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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) Data Release 1 and Gaia Early Data Release 3. 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 ([Fe/H] ≤ −1.0) stars and nearly one million very metal-poor ([Fe/H] ≤ −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.

M31, as the largest galaxy in the Local Group, is of significant importance for the study of stellar formation and evolution. Based on the data of 5859 targets observed in M31 by Gu et al., we selected 30 contact binaries by visual inspection for further study. Using the PHysics Of Eclipsing BinariEs software and employing Bayesian optimization and Markov Chain Monte Carlo sampling, we determined the physical parameters of these 30 systems. The results show that 10 systems exhibit the O’Connell effect, which is well explained by introducing a dark spot on the primary star. A total of 11 systems have mass ratios below 0.15, classifying them as extremely low mass ratio contact binaries, making them promising candidates for binary mergers. Meanwhile, 6 systems have primary star temperatures exceeding 10,000 K, classifying them as early-type contact binaries. The absolute physical parameters reveal that 2 contact binary systems contain massive stellar components, which may eventually evolve into compact binary star systems. To compare the effects of different galactic environments on the evolution of contact binaries, we constructed evolutionary diagrams for these 30 targets and for contact binaries in the Milky Way. The results show that, at the same mass, our targets have larger radii, higher luminosities, and lower orbital angular momenta than contact binaries in the Milky Way, indicating that they are at more advanced evolutionary stages. This may be attributed to the higher metallicity in M31 compared to the Milky Way.

M31, as the largest galaxy in the Local Group, is of significant importance for the study of stellar formation and evolution. Based on the data of 5,859 targets observed in M31 by Gu et al (2024), we selected 30 contact binaries by visual inspection for further study. Using the PHOEBE software and employing Bayesian optimization and Markov Chain Monte Carlo sampling, we determined the physical parameters of these 30 systems. The results show that 10 systems exhibit the O'Connell effect, which is well explained by introducing a dark spot on the primary star. 11 systems have mass ratios below 0.15, classifying them as extremely low mass ratio contact binaries, making them promising candidates for binary mergers. Six systems have primary star temperatures exceeding 10,000 K, classifying them as early-type contact binaries. The absolute physical parameters reveal that two contact binary systems contain massive stellar components, which may eventually evolve into compact binary star systems. To compare the effects of different galactic environments on the evolution of contact binaries, we constructed evolutionary diagrams for these 30 targets and for contact binaries in the Milky Way. The results show that, at the same mass, our targets have larger radii, higher luminosities, and lower orbital angular momenta than contact binaries in the Milky Way, indicating that they are at more advanced evolutionary stages. This may be attributed to the higher metallicity in M31 compared to the Milky Way.

The Mini-SiTian (MST) project is a pathfinder for China's next-generation large-scale time-domain survey, SiTian, aimed at discovering variable stars, transients, and explosive events. MST generates hundreds of thousands of transient alerts every night, approximately 99\\% of which are false alarms, posing a significant challenge to its scientific goals. To mitigate the impact of false positives, we propose a deep learning-based solution and systematically evaluate thirteen convolutional neural networks. The results show that ResNet achieves exceptional specificity (99.70\\%), EfficientNet achieves the highest recall rate (98.68\\%), and DenseNet provides balanced performance with a recall rate of 94.55\\% and specificity of 98.66\\%. Leveraging these complementary strengths, we developed a bagging-based ensemble classifier that integrates ResNet18, DenseNet121, and EfficientNet\\_B0 using a soft voting strategy. This classifier achieved the best AUC value (0.9961) among all models, with a recall rate of 95.37\\% and specificity of 99.25\\%. It has now been successfully deployed in the MST real-time data processing pipeline. Validation using 5,000 practically processed samples with a classification threshold of 0.798 showed that the classifier achieved 88.31\\% accuracy, 91.89\\% recall rate, and 99.82\\% specificity, confirming its effectiveness and robustness under real application conditions.

The rapid development of mega-constellations in low Earth orbit (LEO) severely impacts ground-based optical astronomical observations. By combining WorldWide Telescope (WWT) simulations with 2019 and 2023 observational data from the Xinglong Observatory 80-cm telescope and 2023 data from the Mini-SiTian (MST), we find that satellite visibility increases with deployment, particularly during the summer. For the 80-cm telescope, the fraction of images containing satellite trails increased from an average of 0.34% in 2019 to 0.7% in 2023; meanwhile, for the MST in 2023, the fraction rose from 5% in January to 12% by December, peaking at 19% in the summer. Through stratified analysis of solar elevation and local time, we find that observations during twilight and summer are particularly susceptible to satellite trail interference. Photometric analysis reveals that the interference intensity increases for fainter sources and those closer to the trails. Furthermore, a comparative analysis across different seeing conditions shows that the deviation of median standardized residuals () is significantly greater under poor seeing than under good seeing conditions.

We assess the detectability of tidal disruption events (TDEs) using mock observations from the Mini-SiTian array. We select 100 host galaxy samples from a simulated galaxy catalog based on specific criteria such as redshift, BH mass, and event rate. Taking into account the site conditions and survey strategy, we simulate observations over a 440 deg\\(^2\\) field. The results indicate that \\(0.53 0.73\\) TDEs can be detected per year when observing in both \\(g\\) and \\(r\\) bands with 300-second exposures every 3 days. Applying this method to the SiTian project, we expect to discover approximately 204 TDEs annually, heralding a new era in TDE science.

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]\\( -1.0\\)) stars and nearly one million very metal-poor (VMP; [Fe/H]\\( -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.

Early medical abortion (EMA) with mifepristone-misoprostol commonly relies on subjective metrics (e.g., last menstrual period-derived gestational age) for failure risk assessment, which may introduce uncertainty. This retrospective study aimed to identify objective predictors of EMA failure and explore the utility of different gestational sac size metrics for clinical risk stratification. Early pregnancy outpatients who underwent medical abortion with the mifepristone-misoprostol regimen at Karamay Central Hospital (Xinjiang, China) from December 2024 to July 2025 were included in our study. EMA failure was defined as the need for surgical evacuation. Analyses included univariate assessment, logistic regression, and performance evaluation of gestational sac size metrics. After exclusion, 159 women were included in the final analyses. The overall EMA success rate was 89.31% (142/159). Maternal age ≥35 years was associated with higher failure risk (OR = 2.82, 95% CI, 1.01-7.89,  = 0.048). Gestational sac size emerged as an important objective correlate of EMA failure; among five assessed metrics (ellipsoid volume, maximum diameter, mean diameter, sum of three diameters, triple product of diameters), the triple product of diameters showed the highest correlation with failure (  = 0.316) and a significant association with failure risk (OR per 1,000 mm increase = 1.08, 95% CI, 1.03-1.14,  = 0.003). The triple product model demonstrated good discrimination, with an area under the curve (AUC) of 0.78 (95% CI, 0.68-0.88). Calibration was adequate (Hosmer-Lemeshow  = 0.62), and internal validation using bootstrap resampling confirmed stable performance (optimism-corrected AUC 0.76, 95% CI, 0.65-0.86). Its optimal cutoff (3648) yielded sensitivity = 0.765, specificity = 0.688, and Youden Index = 0.453. Fetal heart activity, embryonic bud presence, and parity were not significantly linked to failure (all  > 0.05). Gestational sac size is an important objective indicator for predicting mifepristone-misoprostol EMA failure, and among various gestational sac size metrics, the triple product of diameters demonstrates the highest predictive value.

[This corrects the article DOI: 10.3389/fmed.2026.1780064.].

Rescue and evacuation of underground interchange tunnels after a fire are challenging. Therefore, a method of integrating building information modeling (BIM) and a fire dynamic simulator (FDS) was proposed to analyze fire characteristics and personnel escapes in underground interchange tunnels. A BIM model of underground interchange tunnels was built, and then different formats (DXF and CAD) were generated and imported into Pyrosim software and Pathfinder software. With an increase in ventilation velocity, the CO concentration and temperature downstream of the fire source increased, and visibility decreased, according to simulation results. The critical ventilation velocity was 3.6 m/s at 30 MW. Evacuation simulation results suggested that the congestion of the transverse passage was very unfavorable for personnel escape: the escape time increased by 14.9% and 20% when the interior and entrance of the transverse passage were severely congested, while a 2.5 m wide transverse passage effectively reduced the escape time. Visibility was the first indicator that it did not meet the safety of the escape. After the tunnel’s personnel have been evacuated, the air supply or exhaust system should be started, and smoke should be expelled at a higher velocity. It is necessary to clear the passageway quickly or increase the automatic firefighting facilities when congestion is severe.