76 research outputs found

    AffirmativeAI: Towards LGBTQ+ Friendly Audit Frameworks for Large Language Models

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    LGBTQ+ community face disproportionate mental health challenges, including higher rates of depression, anxiety, and suicidal ideation. Research has shown that LGBTQ+ people have been using large language model-based chatbots, such as ChatGPT, for their mental health needs. Despite the potential for immediate support and anonymity these chatbots offer, concerns regarding their capacity to provide empathetic, accurate, and affirming responses remain. In response to these challenges, we propose a framework for evaluating the affirmativeness of LLMs based on principles of affirmative therapy, emphasizing the need for attitudes, knowledge, and actions that support and validate LGBTQ+ experiences. We propose a combination of qualitative and quantitative analyses, hoping to establish benchmarks for "Affirmative AI," ensuring that LLM-based chatbots can provide safe, supportive, and effective mental health support to LGBTQ+ individuals. We benchmark LLM affirmativeness not as a mental health solution for LGBTQ+ individuals or to claim it resolves their mental health issues, as we highlight the need to consider complex discrimination in the LGBTQ+ community when designing technological aids. Our goal is to evaluate LLMs for LGBTQ+ mental health support since many in the community already use them, aiming to identify potential harms of using general-purpose LLMs in this context

    Everything You Always Wanted to Know About Storage Compressibility of Pre-Trained ML Models but Were Afraid to Ask

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    As the number of pre-trained machine learning (ML) models is growing exponentially, data reduction tools are not catching up. Existing data reduction techniques are not specifically designed for pre-trained model (PTM) dataset files. This is largely due to a lack of understanding of the patterns and characteristics of these datasets, especially those relevant to data reduction and compressibility. This paper presents the first, exhaustive analysis to date of PTM datasets on storage compressibility. Our analysis spans different types of data reduction and compression techniques, from hash-based data deduplication, data similarity detection, to dictionary-coding compression. Our analysis explores these techniques at three data granularity levels, from model layers, model chunks, to model parameters. We draw new observations that indicate that modern data reduction tools are not effective when handling PTM datasets. There is a pressing need for new compression methods that take into account PTMs' data characteristics for effective storage reduction. Motivated by our findings, we design ELF, a simple yet effective, error-bounded, lossy floating-point compression method. ELF transforms floating-point parameters in such a way that the common exponent field of the transformed parameters can be completely eliminated to save storage space. We develop Elves, a compression framework that integrates ELF along with several other data reduction methods. Elves uses the most effective method to compress PTMs that exhibit different patterns. Evaluation shows that Elves achieves an overall compression ratio of 1.52×1.52\times, which is 1.31×1.31\times, 1.32×1.32\times and 1.29×1.29\times higher than a general-purpose compressor (zstd), an error-bounded lossy compressor (SZ3), and the uniform model quantization, respectively, with negligible model accuracy loss.Comment: This paper presents the first, exhaustive analysis to date of PTM datasets on storage compressibility. Motivated by our findings, we design ELF, a simple yet effective, error-bounded, lossy floating-point compression metho

    JUNO Sensitivity to Invisible Decay Modes of Neutrons

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    We explore the bound neutrons decay into invisible particles (e.g., n→3Îœn\rightarrow 3 \nu or nn→2Îœnn \rightarrow 2 \nu) in the JUNO liquid scintillator detector. The invisible decay includes two decay modes: n→inv n \rightarrow { inv} and nn→inv nn \rightarrow { inv} . The invisible decays of ss-shell neutrons in 12C^{12}{\rm C} will leave a highly excited residual nucleus. Subsequently, some de-excitation modes of the excited residual nuclei can produce a time- and space-correlated triple coincidence signal in the JUNO detector. Based on a full Monte Carlo simulation informed with the latest available data, we estimate all backgrounds, including inverse beta decay events of the reactor antineutrino Μˉe\bar{\nu}_e, natural radioactivity, cosmogenic isotopes and neutral current interactions of atmospheric neutrinos. Pulse shape discrimination and multivariate analysis techniques are employed to further suppress backgrounds. With two years of exposure, JUNO is expected to give an order of magnitude improvement compared to the current best limits. After 10 years of data taking, the JUNO expected sensitivities at a 90% confidence level are τ/B(n→inv)>5.0×1031 yr\tau/B( n \rightarrow { inv} ) > 5.0 \times 10^{31} \, {\rm yr} and τ/B(nn→inv)>1.4×1032 yr\tau/B( nn \rightarrow { inv} ) > 1.4 \times 10^{32} \, {\rm yr}.Comment: 28 pages, 7 figures, 4 table

    Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

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    Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30M⊙M_{\odot} for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

    Spatial distribution pattern of mustelids in the eastern edge of the Qinghai–Tibet Plateau

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    Evolutionary theory predicts that the species of an evolutionarily successful taxon would not overlap in spatial distribution. To test the prediction, we document our research on the spatial associations of mustelids, an evolutionarily successful group of order Carnivore, using infrared camera trap data on species distribution collected from the national nature reserves (NNRs) of Liancheng, Wolong, Tangjiahe and Heizhugou in China in 2017–2021. Data showed seven mustelid species occurring in the study area, including Arctonyx collaris, Meles leucurus, Martes foina, Martes flavigula, Mustela altaica, Mustela nivalis and Mustela sibirica. Following Ricklef’s definition of biological community, we identified five networks of species associations. The mustelids occurred in the networks. Species from the same genus, such as M. foina and M. flavigula, stayed in different networks to avoid competition owing to similar feeding habits or habitat preferences. Species with different feeding habits or habitat preferences either occurred in different networks, such as M. altaica and M. flavigula, or coexisted in the same networks but avoided direct spatial associations, such as M. foina and A. collaris. Asymmetrical associations were found between different genera, such as M. foina and M. altaica, or between different subfamilies, such as M. flavigula and A. collaris. These associations may be attributed to interspecific killing or seed dispersal. However, these associations accounted for only a small proportion and would not impact the species diversity of Mustelidae. It is thus concluded that the prediction is supported by our research findings and that spatial avoidance may be the biogeographic strategy of maintaining the species diversity of the family. We also found that the well protection of the mustelids may benefit the overall biodiversity conservation in Heizhugou, an NNR that has experienced severe deforestation

    The Lived Experience of Child-Owned Wearables: Comparing Children's and Parents' Perspectives on Activity Tracking

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    Children are increasingly using wearables with physical activity tracking features. Although research has designed and evaluated novel features for supporting parent-child collaboration with these wearables, less is known about how families naturally adopt and use these technologies in their everyday life. We conducted interviews with 17 families who have naturally adopted child-owned wearables to understand how they use wearables individually and collaboratively. Parents are primarily motivated to use child-owned wearables for children's long-term health and wellbeing, whereas children mostly seek out entertainment and feeling accomplished through reaching goals. Children are often unable to interpret or contextualize the measures that wearables record, while parents do not regularly track these measures and focus on deviations from their children's routines. We discuss opportunities for making naturally-occurring family moments educational to positively contribute to children's conceptual understanding of health, such as developing age-appropriate trackable metrics for shared goal-setting and data refection.University of California System ; National Science Foundation (NSF

    Correlation between 5-HT and Diarrhea-type Irritable Bowel Syndrome and Regulation by Traditional Chinese Medicine

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    5-hydroxytryptamine (5-HT) is an important brain intestinal peptide that affects gastrointestinal function in patients with diarrhea-type irritable bowel syndrome. In recent years, it has been found that any abnormality in any of the signal transduction processes such as synthesis, release, binding to receptors and reuptake of 5-HT may lead to the development of diarrhoeal irritable bowel syndrome. In order to explore the potential therapeutic value of serotonin in diarrhea type irritable bowel syndrome, but also to provide a theoretical reference and basis for Chinese medicine for the prevention and treatment of diarrhea type irritable bowel syndrome. Through reviewing a large number of domestic and foreign literatures, the author found that traditional Chinese medicine (TCM) had a significant effect in the treatment of diarrhea type irritable bowel syndrome by regulating 5-HT. Therefore, the author reviewed the modern medical understanding of 5-HT, the correlation between 5-HT and diarrhea-type irritable bowel syndrome, and the research progress of TCM intervention with 5-HT in the treatment of diarrhea-type irritable bowel syndrome, in order to explore the potential therapeutic value of 5-HT in diarrhea-type irritable bowel syndrome. Meanwhile, it also provides a theoretical reference and basis for TCM in the prevention and treatment of diarrhea-type irritable bowel syndrome
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