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Using deep learning technology to control vehicles at intersections is a research hotspot in the field of intelligent transportation.Previous studies suffer from the inability to adapt to dynamic changes in the number of self-driving vehicles,slow convergence of training,and locally optimal training results.This work focuses on how autonomous vehicles can use distributed deep reinforcement methods to improve the efficiency of intersections at unsignalized intersections.First,an efficient reward function is proposed to apply the distributed reinforcement learning algorithm to the unsignalized intersection scenario,which can effectively improve the efficiency of intersection passage by relying on only local information even if the vehicle cannot obtain the whole intersection state information.Then,to address the problem of inefficient training of reinforcement learning methods in open intersection scenarios,a transfer learning approach is used to improve the training efficiency by using the trained strategy in the closed figure-of-eight scenario as a warm start and continuing the training in the unsignalized intersection scenario.Finally,this paper proposes a strategy that can be adapted to all proportions of autonomous vehicles,and this strategy can improve intersection access efficiency in scenarios with any proportion of autonomous vehicles.The algorithm is validated on the simulation platform Flow,and the experimental results show that the proposed smart body model converges quickly in training,can adapt to dynamic changes in the proportion of self-driving vehicles,and can effectively improve the efficiency of intersections.

Bombyx mori ELAV‐like‐1 (BmEL‐1) and B. mori ELAV‐like‐2 (BmEL‐2) are 2 members of the ELAV‐like family of RNA‐binding proteins. Mutations in Bmel‐1 and Bmel‐2 resulted in 5.8% and 28.5% decreases in larval weight on the 3rd day of the 5th instar larva (L5D3), respectively. Triglycerides (TG) are the most important energy resource and are the main component of neutral fat (NF) in animals. To investigate the role of Bmelav‐like genes in the synthesis and decomposition of TG, transcriptomic, and metabolic analyses were performed on the whole bodies on the 1st day of the 2nd instar larvae (L2D1) and on fat bodies on L5D3 of Bmel‐1− and Bmel‐2− mutants, respectively. As compared with the control silkworm, differentially expressed genes generated in both mutants were mainly enriched in lysine degradation, fatty acid (FA) metabolism, and unsaturated FAs biosynthesis. The diglyceride and phosphatide contents were significantly lower in Bmel‐1− and Bmel‐2− fat bodies than those of the control group. Consistently, the NF content of both mutants’ fat bodies were reduced by 50% and 60%, respectively. BmEL‐2 positively regulates BmAGPATγ (B. mori 1‐acyl‐sn‐glycerol‐3‐phosphate acyltransferase gamma, LOC101741736) and BmFaF2 (B. mori fatty acid synthetase‐associated factor 2, LOC101739090) expression by binding to the specific regions of their 3′ untranslated regions in BmN cells. This study suggests that BmEL‐2 may be an important regulator of BmAGPATγ and BmFAF2 expression and thereby participates in TG metabolism in the silkworm fat body. [ABSTRACT FROM AUTHOR]

Pyridazine is a significant skeleton that widely exists in drugs and bioactive molecules. We herein describe expeditious approaches to access polysubstituted pyridazines from readily accessible unactivated ketones and acylhydrazones via Cu-promoted C(sp3)–C(sp3) coupling/cyclization sequences in a single-step fashion. Notably, the disparate 3,4,6-trisubstituted pyridazines and 3,5-disubstituted pyridazines could be obtained by tailoring the ketone's structure and reaction conditions. These transformations feature good functional group compatibility, excellent step-economy, and chemoselectivity. The potential synthetic utility of these conversions is illustrated by scale-up reactions and late-stage derivatizations of the as-prepared pyridazine products. [ABSTRACT FROM AUTHOR]

Background: Despite physical and emotional distress in patients with gynecologic malignancies, palliative care (PC) is underutilized. Objectives: We characterize referral practices, symptom burden and functional status at the time of initial PC encounter for patients with gynecologic cancer. Design: Data were extracted from the standardized Quality Data Collection Tool for Palliative Care (QDACT-PC). We describe symptom burden and performance status. Results: At initial specialty PC encounter, patients with gynecologic cancers reported a mean of 3.3 moderate/severe symptoms. Outpatients experienced the most moderate/severe symptoms (mean 3.9) versus inpatient (mean 2.1) or home (mean 1.5). A total of 72.7% of patients had significantly impaired functional status (palliative performance scale [PPS] <70) at initial encounter. Inpatients had a more impaired functional status (mean PPS 48.8) than outpatients (mean PPS 67.0). Conclusions: The symptom burden for gynecologic cancer patients at initial PC encounter is high. Despite better functional status, patients referred in the outpatient setting had the highest symptom burden. [ABSTRACT FROM AUTHOR]

Flavonoids play an important role in forming wine grapes and wine quality characteristics. The flavonoids of three winter red wine grapes, Yeniang No. 2 (YN2), Marselan (Mar), and Guipu No. 6 (GP6), were analyzed by ultra-high-performance liquid chromatography–triple quadrupole mass spectrometry (UPLC-QQQ-MS). Furthermore, the flavonoids in GP6 grapevines using two types of training systems, namely, trellis (T) and espaliers (E), were also compared in this study. Overall, 196 flavonoid metabolites, including 96 flavones, 38 flavonols, 19 flavanones, 18 polyphenols, 15 anthocyanins, 7 isoflavones, and 3 proanthocyanidins, were identified. The flavonoid profiles were remarkably different among these three grape varieties, while they did not change much in the GP6 managed on trellis and espaliers. Grape varieties with different genetic backgrounds have their own unique flavonoid profiles. Compared with Mar-T, isoflavones and flavonols presented higher contents in GP6-T and YN2-T, which mainly contain glycitein, genistin, calycosin, kaempferide, isotrifoliin, and ayanin. The anthocyanin content was significantly higher in YN2-T than in the other two varieties. YN2 and GP6-T present a more stable color, with significantly more acetylated diglucosides and methylated anthocyanins in YN2-T and GP6-T than in Mar-T. Notably, GP6 had more varied flavonoids and the better characteristics to its flavonoid profile out of these three varieties, due to it containing a higher number of anthocyanins, flavone, and flavonols and the greatest number of different flavonoid metabolites (DFMs), with higher contents than YN2 and Mar. Compared with the trellis training system, the espaliers training system increased the content of flavonoids detected in GP6 grape berries; however, the composition of flavonoids strictly depends on the grape variety. [ABSTRACT FROM AUTHOR]

Two pairs of new isobenzofuranone derivative enantiomers, (±)-penicifurans E (1) and (±)-penicifurans F (2), together with four know compounds (3–6) were isolated from the solid fermentation of Penicillium canescens DWS225. The structures of these enantiomers were elucidated by extensive NMR spectroscopic data, and their absolute configurations were assigned by the experimental and calculated ECD data. The neuroprotective effects of all the isolates against oxygen-glucose deprivation/reperfusion injury in pheochromocytoma-12 cells (PC12) were investigated. [ABSTRACT FROM AUTHOR]

Abstract:Aiming at the problem of low fall detection accuracy and poor real-time performance in indoor scenes due to the effects of light change, occlusion of the human body form, and changes in the human body posture under special viewpoint, a lightweight improved fall detection algorithm based on YOLOv8, named FDW-YOLO, is proposed. The C2f module in the backbone network is replaced by the FasterNext module, which reduces the computational complexity while retaining the excellent feature extraction capability. According to the characteristics of human falls with large changes in posture, three network structures with dynamically deformable convolutional modules added at different positions in the neck layer are designed, experiments are conducted on a self-made fall dataset for comparison, and ultimately, the YOLOv8-C scheme is selected based on network performance. A bounding box regression loss function WIoU is introduced into the improved network to replace the original CIoU. The experimental results show that compared with YOLOv8n, the FDW-YOLO fall detection algorithm increases mAP@0.5 from 96.5% to 97.9% and mAP@0.5:0.95 from 72.5% to 74.3%, while the number of parameters and computation is only 4.1x106 and 7.3x109, which is in line with the requirements for deployment in low-computing power industrial scenarios. [ABSTRACT FROM AUTHOR]

Temperature is always one of the most important factors that critically affects the electrical performance of devices. In the present work, the thermochromic function has been realized on oxide neuromorphic transistors gated by a chitosan based electrolyte mixed with temperature-sensitive thermochromic powder. Except for extremely strong proton gating effects, the device exhibits temperature-sensitive thermochromic activities with good electrical performance. It also demonstrates typical synaptic functions at different temperatures, mimicking heat pain sensation activities. Additionally, a high recognition accuracy of ∼93.80% for MNIST handwritten digits is obtained at different temperatures, indicating good stabilities for neuromorphic computing. The present work opens up interesting idea for bionic cognitive electronic skin and bionic thermochromic cognitive platforms. [ABSTRACT FROM AUTHOR]

1D structures/patterns (e.g., line defect arrays, 1D Moiré patterns) embedded in 2D materials provide fascinating platforms for exploring versatile intriguing phenomena, for example, 1D Luttinger liquids and charge density waves (CDWs). Despite persistent efforts, incorporating periodic 1D patterns into 2D materials remains an ongoing pursuit. Herein, the direct preparation of monolayer 1D‐defect‐induced Co4Te7 superlattices (with periodic Te defect lines in the upper Te layer in 1T‐CoTe2) is reported, on lattice‐matched SrTiO3(001) (STO(001)) substrates via molecular beam epitaxy (MBE). Utilizing on‐site scanning tunneling microscopy/spectroscopy (STM/STS) combined with density functional theory (DFT) calculations, the detailed atomic structure of monolayer Co4Te7 is identified, and its formation mechanisms from the synergistic effects of the Co/Te precursor ratio and adlayer‐substrate interfacial coupling are uncovered. The potential flat‐band feature of the monolayer Co4Te7 is also unveiled. This work should hereby offer valuable insights into the engineering of periodic 1D‐defect patterns in 2D materials, as well as the atomic‐scale structure and electronic property characterizations, thus paving ways for their intriguing property investigations. [ABSTRACT FROM AUTHOR]

In the present study, the mitochondrial genomic characteristics of Acanthopsetta nadeshnyi have been reported and have depicted the phylogenetic relationship among Pleuronectidae. Combined with a comparative analysis of 13 PCGs, the TN93 model was used to review the neutral evolution and habitat evolution catalysis of the mitogenome to verify the distancing and purification selectivity of the mitogenome in Pleuronectidae. At the same time, a species differentiation and classification model based on mitogenome analysis data was established. This study is expected to provide a new perspective on the phylogenetic relationship and taxonomic status of A. nadeshnyi and lay a foundation for further exploration of environmental and biological evolutionary mechanisms. [ABSTRACT FROM AUTHOR]