179566 research outputs found
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“Impressively scary":Exploring user perceptions and reactions to unraveling machine learning models in social media applications
No full textMachine learning models deployed locally on social media applications are used for features, such as face filters which read faces in-real time, and they expose sensitive attributes to the apps. However, the deployment of machine learning models, e.g., when, where, and how they are used, in social media applications is opaque to users. We aim to address this inconsistency and investigate how social media user perceptions and behaviors change once exposed to these models. We conducted user studies (N=21) and found that participants were unaware to both what the models output and when the models were used in Instagram and TikTok, two major social media platforms. In response to being exposed to the models' functionality, we observed long term behavior changes in 8 participants. Our analysis uncovers the challenges and opportunities in providing transparency for machine learning models that interact with local user data
Evidence for metal sources, fluid-mixing processes, and S isotope recycling within the feeder zone of an Irish type Zn-Pb deposit
No full textThe origin and evolution of fluids in Irish-type Zn-Pb deposits remains debated, particularly regarding the mobility of metals such as Cu and Ni, sources of sulphur, and the role of fluid mixing and replacement. The Lisheen Zn-Pb deposit, Ireland, offers a well-defined natural laboratory to investigate these questions. While most studies have focused on the Waulsortian Limestone Formation, the primary sulphide host, less is known about mineralisation in underlying units, such as the Lisduff Oolite Member (LOM). The LOM displays enrichment in Cu and Ni and displays intense replacement textures compared to other hosts at Lisheen, making it an ideal target for studying metal mobility and sulphur recycling in carbonate-hosted systems. Through characterising and studying LOM-hosted sulphides, valuable insights into mineralisation processes, especially related to Cu-Ni metals, can be defined. This study integrates petrography, EMPA, and in situ sulphur isotope (δ34S) analysis to investigate sulphide paragenesis, mineral chemistry, and fluid evolution across LOM ore zones. Results reveal a multistage mineralising system involving extensive replacement of early pyrite (Py0, δ34S = −28.4 to −21.9 ‰) by sphalerite and galena, with zoned pyrite (Py1) enriched in As-Cu-Ni-Tl. The δ34S values and trace element trends indicate mixing between hydrothermal and bacteriogenic sulphur-rich fluids, with evidence for sulphur recycling during replacement. Pyrite textures and compositions capture this evolving fluid regime, with trace element enrichment linked to paragenetic stage. The steel ore region, adjacent to major fault intersections, records intense hydrothermal fluid interaction, hosting Ni- and As-rich phases such as nickeline, gersdorffite, and arsenopyrite. These findings highlight the importance of structural controls and fluid mixing in metal transport and deposition, positioning the LOM as a key stratigraphic unit for understanding ore-forming processes in Irish-type systems. These results have implications for targeting similar carbonate-hosted systems globally, especially where deeper or structurally complex ore zones remain underexplored.</p
Genetic origins and climate-induced erosion in economically important Asian walnuts
No full textAbstract The global climate is undergoing unprecedented changes, posing significant threats to species persistence. However, the spatiotemporal impacts on genetic diversity remain poorly understood, hindering species conservation and management. Walnuts, generally referred to as Juglans regia and J. sigillata, are economically vital in Asia, but little is known about their genetic origins and how the species will be affected by future climate change. Using 31 microsatellites, we genotyped 5282 individuals from 233 populations of walnuts in Asia. We assessed genetic diversity patterns and demographic history and investigated potential future genetic erosion risks. Genetic diversity of walnuts was high in the Himalaya and Hengduan Mountains. The 2 species diverged during the Pleistocene (around 1.41 Ma BP), and J. regia contained 2 genetic groups (JR1 and JR2). The JR2 group had the lowest diversity and likely arrived in northern China around 9.77 ka BP, perhaps via human transport. The Western Himalaya likely served both as a glacial refugium and the center of origin for J. regia, and the Eastern Himalaya appears to have been the refugium for J. sigillata. The 2 species appear to have hybridized in the Central Himalaya and the Sichuan basin and surroundings, forming two distinct hybrid zones. Our results indicate that genetic diversity will be reduced by up to 9.03% due to range loss under future climate change and dramatic genetic structure turnover in the Himalaya and Hengduan Mountains. In situ conservation in the Himalaya is essential for safeguarding genetic diversity and adaptive potential in Asian walnuts, while ex situ preservation of genetically unique wild germplasm, coupled with its integration into breeding programs, will enhance climate resilience. The findings advance our understanding of the origin of Asian walnuts and how future climatic change may affect their genetic diversity, offering a model for conservation and breeding strategies in other tree species facing similar threats
Corporate law as public policy
No full textCorporate law is a public policy balance. The state creates the corporation, and provides its legal features. ‘Micro’ aspects of the corporation, like separate legal personality, limited liability, and perpetual succession, were each provided by the state for public benefits rather than for their evident private benefits. Widespread utilisation of the corporation provides ‘macro’ public benefits. Corporations can also harm third parties, and the state should balance benefits and harms. Yet modern corporate law theory downplays the state’s role. Those who focus on the state also tend to miss the state’s foundational role in setting the contours of the corporation and corporate law, and encouraging certain behaviour. Identifying that corporate law is, descriptively, best seen as a public policy outcome shows the state is not a benign white knight which can only restrain corporations, but instead should be seen as culpable in any perceived social harms caused by corporations
Social imaginaries as a lens on co-designing environmental sustainability
No full textSocial imaginaries are a way of envisioning how people maintain society, and of understanding what is valued within that society. In this project, we worked with children on environmentally sustainable solutions for the future using co-design, a common methodology in child-computer interaction. We apply a social imaginary lens to five co-design case studies, from different geographic regions around the world, to describe and analyze variations in design practices as well as in design artifacts, and examine the ways in which children demonstrated a shared understanding of a pro-social world. The primary contribution of this paper is an illustration of the use of social imaginaries for interpreting and organising co-design around environmental sustainability
DNAJC14 Gene Edited Pigs are Resistant to Classical Pestiviruses
No full textInfectious diseases remain a major impediment to livestock production, causing losses to both productivity and welfare. Where key interactions between viruses and host proteins have been identified it is possible to rationally devise intervention strategies. In vitro studies have identified the host protein DNAJC14 as a core component of the replicative cycle of classical pestiviruses. Outbreaks caused by this group of viruses cause enormous losses in stock farming due to culling and export restrictions. Using CRISPR-Cas9 gene editing we produced a cohort of pigs with altered DNAJC14. Primary cells from these animals did not support replication of either classical swine fever virus (CSFV) or bovine viral diarrhea virus (BVDV) in vitro. In vivo challenge with CSFV revealed that the edited pigs displayed complete resistance to infection. This establishes gene editing as an additional strategy that can contribute to the control of classical pestiviruse
HPLT's Second Data Release
No full textWe describe the progress of the High Performance Language Technologies (HPLT) project, a 3-year EU-funded project that started in September 2022. We focus on the up-to-date results on the release of free text datasets derived from web crawls, one of the central objectives of the project. The second release used a revised processing pipeline, and an enlarged set of input crawls. From 4.5 petabytes of web crawls we extracted 7.6T tokens of monolingual text in 193 languages, plus 380 million parallel sentences in 51 language pairs. We also release MultiHPLT, a cross-combination of the parallel data, which produces 1,275 pairs, as well as releasing the containing documents for all parallel sentences in order to enable research in document-level MT. We report changes in the pipeline, analysis and evaluation results for the second parallel data release based on machine translation systems. All datasets are released under a permissive CC0 licence
DeepSpace:Super resolution powered efficient and reliable satellite image data acquistion
No full textLarge constellations of low-earth orbit satellites enable frequent high-resolution earth imaging for numerous geospatial applications. They generate large volumes of data in space, hundreds of Terabytes per day, which much be transported to Earth through constrained intermittent connections to ground stations. The large volumes lead to large day-level delay in data download and exorbitant cloud storage costs. We propose DeepSpace, a new deep learning-based super-resolution approach that compresses satellite imagery by over two orders of magnitude, while preserving image quality using a tailored mixture of experts (MoE) superresolution framework. DeepSpace reduces the network bandwidth requirements for space-Earth transfer, and can compress images for cloud storage. DeepSpace achieves such gains with the limited computational power available on small LEO satellites. We extensively evaluate DeepSpace against a wide range of state-of-the-art baselines considering multiple satellite image datasets and demonstrate the above mentioned benefits. We further demonstrate the effectiveness of DeepSpace through several distinct downstream applications (wildfire detection, land use and cropland classification, and fine-grained plastic detection in oceans)
Social agentics:ACM COMPASS workshop
Get PDFAgentic AI is being heralded as the next step in the development of AI systems. Agentics, complex ensembles of different machine learning, data processing, and generative AI models, can provide new autonomous and proactive decision-making capabilities to organizations, participate in complex workflows, and, when needed, seek guidance from and provide insights to human users in natural languages. Collectively, we wish to explore how and why to design agentic systems to be situated within specific social and organizational contexts, the value of social theory and perspectives to this work, and the potential of this move to address critical issues with AI. Given the focus on social and organization context as essential to agentic design, we see this work as directly related to the ACM COMPASS 2025 theme “computing in place”. We seek to bring together scholars from the diversity of disciplines within ACM to develop research agendas, projects, and joint teaching initiatives that support the development of social agentic design and analysis
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