76 research outputs found
AffirmativeAI: Towards LGBTQ+ Friendly Audit Frameworks for Large Language Models
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
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 , which is ,
and 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
Marginal increase of sunitinib exposure by grapefruit juice
Clinical Oncolog
JUNO Sensitivity to Invisible Decay Modes of Neutrons
We explore the bound neutrons decay into invisible particles (e.g.,
or ) in the JUNO liquid scintillator
detector. The invisible decay includes two decay modes: and . The invisible decays of -shell neutrons in
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 , 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 and
.Comment: 28 pages, 7 figures, 4 table
Real-time Monitoring for the Next Core-Collapse Supernova in JUNO
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 30 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
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Mobile Apps for Childrens Health and Wellbeing: Design Features and Future Opportunities.
Mobile health apps hold great potential for promoting childrens health and wellbeing. However, there is limited understanding of how these technologies are currently designed to support children with their health concerns or wellness goals. To gain insight into the current landscape of mobile apps designed for childrens health, we retrieved and reviewed 43 apps from IOS and Google Play store that are specifically marketed for children. Our qualitative analysis identified the dominant health focuses and goals of childrens mobile health apps. We analyzed the primary users and their expectations as well as the methods of engagement and involvement adopted. Based on our findings, we discussed the opportunities to support children with chronic illnesses through mobile apps, design for dual use, and design for age appropriateness and digital health safety. This study provides insights and recommendations for app designers, health researchers, and policymakers on strategies for engaging children and parents while also promoting childrens health and wellbeing through mobile technology
Spatial distribution pattern of mustelids in the eastern edge of the QinghaiâTibet Plateau
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 2017â2021. 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 Ricklefâs 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
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
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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