Linear and nonlinear terrain deformation maps from a reduced set of interferometric SAR images

In this paper, an advanced technique for the generation of deformation maps using synthetic aperture radar (SAR) data is presented. The algorithm estimates the linear and nonlinear components of the displacement, the error of the digital elevation model (DEM) used to cancel the topographic terms, and the atmospheric artifacts from a reduced set of low spatial resolution interferograms. The pixel candidates are selected from those presenting a good coherence level in the whole set of interferograms and the resulting nonuniform mesh tessellated with the Delauney triangulation to establish connections among them. The linear component of movement and DEM error are estimated adjusting a linear model to the data only on the connections. Later on, this information, once unwrapped to retrieve the absolute values, is used to calculate the nonlinear component of movement and atmospheric artifacts with alternate filtering techniques in both the temporal and spatial domains. The method presents high flexibility with respect to the required number of images and the baselines length. However, better results are obtained with large datasets of short baseline interferograms. The technique has been tested with European Remote Sensing SAR data from an area of Catalonia (Spain) and validated with on-field precise leveling measurements.

Impulse response recovery of linear systems through weighted cumulant slice

Identifiability of the so-called ω-slice algorithm is proven for ARMA linear systems. Although proofs were developed in the past for the simpler cases of MA and AR models, they were not extendible to general exponential linear systems. The results presented in this paper demonstrate a unique feature of the ω-slice method, which is unbiasedness and consistency when order is overdetermined, regardless of the IIR or FIR nature of the underlying system, and numerical robustness.

System identification using a linear combination of cumulant slices

In this paper we develop a new linear approach to identify the parameters of a moving average (MA) model from the statistics of the output. First, we show that, under some constraints, the impulse response of the system can be expressed as a linear combination of cumulant slices. Then, thisresult is used to obtain a new well-conditioned linear methodto estimate the MA parameters of a non-Gaussian process. Theproposed method presents several important differences withexisting linear approaches. The linear combination of slices usedto compute the MA parameters can be constructed from dif-ferent sets of cumulants of different orders, providing a generalframework where all the statistics can be combined. Further-more, it is not necessary to use second-order statistics (the autocorrelation slice), and therefore the proposed algorithm stillprovides consistent estimates in the presence of colored Gaussian noise. Another advantage of the method is that while mostlinear methods developed so far give totally erroneous estimates if the order is overestimated, the proposed approach doesnot require a previous estimation of the filter order. The simulation results confirm the good numerical conditioning of thealgorithm and the improvement in performance with respect to existing methods.

Linear transceiver design in nonregenerative relays with channel state information

This paper deals with the design of nonregenerativerelaying transceivers in cooperative systems where channel stateinformation (CSI) is available at the relay station. The conventionalnonregenerative approach is the amplify and forward(A&F) approach, where the signal received at the relay is simplyamplified and retransmitted. In this paper, we propose an alternativelinear transceiver design for nonregenerative relaying(including pure relaying and the cooperative transmission cases),making proper use of CSI at the relay station. Specifically, wedesign the optimum linear filtering performed on the data to beforwarded at the relay. As optimization criteria, we have consideredthe maximization of mutual information (that provides aninformation rate for which reliable communication is possible) fora given available transmission power at the relay station. Threedifferent levels of CSI can be considered at the relay station: onlyfirst hop channel information (between the source and relay);first hop channel and second hop channel (between relay anddestination) information, or a third situation where the relaymay have complete cooperative channel information includingall the links: first and second hop channels and also the directchannel between source and destination. Despite the latter beinga more unrealistic situation, since it requires the destination toinform the relay station about the direct channel, it is useful as anupper benchmark. In this paper, we consider the last two casesrelating to CSI.We compare the performance so obtained with theperformance for the conventional A&F approach, and also withthe performance of regenerative relays and direct noncooperativetransmission for two particular cases: narrowband multiple-inputmultiple-output transceivers and wideband single input singleoutput orthogonal frequency division multiplex transmissions.

Mutations in NDUFB11, Encoding a Complex I Component of the Mitochondrial Respiratory Chain, Cause Microphthalmia with Linear Skin Defects Syndrome.

Microphthalmia with linear skin defects (MLS) syndrome is an X-linked male-lethal disorder also known as MIDAS (microphthalmia, dermal aplasia, and sclerocornea). Additional clinical features include neurological and cardiac abnormalities. MLS syndrome is genetically heterogeneous given that heterozygous mutations in HCCS or COX7B have been identified in MLS-affected females. Both genes encode proteins involved in the structure and function of complexes III and IV, which form the terminal segment of the mitochondrial respiratory chain (MRC). However, not all individuals with MLS syndrome carry a mutation in either HCCS or COX7B. The majority of MLS-affected females have severe skewing of X chromosome inactivation, suggesting that mutations in HCCS, COX7B, and other as-yet-unidentified X-linked gene(s) cause selective loss of cells in which the mutated X chromosome is active. By applying whole-exome sequencing and filtering for X-chromosomal variants, we identified a de novo nonsense mutation in NDUFB11 (Xp11.23) in one female individual and a heterozygous 1-bp deletion in a second individual, her asymptomatic mother, and an affected aborted fetus of the subject's mother. NDUFB11 encodes one of 30 poorly characterized supernumerary subunits of NADH:ubiquinone oxidoreductase, known as complex I (cI), the first and largest enzyme of the MRC. By shRNA-mediated NDUFB11 knockdown in HeLa cells, we demonstrate that NDUFB11 is essential for cI assembly and activity as well as cell growth and survival. These results demonstrate that X-linked genetic defects leading to the complete inactivation of complex I, III, or IV underlie MLS syndrome. Our data reveal an unexpected role of cI dysfunction in a developmental phenotype, further underscoring the existence of a group of mitochondrial diseases associated with neurocutaneous manifestations.

Integrability of a linear center perturbed by a fourth degree homogeneous polynomial

In this work we study the integrability of a two-dimensional autonomous system in the plane with linear part of center type and non-linear part given by homogeneous polynomials of fourth degree. We give sufficient conditions for integrability in polar coordinates. Finally we establish a conjecture about the independence of the two classes of parameters which appear in the system; if this conjecture is true the integrable cases found will be the only possible ones.

Integrability of a linear center perturbed by a fifth degree homogeneous polynomial

In this work we study the integrability of two-dimensional autonomous system in the plane with linear part of center type and non-linear part given by homogeneous polynomials of fifth degree. We give a simple characterisation for the integrable cases in polar coordinates. Finally we formulate a conjecture about the independence of the two classes of parameters which appear on the system; if this conjecture is true the integrable cases found will be the only possible ones.

Steady-state global optimization of metabolic non-linear dynamic models through recasting into power-law canonical models

Background: Design of newly engineered microbial strains for biotechnological purposes would greatly benefit from the development of realistic mathematical models for the processes to be optimized. Such models can then be analyzed and, with the development and application of appropriate optimization techniques, one could identify the modifications that need to be made to the organism in order to achieve the desired biotechnological goal. As appropriate models to perform such an analysis are necessarily non-linear and typically non-convex, finding their global optimum is a challenging task. Canonical modeling techniques, such as Generalized Mass Action (GMA) models based on the power-law formalism, offer a possible solution to this problem because they have a mathematical structure that enables the development of specific algorithms for global optimization. Results: Based on the GMA canonical representation, we have developed in previous works a highly efficient optimization algorithm and a set of related strategies for understanding the evolution of adaptive responses in cellular metabolism. Here, we explore the possibility of recasting kinetic non-linear models into an equivalent GMA model, so that global optimization on the recast GMA model can be performed. With this technique, optimization is greatly facilitated and the results are transposable to the original non-linear problem. This procedure is straightforward for a particular class of non-linear models known as Saturable and Cooperative (SC) models that extend the power-law formalism to deal with saturation and cooperativity. Conclusions: Our results show that recasting non-linear kinetic models into GMA models is indeed an appropriate strategy that helps overcoming some of the numerical difficulties that arise during the global optimization task.

Definition of linear color models in the RGB vector color space to detect red peaches in orchard images taken under natural illumination

This work proposes the detection of red peaches in orchard images based on the definition of different linear color models in the RGB vector color space. The classification and segmentation of the pixels of the image is then performed by comparing the color distance from each pixel to the different previously defined linear color models. The methodology proposed has been tested with images obtained in a real orchard under natural light. The peach variety in the orchard was the paraguayo (Prunus persica var. platycarpa) peach with red skin. The segmentation results showed that the area of the red peaches in the images was detected with an average error of 11.6%; 19.7% in the case of bright illumination; 8.2% in the case of low illumination; 8.6% for occlusion up to 33%; 12.2% in the case of occlusion between 34 and 66%; and 23% for occlusion above 66%. Finally, a methodology was proposed to estimate the diameter of the fruits based on an ellipsoidal fitting. A first diameter was obtained by using all the contour pixels and a second diameter was obtained by rejecting some pixels of the contour. This approach enables a rough estimate of the fruit occlusion percentage range by comparing the two diameter estimates.

Loanword Phonology, Lexical Exceptions, Morphologically Driven Underapplication, and the Nature of Positionally Biased Constraints

In this paper we provide a formal account for underapplication of vowel reduction to schwa in Majorcan Catalan loanwords and learned words. On the basis of the comparison of these data with those concerning productive derivation and verbal inflection, which show analogous patterns, in this paper we also explore the existing and not yet acknowledged correlation between those processes that exhibit a particular behaviour in the loanword phonology with respect to the native phonology of the language, those processes that show lexical exceptions and those processes that underapply due to morphological reasons. In light of the analysis of the very same data and taking into account the aforementioned correlation, we show how there might exist a natural diachronic relation between two kinds of Optimality Theory constraints which are commonly used but, in principle, mutually exclusive: positional faithfulness and contextual markedness constraints. Overall, phonological productivity is proven to be crucial in three respects: first, as a context of the grammar, given that «underapplication» is systematically found in what we call the productive phonology of the dialect (including loanwords, learned words, productive derivation and verbal inflection); second, as a trigger or blocker of processes, in that the productivity or the lack of productivity of a specific process or constraint in the language is what explains whether it is challenged or not in any of the depicted situations, and, third, as a guiding principle which can explain the transition from the historical to the synchronic phonology of a linguistic variety.

Counter-propagating dual-trap optical tweezers based on linear momentum conservation

We present a dual-trap optical tweezers setup which directly measures forces using linear momentum conservation. The setup uses a counter-propagating geometry, which allows momentum measurement on each beam separately. The experimental advantages of this setup include low drift due to all-optical manipulation, and a robust calibration (independent of the features of the trapped object or buffer medium) due to the force measurement method. Although this design does not attain the high-resolution of some co-propagating setups, we show that it can be used to perform different single molecule measurements: fluctuation-based molecular stiffness characterization at different forces and hopping experiments on molecular hairpins. Remarkably, in our setup it is possible to manipulate very short tethers (such as molecular hairpins with short handles) down to the limit where beads are almost in contact. The setup is used to illustrate a novel method for measuring the stiffness of optical traps and tethers on the basis of equilibrium force fluctuations, i.e., without the need of measuring the force vs molecular extension curve. This method is of general interest for dual trap optical tweezers setups and can be extended to setups which do not directly measure forces.

Anticipating linear stochastic differential equations driven by a Lévy process

In this paper we study the existence of a unique solution for linear stochastic differential equations driven by a Lévy process, where the initial condition and the coefficients are random and not necessarily adapted to the underlying filtration. Towards this end, we extend the method based on Girsanov transformations on Wiener space and developped by Buckdahn [7] to the canonical Lévy space, which is introduced in [25].

Hierarchical linear models in Psychiatry: A bibliometric study

Development of research methods requires a systematic review of their status. This study focuses on the use of Hierarchical Linear Modeling methods in psychiatric research. Evaluation includes 207 documents published until 2007, included and indexed in the ISI Web of Knowledge databases; analyses focuses on the 194 articles in the sample. Bibliometric methods are used to describe the publications patterns. Results indicate a growing interest in applying the models and an establishment of methods after 2000. Both Lotka"s and Bradford"s distributions are adjusted to the data.

Source separation techniques applied to linear prediction

The prediction filters are well known models for signal estimation, in communications, control and many others areas. The classical method for deriving linear prediction coding (LPC) filters is often based on the minimization of a mean square error (MSE). Consequently, second order statistics are only required, but the estimation is only optimal if the residue is independent and identically distributed (iid) Gaussian. In this paper, we derive the ML estimate of the prediction filter. Relationships with robust estimation of auto-regressive (AR) processes, with blind deconvolution and with source separation based on mutual information minimization are then detailed. The algorithm, based on the minimization of a high-order statistics criterion, uses on-line estimation of the residue statistics. Experimental results emphasize on the interest of this approach.