Abstract The goal of the current study was to assess general maturational changes in the ERP in the same sample of infants from 4 to 12 months of age. All participants were tested in two experimental manipulations at each age: a test of facial recognition and one of object recognition. Two sets of analyses were undertaken. First, growth curve modeling with mixed models was used to examine trajectories of development and possible differences in trajectories based on recognition memory (novel versus familiar) and/or stimulus‐specific memory (face versus object recognition). Our results suggest that the Pb, Nc and Slow Wave components change significantly in terms of amplitude and latency over the first year of life. Pb amplitude showed a significant non‐linear increase over time, whereas Pb latency showed a significant linear decrease over time with a plateau beginning at 10 months. Nc amplitude showed a significant linear decrease over time (i.e. a stronger negative value), whereas Nc latency showed a significant linear decrease over time, with a plateau beginning at 8 months. Second, to relate our findings to those reported in the literature, we examined the effects of memory and stimulus and their combination. Differences between recognition memory and stimulus specific memory were found in the responses to familiar and novel faces and objects for all three components, although the pattern differed across the five ages. These results have implications for future studies that involve the recording of the visual ERP, and point to the advantages of growth curve modeling in examining longitudinal data to account for non‐linear development.
This is a beginner's guide for small retail store owners across South Carolina that are interested in creating a healthier shopping experience for their customers. Local health departments and government agencies, non-profit organizations, and community groups can also use this guide as a tool for supporting store owner efforts to provide healthier options. The goal of this guide is to help you: assess your current store environment; develop a Plan to adopt new, healthy strategies in your store with the results from your assessment; implement the strategies identified in your Action Plan using the tools and resources presented in this guide; evaluate your progress in achieving your goals and success in implementing your Action Plan.
AbstractEvidence suggests that autism is associated with impaired emotion perception, but it is unknown how early such impairments are evident. Furthermore, most studies that have assessed emotion perception in children with autism have required verbal responses, making results difficult to interpret. This study utilized high‐density event‐related potentials (ERPs) to investigate whether 3–4‐year‐old children with autism spectrum disorder (ASD) show differential brain activity to fear versus neutral facial expressions. It has been shown that normal infants as young as 7 months of age show differential brain responses to faces expressing different emotions. ERPs were recorded while children passively viewed photos of an unfamiliar woman posing a neutral and a prototypic fear expression. The sample consisted of 29 3–4‐year‐old children with ASD and 22 chronological age‐matched children with typical development. Typically developing children exhibited a larger early negative component (N300) to the fear than to the neutral face. In contrast, children with ASD did not show the difference in amplitude of this early ERP component to the fear versus neutral face. For a later component, typically developing children exhibited a larger negative slow wave (NSW) to the fear than to the neutral face, whereas children with autism did not show a differential NSW to the two stimuli. In children with ASD, faster speed of early processing (i.e. N300 latency) of the fear face was associated with better performance on tasks assessing social attention (social orienting, joint attention and attention to distress). These data suggest that children with ASD, as young as 3 years of age, show a disordered pattern of neural responses to emotional stimuli.
Objectives: This article introduces a youth-reported measure (Essential Youth Experiences [EYE]) developed to assess the experiences of foster youth in their home environment and their critical relationships across a number of service systems. Empirically, the article reports on the psychometric properties of a 9-item scale within the EYE that measures the construct of positive home integration (PHI). Methods: The EYE was administered to 328 preadolescent and adolescent youth (164 sibling dyads) enrolled in a larger randomized clinical trial. Results: Correlational analysis suggests that the PHI Scale shows good psychometric properties and strong current and predictive validity. Conclusion: The PHI is a reliable and valid scale that measures youth perspectives of inclusion in the foster home and relationships with their foster care provider. This scale quickly gathers youth perspectives and differentiates between youth who have more versus less significant needs. Implications for research and social work practice are discussed.
In: Child abuse & neglect: the international journal ; official journal of the International Society for the Prevention of Child Abuse and Neglect, Band 63, S. 19-29
On 2019 August 14, the Advanced LIGO and Virgo interferometers detected the high-significance gravitational wave (GW) signal S190814bv. The GW data indicated that the event resulted from a neutron star-black hole (NSBH) merger, or potentially a low-mass binary BH merger. Due to the low false-alarm rate and the precise localization (23 deg at 90%), S190814bv presented the community with the best opportunity yet to directly observe an optical/near-infrared counterpart to an NSBH merger. To search for potential counterparts, the GROWTH Collaboration performed real-time image subtraction on six nights of public Dark Energy Camera images acquired in the 3 weeks following the merger, covering >98% of the localization probability. Using a worldwide network of follow-up facilities, we systematically undertook spectroscopy and imaging of optical counterpart candidates. Combining these data with a photometric redshift catalog, we ruled out each candidate as the counterpart to S190814bv and placed deep, uniform limits on the optical emission associated with S190814bv. For the nearest consistent GW distance, radiative transfer simulations of NSBH mergers constrain the ejecta mass of S190814bv to be M < 0.04 M at polar viewing angles, or M < 0.03 M if the opacity is κ < 2 cmg. Assuming a tidal deformability for the NS at the high end of the range compatible with GW170817 results, our limits would constrain the BH spin component aligned with the orbital momentum to be χ < 0.7 for mass ratios Q < 6, with weaker constraints for more compact NSs. ; This work was supported by the GROWTH (Global Relay of Observatories Watching Transients Happen) project funded by the National Science Foundation under PIRE grant No. 1545949. GROWTH is a collaborative project among California Institute of Technology (USA), University of Maryland College Park (USA), University of Wisconsin Milwaukee (USA), Texas Tech University (USA), San Diego State University (USA), University of Washington (USA), Los Alamos National Laboratory (USA), Tokyo Institute of Technology (Japan), National Central University (Taiwan), Indian Institute of Astrophysics (India), Indian Institute of Technology Bombay (India), Weizmann Institute of Science (Israel), The Oskar Klein Centre at Stockholm University (Sweden), Humboldt University (Germany), Liverpool John Moores University (UK), and University of Sydney (Australia). D.A.G. acknowledges support from Hubble Fellowship grant HST-HF2-51408.001-A. Support for program No. HST-HF251408.001-A is provided by NASA through a grant from the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS5-26555. We gratefully acknowledge Amazon Web Services, Inc., for a generous grant (PS_IK_ FY2019_Q3_ Caltech_Gravitational_Wave) that funded our use of the Amazon Web Services cloud computing infrastructure to process the DECam data. P.E.N. acknowledges support from the DOE through DE-FOA-0001088, Analytical Modeling for Extreme-Scale Computing Environments. D.A.P. and D.A.G. performed the work associated with this project at the Aspen Center for Physics, which is supported by National Science Foundation grant PHY-1607611. This work was partially supported by a grant from the Simons Foundation. A.J.C.-T. thanks I. Agudo, J. Cepa, V. Dhillon, J. A. Font, A. MartinCarrillo, S. R. Oates, S. B. Pandey, E. Pian, R. Sanchez-Ramirez, A. M. Sintes, V. Sokolov, and B.-B. Zhang for fruitful conversations. F.F. gratefully acknowledges support from NASA through grant 80NSSC18K0565 and from the NSF through grant PHY1806278. M.B., A.G., E.K., S.D., and J.S. acknowledge support from the G.R.E.A.T research environment funded by the Swedish National Science Foundation. J.S. acknowledges support from the Knut and Alice Wallenberg Foundation. J.S.B. and K.Z. are partially supported by a Gordon and Betty Moore Foundation Data-Driven Discovery grant. D.A.H.B. acknowledges research support from the National Research Foundation of South Africa. M.W.C. is supported by the David and Ellen Lee Postdoctoral Fellowship at the California Institute of Technology. S.N. and G.R. are grateful for support from VIDI, Projectruimte, and TOP Grants of the Innovational Research Incentives Scheme (Vernieuwingsimpuls) financed by the Netherlands Organization for Scientific Research (NWO). H.K. and K.Z. thank the LSSTC Data Science Fellowship Program, which is funded by LSSTC, NSF Cybertraining grant No. 1829740, the Brinson Foundation, and the Moore Foundation; his participation in the program has benefited this work. D.D. is supported by an Australian Government Research Training Program Scholarship. P.G. is supported by NASA Earth and Space Science Fellowship (ASTRO18F-0085). D.L.K. was supported by NSF grant AST-1816492. Y.D.H. thanks the support by the program of China Scholarships Council (CSC) under grant No. 201406660015. A.K.H.K. acknowledges support from the Ministry of Science and Technology of the Republic of China (Taiwan) through grants 107-2628-M-007-003 and 1082628-M-007-005-RSP. V.Z.G. acknowledges support from the University of Washington College of Arts and Sciences, Department of Astronomy, and the DIRAC Institute. University of Washington's DIRAC Institute is supported through generous gifts from the Charles and Lisa Simonyi Fund for Arts and Sciences and the Washington Research Foundation. M.J. and A.C. acknowledge the support of the Washington Research Foundation Data Science Term Chair fund and the UW Provost's Initiative in Data-Intensive Discovery. S.M. thanks the LSSTC Data Science Fellowship Program, which is funded by LSSTC, NSF Cybertraining Grant-1829740, the Brinson Foundation, and the Moore Foundation; his participation in the program has benefited this work. M.G. is supported by the Polish NCN MAESTRO grant 2014/14/A/ST9/00121. This research has made use of the VizieR catalog access tool, CDS, Strasbourg, France (doi:10.26093/cds/vizier). The original description of the VizieR service was published in A&AS 143, 23. This project used data obtained with the Dark Energy Camera (DECam), which was constructed by the Dark Energy Survey (DES) collaborating institutions: Argonne National Lab, University of California Santa Cruz, University of Cambridge, Centro de Investigaciones Energeticas, Medioambientales y Tecnologicas-Madrid, University of Chicago, University College London, DES-Brazil consortium, University of Edinburgh, ETH-Zurich, University of Illinois at Urbana-Champaign, Institut de Ciencies de l'Espai, Institut de Fisica d'Altes Energies, Lawrence Berkeley National Lab, Ludwig-Maximilians Universitat, University of Michigan, National Optical Astronomy Observatory, University of Nottingham, Ohio State University, University of Pennsylvania, University of Portsmouth, SLAC National Lab, Stanford University, University of Sussex, and Texas A&M University. Funding for DES, including DECam, has been provided by the U.S. Department of Energy, National Science Foundation, Ministry of Education and Science (Spain), Science and Technology Facilities Council (UK), Higher Education Funding Council (England), National Center for Supercomputing Applications, Kavli Institute for Cosmological Physics, Financiadora de Estudos e Projetos, Fundacao Carlos Chagas Filho de Amparo a Pesquisa, Conselho Nacional de Desenvolvimento Cientifico e Tecnologico and the Ministerio da Ciencia e Tecnologia (Brazil), the German Research Foundation-sponsored cluster of excellence "Origin and Structure of the Universe," and the DES collaborating institutions. The Liverpool Telescope is operated on the island of La Palma by Liverpool John Moores University in the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofisica de Canarias with financial support from the UK Science and Technology Facilities Council. Based on observations made with the Gran Telescopio Canarias (GTC), installed in the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofisica de Canarias, in the island of La Palma. This work is partly based on data obtained with the instrument OSIRIS, built by a Consortium led by the Instituto de Astrofisica de Canarias in collaboration with the Instituto de Astronomia of the Universidad Autonoma de Mexico. OSIRIS was funded by GRANTECAN and the National Plan of Astronomy and Astrophysics of the Spanish Government. Some of the observations reported in this paper were obtained with the Southern African Large Telescope (SALT). Polish participation in SALT is funded by grant No. MNiSW DIR/WK/2016/07.
European Research Council and EU, Grant/Award Number: AdG‐250189, PoC‐727440 and ERC‐SyG‐2013‐610028; Natural Environmental Research Council, Grant/Award Number: NE/L002531/1; National Science Foundation, Grant/Award Number: DEB‐1237733, DEB‐1456729, 9714103, 0632263, 0856516, 1432277, DEB‐9705814, BSR‐8811902, DEB 9411973, DEB 0080538, DEB 0218039, DEB 0620910, DEB 0963447, DEB‐1546686, DEB‐129764, OCE 95‐21184, OCE‐ 0099226, OCE 03‐52343, OCE‐0623874, OCE‐1031061, OCE‐1336206 and DEB‐1354563; National Science Foundation (LTER) , Grant/Award Number: DEB‐1235828, DEB‐1440297, DBI‐0620409, DEB‐9910514, DEB‐1237517, OCE‐0417412, OCE‐1026851, OCE‐1236905, OCE‐1637396, DEB 1440409, DEB‐0832652, DEB‐0936498, DEB‐0620652, DEB‐1234162 and DEB‐0823293; Fundação para a Ciência e Tecnologia, Grant/Award Number: POPH/FSE SFRH/BD/90469/2012, SFRH/BD/84030/2012, PTDC/BIA‐BIC/111184/2009; SFRH/BD/80488/2011 and PD/BD/52597/2014; Ciência sem Fronteiras/CAPES, Grant/Award Number: 1091/13‐1; Instituto Milenio de Oceanografía, Grant/Award Number: IC120019; ARC Centre of Excellence, Grant/Award Number: CE0561432; NSERC Canada; CONICYT/FONDECYT, Grant/Award Number: 1160026, ICM PO5‐002, CONICYT/FONDECYT, 11110351, 1151094, 1070808 and 1130511; RSF, Grant/Award Number: 14‐50‐00029; Gordon and Betty Moore Foundation, Grant/Award Number: GBMF4563; Catalan Government; Marie Curie Individual Fellowship, Grant/Award Number: QLK5‐CT2002‐51518 and MERG‐CT‐2004‐022065; CNPq, Grant/Award Number: 306170/2015‐9, 475434/2010‐2, 403809/2012‐6 and 561897/2010; FAPESP (São Paulo Research Foundation), Grant/Award Number: 2015/10714‐6, 2015/06743‐0, 2008/10049‐9, 2013/50714‐0 and 1999/09635‐0 e 2013/50718‐5; EU CLIMOOR, Grant/Award Number: ENV4‐CT97‐0694; VULCAN, Grant/Award Number: EVK2‐CT‐2000‐00094; Spanish, Grant/Award Number: REN2000‐0278/CCI, REN2001‐003/GLO and CGL2016‐79835‐P; Catalan, Grant/Award Number: AGAUR SGR‐2014‐453 and SGR‐2017‐1005; DFG, Grant/Award Number: 120/10‐2; Polar Continental Shelf Program; CENPES – PETROBRAS; FAPERJ, Grant/Award Number: E‐26/110.114/2013; German Academic Exchange Service; sDiv; iDiv; New Zealand Department of Conservation; Wellcome Trust, Grant/Award Number: 105621/Z/14/Z; Smithsonian Atherton Seidell Fund; Botanic Gardens and Parks Authority; Research Council of Norway; Conselleria de Innovació, Hisenda i Economia; Yukon Government Herschel Island‐Qikiqtaruk Territorial Park; UK Natural Environment Research Council ShrubTundra Grant, Grant/Award Number: NE/M016323/1; IPY; Memorial University; ArcticNet. DOI:10.13039/50110000027. Netherlands Organization for Scientific Research in the Tropics NWO, grant W84‐194. Ciências sem Fronteiras and Coordenação de Pessoal de Nível Superior (CAPES, Brazil), Grant/Award Number: 1091/13‐1. National Science foundation (LTER), Award Number: OCE‐9982105, OCE‐0620276, OCE‐1232779. FCT ‐ SFRH / BPD / 82259 / 2011. U.S. Fish and Wildlife Service/State Wildlife federal grant number T‐15. Australian Research Council Centre of Excellence for Coral Reef Studies (CE140100020). Australian Research Council Future Fellowship FT110100609. M.B., A.J., K.P., J.S. received financial support from internal funds of University of Lódź. NSF DEB 1353139. Catalan Government fellowships (DURSI): 1998FI‐00596, 2001BEAI200208, MECD Post‐doctoral fellowship EX2002‐0022. National Science Foundation Award OPP‐1440435. FONDECYT 1141037 and FONDAP 15150003 (IDEAL). CNPq Grant 306595‐2014‐1 ; Peer reviewed ; Publisher PDF