8468 research outputs found
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JV basketball team group photo [4], 1961-1962
No full textGroup photograph of the Clark University JV basketball team, 1961-1962.
All photographs in this collection were digitized between 2022 and 2023. The photographs in this collection are part of the Photographs and Media record group of Clark University’s Archives & Special Collections.https://commons.clarku.edu/basketball/1008/thumbnail.jp
Women’s basketball team celebrates a win, circa 1970s-1980s
No full textPhotograph of the Clark University women’s basketball team celebrating a win, circa 1970s-1980s.
All photographs in this collection were digitized between 2022 and 2023. The photographs in this collection are part of the Photographs and Media record group of Clark University’s Archives & Special Collections.https://commons.clarku.edu/basketball/1203/thumbnail.jp
Women’s basketball team in the middle of a game [2], 1986-1987
No full textAction photograph of a Clark University women\u27s team basketball game, circa 1987.
All photographs in this collection were digitized between 2022 and 2023.
The photographs in this collection are part of the Photographs and Media record group of Clark University’s Archives & Special Collections.https://commons.clarku.edu/basketball/1188/thumbnail.jp
Action shot of men\u27s basketball game [25], 1984
No full textAn action photograph of the Clark University men\u27s basketball team during a game, 1984.
All photographs in this collection were digitized between 2022 and 2023.
The photographs in this collection are part of the Photographs and Media record group of Clark University’s Archives & Special Collections.https://commons.clarku.edu/basketball/1073/thumbnail.jp
JV basketball team group photo, circa 1970s-1980s
No full textGroup photograph of the Clark University JV basketball team, circa 1970s-1980s.
All photographs in this collection were digitized between 2022 and 2023. The photographs in this collection are part of the Photographs and Media record group of Clark University’s Archives & Special Collections.https://commons.clarku.edu/basketball/1000/thumbnail.jp
Coach Wally Halas and two members from men\u27s basketball team, 1988
No full textPhotograph of Coach Wally Halas and two members of Clark University\u27s men\u27s basketball team, 1988.
All photographs in this collection were digitized between 2022 and 2023.
The photographs in this collection are part of the Photographs and Media record group of Clark University’s Archives & Special Collections.https://commons.clarku.edu/basketball/1076/thumbnail.jp
Action shot of men\u27s basketball game [34], circa 1970s
No full textAn action photograph of the Clark University men\u27s basketball team during a game, circa 1970s.
All photographs in this collection were digitized between 2022 and 2023.
The photographs in this collection are part of the Photographs and Media record group of Clark University’s Archives & Special Collections.https://commons.clarku.edu/basketball/1084/thumbnail.jp
Action shot of Marina Giolas during women’s basketball game [3], circa 1987
No full textAction photograph of Marina Giolas during a Clark University women\u27s basketball game, circa 1987. Giolas was captain of the team for the 1986-1987 season, is one of Clark\u27s 1000-point scorers (even finishing out at over 1,500 points), and received the M. Hazel Hughes Trophy, which is given to the outstanding senior female athlete, upon graduation.
All photographs in this collection were digitized between 2022 and 2023.
The photographs in this collection are part of the Photographs and Media record group of Clark University’s Archives & Special Collections.https://commons.clarku.edu/basketball/1175/thumbnail.jp
Identification of novel components of the retinal determination gene network in Drosophila cell lines
No full textThe retinal determination genetic network controls the development of the visual system in all seeing animals through the molecular regulation of cells to adopt an eye tissue fate. The compound eye of the fruit fly, Drosophila melanogaster, is an excellent model system to study the complex mechanisms within the network that regulate specification of cellular identity during embryogenesis. In Drosophila, the two Pax6 paralogues, eyeless and twin of eyeless, sit at the very pinnacle of the network and their expression early in development activates critical downstream components of the retinal determination pathway. In this study, we investigate the expression of 21 known components of the network in two established embryonic cell lines, Kc167 and S2 cells, that show reciprocal expression patterns for the two Pax6 paralogues. Network mapping reveals that many of the components of the network demonstrate extensive interactions with additional factors. Integrating the transcriptional profile of the cell lines, interaction maps and embryonic expression patterns enables us to identify 16 potential novel components of the genetic network, 11 of which are transcription factors. We confirm the regulatory potential for a subset of the novel transcription factors through the identification of predicted binding sites in previously characterized enhancers for the core genes in the network. © 2025 Royal Society Publishing. All rights reserved
DynamicPATCH: method and software for spatially explicit dynamic patch transition characterization
No full textContext: Decades of research have used spatial pattern metrics at time points, such as those in FRAGSTATS, to measure the net change of landscape configuration and composition during time intervals. However, metrics at time points fail to quantify a time interval’s gross change, which can be substantially larger than net change between two time points. The field of landscape ecology has lacked a conceptual framework and accompanying software to characterize patterns of gross change during time intervals in terms of patches that are spatially explicit with a typology that is mutually exclusive and collectively exhaustive. Objectives: We present a new method and software named Spatially Explicit Dynamic PAtch Transition CHaracterization (DynamicPATCH). DynamicPATCH reads a time series of raster maps of a Boolean variable to map, characterize, and quantify gross patch dynamics in ways that existing metrics miss. We design the method to compare time intervals that vary in their durations. Methods: Our method identifies eight mutually exclusive and collectively exhaustive patch-based transition types: Disappearing, Appearing, Splitting, Merging, Perforating, Filling, Contracting, and Expanding. The method quantifies each type’s gross gain and gross loss in area. The method also shows how each type contributes to the gross increase and gross decrease in the number of patches during each time interval. We illustrate our method with a simple example as well as a case study on the dynamics of marshes and ponds in the Plum Island Ecosystems site of the National Science Foundation’s Long Term Ecological Research network (PIE-LTER) across the years 1938, 1971, and 2013. Results: Our method reveals dramatic gross changes in the size and number of patches of pond and marsh at PIE-LTER, which traditional methods that report only net changes fail to capture. The transition types Perforating and Contracting account for 89% of gross loss in marsh size across the temporal extent. Annual gross increase in the number of marsh patches during the second time interval is 3.8 times greater than during the first time interval, with 40% of gross increase contributed by Appearing and 60% by Splitting. Gross gain of pond is more than twice the size of gross loss of pond, with Merging accounting for 47% of gross gain, followed by Appearing and Expanding. Appearing and Disappearing account for most gross changes in the number of ponds during the temporal extent, which is ten times greater than the net change in the number of ponds. Conclusions: DynamicPATCH offers a new operationalized approach to characterize the spatial–temporal patterns of patch dynamics. DynamicPATCH can be applied to various landscapes to pursue important research agendas in landscape ecology, such as landscape fragmentation, habitat connectivity, process-pattern relationships, and more. Users can obtain the open-source Python package at https://github.com/zay1996/DynamicPATCH. © The Author(s) 2025