Surface registration from range image fusion

The registration of full 3-D models is an important task in computer vision. Range finders only reconstruct a partial view of the object. Many authors have proposed several techniques to register 3D surfaces from multiple views in which there are basically two aspects to consider. First, poor registration in which some sort of correspondences are established. Second, accurate registration in order to obtain a better solution. A survey of the most common techniques is presented and includes experimental results of some of them

A review of sensor fusion techniques for underwater vehicle navigation

This work provides a general description of the multi sensor data fusion concept, along with a new classification of currently used sensor fusion techniques for unmanned underwater vehicles (UUV). Unlike previous proposals that focus the classification on the sensors involved in the fusion, we propose a synthetic approach that is focused on the techniques involved in the fusion and their applications in UUV navigation. We believe that our approach is better oriented towards the development of sensor fusion systems, since a sensor fusion architecture should be first of all focused on its goals and then on the fused sensors

Fusion of the human gene for the polyubiquitination co-effector UEV-1 with Kua, a newly identified gene

UEV proteins are enzymatically inactive variants of the E2 ubiquitin-conjugating enzymes that regulate noncanonical elongation of ubiquitin chains. In Saccharomyces cerevisiae, UEV is part of the RAD6-mediated error-free DNA repair pathway. In mammalian cells, UEV proteins can modulate c-FOS transcription and the G2-M transition of the cell cycle. Here we show that the UEV genes from phylogenetically distant organisms present a remarkable conservation in their exon–intron structure. We also show that the human UEV1 gene is fused with the previously unknown gene Kua. In Caenorhabditis elegans and Drosophila melanogaster, Kua and UEV are in separated loci, and are expressed as independent transcripts and proteins. In humans, Kua and UEV1 are adjacent genes, expressed either as separate transcripts encoding independent Kua and UEV1 proteins, or as a hybrid Kua–UEV transcript, encoding a two-domain protein. Kua proteins represent a novel class of conserved proteins with juxtamembrane histidine-rich motifs. Experiments with epitope-tagged proteins show that UEV1A is a nuclear protein, whereas both Kua and Kua–UEV localize to cytoplasmic structures, indicating that the Kua domain determines the cytoplasmic localization of Kua–UEV. Therefore, the addition of a Kua domain to UEV in the fused Kua–UEV protein confers new biological properties to this regulator of variant polyubiquitination.[Kua cDNAs isolated by RT-PCR and described in this paper have been deposited in the GenBank data library under accession nos. AF1155120 (H. sapiens) and AF152361 (D. melanogaster). Genomic clones containing UEV genes: S. cerevisiae, YGL087c (accession no. Z72609); S. pombe, c338 (accession no. AL023781); P. falciparum, MAL3P2 (accession no. AL034558); A. thaliana, F26F24 (accession no. AC005292); C. elegans, F39B2 (accession no. Z92834); D. melanogaster, AC014908; and H. sapiens, 1185N5 (accession no. AL034423). Accession numbers for Kua cDNAs in GenBank dbEST: M. musculus, AA7853; T. cruzi, AI612534. Other Kua-containing sequences: A. thaliana genomic clones F10M23 (accession no. AL035440), F19K23 (accession no. AC000375), and T20K9 (accession no. AC004786).

Fusion of data sets in multivariate linear regression with errors-in-variables

We consider the application of normal theory methods to the estimation and testing of a general type of multivariate regressionmodels with errors--in--variables, in the case where various data setsare merged into a single analysis and the observable variables deviatepossibly from normality. The various samples to be merged can differ on the set of observable variables available. We show that there is a convenient way to parameterize the model so that, despite the possiblenon--normality of the data, normal--theory methods yield correct inferencesfor the parameters of interest and for the goodness--of--fit test. Thetheory described encompasses both the functional and structural modelcases, and can be implemented using standard software for structuralequations models, such as LISREL, EQS, LISCOMP, among others. An illustration with Monte Carlo data is presented.

Multiresolution-based image fusion with additive wavelet decomposition

The standard data fusion methods may not be satisfactory to merge a high-resolution panchromatic image and a low-resolution multispectral image because they can distort the spectral characteristics of the multispectral data. The authors developed a technique, based on multiresolution wavelet decomposition, for the merging and data fusion of such images. The method presented consists of adding the wavelet coefficients of the high-resolution image to the multispectral (low-resolution) data. They have studied several possibilities concluding that the method which produces the best results consists in adding the high order coefficients of the wavelet transform of the panchromatic image to the intensity component (defined as L=(R+G+B)/3) of the multispectral image. The method is, thus, an improvement on standard intensity-hue-saturation (IHS or LHS) mergers. They used the ¿a trous¿ algorithm which allows the use of a dyadic wavelet to merge nondyadic data in a simple and efficient scheme. They used the method to merge SPOT and LANDSATTM images. The technique presented is clearly better than the IHS and LHS mergers in preserving both spectral and spatial information.

Introduction of sensor spectral response into image fusion methods. Application to wavelet-based methods

Usual image fusion methods inject features from a high spatial resolution panchromatic sensor into every low spatial resolution multispectral band trying to preserve spectral signatures and improve spatial resolution to that of the panchromatic sensor. The objective is to obtain the image that would be observed by a sensor with the same spectral response (i.e., spectral sensitivity and quantum efficiency) as the multispectral sensors and the spatial resolution of the panchromatic sensor. But in these methods, features from electromagnetic spectrum regions not covered by multispectral sensors are injected into them, and physical spectral responses of the sensors are not considered during this process. This produces some undesirable effects, such as resolution overinjection images and slightly modified spectral signatures in some features. The authors present a technique which takes into account the physical electromagnetic spectrum responses of sensors during the fusion process, which produces images closer to the image obtained by the ideal sensor than those obtained by usual wavelet-based image fusion methods. This technique is used to define a new wavelet-based image fusion method.

Clathrin Assembly Lymphoid Myeloid Leukemia (CALM) Protein: Localization in Endocytic-coated Pits, Interactions with Clathrin, and the Impact of Overexpression on Clathrin-mediated Traffic

The clathrin assembly lymphoid myeloid leukemia (CALM) gene encodes a putative homologue of the clathrin assembly synaptic protein AP180. Hence the biochemical properties, the subcellular localization, and the role in endocytosis of a CALM protein were studied. In vitro binding and coimmunoprecipitation demonstrated that the clathrin heavy chain is the major binding partner of CALM. The bulk of cellular CALM was associated with the membrane fractions of the cell and localized to clathrin-coated areas of the plasma membrane. In the membrane fraction, CALM was present at near stoichiometric amounts relative to clathrin. To perform structure-function analysis of CALM, we engineered chimeric fusion proteins of CALM and its fragments with the green fluorescent protein (GFP). GFP-CALM was targeted to the plasma membrane-coated pits and also found colocalized with clathrin in the Golgi area. High levels of expression of GFP-CALM or its fragments with clathrin-binding activity inhibited the endocytosis of transferrin and epidermal growth factor receptors and altered the steady-state distribution of the mannose-6-phosphate receptor in the cell. In addition, GFP-CALM overexpression caused the loss of clathrin accumulation in the trans-Golgi network area, whereas the localization of the clathrin adaptor protein complex 1 in the trans-Golgi network remained unaffected. The ability of the GFP-tagged fragments of CALM to affect clathrin-mediated processes correlated with the targeting of the fragments to clathrin-coated areas and their clathrin-binding capacities. Clathrin-CALM interaction seems to be regulated by multiple contact interfaces. The C-terminal part of CALM binds clathrin heavy chain, although the full-length protein exhibited maximal ability for interaction. Altogether, the data suggest that CALM is an important component of coated pit internalization machinery, possibly involved in the regulation of clathrin recruitment to the membrane and/or the formation of the coated pit.

Does the sun shine by p p or CNO fusion reactions?

We show that solar neutrino experiments set an upper limit of 7.8% (7.3% including the recent KamLAND measurements) to the fraction of energy that the Sun produces via the CNO fusion cycle, which is an order of magnitude improvement upon the previous limit. New experiments are required to detect CNO neutrinos corresponding to the 1.5% of the solar luminosity that the standard solar model predicts is generated by the CNO cycle.

Comment on: Deuterium nuclear fusion at room temperature: A pertinent inequality on barrier penetration

In a recent letter, Rosen claims to justify ...

Mobile robot experimental modeling and control strategies using sensor fusion

This research work deals with the problem of modeling and design of low level speed controller for the mobile robot PRIM. The main objective is to develop an effective educational, and research tool. On one hand, the interests in using the open mobile platform PRIM consist in integrating several highly related subjects to the automatic control theory in an educational context, by embracing the subjects of communications, signal processing, sensor fusion and hardware design, amongst others. On the other hand, the idea is to implement useful navigation strategies such that the robot can be served as a mobile multimedia information point. It is in this context, when navigation strategies are oriented to goal achievement, that a local model predictive control is attained. Hence, such studies are presented as a very interesting control strategy in order to develop the future capabilities of the system. In this context the research developed includes the visual information as a meaningful source that allows detecting the obstacle position coordinates as well as planning the free obstacle trajectory that should be reached by the robot

Maximum likelihood Linear Programming Data Fusion for Speaker Recognition

Biometric system performance can be improved by means of data fusion. Several kinds of information can be fused in order to obtain a more accurate classification (identification or verification) of an input sample. In this paper we present a method for computing the weights in a weighted sum fusion for score combinations, by means of a likelihood model. The maximum likelihood estimation is set as a linear programming problem. The scores are derived from a GMM classifier working on a different feature extractor. Our experimental results assesed the robustness of the system in front a changes on time (different sessions) and robustness in front a change of microphone. The improvements obtained were significantly better (error bars of two standard deviations) than a uniform weighted sum or a uniform weighted product or the best single classifier. The proposed method scales computationaly with the number of scores to be fussioned as the simplex method for linear programming.

Mitochondrial fusion is increased by the nuclear coactivator PGC-1beta

Background There is no evidence to date on whether transcriptional regulators are able to shift the balance between mitochondrial fusion and fission events through selective control of gene expression. Methodology/Principal Findings Here, we demonstrate that reduced mitochondrial size observed in knock-out mice for the transcriptional regulator PGC-1β is associated with a selective reduction in Mitofusin 2 (Mfn2) expression, a mitochondrial fusion protein. This decrease in Mfn2 is specific since expression of the remaining components of mitochondrial fusion and fission machinery were not affected. Furthermore, PGC-1β increases mitochondrial fusion and elongates mitochondrial tubules. This PGC-1β-induced elongation specifically requires Mfn2 as this process is absent in Mfn2-ablated cells. Finally, we show that PGC-1β increases Mfn2 promoter activity and transcription by coactivating the nuclear receptor Estrogen Related Receptor α (ERRα). Conclusions/Significance Taken together, our data reveal a novel mechanism by which mammalian cells control mitochondrial fusion. In addition, we describe a novel role of PGC-1β in mitochondrial physiology, namely the control of mitochondrial fusion mainly through Mfn2.

Fusion of the extended modified liquid drop model for nucleation and dynamical nucleation theory

We present a new phenomenological approach to nucleation, based on the combination of the extended modified liquid drop model and dynamical nucleation theory. The new model proposes a new cluster definition, which properly includes the effect of fluctuations, and it is consistent both thermodynamically and kinetically. The model is able to predict successfully the free energy of formation of the critical nucleus, using only macroscopic thermodynamic properties. It also accounts for the spinodal and provides excellent agreement with the result of recent simulations.