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A Cosmic Miracle: A Remarkably Luminous Galaxy at z spec = 14.44 Confirmed with JWST
Get PDFJWST has revealed a stunning population of bright galaxies at surprisingly early epochs, , where few such sources were expected. Here we present the most distant example of this class yet -- MoM-z14, a luminous ( ) source in the COSMOS field at that expands the observational frontier to a mere 280 million years after the Big Bang. The redshift is confirmed with NIRSpec/PRISM spectroscopy through a sharp Lyman- break and detections of five rest-UV emission lines. The number density of bright sources implied by our "Mirage or Miracle" survey spanning arcmin is larger ( ) than pre-JWST consensus models. The high EWs of UV lines ( Å) signal a rising star-formation history, with a increase in the last 5 Myr ( ). The source is extremely compact (circularized pc), and yet elongated ( ), suggesting an AGN is not the dominant source of UV light. The steep UV slope ( ) implies negligible dust attenuation and a young stellar population. The absence of a strong damping wing provides tentative evidence that the immediate surroundings of MoM-z14 may be partially ionized at a redshift where virtually every reionization model predicts a neutral fraction. The nitrogen emission and highly super-solar [N/C] hint at an abundance pattern similar to local globular clusters that may have once hosted luminous supermassive stars. Since this abundance pattern is also common among the most ancient stars born in the Milky Way, we may be directly witnessing the formation of such stars in dense clusters, connecting galaxy evolution across the entire sweep of cosmic time
Doxxed: How Privacy Abuse Harms
No full textWhat happens when your personal information is weaponized against you online?This groundbreaking book offers a novel examination of doxxing—the malicious sharing of private, identifiable and sensitive information—through a feminist and post-humanist lens. Drawing on in-depth interviews with 18 victim-survivors, it reveals the deeply gendered harms of privacy abuse, from public shaming and reputational damage to the erosion of informational autonomy.Challenging conventional understandings of digital abuse, the book foregrounds the lived experiences of those affected and calls for urgent, victim-centred reforms. A vital resource for scholars and advocates, it reimagines data rights in a digital world increasingly shaped by surveillance and control
Beyond connectivity: Stock market participation in a network
Get PDFWhat are the aggregate and distributional consequences of the relationship between an individual’s social network and financial decisions? Motivated by several well-documented facts about the influence of social connections on financial decisions, we build and calibrate a model of stock market participation with a social network that emphasizes the interplay between connectivity and network structure. Since connections to informed agents influence peers through utility and learning, there is a pivotal role for homophily. An increase in the average number of connections raises the average participation rate, mostly due to richer agents. Higher homophily benefits richer agents by creating clusters where information spreads more efficiently. We also show that peer effects in participation costs is crucial for matching stock market participation among poorer agents. Finally, we provide empirical evidence consistent with the importance of connectivity and sorting
Response of emperor penguins to 40 years of changing ice conditions at the Astrid, Mertz, and SANAE colonies using satellite remote sensing (1984-2024)
No full textEmperor penguins are an iconic Antarctic species threatened by climate change. The birds are highly reliant on stable fast ice for successful breeding, and some studies project possible quasi-extinction for over 90% of colonies by 2100 due to future sea ice loss. Recent record-low Antarctic sea ice conditions highlight the threat to the species. To better model the future response of emperor penguins to climate change and increasing extreme ice events in sea ice and at the margins of the ice sheet, it is essential to better understand how colonies have responded to past conditions. In this study we identify the historical locations of the Sanae, Astrid and Mertz colonies in all available Landsat 4-9, ASTER, and Sentinel-2 imagery, spanning the years 1984-2024. We record the location and surface type of the colonies’ breeding locations each year, while also recording extreme ice events (major calving events, early fast ice breakout), distance to the fast ice edge, and colony range within a season. Colonies typically return to approximately the same sheltered sites annually throughout the 35-40 year period, but we observe variations due to major glacier calving events. Following such events at Mertz (2010) and Sanae (2011) that disrupt breeding sites, colonies relocate to different sites nearby where they may be more vulnerable to earlier fast ice breakout, or have to travel longer distances for foraging. In subsequent years the colonies eventually return to sites close to their original location. However, the Astrid colony does not relocate following a major calving event (2006). Additionally, we observe early fast ice breakouts that are likely to impact breeding success at Mertz and Sanae colonies, including as early as September at Mertz in 2016. Such changes to breeding success are related both to broader sea ice conditions and variations in colony location. Notably, we observe all three colonies to move onto the neighbouring ice shelf in some years (and at Mertz, onto icebergs too), including when stable fast ice is available, suggesting this behaviour may be more common than previously thought. Observation of these behaviours contributes to broader understanding of emperor penguins’ adaptability and will aid future efforts to model the response of the species to ice loss. Additionally, we demonstrate the value of cloud computing in enabling long-term studies of many images over multiple satellite platforms to better understand colony histories
The intersection of education and health: schools as a catalyst for childhood obesity prevention
No full textTowards a research and policy agenda for climate action in smaller municipalities and rural regions
No full textMultimodal models for skin cancer classification using clinical freetext and dermatoscopic images
Get PDFBackgroundSkin cancer is one of the most prevalent cancers globally, with early detection critical to ensure reduced mortality risk. To aid early detection, machine learning (ML) skin cancer detection models have been proposed, currently with a focus on dermatoscopic imaging only. However, freetext may provide extra diagnostic information that is not present in images alone.MethodsWe constructed a multimodal dataset comprising 5481 dermatoscopic images from 4538 patients, including patient metadata and clinical notes, with binary labels (benign vs. malignant, 7% malignant). To assess and mitigate bias from leading language, we developed a clinical text preprocessing pipeline combining regular expressions and large language models, enabling multiple levels of filtering. We train multimodal ML models on this dataset to explore the effect of freetext on model performance.ResultsOur results show that incorporating unfiltered text significantly improves classification performance (0.970 AUROC) compared to visual data alone (0.909 AUROC); even with leading language removed, performance gains persist (0.948 AUROC).ConclusionsThis work benchmarks clinical freetext inclusion in skin lesion classification, demonstrating that clinical text contributes predictive value beyond that available in images alone. The model’s high performance on unfiltered clinical text highlights the high levels of bias, and possible shortcutting, present in this text which may make it unsuitable for inclusion in some ML models. By systematically filtering clinical notes via our proposed technique, we show that multimodal models retain improved accuracy while reducing bias. These results provide practical guidance for integrating clinical text into real-world skin cancer detection systems and establish a foundation for future multimodal research in dermatology
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