected future warming, larch could experience up to 50% greater stem water use, which may severely affect future growth on already dry sites. Our data further indicate that because of the confounding influences of radial growth and short-term water dynamics on stem size, conventional methodology probably overstates the effect of water-linked meteorological variables (i.e. precipitation and relative humidity) on intra-annual tree growth. We suggest future studies use intra-seasonal measurements of cell development and consider whether climatic factors produce reversible changes in stem diameter. These study design elements may help researchers more accurately quantify and attribute changes in forest productivity in response to future warming.

A new method to measure higher visual functions in an immersive environment

BACKGROUND: Higher visual functions can be defined as cognitive processes responsible for object recognition, color and shape perception, and motion detection. People with impaired higher visual functions after unilateral brain lesion are often tested with paper pencil tests, but such tests do not assess the degree of interaction between the healthy brain hemisphere and the impaired one. Hence, visual functions are not tested separately in the contralesional and ipsilesional visual hemifields. METHODS: A new measurement setup, that involves real-time comparisons of shape and size of objects, orientation of lines, speed and direction of moving patterns, in the right or left visual hemifield, has been developed. The setup was implemented in an immersive environment like a hemisphere to take into account the effects of peripheral and central vision, and eventual visual field losses. Due to the non-flat screen of the hemisphere, a distortion algorithm was needed to adapt the projected images to the surface. Several approaches were studied and, based on a comparison between projected images and original ones, the best one was used for the implementation of the test. Fifty-seven healthy volunteers were then tested in a pilot study. A Satisfaction Questionnaire was used to assess the usability of the new measurement setup. RESULTS: The results of the distortion algorithm showed a structural similarity between the warped images and the original ones higher than 97%. The results of the pilot study showed an accuracy in comparing images in the two visual hemifields of 0.18 visual degrees and 0.19 visual degrees for size and shape discrimination, respectively, 2.56° for line orientation, 0.33 visual degrees/s for speed perception and 7.41° for recognition of motion direction. The outcome of the Satisfaction Questionnaire showed a high acceptance of the battery by the participants. CONCLUSIONS: A new method to measure higher visual functions in an immersive environment was presented. The study focused on the usability of the developed battery rather than the performance at the visual tasks. A battery of five subtasks to study the perception of size, shape, orientation, speed and motion direction was developed. The test setup is now ready to be tested in neurological patients.

A new Bayesian approach to the reconstruction of spectral functions

We present a novel approach for the reconstruction of spectra from Euclidean correlator data that makes close contact to modern Bayesian concepts. It is based upon an axiomatically justified dimensionless prior distribution, which in the case of constant prior function m(ω) only imprints smoothness on the reconstructed spectrum. In addition we are able to analytically integrate out the only relevant overall hyper-parameter α in the prior, removing the necessity for Gaussian approximations found e.g. in the Maximum Entropy Method. Using a quasi-Newton minimizer and high-precision arithmetic, we are then able to find the unique global extremum of P[ρ|D] in the full Nω » Nτ dimensional search space. The method actually yields gradually improving reconstruction results if the quality of the supplied input data increases, without introducing artificial peak structures, often encountered in the MEM. To support these statements we present mock data analyses for the case of zero width delta peaks and more realistic scenarios, based on the perturbative Euclidean Wilson Loop as well as the Wilson Line correlator in Coulomb gauge.

Lake ice phenology from AVHRR data for European lakes: An automated two-step extraction method

Several lake ice phenology studies from satellite data have been undertaken. However, the availability of long-term lake freeze-thaw-cycles, required to understand this proxy for climate variability and change, is scarce for European lakes. Long time series from space observations are limited to few satellite sensors. Data of the Advanced Very High Resolution Radiometer (AVHRR) are used in account of their unique potential as they offer each day global coverage from the early 1980s expectedly until 2022. An automatic two-step extraction was developed, which makes use of near-infrared reflectance values and thermal infrared derived lake surface water temperatures to extract lake ice phenology dates. In contrast to other studies utilizing thermal infrared, the thresholds are derived from the data itself, making it unnecessary to define arbitrary or lake specific thresholds. Two lakes in the Baltic region and a steppe lake on the Austrian–Hungarian border were selected. The later one was used to test the applicability of the approach to another climatic region for the time period 1990 to 2012. A comparison of the extracted event dates with in situ data provided good agreements of about 10 d mean absolute error. The two-step extraction was found to be applicable for European lakes in different climate regions and could fill existing data gaps in future applications. The extension of the time series to the full AVHRR record length (early 1980 until today) with adequate length for trend estimations would be of interest to assess climate variability and change. Furthermore, the two-step extraction itself is not sensor-specific and could be applied to other sensors with equivalent near- and thermal infrared spectral bands.

Development of a rapid column-switching LC-MS/MS method for the quantification of THCCOOH and THCCOOH-glucuronide in whole blood for assessing cannabis consumption frequency

The concentration of 11-nor-9-carboxy-Δ(9)-tetrahydrocannabinol (THCCOOH) in whole blood is used as a parameter for assessing the consumption behavior of cannabis consumers. The blood level of THCCOOH-glucuronide might provide additional information about the frequency of cannabis use. To verify this assumption, a column-switching liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for the rapid and direct quantification of free and glucuronidated THCCOOH in human whole blood was newly developed. The method comprised protein precipitation, followed by injection of the processed sample onto a trapping column and subsequent gradient elution to an analytical column for separation and detection. The total LC run time was 4.5 min. Detection of the analytes was accomplished by electrospray ionization in positive ion mode and selected reaction monitoring using a triple-stage quadrupole mass spectrometer. The method was fully validated by evaluating the following parameters: linearity, lower limit of quantification, accuracy and imprecision, selectivity, extraction efficiency, matrix effect, carry-over, dilution integrity, analyte stability, and re-injection reproducibility. All acceptance criteria were analyzed and the predefined criteria met. Linearity ranged from 5.0 to 500 μg/L for both analytes. The method was successfully applied to whole blood samples from a large collective of cannabis consumers, demonstrating its applicability in the forensic field.

A LAPLACE TRANSFORM PAIR MODEL TO DETERMINE BREMSSTRAHLUNG SPECTRA FROM ATTENUATION DATA (RADIATION, X-RAY, SPECTRAL MODELING)

Every x-ray attenuation curve inherently contains all the information necessary to extract the complete energy spectrum of a beam. To date, attempts to obtain accurate spectral information from attenuation data have been inadequate.^ This investigation presents a mathematical pair model, grounded in physical reality by the Laplace Transformation, to describe the attenuation of a photon beam and the corresponding bremsstrahlung spectral distribution. In addition the Laplace model has been mathematically extended to include characteristic radiation in a physically meaningful way. A method to determine the fraction of characteristic radiation in any diagnostic x-ray beam was introduced for use with the extended model.^ This work has examined the reconstructive capability of the Laplace pair model for a photon beam range of from 50 kVp to 25 MV, using both theoretical and experimental methods.^ In the diagnostic region, excellent agreement between a wide variety of experimental spectra and those reconstructed with the Laplace model was obtained when the atomic composition of the attenuators was accurately known. The model successfully reproduced a 2 MV spectrum but demonstrated difficulty in accurately reconstructing orthovoltage and 6 MV spectra. The 25 MV spectrum was successfully reconstructed although poor agreement with the spectrum obtained by Levy was found.^ The analysis of errors, performed with diagnostic energy data, demonstrated the relative insensitivity of the model to typical experimental errors and confirmed that the model can be successfully used to theoretically derive accurate spectral information from experimental attenuation data. ^

Multiple gradient echo propeller (MGREP) MRI: Technical development and potential applications

The PROPELLER (Periodically Rotated Overlapping Parallel Lines with Enhanced Reconstruction) magnetic resonance imaging (MRI) technique has inherent advantages over other fast imaging methods, including robust motion correction, reduced image distortion, and resistance to off-resonance effects. These features make PROPELLER highly desirable for T2*-sensitive imaging, high-resolution diffusion imaging, and many other applications. However, PROPELLER has been predominantly implemented as a fast spin-echo (FSE) technique, which is insensitive to T2* contrast, and requires time-inefficient signal averaging to achieve adequate signal-to-noise ratio (SNR) for many applications. These issues presently constrain the potential clinical utility of FSE-based PROPELLER. ^ In this research, our aim was to extend and enhance the potential applications of PROPELLER MRI by developing a novel multiple gradient echo PROPELLER (MGREP) technique that can overcome the aforementioned limitations. The MGREP pulse sequence was designed to acquire multiple gradient-echo images simultaneously, without any increase in total scan time or RF energy deposition relative to FSE-based PROPELLER. A new parameter was also introduced for direct user-control over gradient echo spacing, to allow variable sensitivity to T2* contrast. In parallel to pulse sequence development, an improved algorithm for motion correction was also developed and evaluated against the established method through extensive simulations. The potential advantages of MGREP over FSE-based PROPELLER were illustrated via three specific applications: (1) quantitative T2* measurement, (2) time-efficient signal averaging, and (3) high-resolution diffusion imaging. Relative to the FSE-PROPELLER method, the MGREP sequence was found to yield quantitative T2* values, increase SNR by ∼40% without any increase in acquisition time or RF energy deposition, and noticeably improve image quality in high-resolution diffusion maps. In addition, the new motion algorithm was found to improve the performance considerably in motion-artifact reduction. ^ Overall, this work demonstrated a number of enhancements and extensions to existing PROPELLER techniques. The new technical capabilities of PROPELLER imaging, developed in this thesis research, are expected to serve as the foundation for further expanding the scope of PROPELLER applications. ^

High resolution color reflectance and hematite and goethite record of ODP Hole 184-1143A in the South China Sea

Precipitation has a larger variability than temperature in tropical monsoon regions, thus it is an important climate variable. However, reconstructions of long-term rainfall histories are scarce because of the lack of reliable proxies. Here we document that iron oxide minerals, specifically the ratio of hematite to goethite (Hm/Gt), is a reasonable precipitation proxy. Using diffuse reflectance spectrophotometry, we measured samples from Ocean Drilling Program (ODP) 1143 drilling site (9°21.72'N, 113°17.11'E, 2777 m water depth) for hematite and goethite, whose formation processes are favored by opposing climate conditions. In order to determine the content of hematite and goethite we produced a set of calibration samples by removing the iron oxides to generate the natural matrix to which hematite and goethite in known percentages were added. From these calibration samples we developed a transfer function for determining hematite and goethite concentration from a sample's spectral reflectance. Applying this method to ODP 1143 sediments (top 34 m of a 510 m core with sampling interval of 10 cm) we were able to reconstruct a continuous precipitation history for SE Asia of the past 600 kyr using the Hm/Gt ratio as a proxy of the precipitation variability of Asian monsoon. The reliability of this Hm/Gt proxy is corroborated by its consistency with the stalagmite delta18O data from South China. Comparing long-term Hm/Gt records with the surface temperature gradient of equatorial Pacific Ocean, we found that monsoon precipitation and El Niño are correlated for the last 600 kyr. The development of El Niño-like conditions decreased SE Asia precipitation, whereas precipitation increases in response to La Niña intensification

A Variational Stereo Method for the Three-Dimensional Reconstruction of Ocean Waves

We develop a novel remote sensing technique for the observation of waves on the ocean surface. Our method infers the 3-D waveform and radiance of oceanic sea states via a variational stereo imagery formulation. In this setting, the shape and radiance of the wave surface are given by minimizers of a composite energy functional that combines a photometric matching term along with regularization terms involving the smoothness of the unknowns. The desired ocean surface shape and radiance are the solution of a system of coupled partial differential equations derived from the optimality conditions of the energy functional. The proposed method is naturally extended to study the spatiotemporal dynamics of ocean waves and applied to three sets of stereo video data. Statistical and spectral analysis are carried out. Our results provide evidence that the observed omnidirectional wavenumber spectrum S(k) decays as k-2.5 is in agreement with Zakharov's theory (1999). Furthermore, the 3-D spectrum of the reconstructed wave surface is exploited to estimate wave dispersion and currents.

An optimization method for conceptual design in engineering systems based on high order singular value decomposition

Se presenta un nuevo método de diseño conceptual en Ingeniería Aeronáutica basado el uso de modelos reducidos, también llamados modelos sustitutos (‘surrogates’). Los ingredientes de la función objetivo se calculan para cada indiviudo mediante la utilización de modelos sustitutos asociados a las distintas disciplinas técnicas que se construyen mediante definiciones de descomposición en valores singulares de alto orden (HOSVD) e interpolaciones unidimensionales. Estos modelos sustitutos se obtienen a partir de un número limitado de cálculos CFD. Los modelos sustitutos pueden combinarse, bien con un método de optimización global de tipo algoritmo genético, o con un método local de tipo gradiente. El método resultate es flexible a la par que mucho más eficiente, computacionalmente hablando, que los modelos convencionales basados en el cálculo directo de la función objetivo, especialmente si aparecen un gran número de parámetros de diseño y/o de modelado. El método se ilustra considerando una versión simplificada del diseño conceptual de un avión. Abstract An optimization method for conceptual design in Aeronautics is presented that is based on the use of surrogate models. The various ingredients in the target function are calculated for each individual using surrogates of the associated technical disciplines that are constructed via high order singular value decomposition and one dimensional interpolation. These surrogates result from a limited number of CFD calculated snapshots. The surrogates are combined with an optimization method, which can be either a global optimization method such as a genetic algorithm or a local optimization method, such as a gradient-like method. The resulting method is both flexible and much more computationally efficient than the conventional method based on direct calculation of the target function, especially if a large number of free design parameters and/or tunablemodeling parameters are present. The method is illustrated considering a simplified version of the conceptual design of an aircraft empennage.

A new feature extraction method for signal classification applied to cat spinal cord signals

In the spinal cord of the anesthetized cat, spontaneous cord dorsum potentials (CDPs) appear synchronously along the lumbo-sacral segments. These CDPs have different shapes and magnitudes. Previous work has indicated that some CDPs appear to be specially associated with the activation of spinal pathways that lead to primary afferent depolarization and presynaptic inhibition. Visual detection and classification of these CDPs provides relevant information on the functional organization of the neural networks involved in the control of sensory information and allows the characterization of the changes produced by acute nerve and spinal lesions. We now present a novel feature extraction approach for signal classification, applied to CDP detection. The method is based on an intuitive procedure. We first remove by convolution the noise from the CDPs recorded in each given spinal segment. Then, we assign a coefficient for each main local maximum of the signal using its amplitude and distance to the most important maximum of the signal. These coefficients will be the input for the subsequent classification algorithm. In particular, we employ gradient boosting classification trees. This combination of approaches allows a faster and more accurate discrimination of CDPs than is obtained by other methods.

On the design of spherical gradient index lenses

Classical spherical gradient index (GRIN) lenses (such as Maxwell Fish Eye lens, Eaton lens, Luneburg lens, etc.) design procedure using the Abel integral equation is reviewed and reorganized. Each lens is fully defined by a function called the angle of flight which describes the ray deflection through the lens. The radial refractive index distribution is obtained by applying a linear integral transformation to the angle of flight. The interest of this formulation is in the linearity of the integral transformation which allows us to derive new solutions from linear combinations of known lenses. Beside the review of the classical GRIN designs, we present a numerical method for GRIN lenses defined by the Abel integral equation with fixed limits, which is an ill-posed problem.