Red supergiants (RSGs) are essential to understanding the evolution and the contribution to the interstellar medium of massive stars. However, the number of identified RSGs within the Milky Way is still limited mainly due to the difficulty of measuring stellar extinction and distance. The release of approximately one million RVS spectra in Gaia DR3 presents new opportunity for identifying Galactic RSGs, because the equivalent width of the calcium triplet lines (EW(CaT)) in the spectra is an excellent indicator of stellar surface gravity. This work uses the RVS spectra with signal-to-noise ratio (SNR) greater than 100 to search for the Galactic RSGs. The dwarf stars and red giants are removed and the RSG candidates are selected by the location in the EW(CaT) vs. BP-RP diagram. The early-type RSG candidates (K0-M2) are then identified by BP-RP > 1.584 and EW(CaT) > 1.1 nm. To identify late-type RSG candidates (after M2), the criteria of the average equivalent widths of TiO in the XP spectra (EW(TiO)) > 10 nm, the color index K-W3 < 0.5 and the period-amplitude sequence from Gaia DR3 LPV catalog are further applied to reduce the contamination of late-type red giants and asymptotic giant branch stars. This method yields 30 early-type (K0-M2) and 6196 late-type (after M2) RSG candidates, which is a significant increase to the present Galactic RSG sample. The application of this approach to the spectra with SNR > 50 results in 48 early-type and 11,491 late-type RSG candidates. This preliminary analysis paves the way for more extensive research with Gaia DR4 when larger spectral datasets are expected to significantly enhance our understanding of Galactic RSG populations.

Fast radio bursts (FRBs) are widely considered to originate from magnetars that power the explosion through releasing magnetic energy. Active repeating FRBs have been seen to produce hundreds of bursts per hour and can stay active for months, thus may provide stringent constraints on the energy budget of FRBs' central engine. Within a time span of 214 days, we detected 11,553 bursts from the hyper-active FRB 20240114A that reached a peak burst rate of 729 hr$^{-1}$. This is the largest burst sample from any single FRB source, exceeding the cumulative total of all published bursts from all known FRBs to date. Assuming typical values of radio efficiency and beaming factor, the estimated total isotropic burst energy of this source exceeds 86% of the dipolar magnetic energy of a typical magnetar. The total released energy from this source exceeds that of other known repeaters by about one and a half orders of magnitude, yielding the most stringent lower limit of $4.7\times10^{32}$ G cm$^3$ for the magnetar's magnetic moment. The source remained active at the end of this observation campaign. Our findings thus require either the FRB's central magnetar engine's possessing exceptionally high emission efficiency or a more powerful compact object than a typical magnetar.

Blazars are often observed to flare across multiple wavelengths. Orphan flares from blazars have been only detected a few times, providing an opportunity to understand the structure of the jet in the accreting system. We report a remarkable orphan X-ray flare from a blazar candidate EP240709a, detected by Einstein Probe (EP) in July 2024. The multi-band spectral properties and variability support EP240709a as a high-energy peaked BL Lacertae-type object. The flux in 0.5-10 keV increases by at least 28 times to the value of low state in 2020, with non-detection of remarkable flaring in other bands during the same period. EP240709a exhibits the harder-when-brighter tendency in the X-ray band during the orphan flare, while its infrared-optical spectra are featureless. We employ one-zone and two-zone leptonic synchrotron self-Compton models to perform the spectral energy distribution fitting. Detecting this rare orphan flare shows the potential of EP in discovering peculiar activities from AGN in high-cadence X-ray sky surveys.

The granulation of red supergiants (RSGs) in the Magellanic Clouds are systematically investigated by combining the latest RSGs samples and light curves from the Optical Gravitational Lensing Experiment and the All-Sky Automated Survey for Supernovae. The present RSGs samples are firstly examined for foreground stars and possible misidentified sources, and the light curves are sequentially checked to remove the outliers by white noise and photometric quality. The Gaussian Process regression is used to model the granulation, and the Markov Chain Monte Carlo is applied to derive the granulation amplitude $\sigma$ and the period of the undamped oscillator $\rho$, as well as the damping timescale $\tau$. The dimensionless quality factor $Q$ is then calculated through $Q=\pi \tau/\rho$. RSGs around $Q = 1/\sqrt{2}$ are considered to have significant granulation signals and are used for further analysis. Combining granulation parameters with stellar parameters, robust scaling relations for the timescale $\rho$ are established, while the scaling relations for amplitude $\sigma$ are represented by a piecewise function, possibly related to the tendency of amplitudes in faint RSGs to converge towards a certain value. Comparing results between the SMC and LMC confirms that amplitudes and timescales become larger with metallicity. In examining the scaling relations between the two galaxies, it is found that $\rho$ is nearly independent of metallicity, whereas $\sigma$ is more significantly affected by metallicity. The Gaussian Process method is compared with the periodogram fitting of the granulations, and the advantages of either are discussed.

We report on a comprehensive multi-wavelength study of the pulsars in the globular cluster (GC) M5, including the discovery of M5G, a new compact non-eclipsing "black widow" pulsar. Thanks to the analysis of 34 years of radio data taken with the FAST and Arecibo telescopes, we obtained new phase-connected timing solutions for four pulsars in the clusters and improved those of the other three known pulsars. These have resulted in, among other things: a) much improved proper motions for five pulsars, with transverse velocities that are smaller than their respective escape velocities; b) 3-sigma and 1.5-sigma detections of Shapiro delays in M5F and M5D, respectively; c) greatly improved measurement of the periastron advance in M5B, whose value of 0.01361(6) implies that M5B is still likely to be a heavy neutron star. The binary pulsars M5D, E and F are confirmed to be in low-eccentricity binary systems, the low-mass companions of which are newly identified to be He white dwarfs using Hubble Space Telescope data. Four pulsars are also found to be associated with X-ray sources. Similarly to the eclipsing pulsar M5C, M5G shows little or no non-thermal X-ray emission, indicative of weak synchrotron radiation produced by intra-binary shocks. All the seven pulsars known in M5 have short spin periods and five are in binary systems with low orbital eccentricities. These characteristics differ from the overall GC pulsar population, but confirm the expectations for the pulsar population in a cluster with a small rate of stellar encounters per binary system.

An extinction distribution of the Andromeda Galaxy (M31) is constructed with member stars as tracers by fitting multiband photometric data from UKIRT/WFCAM, PS1, and Gaia DR3. The resulting extinction distribution covers approximately 10 deg$^2$ of M31 with a resolution of approximately 50 arcsec, providing the largest coverage to date based on stellar observations. The derived average extinction, $A_V = 1.17$ mag, agrees well with previous studies. To account for foreground extinction, an extinction map of the Milky Way toward M31 with a resolution of $\sim$ 1.7 arcmin is also constructed, yielding an average extinction of $A_V \approx 0.185$ mag. The results offer a valuable tool for extinction correction in future observations, such as those from the China Space Station Telescope, and provide insights for improving dust models based on the spatial distribution of dust in galaxies like M31.

This study investigates the metallicity distribution in M31 and M33 by using the near-infrared color index $J-K$ of tip-red-giant-branch (TRGB) of the member stars from \cite{2021ApJ...907...18R} after removing the foreground dwarf stars by the near-infrared $J-H/H-K$ diagram as well as the Gaia astrometric measurements. We employ the Voronoi binning technique to divide the galaxy into sub-regions, the PN method to determine the TRGB position in the $J-K$/$K$ diagram, and the bootstrap method to estimate the uncertainties. The TRGB positions are calculated to be $J-K = 1.195 \pm 0.002$ and $1.100 \pm 0.003$, and$K = 17.615 \pm 0.007$and$18.185 \pm 0.053$ for M31 and M33 respectively as an entity, consistent with previous results. The $J-K$ gradient of M31 is found to be $-$0.0055 kpc$^{-1}$ at $R_{\rm GC}=(0, 24)$ kpc and $-$0.0002 kpc$^{-1}$ at $R_{\rm GC}=(24, 150)$ kpc. Notably, two dust rings are evident at 11.5 kpc and 14.5 kpc, in agreement with previous studies. The $J-K$ of M33 is analyzed in four directions and generally shows a trend of gradually decreasing from the inside to the outside, however, it shows an increasing trend of 0.022 kpc$^{-1}$ in the inner 0$-$2 kpc in the west. Through the color$-$metallicity relation of TRGB, the metallicity gradient of M31 turns to be $-0.040 \pm 0.0012$ dex kpc$^{-1}$ with R_{\rm GC}&lt;30 kpc and $-0.001 \pm 0.0002$dex kpc$^{-1}$with$R_{\rm GC}>30$kpc, and for M33,$-$0.269$\pm$ 0.0206 dex kpc$^{-1}$ with R_{\rm GC}&lt;9 kpc.

The blazar sequence, including negative correlations between radiative luminosity $L_{\rm rad}$ and synchrotron peak frequency $\nu$, and between Compton dominance $Y$ and $\nu$, is widely adopted as a phenomenological description of spectral energy distributions (SEDs) of blazars, although its underlying cause is hotly debated. In particular, these correlations turn positive after correcting Doppler boosting effect. In this work, we revisit the phenomenological and intrinsic blazar sequence with three samples, which are historical sample (SEDs are built with historical data), quasi-simultaneous sample (SEDs are built with quasi-simultaneous data) and Doppler factor corrected sample (a sample with available Doppler factors), selected from literature. We find that phenomenological blazar sequence holds in historical sample, but does not exist in quasi-simultaneous sample, and intrinsic correlation between $L_{\rm rad}$ and $\nu$ becomes positive in Doppler factor corrected sample. We also analyze if the blazar sequence still exists in subclasses of blazars, i.e., flat-spectrum radio quasars and BL Lacertae objects, with different values of $Y$. To interpret these correlations, we apply a simple scaling model, in which physical parameters of the dissipation region are connected to the location of the dissipation region. We find that the model generated results are highly sensitive to the chosen ranges and distributions of physical parameters. Therefore, we suggest that even though the simple scaling model can reproduce the blazar sequence under specific conditions that have been fine-tuned, such results may not have universal applicability. Further consideration of a more realistic emission model is expected.

We demonstrate how near infrared (NIR) imaging of resolved luminous asymptotic giant branch (AGB) stars can be used to measure well-constrained star formation histories (SFHs) across cosmic time. Using UKIRT J and K-band imaging of M31, we first show excellent agreement over the past $\sim8$ Gyr between the PHAT SFH of M31's outer disk derived from a deep optical color-magnitude diagram (CMD; $\sim3.3\times10^{7}$ stars with $M_{F814W} \lesssim +2$), and our spatially-matched SFH based only on modeling AGB stars on a NIR CMD ($\sim2.3\times10^{4}$ stars with $M_{J} \lesssim -5$). We find that only hundreds of AGB stars are needed for reliable SFH recovery, owing to their excellent age sensitivity in the NIR. We then measure the spatially resolved SFH of M31's inner stellar halo ($D_{M31, projected} \sim20-30$ kpc) using $\sim10^4$ AGB stars. We find: (i) a dominant burst of star formation across M31's inner stellar halo from $4-5$ Gyr ago and lower level, spatially distributed star formation $\sim1-2$ Gyr ago; (ii) a younger 'quenching time' in the vicinity of NGC 205 ($\sim1$ Gyr ago) than near M32 ($\sim1.6$ Gyr ago); (iii) $M_{\star}\sim4\pm0.5\times10^9 M_{\odot}$ formed over the past $\sim8$ Gyr. We discuss some caveats and the enormous potential of resolved AGB stars in the NIR for measuring SFHs back to ancient epochs ($\sim13$ Gyr ago) in galaxies to large distances ($D\gtrsim20$ Mpc) with JWST, Roman, and Euclid.

Elliptic Fourier analysis (EFA) is a powerful tool for shape analysis, which is often employed in geometric morphometrics. However, the normalization of elliptic Fourier descriptors has persistently posed challenges in obtaining unique results in basic contour transformations, requiring extensive manual alignment. Additionally, contemporary contour/outline extraction methods often struggle to handle complex digital images. Here, we reformulated the procedure of EFDs calculation to improve computational efficiency and introduced a novel approach for EFD normalization, termed true EFD normalization, which remains invariant under all basic contour transformations. These improvements are crucial for processing large sets of contour curves collected from different platforms with varying transformations. Based on these improvements, we developed ElliShape, a user-friendly software. Particularly, the improved contour/outline extraction employs an interactive approach that combines automatic contour generation for efficiency with manual correction for essential modifications and refinements. We evaluated ElliShape's stability, robustness, and ease of use by comparing it with existing software using standard datasets. ElliShape consistently produced reliable reconstructed shapes and normalized EFD values across different contours and transformations, and it demonstrated superior performance in visualization and efficient processing of various digital images for contour this http URL output annotated images and EFDs could be utilized in deep learning-based data training, thereby advancing artificial intelligence in botany and offering innovative solutions for critical challenges in biodiversity conservation, species classification, ecosystem function assessment, and related critical issues.

Utilizing Zwicky Transient Facility (ZTF) data and existing RR Lyrae stars (RRLs) catalogs, this study achieves the first calibration of the $P - \phi_{31} - R_{21} - \text{[Fe/H]}$and$P-\phi_{31}-A_{2}-A_{1}-\text{[Fe/H]}$ relations in the ZTF photometric system for RRab and RRc stars. We also re-calibrate the period-absolute magnitude-metallicity (PMZ) and period-Wesenheit-metallicity (PWZ) relations in the ZTF $gri$-bands for RRab and RRc stars. Based on nearly 4100 stars with precise measurements of $P$, $\phi_{31}$, $A_{2}$, and $A_{1}$, and available spectroscopic-metallicity estimates, the photometric-metallicity relations exhibit strong internal consistency across different bands, supporting the use of a weighted averaging method for the final estimates. The photometric-metallicity estimates of globular clusters based on RR Lyrae members also show excellent agreement with high-resolution spectroscopic measurements, with typical scatter of 0.15 dex for RRab stars and 0.14 dex for RRc stars, respectively. Using hundreds of local RRLs with newly derived photometric metallicities and precise Gaia Data Release 3 parallaxes, we establish the PMZ and PWZ relations in multiple bands. Validation with globular cluster RR Lyrae members reveals typical distance errors of 3.1% and 3.0% for the PMZ relations, and 3.1% and 2.6% for the PWZ relations for RRab and RRc stars, respectively. Compared to PMZ relations, the PWZ relations are tighter and almost unbiased, making them the recommended choice for distance calculations. We present a catalog of 73,795 RRLs with precise photometric metallicities; over 95% of them have accurate distance measurements. Compared to Gaia DR3, approximately 25,000 RRLs have precise photometric metallicities and distances derived for the first time.

Globular clusters harbor numerous millisecond pulsars, but long-period pulsars ($P \gtrsim 100$ ms) are rarely found. In this study, we employed a fast folding algorithm to analyze observational data from multiple globular clusters obtained by the Five-hundred-meter Aperture Spherical radio Telescope (FAST), aiming to detect the existence of long-period pulsars. We estimated the impact of the median filtering algorithm in eliminating red noise on the minimum detectable flux density ($S_{\rm min}$) of pulsars. Subsequently, we successfully discovered two isolated long-period pulsars in M15 with periods approximately equal to 1.928451 seconds and 3.960716 seconds, respectively. On the $P-\dot{P}$ diagram, both pulsars are positioned below the spin-up line, suggesting a possible history of partial recycling in X-ray binary systems disrupted by dynamical encounters later on. According to timing results, these two pulsars exhibit remarkably strong magnetic fields. If the magnetic fields were weakened during the accretion process, then a short duration of accretion might explain the strong magnetic fields of these pulsars.

Motivated by the vast gap between photometric and spectroscopic data volumes, there is great potential in using 5D kinematic information to identify and study substructures of the Milky Way. We identify substructures in the Galactic halo using 46,575 RR Lyrae stars (RRLs) from Gaia DR3 with the photometric metallicities and distances newly estimated by Li et al. (2023). Assuming a Gaussian prior distribution of radial velocity, we calculate the orbital distribution characterized by the integrals of motion for each RRL based on its 3D positions, proper motions and corresponding errors, and then apply the friends-of-friends algorithm to identify groups moving along similar orbits. We have identified several known substructures, including Sagittarius (Sgr) Stream, Hercules-Aquila Cloud (HAC), Virgo Overdensity (VOD), Gaia-Enceladus-Sausage (GES), Orphan-Chenab stream, Cetus-Palca, Helmi Streams, Sequoia, Wukong and Large Magellanic Cloud (LMC) leading arm, along with 18 unknown groups. Our findings indicate that HAC and VOD have kinematic and chemical properties remarkably similar to GES, with most HAC and VOD members exhibiting eccentricity as high as GES, suggesting that they may share a common origin with GES. The ability to identify the low mass and spatially dispersed substructures further demonstrates the potential of our method, which breaks the limit of spectroscopic survey and is competent to probe the substructures in the whole Galaxy. Finally, we have also identified 18 unknown groups with good spatial clustering and proper motion consistency, suggesting more excavation of Milky Way substructures in the future with only 5D data.

A complete sample of red supergiant stars (RSGs) is important for studying their properties. Identifying RSGs in extragalatic field first requires removing the Galactic foreground dwarfs. The color-color diagram (CCD) method, specifically using $r-z/z-H$ and $J-H/H-K$, has proven successful in several studies. However, in metal-poor galaxies, faint RSGs will mix into the dwarf branch in the CCD and would be removed, leading to an incomplete RSG sample. This work attempts to improve the CCD method in combination with the Gaia astrometric measurement to remove foreground contamination in order to construct a complete RSG sample in metal-poor galaxies. The empirical regions of RSGs in both CCDs are defined and modified by fitting the locations of RSGs in galaxies with a range of metallicity. The metal-poor galaxy NGC 6822 is taken as a case study for its low metallicity ([Fe/H] $\approx$ -1.0) and moderate distance (about 500 kpc). In the complete sample, we identify 1,184 RSG, 1,559 oxygen-rich AGB (O-AGBs), 1,075 carbon-rich AGB (C-AGBs), and 140 extreme AGB (x-AGBs) candidates, with a contamination rate of approximately 20.5%, 9.7%, 6.8%, and 5.0%, respectively. We also present a pure sample, containing only the sources away from the dwarf branch, which includes 843 RSG, 1,519 O-AGB, 1,059 C-AGB, and 140 x-AGB candidates, with a contamination rate of approximately 6.5%, 8.8%, 6.1%, and 5.0%, respectively. About 600 and 450 RSG candidates are newly identified in the complete and pure sample, respectively, compared to the previous RSG sample in NGC 6822.

The search for extraterrestrial intelligence (SETI) is to search for technosignatures associated with extraterrestrial life, such as engineered radio signals. In this paper, we apply the multibeam coincidence matching (MBCM) strategy, and propose a new search mode based on the MBCM which we call MBCM blind search mode. In our recent targeted SETI research, 33 exoplanet systems are observed by the Five-hundred-meter Aperture Spherical radio Telescope (FAST). With this blind search mode, we search for narrowband drifting signals across $1.05-1.45$ GHz in two orthogonal linear polarization directions separately. There are two special signals, one of which can only be detected by the blind search mode while the other can be found by both blind and targeted search modes. This result reveals huge advantages of the new blind search mode. However, we eliminate the possibility of the special signals being ETI signals based on much evidence, such as the polarization, drift, frequency and beam coverage characteristics. Our observations achieve an unprecedented sensitivity and our work provides a deeper understanding to the polarization analysis of extraterrestrial signals.

As a major approach to looking for life beyond the Earth, the search for extraterrestrial intelligence (SETI) is committed to detecting technosignatures such as engineered radio signals that are indicative of technologically capable life. In this paper, we report a targeted SETI campaign employing an observation strategy named multi-beam coincidence matching (MBCM) at the Five-hundred-meter Aperture Spherical radio Telescope (FAST) towards 33 known exoplanet systems, searching for ETI narrow-band drifting signals across 1.05-1.45 GHz in two orthogonal linear polarization directions separately. A signal at 1140.604 MHz detected from the observation towards Kepler-438 originally peaked our interest because its features are roughly consistent with assumed ETI technosignatures. However, evidences such as its polarization characteristics are almost able to eliminate the possibility of an extraterrestrial origin. Our observations achieve an unprecedented sensitivity since the minimum equivalent isotropic radiated power (EIRP) we are able to detect reaches 1.48 x10^9 W.

The existing single-pulse search algorithms for fast radio bursts (FRBs) do not adequately consider the frequency bandpass pattern of the pulse, rendering them incomplete for the relatively narrow-spectrum detection of pulses. We present a new search algorithm for narrow-band pulses to update the existing standard pipeline, Bandpass-Adaptive Single-pulse SEarch Toolkit (BASSET). The BASSET employs a time-frequency correlation analysis to identify and remove the noise involved by the zero-detection frequency band, thereby enhancing the signal-to-noise ratio (SNR) of the pulses. The BASSET algorithm was implemented on the FAST real dataset of FRB 20190520B, resulting in the discovery of additional 79 pulses through reprocessing. The new detection doubles the number of pulses compared to the previously known 75 pulses, bringing the total number of pulses to 154. In conjunction with the pulse calibration and the Markov Chain Monte Carlo (MCMC) simulated injection experiments, this work updates the quantified parameter space of the detection rate. Moreover, a parallel-accelerated version of the BASSET code was provided and evaluated through simulation. BASSET has the capacity of enhancing the detection sensitivity and the SNR of the narrow-band pulses from the existing pipeline, offering high performance and flexible applicability. BASSET not only enhances the completeness of the low-energy narrow-band pulse detection in a more robust mode, but also has the potential to further elucidate the FRB luminosity function at a wider energy scale.

We present constraints on the baryonic matter density parameter, $\Omega_b$, within the framework of the $\Lambda$CDM model. Our analysis utilizes observational data on the effective optical depth from high-redshift quasars. To parameterize the photoionization rate $\Gamma_{-12}$, we employ a Bézier polynomial. Additionally, we approximate the Hubble parameter at high redshifts as $H(z)\approx 100h\Omega_m^{1/2} (1+z)^{3/2}$ km s$^{-1}$ Mpc$^{-1}$. Confidence regions are obtained with $h=0.701\pm0.013$ and $\Omega_m = 0.315$, optimized by the Planck mission. The best-fit values are $\Omega_b =0.043^{+0.005}_{-0.006}$ and $\Omega_b = 0.045^{+0.004}_{-0.006}$, corresponding to an old data set and a new data set, respectively. And we test the non-parametric form of $\Gamma_{-12}$, obtaining $\Omega_b = 0.048^{+0.001}_{-0.003}$. These results are consistent with the findings of Planck at the 1 $\sigma$ confidence level. Our findings underscore the effectiveness of quasar datasets in constraining $\Omega_b$, eliminating the need for independent photoionization rate data. This approach provides detailed cosmic information about baryon density and the photoionization history of the intergalactic medium.

The color index $(J-K)_0$ of tip-red giant branch (TRGB) is used to study the metallicity distribution in the Large and Small Magellanic Cloud. With the most complete and pure sample of red member stars so far, the areas are divided into 154 and 70 bins for the LMC and SMC respectively with similar number of stars by the Voronoi binning. For each bin, the position of TRGB on the near-infrared color-magnitude diagram, specifically $(J-K)_0/K_0$, is determined by the Poison-Noise weighted method. Converting the color index of TRGB into metallicity, the metallicity gradients in the LMC and the SMC are obtained in four major directions. For the LMC, the gradient to the north is $-0.006 \pm 0.004$dex kpc$^{-1}$, to the south$-0.010 \pm 0.005$dex kpc$^{-1}$, to the east $-0.006 \pm 0.003$ dex kpc$^{-1}$, and to the west $-0.010 \pm 0.003$ dex kpc$^{-1}$. The farthest distance extends to 16 kpc. For the SMC, the gradients to the north, south, east, and west are $-0.017 \pm 0.031$ dex kpc$^{-1}$, $-0.016 \pm 0.007$ dex kpc$^{-1}$, $-0.003 \pm 0.002$ dex kpc$^{-1}$, and $-0.004 \pm 0.003$ dex kpc$^{-1}$, respectively. The farthest distance for the SMC extends to 27 kpc. The gradient is large from the center to 1 kpc.

The identification of star clusters holds significant importance in studying galaxy formation and evolution history. However, the task of swiftly and accurately identifying star clusters from vast amounts of photometric images presents an immense challenge. To address these difficulties, we employ deep learning models for image classification to identify young disk star clusters in M31 from the Pan-Andromeda Archaeological Survey (PAndAS) images. For training, validation, and testing, we utilize the Panchromatic Hubble Andromeda Treasury (PHAT) survey catalogs. We evaluate the performance of various deep learning models, using different classification thresholds and limiting magnitudes. Our findings indicate that the ResNet-50 model exhibits the highest overall accuracy. Moreover, using brighter limiting magnitudes and increasing the classification thresholds can effectively enhance the accuracy and precision of cluster identification. Through our experiments, we found that the model achieves optimal performance when the limiting magnitude is set to brighter than 21 mag. Based on this, we constructed a training dataset with magnitudes less than 21 mag and trained a second ResNet-50 model. This model achieved a purity of 89.30%, a recall of 73.55%, and an F1 score of 80.66% when the classification threshold was set to 0.669. Applying the second model to all sources in the PAndAS fields within a projected radius of 30 kpc from the center of M31, we identified 2,228 new unique star cluster candidates. We conducted visual inspections to validate the results produced by our automated methods, and we ultimately obtained 1,057 star cluster candidates, of which 745 are newly identified.