An Analysis of Errors in Graph-Based Keypoint Matching and Proposed Solutions

International audienceAn error occurs in graph-based keypoint matching when key-points in two different images are matched by an algorithm but do not correspond to the same physical point. Most previous methods acquire keypoints in a black-box manner, and focus on developing better algorithms to match the provided points. However to study the complete performance of a matching system one has to study errors through the whole matching pipeline, from keypoint detection, candidate selection to graph optimisation. We show that in the full pipeline there are six different types of errors that cause mismatches. We then present a matching framework designed to reduce these errors. We achieve this by adapting keypoint detectors to better suit the needs of graph-based matching, and achieve better graph constraints by exploiting more information from their keypoints. Our framework is applicable in general images and can handle clutter and motion discontinuities. We also propose a method to identify many mismatches a posteriori based on Left-Right Consistency inspired by stereo matching due to the asymmetric way we detect keypoints and define the graph

Identification and functional characterisation of CRK12:CYC9, a novel cyclin-dependent kinase (CDK)-cyclin complex in Trypanosoma brucei

The protozoan parasite, Trypanosoma brucei, is spread by the tsetse fly and causes trypanosomiasis in humans and animals. Both the life cycle and cell cycle of the parasite are complex. Trypanosomes have eleven cdc2-related kinases (CRKs) and ten cyclins, an unusually large number for a single celled organism. To date, relatively little is known about the function of many of the CRKs and cyclins, and only CRK3 has previously been shown to be cyclin-dependent in vivo. Here we report the identification of a previously uncharacterised CRK:cyclin complex between CRK12 and the putative transcriptional cyclin, CYC9. CRK12:CYC9 interact to form an active protein kinase complex in procyclic and bloodstream T. brucei. Both CRK12 and CYC9 are essential for the proliferation of bloodstream trypanosomes in vitro, and we show that CRK12 is also essential for survival of T. brucei in a mouse model, providing genetic validation of CRK12:CYC9 as a novel drug target for trypanosomiasis. Further, functional characterisation of CRK12 and CYC9 using RNA interference reveals roles for these proteins in endocytosis and cytokinesis, respectively

Phthalocyanine-nanocarbon ensembles: From discrete molecular and supramolecular systems to hybrid nanomaterials

This document is the Accepted Manuscript version of a Published Work that appeared in final form in Accounts of Chemical Research, copyright © American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see http://dx.doi.org/10.1021/ar5004384Conspectus Phthalocyanines (Pcs) are macrocyclic and aromatic compounds that present unique electronic features such as high molar absorption coefficients, rich redox chemistry, and photoinduced energy/electron transfer abilities that can be modulated as a function of the electronic character of their counterparts in donor-acceptor (D-A) ensembles. In this context, carbon nanostructures such as fullerenes, carbon nanotubes (CNTs), and, more recently, graphene are among the most suitable Pc companions. Pc-C60 ensembles have been for a long time the main actors in this field, due to the commercial availability of C60 and the ell-established synthetic methods for its functionalization. As a result, many Pc-C60 architectures have been prepared, featuring different connectivities (covalent or supramolecular), intermolecular interactions (self-organized or molecularly dispersed species), and Pc HOMO/LUMO levels. All these elements provide a versatile toolbox for tuning the photophysical properties in terms of the type of process (photoinduced energy/electron transfer), the nature of the interactions beteen the electroactive units (through bond or space), and the kinetics of the formation/decay of the photogenerated species. Some recent trends in this field include the preparation of stimuli-responsive multicomponent systems ith tunable photophysical properties and highly ordered nanoarchitectures and surface-supported systems shoing high charge mobilities. A breakthrough in the Pc-nanocarbon field as the appearance of CNTs and graphene, hich opened a ne avenue for the preparation of intriguing photoresponsive hybrid ensembles shoing light-stimulated charge separation. The scarce solubility of these 1-D and 2-D nanocarbons, together ith their loer reactivity ith respect to C60 stemming from their less strained sp2 carbon netorks, has not meant an unsurmountable limitation for the preparation of variety of Pc-based hybrids. These systems, hich sho improved solubility and dispersibility features, bring together the unique electronic transport properties of CNTs and graphene ith the excellent light-harvesting and tunable redox properties of Pcs. A singular and distinctive feature of these Pc-CNT/graphene (single- or fe-layers) hybrid materials is the control of the direction of the photoinduced charge transfer as a result of the band-like electronic structure of these carbon nanoforms and the adjustable electronic levels of Pcs. Moreover, these conjugates present intensified light-harvesting capabilities resulting from the grafting of several chromophores on the same nanocarbon platform.In this Account, recent progress in the construction of covalent and supramolecular Pc-nanocarbon ensembles is summarized, ith a particular emphasis on their photoinduced behavior. e believe that the high degree of control achieved in the preparation of Pc-carbon nanostructures, together ith the increasing knoledge of the factors governing their photophysics, ill allo for the design of next-generation light-fueled electroactive systems. Possible implementation of these Pc-nanocarbons in high performance devices is envisioned, finally turning into reality much of the expectations generated by these materialsFinancial support from the Spanish MICINN (CTQ2011-24187/BQU), the Comunidad de Madrid (S2013/MIT-2841 FOTOCARBON) and the EU (“SO2S” FP7-PEOPLE-2012-ITN, no.: 316975) is acknowledge

Two Novel Methods For The Determination Of The Number Of Components In Independent Components Analysis Models

Independent Components Analysis is a Blind Source Separation method that aims to find the pure source signals mixed together in unknown proportions in the observed signals under study. It does this by searching for factors which are mutually statistically independent. It can thus be classified among the latent-variable based methods. Like other methods based on latent variables, a careful investigation has to be carried out to find out which factors are significant and which are not. Therefore, it is important to dispose of a validation procedure to decide on the optimal number of independent components to include in the final model. This can be made complicated by the fact that two consecutive models may differ in the order and signs of similarly-indexed ICs. As well, the structure of the extracted sources can change as a function of the number of factors calculated. Two methods for determining the optimal number of ICs are proposed in this article and applied to simulated and real datasets to demonstrate their performance

Principles of genetic circuit design

Cells navigate environments, communicate and build complex patterns by initiating gene expression in response to specific signals. Engineers seek to harness this capability to program cells to perform tasks or create chemicals and materials that match the complexity seen in nature. This Review describes new tools that aid the construction of genetic circuits. Circuit dynamics can be influenced by the choice of regulators and changed with expression 'tuning knobs'. We collate the failure modes encountered when assembling circuits, quantify their impact on performance and review mitigation efforts. Finally, we discuss the constraints that arise from circuits having to operate within a living cell. Collectively, better tools, well-characterized parts and a comprehensive understanding of how to compose circuits are leading to a breakthrough in the ability to program living cells for advanced applications, from living therapeutics to the atomic manufacturing of functional materials.National Institute of General Medical Sciences (U.S.) (Grant P50 GM098792)National Institute of General Medical Sciences (U.S.) (Grant R01 GM095765)National Science Foundation (U.S.). Synthetic Biology Engineering Research Center (EEC0540879)Life Technologies, Inc. (A114510)National Science Foundation (U.S.). Graduate Research FellowshipUnited States. Office of Naval Research. Multidisciplinary University Research Initiative (Grant 4500000552

RelocNet: Continous metric learning relocalisation using neural nets

We propose a method of learning suitable convolutional representations for camera pose retrieval based on nearest neighbour matching and continuous metric learning-based feature descriptors. We introduce information from camera frusta overlaps between pairs of images to optimise our feature embedding network. Thus, the final camera pose descriptor differences represent camera pose changes. In addition, we build a pose regressor that is trained with a geometric loss to infer finer relative poses between a query and nearest neighbour images. Experiments show that our method is able to generalise in a meaningful way, and outperforms related methods across several experiments

Multifrequency radar observations of marine clouds during the EPCAPE campaign

The Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) was a year-round campaign conducted by the US Department of Energy at the Scripps Institution of Oceanography in La Jolla, CA, USA, with a focus on characterizing atmospheric processes at a coastal location. The ground-based prototype of a new Ka-, W-, and G-band (35.75, 94.88, and 238.8 GHz) profiling atmospheric radar, named CloudCube, which was developed at the Jet Propulsion Laboratory, took part in the experiment during 6 weeks in March and April 2023. This article describes the unique data sets that were obtained during the field campaign from a variety of marine clouds and light precipitation. These are, to the best of the authors' knowledge, the first observations of atmospheric clouds using simultaneous multifrequency measurements including 238.8 GHz. These data sets therefore provide an exceptional opportunity to study and analyze hydrometeors with diameters in the millimeter- and submillimeter size range that can be used to better understand cloud and precipitation structure, formation, and evolution. The data sets referenced in this article are intended to provide a complete, extensive, and high-quality collection of G-band data in the form of Doppler spectra and Doppler moments. In addition, Ka-band and W-band reflectivity and Ka-, W-, and G-band reflectivity ratio profiles are included for several cases of interest on 6 different days. The data sets can be found at https://doi.org/10.5281/zenodo.10076227 (Socuellamos et al., 2024).</p

Multiple structure alignment and consensus identification for proteins

<p>Abstract</p> <p>Background</p> <p>An algorithm is presented to compute a multiple structure alignment for a set of proteins and to generate a consensus (pseudo) protein which captures common substructures present in the given proteins. The algorithm represents each protein as a sequence of triples of coordinates of the alpha-carbon atoms along the backbone. It then computes iteratively a sequence of transformation matrices (i.e., translations and rotations) to align the proteins in space and generate the consensus. The algorithm is a heuristic in that it computes an approximation to the optimal alignment that minimizes the sum of the pairwise distances between the consensus and the transformed proteins.</p> <p>Results</p> <p>Experimental results show that the algorithm converges quite rapidly and generates consensus structures that are visually similar to the input proteins. A comparison with other coordinate-based alignment algorithms (MAMMOTH and MATT) shows that the proposed algorithm is competitive in terms of speed and the sizes of the conserved regions discovered in an extensive benchmark dataset derived from the HOMSTRAD and SABmark databases.</p> <p>The algorithm has been implemented in C++ and can be downloaded from the project's web page. Alternatively, the algorithm can be used via a web server which makes it possible to align protein structures by uploading files from local disk or by downloading protein data from the RCSB Protein Data Bank.</p> <p>Conclusions</p> <p>An algorithm is presented to compute a multiple structure alignment for a set of proteins, together with their consensus structure. Experimental results show its effectiveness in terms of the quality of the alignment and computational cost.</p