Archaeological Investigations at 41AN115

41AN115 is located in the northwestern part of Anderson County, Texas, on a western terrace of Town Creek approximately nine miles from the Trinity River. It is a multi-component prehistoric occupation, and the artifacts found here indicate it has been used from Late Paleoindian to Woodland period times. The late Paleoindian occupation is represented by Dalton and San Patrice dart points; the Archaic occupations are marked by Bell, Bulverde, and Yarbrough dart points; while the Woodland period occupation includes Gary points and sandy paste pottery. The site was used intermittently over thousands of years as a hunting camp and later as a seasonal campsite. The tool kit included flake knives, gravers, spokeshaves, punches, and scrapers, along with many ground stone tools. The lithic materials chosen for tool use are a combination of local and non-local material with cherts, fine-grained quartzite, ferruginous sandstone, and petrified wood. One Late Archaic occupational features has been found at the site

ALCOA #1 (41AN87): A Frankston Phase Settlement along Mound Prairie Creek, Anderson County, Texas

The ALCOA #1 (41AN87) site is a Frankston Phase (ca. A.D. 1400-1650) site located on a high alluvial terrace of Mound Prairie Creek, about seven kilometers northeast of Palestine, Texas. Mound Prairie Creek, a perennial stream, flows southeast to east across the county and drains into the Neches River. The site is approximately 10 meters above the Mound Prairie Creek floodplain, and the creek channel is 300 meters to the south. Although the investigations at the site have been rather limited to date, it appears that the ALCOA #1 site is a single component Frankston Phase homestead, or possibly a small hamlet. Other Frankston phase sites are known on Mound Prairie Creek, Hurricane Creek, Walnut Creek, and Brushy Creek, all Neches River tributaries, and the possibility exists that these may be part of a larger related Caddo community and settlement system

Explore the concept of “light” and its interaction with matter: an inquiry-based science education project in primary school

The exploration process leading to the understanding of physical phenomena, such as light and its interaction with matter, raises great interest and curiosity in children. However, in most primary schools, children rarely have the opportunity to conduct science activities in which they can engage in an enquiry process even if by the action of the teacher. In this context, we have organised several in-service teacher training courses and carried out several pedagogic interventions in Portuguese primary schools, with the aim of promoting inquirybased science education. This article describes one of those projects, developed with a class of the third grade, which explored the curricular topic “Light Experiments”. Various activities were planned and implemented, during a total of ten hours spread over five lessons. The specific objectives of this paper are: to illustrate and analyse the teaching and learning process promoted in the classroom during the exploration of one of these lessons, and to assess children’s learning three weeks after the lessons. The results suggest that children made significant learning which persisted. We conclude discussing some processes that stimulated children’ learning, including the importance of teacher questioning in scaffolding children's learning and some didactic implications for teacher training.CIEC – Research Centre on Child Studies, IE, UMinho (FCT R&D unit 317), Portuga

Mixing methods to explore appearance in dementia care

This paper considers approaches to investigating appearance and the work invested in maintaining it within dementia care. Our focus is upon methodological and methods-related issues associated with the challenge of generating knowledge of the embodied worlds of people with dementia. We begin with a brief overview of the literature on appearance and dementia, and consider what it teaches us about the nature of appearance and ways of understanding it. We describe and discuss the mixing of methods for an on-going investigation into hairdressing in dementia care: The Hair and Care project. Based upon the experience of research in care-based hair salons, we argue for a creative use of methods in dementia studies as an avenue to better engaging with the embodied experiences of people with dementia and, as a result, understanding how people use their bodies and senses to create meaningful worlds. © The Author(s) 2013 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav

Rationalization and Design of the Complementarity Determining Region Sequences in an Antibody-Antigen Recognition Interface

Protein-protein interactions are critical determinants in biological systems. Engineered proteins binding to specific areas on protein surfaces could lead to therapeutics or diagnostics for treating diseases in humans. But designing epitope-specific protein-protein interactions with computational atomistic interaction free energy remains a difficult challenge. Here we show that, with the antibody-VEGF (vascular endothelial growth factor) interaction as a model system, the experimentally observed amino acid preferences in the antibody-antigen interface can be rationalized with 3-dimensional distributions of interacting atoms derived from the database of protein structures. Machine learning models established on the rationalization can be generalized to design amino acid preferences in antibody-antigen interfaces, for which the experimental validations are tractable with current high throughput synthetic antibody display technologies. Leave-one-out cross validation on the benchmark system yielded the accuracy, precision, recall (sensitivity) and specificity of the overall binary predictions to be 0.69, 0.45, 0.63, and 0.71 respectively, and the overall Matthews correlation coefficient of the 20 amino acid types in the 24 interface CDR positions was 0.312. The structure-based computational antibody design methodology was further tested with other antibodies binding to VEGF. The results indicate that the methodology could provide alternatives to the current antibody technologies based on animal immune systems in engineering therapeutic and diagnostic antibodies against predetermined antigen epitopes

Scintillation light detection in the 6-m drift-length ProtoDUNE Dual Phase liquid argon TPC

DUNE is a dual-site experiment for long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon decay searches. ProtoDUNE Dual Phase (DP) is a 6  ×  6  ×  6 m 3 liquid argon time-projection-chamber (LArTPC) that recorded cosmic-muon data at the CERN Neutrino Platform in 2019-2020 as a prototype of the DUNE Far Detector. Charged particles propagating through the LArTPC produce ionization and scintillation light. The scintillation light signal in these detectors can provide the trigger for non-beam events. In addition, it adds precise timing capabilities and improves the calorimetry measurements. In ProtoDUNE-DP, scintillation and electroluminescence light produced by cosmic muons in the LArTPC is collected by photomultiplier tubes placed up to 7 m away from the ionizing track. In this paper, the ProtoDUNE-DP photon detection system performance is evaluated with a particular focus on the different wavelength shifters, such as PEN and TPB, and the use of Xe-doped LAr, considering its future use in giant LArTPCs. The scintillation light production and propagation processes are analyzed and a comparison of simulation to data is performed, improving understanding of the liquid argon properties

Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

Liquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between data and simulation

Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

Liquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on experimental data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between experimental data and simulation