Investigating the physical and chemical structure of massive star-forming regions is critical for understanding the formation and early evolution of massive stars. We performed a detailed line survey toward six dense cores, named MM1, MM4, MM6, MM7, MM8, and MM11, in the G9.62+0.19 star-forming region resolved in Atacama Large Millimeter/submillimeter Array (ALMA) band 3 observations. Toward these cores, about 172 transitions have been identified and attributed to 16 species, including organic oxygen-, nitrogen-, and sulphur-bearing molecules and their isotopologues. Four dense cores, MM7, MM8, MM4, and MM11, are line-rich sources. Modelling of these spectral lines reveals that the rotational temperature lies in the range 72–115, 100–163, 102–204, and 84–123 K for MM7, MM8, MM4, and MM11, respectively. The molecular column densities are 1.6 × 10¹⁵–9.2 × 10¹⁷ cm⁻² toward the four cores. The cores MM8 and MM4 show a chemical difference between oxygen- and nitrogen-bearing species, i.e. MM4 is rich in oxygen-bearing molecules, while nitrogen-bearing molecules, especially vibrationally excited HC₃N lines, are mainly observed in MM8. The distinct initial temperatures at the accretion phase may lead to this N/O differentiation. Through analysing column densities and spatial distributions of O-bearing complex organic molecules (COMs), we found that C₂H₅OH and CH₃OCH₃ might have a common precursor, CH₃OH. CH₃OCHO and CH₃OCH₃ are likely chemically linked. In addition, the observed variation in HC₃N and HC₅N emission may indicate their different formation mechanisms in hot and cold regions.

Orion KL is one of the prime templates of astrochemical and prebiotic chemical studies. We wish to explore more organic molecules with increasing complexity in this region. In particular, we have searched for one of the most complex organic molecules detected in space so far, ethyl formate (C₂H₅OCHO). This species is the next step in chemical complexity after the simplest member of esters (methyl formate, CH₃OCHO). The mechanisms leading to its formation are still poorly known. We have used high angular resolution (∼1.″5) ALMA observations covering a large bandwidth from 214 to 247 GHz. We have detected 82 unblended lines of C₂H₅OCHO (49 and 33 of the trans- and gauche-conformers, respectively). The line images showed that C₂H₅OCHO arises mainly from the compact ridge and the hot core-southwest regions. The derived rotational temperatures and column densities are 122 ± 34 K, (0.9 ± 0.3) × 10¹⁶ cm⁻² for the hot core-SW, and 103 ± 13 K, (0.6 ± 0.3) × 10¹⁶ cm⁻² for the compact ridge. The comparison of spatial distribution and abundance ratios with chemically related molecules (methyl formate, ethanol, and formic acid) indicates that C₂H₅OCHO is likely formed on the surface of dust grains by addition of CH₃ to functional-group radicals (CH₂OCHO) derived from methyl formate (CH₃OCHO).

We perform the quasi-periodic oscillation (QPO) analysis of blazar PKS 1424−418 in the γ-ray (0.1–300 GeV) band from 2009 May 12 to 2019 September 17 (MJD 54963−58743). Using the spectral domain methods, Bhatta & Dhital reported that this source has 353 days periodic flux oscillations in the γ-ray flux. Adopting time domain methods, we confirm the previous detection that a possible γ-ray QPO of ∼355 days with the high significance level. Combining two methods of time domain and spectral domain provides stronger evidence for the existence of the QPO. Especially, after the strongest flare, γ-ray light-curve exhibits stronger periodic significance compared with the whole observation period. Assuming that the QPO is come from the orbital motion in a supermassive binary black hole system, the mass of primary black hole for this source is estimate as M ∼ 3.5 × 10⁸–5.5 × 10⁹ M _⊙.

Introduction: Weed poses a greater threat to rice yield and quality in upland environments compared to paddy fields. Effective weed detection is a critical prerequisite for intelligent weed control technologies. However, the current weed detection methods for upland rice often struggle to achieve a balance between accuracy and lightweight design, significantly hindering the practical application and widespread adoption of intelligent weeding technologies in real-world agricultural scenarios. To address this issue, we enhanced the baseline model RT-DETR and proposed a lightweight weed detection model for upland rice, named PHRF-RTDETR.Methods: First, we propose a novel lightweight backbone network, termed PGRNet, to replace the original computationally intensive feature extraction network in RT-DETR. Second, we integrate HiLo, a mechanism excluding parameter growth, into the AIFI module to enhance the model’s capability of capturing multi-frequency features. Furthermore, the RepC3 block is optimized by incorporating the RetBlock structure, resulting in RetC3, which effectively balances feature fusion and computational efficiency. Finally, the conventional GIoU loss is replaced with the Focaler-WIoUv3 loss function to significantly improve the model’s generalization performance.Results: The experimental results show that PHRF-RTDETR achieves precision, recall, mAP50, and mAP50:95 scores of 92%, 85.6%, 88.2%, and 76.6%, respectively, with all metrics deviating by less than 1.7 percentage points from the baseline model in upland rice weed detection. In terms of lightweight indicators, PHRF-RTDETR achieved reductions in floating-point operations, parameter count, and model size by 59.3%, 53.7%, and 53.9%, respectively, compared to the baseline model. Compared with the traditional target detection models of Faster R-CNN and SSD, YOLO series models, and RT-DETR series models, the PHRF-RTDETR model effectively balances lightweight and accuracy performance for weed detection in upland rice.Discussion: Overall, the PHRF-RTDETR model demonstrates potential for implementation in the detection modules of intelligent weeding robots for upland rice systems, offering dual benefits of reducing agricultural production costs through labor efficiency and contributing to improved food security in drought-prone regions.

We investigate the physical properties and radiation mechanisms of 11 states of five narrow-line Seyfert 1 (NLS1) galaxies detected by the Large Area Telescope on board Fermi through modeling the quasi-simultaneous multi-band observations. We obtain the best-fitting model parameters and their uncertainties for each state with the χ²-minimization procedure and discuss their implications on the characteristics of jet. Similar to blazars, their spectral energy distributions (SEDs) have a two-humped structure and their non-thermal emission can be modelled with the single-zone synchrotron + inverse Compton (IC) model. For all states, the GeV γ-rays may be contributed by the external Compton (EC) emission components. The observations of Fermi are mostly located at the declining stage of the EC humps. T_ext < 0.5 eV in all cases (T_ext is the characteristic temperature of external soft photons), suggesting that their radiation zones may be usually located outside of the broad line region (BLR) and the soft photons of Compton scattering mainly come from the dust torus. Compared with the bright Fermi blazars studied by Ghisellini et al. (2014, Nature, 515, 376), the P_jet (the power of the jets) of NLS1 galaxies detected by Fermi is similar to that of the flat spectrum radio quasars (FSRQs) but a little larger than that of the BL Lac objects (BL Lacs). However, a comparison of P_r (the powers of radiations) with the FSRQs and BL Lac objects shows that NLS1 galaxies’ P_r has values comparable to BL Lac objects but lower than FSRQs in spite of having similar P_jet values and the same energy carrier (the cold protons) as the FSRQs. Observations indicate that γ-NLS1 galaxies might have lower η (efficiency of gravitational energy release) values than GeV blazars.