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Context: The reaction between Na and HF is a typical harpooning reaction which is of great interest due to its significance in understanding the elementary chemical reaction kinetics. This work aims to investigate the detailed reaction mechanisms of sodium with hydrogen fluoride and the adsorption of HF on the resultant NaF as well as the (NaF)4 tetramer. The results suggest that the reaction between Na and HF leads to the formation of sodium fluoride salt NaF and hydrogen gas. Na interacts with HF to form a complex HF···Na, and then the approaching of F atom of HF to Na results in a transition state H···F···Na. Accompanied by the broken of H-F bond, the bond forms between F and Na atoms as NaF, then the product NaF is yielded due to the removal of H atom. The resultant NaF can further form (NaF)4 tetramer. The interaction of NaF with HF leads to the complex NaF···HF; the form I as well as II of (NaF)4 can interact with HF to produce two complexes (i.e., (NaF)4(I-1)···HF, (NaF)4(I-2)···HF, (NaF)4(II-1)···HF and (NaF)4(II-2)···HF), but the form III of (NaF)4 can interact with HF to produce only one complex (NaF)4(III)···HF. These complexes were explored in terms of noncovalent interaction (NCI) and quantum theory of atoms in molecules (QTAIM) analyses. NCI analyses confirm the existences of attractive interactions in the complexes HF···Na, NaF···HF, (NaF)4(I-1)···HF, (NaF)4(I-2)···HF, (NaF)4(II-1)···HF and (NaF)4(II-2)···HF, and (NaF)4(III)···HF. QTAIM analyses suggest that the F···Na interaction forms in the HF···Na complex while the F···H hydrogen bonds form in NaF···HF, (NaF)4(I-1)···HF, (NaF)4(I-2)···HF, (NaF)4(II-1)···HF and (NaF)4(II-2)···HF, and (NaF)4(III)···HF complexes. Natural bond orbital (NBO) analyses were also applied to analyze the intermolecular donor-acceptor orbital interactions in these complexes. These results would provide valuable insight into the chemical reaction of Na and HF and the adsorption interaction between sodium fluoride salt and HF. Methods: The calculations were carried out at the M06-L/6-311++G(2d,2p) level of theory which were performed using the Gaussian16 program. Intrinsic reaction coordinate (IRC) calculations were carried out at the same level of theory to confirm that the obtained transition state was true. The molecular surface electrostatic potential (MSEP) was employed to understand how the complex forms. Quantum theory of atoms in molecules (QTAIM) and noncovalent interaction (NCI) analysis was used to know the topology parameters at bond critical points (BCPs) and intermolecular interactions in the complex and intermediate. The topology parameters and the BCP plots were obtained by the Multiwfn software. [ABSTRACT FROM AUTHOR]

In this paper, we introduce the AAPF* algorithm, an innovative approach that synergistically integrates the A-star search algorithm (A*) with the artificial potential field (APF) method. This algorithm is designed to enhance safety and ensure smoother global path planning for autonomous vehicles, particularly addressing vehicle cornering constraints. Initially, for augmenting the safety of autonomous vehicle, we implement an obstacle expansion strategy with a factor of 2 units, enhancing environmental adaptability. The study then delves into the classical A* algorithm, examining its core principles and characteristics, leading to the development of novel heuristic functions and search strategies that address the limitations inherent in the classic A* algorithm. Subsequently, we explore the APF algorithm, recognized for its excellence in obstacle avoidance in path planning. The paper culminates in the amalgamation of the APF’s repulsive field concept with the improved A* algorithm, crafting a comprehensive global planning algorithm tailored for autonomous vehicle path planning schemes. Experiments conducted in a simulated environment model validate the AAPF* algorithm’s efficacy in improving both the safety and smoothness, demonstrating its potential for real-world applications. [ABSTRACT FROM AUTHOR]

With the development of deep learning, Remote Sensing Image (RSI) semantic segmentation has produced significant advances. However, due to the sparse distribution of the objects and the high similarity between classes, the task of semantic segmentation in RSI is still extremely challenging. In this paper, we propose a novel semantic segmentation framework for RSI called HST-UNet that can overcome the shortcomings of the existing models and extract and recover the global and local features of RSI, which is a hybrid semantic segmentation model with Shunted Transformer as encoder and Multi-Scale Convolutional Attention Network (MSCAN) as decoder. Then, to better fuse the information from the Encoder and the Decoder and alleviate the ambiguity, we design a Learnable Weighted Fusion (LWF) module to effectively connect to the decoder features. Extensive experiments demonstrate that the proposed HST-UNet outperforms the state-of-the-art methods, achieving F1 score/MIoU accuracy of 71.44%/83.00% on the ISPRS Vaihingen dataset and 77.36%/87.09% on ISPRS Potsdam dataset. The code will be available at https://github.com/HC-Zhou/HST-UNet. [ABSTRACT FROM AUTHOR]

Polyphenol compounds can modify myofibrillar proteins to improve the quality of fish and surimi. Nevertheless, research into the precise mechanisms of interaction between phenolic substances and sea bass myofibrillar proteins is lacking. This study aimed to explore the interaction mechanism between five phenolic compounds (caffeic acid (CFA), gallic acid (GA), chlorogenic acid (CHA), resveratrol (RES), and catechin (CAT)) with sea bass myofibrillar protein (MP). The results of UV–vis absorption spectroscopy, Fourier transform infrared (FT-IR) spectroscopy, and fluorescence spectroscopy (namely, multi-spectroscopy) showed that all five phenolic compounds could spontaneously form new complexes with MP, with a binding molar ratio of 1:1. The interaction between CFA and MP is predominantly electrostatic, while the interaction between GA and MP is mainly hydrophobic. The rest of phenolic compounds and MP are mediated by hydrogen bonds and van der Waals forces. And molecular dynamics (MD) simulations indicated that CHA-myosin had the minimum root mean square deviation, while CFA-myosin had the smallest Rg value. In addition, the amino acid Lys-179 was the key residue for the interaction between five phenolic compounds and myosin. This study contributes to a better understanding of the interaction between phenolic compounds and sea bass MP, which could develop the processing of aquatic food products. [ABSTRACT FROM AUTHOR]