Boson Star Normal Modes

Boson stars are gravitationally bound objects that arise in ultralight dark matter models and form in the centers of galactic halos or axion miniclusters. We systematically study the excitations of a boson star, taking into account the mixing between positive and negative frequencies introduced by gravity. We show that the spectrum contains zero-energy modes in the monopole and dipole sectors resulting from spontaneous symmetry breaking by the boson star background. We analyze the general properties of the eigenmodes and derive their orthogonality and completeness conditions which have non-standard form due to the positive-negative frequency mixing. The eigenvalue problem is solved numerically for the first few energy levels in different multipole sectors and the results are compared to the solutions of the Schr\"odinger equation in fixed boson star gravitational potential. The two solutions differ significantly for the lowest modes, but get close for higher levels. We further confirm the normal mode spectrum in 3D wave simulations where we inject perturbations with different multipoles. As an application of the normal mode solutions, we compute the matrix element entering the evaporation rate of a boson star immersed in a hot axion gas. The computation combines the use of exact wavefunctions for the low-lying bound states and of the Schr\"odinger approximation for the high-energy excitations.Comment: 33 pages, 21 figure

Mutation of SLC35D3 causes metabolic syndrome by impairing dopamine signaling in striatal D1 neurons

We thank Dr. Ya-Qin Feng from Shanxi Medical University, Dr. Tian-Yun Gao from Nanjing University and Dr. Yan-Hong Xue from Institute of Biophysics (CAS) for technical assistance in this study. We are very thankful to Drs. Richard T. Swank and Xiao-Jiang Li for their critical reading of this manuscript and invaluable advice. Funding: This work was partially supported by grants from National Basic Research Program of China (2013CB530605; 2014CB942803), from National Natural Science Foundation of China 1230046; 31071252; 81101182) and from Chinese Academy of Sciences (KSCX2-EW-R-05, KJZD-EW-L08). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD

Influences of commuting mode, air conditioning mode and meteorological parameters on fine particle (PM2.5) exposure levels in traffic microenvironments

With the aim of determining the impacts of various factors on commuter exposure to fine particulate matter (PM2.5), a series of field studies were carried out to measure commuter exposure to PM2.5 on six major commuting modes (in-cabin mode: bus, taxi and metro; on-roadway mode: walking, bicycle and motorcycle) in a highly industrialized city in the Pearl River Delta, China. The results showed that the exposure level was greatly influenced by the commuter mode, with the on-roadway mode showing a higher PM2.5 concentration (76 μg/m3). An experiment with the taxi mode suggested that the use of air-conditioning can effectively reduce exposure levels in most cases (by at least 83%). Apart from traffic-related emissions, ambient PM2.5 concentration also had important impacts on exposure levels in most commuting modes, which was further ascertained by the seasonal variations in exposure levels and their significant correlations (p < 0.05) with meteorological parameters (temperature, relative humidity, wind speed and direction). The results of a General Linear Model analysis show that temperature, traffic mode and wind speed were significant factors that explained 27.3% of variability for the in-cabin mode, while relative humidity and wind speed were the significant determinants for the on-roadway mode, which contributed 14.1% of variability. In addition, wind direction was also an important determinant for both in-cabin and on-roadway modes. This study has some valuable implications that can help commuters to adopt appropriate travel behavior to reduce their personal exposure to such pollutants

RQ-RAG: Learning to Refine Queries for Retrieval Augmented Generation

Large Language Models (LLMs) exhibit remarkable capabilities but are prone to generating inaccurate or hallucinatory responses. This limitation stems from their reliance on vast pretraining datasets, making them susceptible to errors in unseen scenarios. To tackle these challenges, Retrieval-Augmented Generation (RAG) addresses this by incorporating external, relevant documents into the response generation process, thus leveraging non-parametric knowledge alongside LLMs' in-context learning abilities. However, existing RAG implementations primarily focus on initial input for context retrieval, overlooking the nuances of ambiguous or complex queries that necessitate further clarification or decomposition for accurate responses. To this end, we propose learning to Refine Query for Retrieval Augmented Generation (RQ-RAG) in this paper, endeavoring to enhance the model by equipping it with capabilities for explicit rewriting, decomposition, and disambiguation. Our experimental results indicate that our method, when applied to a 7B Llama2 model, surpasses the previous state-of-the-art (SOTA) by an average of 1.9\% across three single-hop QA datasets, and also demonstrates enhanced performance in handling complex, multi-hop QA datasets. Our code is available at https://github.com/chanchimin/RQ-RAG

ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debate

Text evaluation has historically posed significant challenges, often demanding substantial labor and time cost. With the emergence of large language models (LLMs), researchers have explored LLMs' potential as alternatives for human evaluation. While these single-agent-based approaches show promise, experimental results suggest that further advancements are needed to bridge the gap between their current effectiveness and human-level evaluation quality. Recognizing that best practices of human evaluation processes often involve multiple human annotators collaborating in the evaluation, we resort to a multi-agent debate framework, moving beyond single-agent prompting strategies. The multi-agent-based approach enables a group of LLMs to synergize with an array of intelligent counterparts, harnessing their distinct capabilities and expertise to enhance efficiency and effectiveness in handling intricate tasks. In this paper, we construct a multi-agent referee team called ChatEval to autonomously discuss and evaluate the quality of generated responses from different models on open-ended questions and traditional natural language generation (NLG) tasks. Our analysis shows that ChatEval transcends mere textual scoring, offering a human-mimicking evaluation process for reliable assessments. Our code is available at https://github.com/chanchimin/ChatEval

The blood parameters and liver function changed inconsistently among children between burns and traumatic injuries

Objective Burn and traumatic injury are two kinds of injury by modality. They cause acute phase response and lead to a series of pathological and physiological changes. In this study, we explored whether there are differences in routine blood parameters and liver enzyme levels between burned and traumatically injured children. Methods Patients under 18 years old with injuries were recruited. Their demographic and clinical data were recorded. Collected clinical data included routine blood parameters (white blood cell count (WBC), red blood cell count (RBC), platelets (PLT), hemoglobin (HB)), serological enzyme levels (alanine aminotransferase (ALT), aspartate transaminase (AST), glutamyltransferase (GGT), alkaline phosphatase (ALP), cholinesterase (CHE)), and total protein (TP) levels (albumin (ALB), globulin (GLB)). A generalized linear model and multivariate analysis of variance were used to conduct comparisons. Results A total of 162 children (109 with burns and 53 with traumatic injuries) with a mean age of 4.36 ± 4.29 years were enrolled in the study. Burned children had higher levels of RBC, HB, WBC, AST and lower levels of TP, CHE, ALB than traumatically injured children (P < 0.05). Moreover, the concentration of WBC and HB was higher in males compared to females (P < 0.001). Conversely, the level of AST and TP in males was lower, AST levels were significantly lower in males (P = 0.005). Age positively correlated with the levels of HB, AST and TP (P < 0.001), and negatively correlated with WBC (P < 0.001). With decreasing body mass index (BMI), the levels of WBC, HB, AST and TP significantly increased in both groups of injured children (P < 0.001). In addition, ISS was positively correlated with WBC and HB levels (P < 0.001), but negatively correlated with AST and TP levels (P < 0.001). Conclusions Children with burn injuries suffered a greater acute response and liver damage than traumatically injured children. This may in part underlie clinical observations of differences in children morbidity and mortality in response to different injury types

COVID-19 Vaccination Preferences of University Students and Staff in Hong Kong

IMPORTANCE: COVID-19 has required universities to rapidly develop vaccination policies for students and staff, yet little is known about the preferences of these individuals toward vaccination. OBJECTIVE: To quantify student and staff preferences for COVID-19 vaccination at a university in Hong Kong. DESIGN, SETTING, AND PARTICIPANTS: A cross-sectional online survey study was conducted from July 20 to September 21, 2021, before the announcement of a campus-wide vaccine mandate. A survey of 42 451 eligible university students and staff used discrete-choice experiment methods to quantify 7 attributes of COVID-19 vaccination: risk of a mild or moderate adverse event after vaccination, risk of a severe adverse event after vaccination, efficacy against COVID-19 infection, efficacy against severe manifestation of COVID-19 infection, duration of protection after vaccination, incentive for completing vaccination, and out-of-pocket costs. MAIN OUTCOMES AND MEASURES: A mixed logit regression model was used to estimate the preferences of attributes for COVID-19 vaccines and marginal willingness to pay (mWTP) adjusted for background characteristics, role, vaccination, and COVID-19 infection status of family or friends, adverse event status after vaccination among family and friends of participants, and scenario block. RESULTS: Among 42 451 eligible university students and staff invited, 3423 individuals completed the survey (mean [SD] age, 27.1 [9.9] years; 2053 [60.0%] women). Participants included 2506 students (73.2%) and 917 staff (26.8%), with a response rate of 8.1%. Quarantine-free travel was preferred (β = 0.86; 95% CI, 0.72-0.99; mWTP: $235.9; 95$190.3-$294.2), followed by efficacy against any COVID-19 infection (β = 0.30; 95$84.1; 95% CI, $71.8-$100.8), against severe manifestation of COVID-19 infection (β = 0.25; 95% CI, 0.24-0.27; mWTP: $69.7; 95$465-$653), and risk of severe adverse events following vaccination (β = −0.24; 95$66.8; 95% CI, −$81.5 to −$55.3). Participants were less concerned about protection duration (β = 0.17; 95% CI, 0.15-0.18; mWTP: $46.0; 95$38.6-$56.2) and risk of mild to moderate adverse events (β = −0.12; 95$32.7; 95% CI, −$41.2 to −$26.4). CONCLUSIONS AND RELEVANCE: Preference of all attributes were significant and were considered important by the participants for vaccine decision-making. Insights drawn could assist policy makers in future vaccination decisions, such as campus vaccine mandate and requirement of a third dose