Half-life Limit of 19Mg

A search for 19Mg was performed using projectile fragmentation of a 150 MeV/nucleon 36Ar beam. No events of 19Mg were observed. From the time-of-flight through the fragment separator an upper limit of 22 ns for the half-life of 19Mg was established

Structure and primase-mediated activation of a bacterial dodecameric replicative helicase

International audienceReplicative helicases are essential ATPases that unwind DNA to initiate chromosomal replication. While bacterial replicative DnaB helicases are hexameric, Helicobacter pylori DnaB (HpDnaB) was found to form double hexamers, similar to some archaeal and eukaryotic replicative helicases. Here we present a structural and functional analysis of HpDnaB protein during primosome formation. The crystal structure of the HpDnaB at 6.7 ˚ A resolution reveals a dode-cameric organization consisting of two hexamers assembled via their N-terminal rings in a stack-twisted mode. Using fluorescence anisotropy we show that HpDnaB dodecamer interacts with single-stranded DNA in the presence of ATP but has a low DNA unwinding activity. Multi-angle light scattering and small angle X-ray scattering demonstrate that interaction with the DnaG primase helicase-binding domain dissociates the helicase dodecamer into single ringed primosomes. Functional assays on the proteins and associated complexes indicate that these single ringed primosomes are the most active form of the helicase for ATP hydrolysis, DNA binding and unwinding. These findings shed light onto an activation mechanism of HpDnaB by the primase that might be relevant in other bacteria and possibly other organisms exploiting dodecameric helicases for DNA replication

One-neutron knockout from 57^{57}Ni

The single-particle structure of $^{57}$Ni and level structure of $^{56}$Ni were investigated with the \mbox{$^{9}$Be ($^{57}$Ni,$^{56}$Ni+$\gamma$)$\it{X}$} reaction at 73 MeV/nucleon. An inclusive cross section of 41.4(12) mb was obtained for the reaction, compared to a theoretical prediction of 85.4 mb, hence only 48(2)% of the theoretical cross section is exhausted. This reduction in the observed spectroscopic strength is consistent with that found for lighter well-bound nuclei. One-neutron removal spectroscopic factors of 0.58(11) to the ground state and 3.7(2) to all excited states of $^{56}$Ni were deduced.Comment: Phys. Rev. C, accepte

Reconstruction of 3D surfaces from incomplete digitisations using statistical shape models for manufacturing processes

[EN] Digitization of large parts with tight geometric tolerances is a time-consuming process that requires a detailed scan of the outer surface and the acquisition and processing of massive data. In this work, we propose a methodology for fast digitization using a partial scan in which large regions remain unmeasured. Our approach capitalizes on a database of fully scanned parts from which we extract a low-dimensional description of the shape variability using Statistical Shape Analysis. This lowdimensional description allows an accurate representation of any sample in the database with few independent parameters. Therefore, we propose a reconstruction algorithm that takes as input an incomplete measurement (faster than a complete digitization), identifies the statistical shape parameters and outputs a full scan reconstruction. We showcase an application to the digitization of large aeronautical fuselage panels. A statistical shape model is constructed from a database of 793 shapes that were completely digitized, with a point cloud of about 16 million points for each shape. Tests carried out at the manufacturing facility showed an overall reduction in the digitization time by 80% (using a partial digitization of 3 million points per shape) while keeping a high accuracy (reconstruction precision of 0.1mm) on the reconstructed surface.The authors want to thank Stelia Aerospace for providing the data and their helpful support through the project, and also the financial support of the regional research consortium RFI Atlanstic2020 in Pays de la Loire, France.Navarro-Jiménez, J.; Aguado, JV.; Bazin, G.; Albero Gabarda, V.; Borzacchiello, D. (2023). Reconstruction of 3D surfaces from incomplete digitisations using statistical shape models for manufacturing processes. Journal of Intelligent Manufacturing. 34(5):2345-2358. https://doi.org/10.1007/s10845-022-01918-z23452358345Ballester, A., Piérola, A., Parrilla, E., Izquierdo, M., Uriel, J., Nácher, B., Ortiz, V., Gonzalez, J. C., Page, A., & Alemany, S. (2017). Fast, portable and low-cost 3d foot digitizers: Validity and reliability of measurements. Proceedings of 3DBODY. TECH (pp. 11–12).Barrault, M., Yvon, M., Nguyen, N. C., & Patera, A. T. (2004). An ‘empirical interpolation’ method: Application to efficient reduced-basis discretization of partial differential equations. Comptes Rendus Mathematique, 339(9), 667–672.Belongie, S., Malik, J., & Puzicha, J. (2002). Shape matching and object recognition using shape contexts. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(4), 509–522.Berger, M., Andrea, T., Lee, S., Pierre, A., Joshua, L., Andrei, S., & Claudio, S. (2014). State of the art in surface reconstruction from point clouds. In Eurographics 2014—State of the art reports (Vol. 1, pp. 161–185).Bernard, F., Salamanca, L., Thunberg, J., Tack, A., Jentsch, D., Lamecker, H., et al. (2017). Shape-aware surface reconstruction from sparse 3d point-clouds. Medical Image Analysis, 38, 77–89.Bookstein, F. L. (1997). Morphometric tools for landmark data: Geometry and biology. Cambridge University Press.Chatterjee, A. (2000). An introduction to the proper orthogonal decomposition. Current Science, 78(7), 808–817.Chaturantabut, S., & Sorensen, D. C. (2010). Nonlinear model reduction via discrete empirical interpolation. SIAM Journal on Scientific Computing, 32(5), 2737–2764.Cohen, Y., Faccio, M., Pilati, F., & Yao, X. (2019). Design and management of digital manufacturing and assembly systems in the industry 4.0 era. The International Journal of Advanced Manufacturing Technology, 105(9), 3565–3577.Cootes, T. F., Taylor, C. J., Cooper, D. H., & Graham, J. (1992). Training models of shape from sets of examples. In D. Hogg, & R. Boyle (Eds.), BMVC92 (pp. 9–18). Springer London.D’Apuzzo, N. (2006). Overview of 3d surface digitization technologies in Europe. In Three-dimensional image capture and applications VII (Vol. 6056, pp. 605605). International Society for Optics and Photonics.Davies, R. H. (2002). Learning shape: Optimal models for analysing natural variability. University of Manchester Manchester.Drouot, A., Zhao, R., Irving, L., Sanderson, D., & Ratchev, S. (2018). Measurement assisted assembly for high accuracy aerospace manufacturing. 16th IFAC symposium on information control problems in manufacturing INCOM 2018. IFAC-PapersOnLine (Vol. 51, No. 11, pp. 393–398).Duchon, J. (1977). Splines minimizing rotation-invariant semi-norms in Sobolev spaces. In W. Schempp, & K. Zeller (Eds.), Constructive theory of functions of several variables (pp. 85–100). Springer.Feng, J.C.-X., & Wang, X. (2002). Digitizing uncertainty modeling for reverse engineering applications: Regression versus neural networks. Journal of Intelligent Manufacturing, 13(3), 189–199.Gao, J., Gindy, N., & Chen, X. (2006). An automated GD&T inspection system based on non-contact 3d digitization. International Journal of Production Research, 44(1), 117–134.Guo, G., Jiang, T. T., Wang, Y. Z., & Gao, W. (2013). 2-D shape completion with shape priors. Chinese Science Bulletin, 58(27), 3430–3436.Hao, R., Lu, B., Cheng, Y., Li, X., & Huang, B. (2021). A steel surface defect inspection approach towards smart industrial monitoring. Journal of Intelligent Manufacturing, 32(7), 1833–1843.Heimann, T., & Meinzer, H.-P. (2009). Statistical shape models for 3d medical image segmentation: A review. Medical Image Analysis, 13(4), 543–563.Jolliffe, I. T. (2002). Principal components in regression analysis. Principal Component Analysis, 167–198.Jolliffe, I. T., & Cadima, J. (2016). Principal component analysis: A review and recent developments. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 374(2065), 20150202.Khalfaoui, S., Seulin, R., Fougerolle, Y., & Fofi, D. (2013). An efficient method for fully automatic 3d digitization of unknown objects. Computers in Industry, 64(9), 1152–1160 (Special Issue: 3D Imaging in Industry).Kurfess, T. R., Saldana, C., Saleeby, K., & Dezfouli, M. P. (2020). A review of modern communication technologies for digital manufacturing processes in industry 4 0. Journal of Manufacturing Science and Engineering, 142(11), 110815.Lauzeral, N., Borzacchiello, D., Kugler, M., George, D., Rémond, Y., Hostettler, A., & Chinesta, F. (2019). Shape parametrization of bio-mechanical finite element models based on medical images. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 7(5–6), 480–489.Lee J., et al. (2020). Industrial AI. Applications with Sustainable Performance.Marton, Z. C., Rusu, R. B., & Beetz, M. (2009). On fast surface reconstruction methods for large and noisy point clouds. In 2009 IEEE international conference on robotics and automation (pp. 3218–3223).Meinguet, J. (1979). Multivariate interpolation at arbitrary points made simple. Zeitschrift für angewandte Mathematik und Physik ZAMP, 30(2), 292–304.Mian, S. H., & Al-Ahmari, A. (2019). Comparative analysis of different digitization systems and selection of best alternative. Journal of Intelligent Manufacturing, 30(5), 2039–2067.Panczuk, R., Foissac, P.-Y. (2008). Method and device for machining panels, E.U. Patent EP1689558B1.Pauly, M., Mitra, N. J., Giesen, J., Gross, M. H., & Guibas, L. J. (2005). Example-based 3d scan completion. In Symposium on geometry processing, number CONF (pp. 23–32).Pimenov, D. Y., Andrés, B., & Tadeusz, M. (2018). 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The digitization of quality control operations with cloud platform computing technologies (pp. 305–334). Springer

An Efficient Approach to Obtaining Large Numbers of Distant Supernova Host Galaxy Redshifts

We use the wide-field capabilities of the 2dF fibre positioner and the AAOmega spectrograph on the Anglo-Australian Telescope (AAT) to obtain redshifts of galaxies that hosted supernovae during the first three years of the Supernova Legacy Survey (SNLS). With exposure times ranging from 10 to 60 ksec per galaxy, we were able to obtain redshifts for 400 host galaxies in two SNLS fields, thereby substantially increasing the total number of SNLS supernovae with host galaxy redshifts. The median redshift of the galaxies in our sample that hosted photometrically classified Type Ia supernovae (SNe Ia) is 0.77, which is 25% higher than the median redshift of spectroscopically confirmed SNe Ia in the three-year sample of the SNLS. Our results demonstrate that one can use wide-field fibre-fed multi-object spectrographs on 4m telescopes to efficiently obtain redshifts for large numbers of supernova host galaxies over the large areas of sky that will be covered by future high-redshift supernova surveys, such as the Dark Energy Survey.Comment: 22 pages, 4 figures, accepted for publication in PAS

Reading the Radical American Periodical

This special issue probes our definitions and understandings of both the ‘radical’ and the ‘American’ in North American print and periodical culture. As many of the subsequent papers demonstrate, notions of radicalism as expressed in American periodicals often necessitate(d) looking beyond the nation state. Similarly, this issue highlights the fluidity of ‘radicalism’ as a temporal and technological concept; relatable not only to literary content, but also to graphic design, editorial control, foreign language use, subscription policies, and other aspects of production, dissemination and reception. Thematically and conceptually diverse, the articles collated here provide a judicious intervention into the developing field of periodical studies

Temperature and Bias Voltage Dependence of the MPPC Detectors

to appear in the IEEE Transactions on Nuclear ScienceInternational audienceThis work reports on the characterization of the Multi-Pixel Photon Counter (MPPC) detectors as a function of the temperature and bias voltage. Devices of 1x1 mm2 and 3x3 mm2 total area and 50x50 µm2 µcell size produced by Hamamatsu Photonics have been studied. The temperature has been varied from -110°C to -50°C using a cryostat cooled by liquid nitrogen and from 0 to 38°C using a climatic chamber. Important electrical parameters of the MPPC detectors as gain, breakdown voltage, quenching resistance, capacitance and dark count rate have been measuredsubstrate (on the rear side) and by a metal layer (on the front side). Each µcell is represented by a p+/n junction working in Geiger-mode connected in series with its integrated passive quenching resistance. The detectors are operated with each µcell biased to a bias voltage Vbias above the breakdown voltage VBD. The Vbias exceeds the VBD by an amount called overvoltage ΔV = Vbias – VBD, which has a critical influence on detector performance

Predictive coding during action observation - A depth-resolved intersubject functional correlation study at 7T

While the brain regions involved in action observation are relatively well documented in humans and primates, how these regions communicate to help understand and predict actions remains poorly understood. Traditional views emphasized a feed-forward architecture in which visual features are organized into increasingly complex representations that feed onto motor programs in parietal and then premotor cortices where the matching of observed actions upon the observer's own motor programs contributes to action understanding. Predictive coding models place less emphasis on feed-forward connections and propose that feed-back connections from premotor regions back to parietal and visual neurons represent predictions about upcoming actions that can supersede visual inputs when actions become predictable, with visual input then merely representing prediction errors. Here we leverage the notion that feed-back connections target specific cortical layers to help adjudicate across these views. Specifically, we test whether observing sequences of hand actions in their natural order, which permits participants to predict upcoming actions, triggers more feed-back input to parietal regions than seeing the same actions in a scrambled sequence that hinders making predictions. Using submillimeter fMRI acquisition at 7T, we find that watching predictable sequences triggers more action-related activity (as measured using intersubject functional correlation) in the parietal cortical area PFt at depths receiving feed-back connections (layers III and V/VI) than watching the exact same actions in scrambled and hence unpredictable sequence. In addition, functional connectivity analysis performed using intersubject functional connectivity confirms that these increased action-related signals in PFt could originate from ventral premotor region BA44. This data showcases the utility of intersubject functional correlation in combination with 7T MRI to explore the architecture of social cognition under more naturalistic conditions, and provides evidence for models that emphasize the importance of feed-back connections in action prediction