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[TAHIRAH WILLIAMS], who signed a letter of intent with UConn last week, was 8 when UConn won its first title in 1995. The chance to play in Storrs was always her dream. She has seen UConn win four titles in the past five years. She's also seen UConn win historic twin titles.

Cosmological observations indicate that dark matter makes up 85% of all matter in the universe yet its microscopic composition remains a mystery. Dark matter could arise from ultralight quantum fields that form macroscopic objects. Here we use the global positioning system as a ~ 50,000 km aperture dark matter detector to search for such objects in the form of domain walls. Global positioning system navigation relies on precision timing signals furnished by atomic clocks. As the Earth moves through the galactic dark matter halo, interactions with domain walls could cause a sequence of atomic clock perturbations that propagate through the satellite constellation at galactic velocities ~ 300 km s −1 . Mining 16 years of archival data, we find no evidence for domain walls at our current sensitivity level. This improves the limits on certain quadratic scalar couplings of domain wall dark matter to standard model particles by several orders of magnitude. The composition of dark matter in the universe remains a mystery, with one hypothetical form being topological defects. Here the authors determine a stronger constraint on the coupling of this dark matter to atomic clocks on board global positioning satellites through the analysis of 16 years of archival data.

This research employs machine learning (Mask Region-Based Convolutional Neural Networks [Mask R-CNN]) and cluster analysis (Density-based spatial clustering of applications with noise [DBSCAN]) to identify more than 20,000 relict charcoal hearths (RCHs) organized in large “fields” within and around State Game Lands (SGLs) in Pennsylvania. This research has two important threads that we hope will advance the archaeological study of landscapes. The first is the significant historical impact of charcoal production, a poorly understood industry of the late eighteenth to early twentieth century, on the historic and present landscape of the United States. Although this research focuses on charcoal production in Pennsylvania, it has broad application for both identifying and contextualizing historical charcoal production throughout the world and for better understanding modern charcoal production. The second thread is the use of open data, open source, and open access tools to conduct this analysis, as well as the open publication of the resultant data. Not only does this research demonstrate the significance of open access tools and data but the open publication of our code as well as our data allow others to replicate our work, to tweak our code and protocols for their own work, and reuse our results. Esta investigación emplea el aprendizaje automatizado (Redes Neuronales Convolucionales basadas en Regiones “Máscara” [Mask R-CNN; en sus siglas en inglés]) y el análisis de agrupamientos o clústers (Agrupamiento Espacial Basado en Densidad de Aplicaciones con Ruido [DBSCAN; en sus siglas en inglés]), para identificar más de 20,000 áreas de combustión de hornos de producción de carbón (RCHs; en sus siglas inglés), dispuestos en “campos” amplios dentro y alrededor de Campos de Caza Estatales (SGLs; en sus siglas inglés), en Pensilvania. Esta investigación tiene dos importantes desafíos que esperamos que desarrollará el estudio de los paisajes en arqueología. El primero es el impacto histórico significativo de la producción de carbón, una industria poco entendida de la época temprana del S. XVIII e inicios del S. XIX, del paisaje histórico y actual de Estados Unidos. No obstante, esta investigación se centra alrededor de la producción de carbón en Pensilvania, tiene una aplicación amplia para la identificación y contextualización de la producción de carbón histórica en todo el mundo y para lograr un mejor entendimiento de la producción moderna de carbón. El segundo desafío es el uso de las herramientas de datos libres, fuentes libres y accesos libres para llevar a cabo este análisis, así como la publicación libre del dato resultante. Esta investigación no solamente demuestra el significado de las herramientas y los datos libres, sino que además la publicación libre de nuestro código, así como nuestros datos, permitirá a otros replicar nuestro trabajo, refinar nuestro código y protocolos para su propia investigación, así como reusar nuestros resultados.

These data were used to build an object detection model to locate Relict Charcoal Hearths (RCH) as described in the paper \"When Computers Dream of Charcoal: Using Deep Learning, Open Tools and Open Data to Identify Relict Charcoal Hearths in and around State Game Lands in Pennsylvania\" [1]. This is the first grouping of data for the paper above. The second grouping is also available in this journal, see \"Object detection model, image data and results from the \"When Computers Dream of Charcoal: Using Deep Learning, Open Tools and Open Data to Identify Relict Charcoal Hearths in and around State Game Lands in Pennsylvania\" paper\".

These data were used to build an object detection model to locate Relict Charcoal Hearths (RCH) as described in the paper \"When Computers Dream of Charcoal: Using Deep Learning, Open Tools and Open Data to Identify Relict Charcoal Hearths in and around State Game Lands in Pennsylvania\" [1]. This is the second grouping of data for the paper above. The first grouping is also available in this journal, see \"Geospatial and image data from the \"When Computers Dream of Charcoal: Using Deep Learning, Open Tools and Open Data to Identify Relict Charcoal Hearths in and around State Game Lands in Pennsylvania\" paper\" [2].

EDITOR: The parents of the seniors on the Maria Carrillo High boys' soccer team met with Mr. Klick, principal, and discussed the team's disqualification. During the meeting Mr. Klick read the athletic director's job description. It stated, \"to oversee all teams and to know the rules.\" The AD is the safety net so mistakes are not made.

As expected, UConn freshman Caron Butler received and began serving an NCAA-imposed three-game suspension Friday, but the school also announced senior center Souleymane Wane has been suspended three games for an undisclosed eligibility issue. Butler and UConn reported to the NCAA that the player received about $400 to help pay tuition costs at Maine Central Insititute. In doing so, they applied for amnesty, meaning Butler would sit out three regular season games, admit no guilt and not have to pay back any money. If he and UConn had challenged and the ruling didn't go in their favor, the penalty could have been more severe. Butler, 20, said it was not athletics that led to his meeting Jameel Ghuari, employed by the Bray Center in Butler's hometown of Racine, Wis. Ghuari directed funds for special needs of youth in the area. When Butler was 14, and a freshman at Case High, he served 18 months in juvenile hall for possession of a firearm. When he got out, he met Ghuari.