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The stochastic gravitational wave background (SGWB) provides a unique opportunity to probe the early Universe, potentially encoding information about the primordial curvature power spectrum and the energy scale of reheating. Recent observations by collaborations such as NANOGrav, PPTA, EPTA+InPTA, and CPTA have detected a stochastic common-spectrum signal, which may originate from scalar-induced gravitational waves (SIGWs) generated by primordial curvature perturbations during inflation. In this study, we explore the hypothesis that the NANOGrav signal is sourced by SIGWs and aim to constrain the shape of the primordial curvature power spectrum and the reheating energy scale using the NANOGrav 15-year data set. We model the primordial curvature power spectrum with a lognormal form and focus on the case where the equation of state during reheating is $w=1/6$, corresponding to an inflaton potential $V(\phi) \sim \phi^{14/5}$. Employing Bayesian inference, we obtain posterior distributions for the lognormal power spectrum parameters and the reheating temperature. Our results indicate a narrow peak in the primordial power spectrum ($\Delta < 0.001$ at 90\% confidence) and a lower bound on the reheating temperature ($T_{\rm rh} \geq 0.1 {\rm GeV}$), consistent with Big Bang Nucleosynthesis constraints. The best-fit SIGW energy density spectrum exhibits a distinct turning point around $f \sim 10^{-8.1}\,{\rm Hz}$, corresponding to the transition from reheating to the radiation-dominated era. This feature, combined with the sharp high-frequency decrease due to the narrow primordial power spectrum peak, offers a unique signature for probing early Universe properties., Comment: 18 pages, 3 figures

We present our optical observations and multi-wavelength analysis of the GRB\,200613A detected by \texttt{Fermi} satellite. Time-resolved spectral analysis of the prompt $\gamma$-ray emission was conducted utilizing the Bayesian block method to determine statistically optimal time bins. Based on the Bayesian Information Criterion (BIC), the data generally favor the Band+Blackbody (short as BB) model. We speculate that the main Band component comes from the Blandford-Znajek mechanism, while the additional BB component comes from the neutrino annihilation process. The BB component becomes significant for a low-spin, high-accretion rate black hole central engine, as evidenced by our model comparison with the data. The afterglow light curve exhibits typical power-law decay, and its behavior can be explained by the collision between the ejecta and constant interstellar medium (ISM). Model fitting yields the following parameters: $E_{K,iso} = (2.04^{+11.8}_{-1.50})\times 10^{53}$ erg, $\Gamma_0=354^{+578}_{-217}$, $p=2.09^{+0.02}_{-0.03}$, $n_{18}=(2.04^{+9.71}_{-1.87})\times 10^{2}$ cm$^{-3}$, $\theta_j=24.0^{+6.50}_{-5.54}$ degree, $\epsilon_e=1.66^{+4.09}_{-1.39})\times 10^{-1}$ and $\epsilon_B=(7.76^{+48.5}_{-5.9})\times 10^{-6}$. In addition, we employed the public Python package \texttt{Prospector} perform a spectral energy distribution (SED) modeling of the host galaxy. The results suggest that the host galaxy is a massive galaxy ($\log(M_\ast / M_\odot)=11.75^{+0.10}_{-0.09}$) with moderate star formation rate ($\mbox{SFR}=22.58^{+13.63}_{-7.22} M_{\odot}$/yr). This SFR is consistent with the SFR of $\sim 34.2 M_{\odot}$ yr$^{-1}$ derived from the [OII] emission line in the observed spectrum., Comment: 30 pages, 16 figures, accepted by ApJ

Synthetic Lethal (SL) relationships, though rare among the vast array of gene combinations, hold substantial promise for targeted cancer therapy. Despite advancements in AI model accuracy, there is still a significant need among domain experts for interpretive paths and mechanism explorations that align better with domain-specific knowledge, particularly due to the high costs of experimentation. To address this gap, we propose an iterative Human-AI collaborative framework with two key components: 1) Human-Engaged Knowledge Graph Refinement based on Metapath Strategies, which leverages insights from interpretive paths and domain expertise to refine the knowledge graph through metapath strategies with appropriate granularity. 2) Cross-Granularity SL Interpretation Enhancement and Mechanism Analysis, which aids experts in organizing and comparing predictions and interpretive paths across different granularities, uncovering new SL relationships, enhancing result interpretation, and elucidating potential mechanisms inferred by Graph Neural Network (GNN) models. These components cyclically optimize model predictions and mechanism explorations, enhancing expert involvement and intervention to build trust. Facilitated by SLInterpreter, this framework ensures that newly generated interpretive paths increasingly align with domain knowledge and adhere more closely to real-world biological principles through iterative Human-AI collaboration. We evaluate the framework's efficacy through a case study and expert interviews.

Existing Masked Image Modeling (MIM) depends on a spatial patch-based masking-reconstruction strategy to perceive objects'features from unlabeled images, which may face two limitations when applied to chest CT: 1) inefficient feature learning due to complex anatomical details presented in CT images, and 2) suboptimal knowledge transfer owing to input disparity between upstream and downstream models. To address these issues, we propose a new MIM method named Tissue-Contrastive Semi-Masked Autoencoder (TCS-MAE) for modeling chest CT images. Our method has two novel designs: 1) a tissue-based masking-reconstruction strategy to capture more fine-grained anatomical features, and 2) a dual-AE architecture with contrastive learning between the masked and original image views to bridge the gap of the upstream and downstream models. To validate our method, we systematically investigate representative contrastive, generative, and hybrid self-supervised learning methods on top of tasks involving segmenting pneumonia, mediastinal tumors, and various organs. The results demonstrate that, compared to existing methods, our TCS-MAE more effectively learns tissue-aware representations, thereby significantly enhancing segmentation performance across all tasks.

The growing tensions between the early Universe and the late Universe increasingly highlight the importance of developing precise probes for late cosmology. As significant late-Universe probes, Type Ia supernovae (SNe Ia) and gravitational waves (GWs) can provide measurements of relative and absolute distances, respectively. Their complementary nature is likely to break the degeneracies among cosmological parameters, thereby yielding more precise constraints. In this study, we use 43 gravitational-wave sources from the Third LIGO-Virgo-KAGRA Gravitational-Wave Transient Catalog (GWTC-3) and 1590 SNe Ia from Pantheon+ compilation to constrain the dark energy models, as an attempt to achieve precise late-Universe cosmological constraints. For the dark siren GW event, we estimate the corresponding redshift using the binary black hole redshift distribution model. The combination of GW and SNe Ia data could provide the precision on the Hubble constant (H0) and the present matter density (Omega_m) of approximately 20% and 8% for the LambdaCDM model. If we consider the equation of state of dark energy (w), the combination sample constrains the precision of w to approximately 30%. Although the combination of GW and SNe Ia observations effectively breaks degeneracies among various cosmological parameters, yielding more stringent constraints, the precision of these constraints still does not meet the stringent standards required by precision cosmology. However, it is reasonable to anticipate that, in the near future, the joint observations of GWs and SNe Ia will become a powerful tool, particularly in the late Universe, for the precise measurement of cosmological parameters., Comment: 14 pages, 3 figures

The term credential encompasses educational certificates, degrees, certifications, and government-issued licenses. An occupational credential is a verification of an individuals qualification or competence issued by a third party with relevant authority. Job seekers often leverage such credentials as evidence that desired qualifications are satisfied by their holders. Many U.S. education and workforce development organizations have recognized the importance of credentials for employment and the challenges of understanding the value of credentials. In this study, we identified and ontologically defined credential and credential-related terms at the textual and semantic levels based on the Occupation Ontology (OccO), a BFO-based ontology. Different credential types and their authorization logic are modeled. We additionally defined a high-level hierarchy of credential related terms and relations among many terms, which were initiated in concert with the Alabama Talent Triad (ATT) program, which aims to connect learners, earners, employers and education/training providers through credentials and skills. To our knowledge, our research provides for the first time systematic ontological modeling of the important domain of credentials and related contents, supporting enhanced credential data and knowledge integration in the future., Comment: 11

This paper introduces an astronomical image alignment algorithm. This algorithm uses the means of the rows and columns of the original image for alignment, and finds the optimal offset corresponding to the maximum similarity by comparing different offsets between images. The similarity is evaluated by the standard deviation of the quotient divided by the means. This paper also discusses the theoretical feasibility of this algorithm. Through practical testing, it has been confirmed that the algorithm is fast and robust., Comment: 7 figures

Giant planets like Jupiter and Saturn, play important roles in the formation and habitability of Earth-like planets. The detection of solar system analogs that have multiple cold giant planets is essential for our understanding of planet habitability and planet formation. Although transit surveys such as Kepler and TESS have discovered thousands of exoplanets, these missions are not sensitive to long period planets due to their limited observation baseline. The Tianyu project, comprising two 1-meter telescopes (Tianyu-I and II), is designed to detect transiting cold giant planets in order to find solar system analogs. Featuring a large field of view and equipped with a high-speed CMOS camera, Tianyu-I will perform a high-precision photometric survey of about 100 million stars, measuring light curves at hour-long cadence. The candidates found by Tianyu-I will be confirmed by Tianyu-II and other surveys and follow-up facilities through multi-band photometry, spectroscopy, and high resolution imaging. Tianyu telescopes will be situated at an elevation about 4000 meters in Lenghu, China. With a photometric precision of 1% for stars with V < 18 mag, Tianyu is expected to find more than 300 transiting exoplanets, including about 12 cold giant planets, over five years. A five-year survey of Tianyu would discover 1-2 solar system analogs. Moreover, Tianyu is also designed for non-exoplanetary exploration, incorporating multiple survey modes covering timescales from sub-seconds to months, with a particular emphasis on events occurring within the sub-second to hour range. It excels in observing areas such as infant supernovae, rare variable stars and binaries, tidal disruption events, Be stars, cometary activities, and interstellar objects. These discoveries not only enhance our comprehension of the universe but also offer compelling opportunities for public engagement in scientific exploration., Comment: 48 pages, 16 figures, accepted by Acta Astronomica Sinica

A distinct feature of Hermitian quantum chaotic dynamics is the exponential increase of certain out-of-time-order-correlation (OTOC) functions around the Ehrenfest time with a rate given by a Lyapunov exponent. Physically, the OTOCs describe the growth of quantum uncertainty that crucially depends on the nature of the quantum motion. Here, we employ the OTOC in order to provide a precise definition of dissipative quantum chaos. For this purpose, we compute analytically the Lyapunov exponent for the vectorized formulation of the large $q$-limit of a $q$-body Sachdev-Ye-Kitaev model coupled to a Markovian bath. These analytic results are confirmed by an explicit numerical calculation of the Lyapunov exponent for several values of $q \geq 4$ based on the solutions of the Schwinger-Dyson and Bethe-Salpeter equations. We show that the Lyapunov exponent decreases monotonically as the coupling to the bath increases and eventually becomes negative at a critical value of the coupling signaling a transition to a dynamics which is no longer quantum chaotic. Therefore, a positive Lyapunov exponent is a defining feature of dissipative many-body quantum chaos. The observation of the breaking of the exponential growth for sufficiently strong coupling suggests that dissipative quantum chaos may require in certain cases a sufficiently weak coupling to the environment., Comment: 32 pages, 4 figures, we have added references and made minor corrections

We present 206 unpublished optical spectra of 104 type II supernovae obtained by the Xinglong 2.16m telescope and Lijiang 2.4m telescope during the period from 2011 to 2018, spanning the phases from about 1 to 200 days after the SN explosion. The spectral line identifications, evolution of line velocities and pseudo equivalent widths, as well as correlations between some important spectral parameters are presented. Our sample displays a large range in expansion velocities. For instance, the Fe~{\sc ii} $5169$ velocities measured from spectra at $t\sim 50$ days after the explosion vary from ${\rm 2000\ km\ s^{-1}}$ to ${\rm 5500\ km\ s^{-1}}$, with an average value of ${\rm 3872 \pm 949\ km\ s^{-1}}$. Power-law functions can be used to fit the velocity evolution, with the power-law exponent quantifying the velocity decline rate. We found an anticorrelation existing between H$\beta$ velocity at mid-plateau phase and its velocity decay exponent, SNe II with higher velocities tending to have smaller velocity decay rate. Moreover, we noticed that the velocity decay rate inferred from the Balmer lines (i.e., H$\alpha$ and H$\beta$) have moderate correlations with the ratio of absorption to emission for H$\alpha$ (a/e). In our sample, two objects show possibly flash-ionized features at early phases. Besides, we noticed that multiple high-velocity components may exist on the blue side of hydrogen lines of SN 2013ab, possibly suggesting that these features arise from complex line forming region. All our spectra can be found in WISeREP and Zenodo.

Photometric stellar surveys now cover a large fraction of the sky, probe to fainter magnitudes than large-scale spectroscopic surveys, and are relatively free from the target-selection biases often associated with such studies. Photometric-metallicity estimates that include narrow/medium-band filters can achieve comparable accuracy and precision to existing low-resolution spectroscopic surveys such as SDSS/SEGUE and LAMOST. Here we report on an effort to identify likely members of the Galactic disk system among the very metal-poor (VMP; [Fe/H] $\leq$ --2) and extremely metal-poor (EMP; [Fe/H] $\leq$ --3) stars. Our analysis is based on an initial sample of $\sim11.5$ million stars with full space motions selected from the SkyMapper Southern Survey (SMSS) and Stellar Abundance and Galactic Evolution Survey (SAGES). After applying a number of quality cuts to obtain the best available metallicity and dynamical estimates, we analyze a total of $\sim$5.86 million stars in the combined SMSS/SAGES sample. We employ two techniques that, depending on the method, identify between 876 and 1,476 VMP stars (6.9%-11.7% of all VMP stars) and between 40 and 59 EMP stars (12.4%-18.3% of all EMP stars) that appear to be members of the Galactic disk system on highly prograde orbits (v$_{\phi} > 150$ km/s). The total number of candidate VMP/EMP disk-like stars is 1,496, the majority of which have low orbital eccentricities, ecc $\le 0.4$; many have ecc $\le 0.2$. The large fractions of VMP/EMP stars associated with the Milky Way disk system strongly suggest the presence of an early forming ``primordial" disk., Comment: It is now accepted to the ApJS

We report the confirmation of a sub-Saturn-size exoplanet, TOI-1194 b with a mass about $0.456_{-0.051}^{+0.055}$ $M_{J}$, and a very low mass companion star with a mass of about $96.5\pm1.5$ $M_J$, TOI-1251 B. Exoplanet candidates provided by the Transiting Exoplanet Survey Satellite (TESS) are suitable for further follow-up observations by ground-based telescopes with small and medium apertures. The analysis is performed based on data from several telescopes worldwide, including telescopes in the Sino-German multiband photometric campaign, which aimed at confirming TESS Objects of Interest (TOIs) using ground-based small-aperture and medium-aperture telescopes, especially for long-period targets. TOI-1194 b is confirmed based on the consistent periodic transits depths from the multiband photometric data. We measure an orbital period of $2.310644\pm0.000001$ d, and radius is $0.767_{-0.041}^{+0.045}$ $R_J$, and amplitude of RV curve is $69.4_{-7.3}^{+7.9}$ m/s. TOI-1251 B is confirmed based on the multiband photometric and high-resolution spectroscopic data, whose orbiting period is $5.963054_{-0.000001}^{+0.000002}$ d, the radius is $0.947_{-0.033}^{+0.035}$ $R_J$, and amplitude of RV curve is $9849_{-40}^{+42}$ m/s., Comment: 28 pages, 8 figures, Accepted by RAA on Oct. 18th, 2023

Hypothetical induction is recognized as the main reasoning type when scientists make observations about the world and try to propose hypotheses to explain those observations. Past research on hypothetical induction is under a constrained setting: (1) the observation annotations in the dataset are carefully manually handpicked sentences (resulting in a close-domain setting); and (2) the ground truth hypotheses are mostly commonsense knowledge, making the task less challenging. In this work, we tackle these problems by proposing the first dataset for social science academic hypotheses discovery, with the final goal to create systems that automatically generate valid, novel, and helpful scientific hypotheses, given only a pile of raw web corpus. Unlike previous settings, the new dataset requires (1) using open-domain data (raw web corpus) as observations; and (2) proposing hypotheses even new to humanity. A multi-module framework is developed for the task, including three different feedback mechanisms to boost performance, which exhibits superior performance in terms of both GPT-4 based and expert-based evaluation. To the best of our knowledge, this is the first work showing that LLMs are able to generate novel (''not existing in literature'') and valid (''reflecting reality'') scientific hypotheses., Comment: Accepted by ACL 2024 (findings)

Serial femtosecond crystallography at X-ray free electron laser facilities opens a new era for the determination of crystal structure. However, the data processing of those experiments is facing unprecedented challenge, because the total number of diffraction patterns needed to determinate a high-resolution structure is huge. Machine learning methods are very likely to play important roles in dealing with such a large volume of data. Convolutional neural networks have made a great success in the field of pattern classification, however, training of the networks need very large datasets with labels. Th is heavy dependence on labeled datasets will seriously restrict the application of networks, because it is very costly to annotate a large number of diffraction patterns. In this article we present our job on the classification of diffraction pattern by weakly supervised algorithms, with the aim of reducing as much as possible the size of the labeled dataset required for training. Our result shows that weakly supervised methods can significantly reduce the need for the number of labeled patterns while achieving comparable accuracy to fully supervised methods., Comment: $\copyright$ 2023 Optica Publishing Group. Users may use, reuse, and build upon the article, or use the article for text or data mining, so long as such uses are for non-commercial purposes and appropriate attribution is maintained. All other rights are reserved. Link for fulltext: https://opg.optica.org/oe/fulltext.cfm?uri=oe-31-20-32909&id=538502

In this paper, a total of approximately 2.6 million dwarfs were constructed as standard stars, with an accuracy of about 0.01-0.02 mag for each band, by combining spectroscopic data from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope Data Release 7, photometric data from the corrected Gaia Early Data Release 3, and photometric metallicities. Using the spectroscopy based stellar color regression method (SCR method) and the photometric-based SCR method (SCR' method), we performed the relative calibration of the Nanshan One-meter Wide-field Telescope imaging data. Based on the corrected Pan-STARRS DR1 photometry, the absolute calibration was also performed. In the photometric calibration process, we analyzed the dependence of the calibration zero points on different images (observation time), different gates of the CCD detector, and different CCD positions. We found that the stellar flat and the relative gain between different gates depend on time. The amplitude of gain variation in three channels is approximately 0.5%-0.7% relative to the other channel, with a maximum value of 4%. In addition, significant spatial variations of the stellar flat fitting residual are found and corrected. Using repeated sources in the adjacent images, we checked and discovered internal consistency of about 1-2 mmag in all the filters. Using the PS1 magnitudes synthesized by Gaia DR3 BP/RP spectra by the synthetic photometry method, we found that the photometric calibration uniformity is about 1-2 mmag for all the bands, at a spatial resolution of 1.3 degree. A detailed comparison between the spectroscopy-based SCR and photometric-based SCR method magnitude offsets was performed, and we achieved an internal consistency precision of about 2 mmag or better with resolutions of 1.3 degree for all the filters. Which is mainly from the position-dependent errors of the E(B-V) used in SCR' method., Comment: 15 pages in Chinese language, 8 figures, Chinese Science Bulletin accepted and published online (https://www.sciengine.com/CSB/doi/10.1360/TB-2023-0052), see main results in Figures 6, 7 and 8

We present precise photometric estimates of stellar parameters, including effective temperature, metallicity, luminosity classification, distance, and stellar age, for nearly 26 million stars using the methodology developed in the first paper of this series, based on the stellar colors from the Stellar Abundances and Galactic Evolution Survey (SAGES) DR1 and Gaia EDR3. The optimal design of stellar-parameter sensitive $uv$ filters by SAGES has enabled us to determine photometric-metallicity estimates down to $-3.5$, similar to our previous results with the SkyMapper Southern Survey (SMSS), yielding a large sample of over five million metal-poor (MP; [Fe/H]$\le -1.0$) stars and nearly one million very metal-poor (VMP; [Fe/H]$\le -2.0$) stars. The typical precision is around $0.1$ dex for both dwarf and giant stars with [Fe/H]$>-1.0$, and 0.15-0.25/0.3-0.4 dex for dwarf/giant stars with [Fe/H]$<-1.0$. Using the precise parallax measurements and stellar colors from Gaia, effective temperature, luminosity classification, distance and stellar age are further derived for our sample stars. This huge data set in the Northern sky from SAGES, together with similar data in the Southern sky from SMSS, will greatly advance our understanding of the Milky Way, in particular its formation and evolution., Comment: 14 pages, 14 figures, 3 tables, accepted by ApJ. arXiv admin note: text overlap with arXiv:2104.14154

The Stellar Abundances and Galactic Evolution Survey (SAGES) of the northern sky is a specifically-designed multi-band photometric survey aiming to provide reliable stellar parameters with accuracy comparable to those from low-resolution optical spectra. It was carried out with the 2.3-m Bok telescope of Steward Observatory and three other telescopes. The observations in the $u_s$ and $v_s$ passband produced over 36,092 frames of images in total, covering a sky area of $\sim9960$ degree$^2$. The median survey completeness of all observing fields for the two bands are of $u_{\rm s}=20.4$ mag and $v_s=20.3$ mag, respectively, while the limiting magnitudes with signal-to-noise ratio (S/N) of 100 are $u_s\sim17$ mag and $v_s\sim18$ mag, correspondingly. We combined our catalog with the data release 1 (DR1) of the first of Panoramic Survey Telescope And Rapid Response System (Pan-STARRS1, PS1) catalog, and obtained a total of 48,553,987 sources which have at least one photometric measurement in each of the SAGES $u_s$ and $v_s$ and PS1 $grizy$ passbands, which is the DR1 of SAGES and it will be released in our paper. We compare our $gri$ point-source photometry with those of PS1 and found an RMS scatter of $\sim2$% in difference of PS1 and SAGES for the same band. We estimated an internal photometric precision of SAGES to be on the order of $\sim1$%. Astrometric precision is better than $0^{\prime\prime}.2$ based on comparison with the DR1 of Gaia mission. In this paper, we also describe the final end-user database, and provide some science applications., Comment: 49 pages, 21 figures, 5 table, accepted for publication in ApJS

Understanding the relationship between micromechanics and macroscopic plastic deformation is vital for elucidating the deformation mechanism of amorphous solids, such as granular materials. In this study, we directly measure T1 events, which are topological rearrangements of particles, and the associated microscopic stresses in dense packings of photoelastic disks under pure shear. We observe a remarkable similarity between the evolution of the total number of T1 events and the global stress-strain curve. The competition between the birth and death of T1 events establishes a dynamic equilibrium after the yield strain, contributing to the overall plastic behavior. Despite the erratic stress fluctuations of individual T1 events, the local stresses decrease on average once T1 events occur, indicating their soft characteristics. Furthermore, we demonstrate that the microscopic stress fluctuations exhibit a long-range anisotropic spatial correlation similar to the Eschelby character, but with a distinct scaling of $r^{-1.5}$. Interestingly, we also find a striking similarity in the correlation functions of T1 and non-T1 regions. These findings establish a significant connection between macroscopic mechanical behavior and the elementary deformation of T1 events, shedding light on the fundamental understanding of granular materials as amorphous solids with contact-scale plastic deformation.

Genes are fundamental for analyzing biological systems and many recent works proposed to utilize gene expression for various biological tasks by deep learning models. Despite their promising performance, it is hard for deep neural networks to provide biological insights for humans due to their black-box nature. Recently, some works integrated biological knowledge with neural networks to improve the transparency and performance of their models. However, these methods can only incorporate partial biological knowledge, leading to suboptimal performance. In this paper, we propose the Biological Factor Regulatory Neural Network (BFReg-NN), a generic framework to model relations among biological factors in cell systems. BFReg-NN starts from gene expression data and is capable of merging most existing biological knowledge into the model, including the regulatory relations among genes or proteins (e.g., gene regulatory networks (GRN), protein-protein interaction networks (PPI)) and the hierarchical relations among genes, proteins and pathways (e.g., several genes/proteins are contained in a pathway). Moreover, BFReg-NN also has the ability to provide new biologically meaningful insights because of its white-box characteristics. Experimental results on different gene expression-based tasks verify the superiority of BFReg-NN compared with baselines. Our case studies also show that the key insights found by BFReg-NN are consistent with the biological literature.