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With the wide application of vision‐based autonomous driving and mobile robots, the impact of frequent sand‐dust weather on computer vision applications in landlocked countries during spring and autumn has also attracted more and more attention. Although there has been a lot of research on sand‐dust image enhancement, no research has been conducted on how to improve the positioning accuracy of vision‐based autonomous driving or mobile robots in sand‐dust environments, especially because there is currently a lack of dataset to evaluate visual positioning in sand‐dust weather. Therefore, a complete set of visual positioning dataset construction methods in sand‐dust weather is proposed to fill the gap in the evaluation dataset of application fields such as autonomous driving or mobile robot attitude estimation in sand‐dust weather. At the same time, this method is also suitable for the construction of visual positioning dataset under haze and other similar weather. In addition, this paper further demonstrates to readers how to use the converted dust visual positioning dataset to conduct positioning evaluation experiment of automatic driving in sand‐dust weather. A complete set of visual positioning data set construction methods are proposed in sand‐dust weather to fill the gap in the evaluation data set of application fields such as autonomous driving or mobile robot attitude estimation in sand‐dust weather. At the same time, this method is also suitable for the construction of visual positioning data sets under haze and other similar weather. In addition, this paper further demonstrates to readers how to use the converted dust visual positioning data set to conduct positioning evaluation experiment of automatic driving in sand‐dust weather.

Crocins are water-soluble apocarotenoids isolated from the flowers of crocus and gardenia. They exhibit various pharmacological effects, including neuroprotection, anti-inflammatory properties, hepatorenal protection, and anticancer activity. They are often used as coloring and seasoning agents. Due to the limited content of crocins in plants and the high cost of chemical synthesis, the supply of crocins is insufficient to meet current demand. The biosynthetic pathways for crocins have been elucidated to date, which allows the heterologous production of these valuable compounds in microorganisms by fermentation. This review article provides a comprehensive overview of the chemistry, pharmacological activity, biosynthetic pathways, and heterologous production of crocins, aiming to lay the foundation for the large-scale production of these valuable natural products by using engineered microbial cell factories.

To solve the object detection task in the harsh sandy environment, this paper proposes a lightweight sandy vegetation object detection algorithm based on attention mechanism. We reduce the number of model parameters by lightweight design of the anchor-free object detection algorithm model, thereby reducing the model inference time and memory cost. Specifically, the algorithm uses a lightweight backbone network to extract features, and uses linear interpolation in the neck network to achieve multi-scale. Model algorithm compression is performed by depthwise separable convolution in the head network. At the same time, the channel attention mechanism is added to the model to further optimize the algorithm. Experiments have proved the superiority of the algorithm, the mAP in the training effect is 76%, and the prediction time per frame is 0.0277 seconds. It realizes the efficiency and accuracy of the algorithm operation in the desert environment.

SYCP1 and SYCP3 are essential testis‐specific genes for centromere pairing during meiosis, as well as for spermatogenesis and fertility in male germ cells. However, it is still unclear regarding the expression patterns in the fertile reciprocal hybrid offspring of Megalobrama amblycephala (blunt snout bream, BSB, 2n = 48) × Culter alburnus (topmouth culter, TC, 2n = 48). This research elucidated the genetic and expression characteristics of SYCP1 and SYCP3 through molecular cloning, sequence alignment, Western blotting, and immunohistochemistry to assess their roles in both hybrids and parents. The findings revealed that SYCP1 and SYCP3 exhibited high homology between M. amblycephala and C. alburnus, with varying degrees of chimerism in the BT and TB hybrids. The expression level of SYCP1 in these hybrids was intermediate between parents, while SYCP3 was more similar to M. amblycephala and significantly different from C. alburnus (p < 0.05). Western blotting confirmed the normal expression of both SYCP1 and SYCP3 proteins in the hybrid offspring. Immunohistochemistry verified the significant presence of these proteins in the testes of mature hybrids. These findings suggested that BT and TB hybrids retained the stability of the SYCP1 and SYCP3 genes inherited from their heterozygous parental origins, supporting independent protein expression despite slight variations in the CDS structure. Our results demonstrate that the normal expression of key meiotic genes plays an important role in overcoming reproductive barriers in distant hybridization, which is of great significance for genetic breeding in fish.

Over the past decades, vehicular ad hoc networks (VANETs) have been a core networking technology to provide drivers and passengers with safety and convenience. As a new emerging technology, the vehicular cloud computing (VCC) can provide cloud services for various data-intensive applications in VANETs, such as multimedia streaming. However, the vehicle mobility and intermittent connectivity present challenges to the large-scale data dissemination with underlying computing and networking architecture. In this paper, we will explore the service scheduling of virtual RSUs for diverse request demands in the dynamic traffic flow in vehicular cloud environment. Specifically, we formulate the RSU allocation problem as maximum service capacity with multiple-source and multiple-destination, and propose a bidirectional RSU allocation strategy. In addition, we formulate the content replication in distributed RSUs as the minimum replication set coverage problem in a two-layer mapping model, and analyze the solutions in different scenarios. Numerical results further prove the superiority of our proposed solution, as well as the scalability to various traffic condition variations.

The frequent sand-dust weather in inland areas has severely affected the local outdoor computer vision applications. To improve the poor image quality and color shift caused by sand-dust weather, different from the previous ideas of the sand-dust image enhancement algorithm, this paper proposes a generative adversarial network to enhance the sand-dust images. We improve the classic pix2pix network by introducing the dual attention mechanism to the U-net architecture and improve the loss function of the generator through Smooth L1 and SSIM to further enhance the color reproduction, detail features, the structural similarity, and the convergence speed of the generator. In addition, we also publish the first artificially synthesized sand-dust image data set online. The experimental results show that the enhancement method proposed in this paper has obvious advantages in both artificially synthesized images and natural real images, compared with the current traditional sand-dust enhancement algorithms and the previous network models.

A mobile robot with a robotic arm needs to be able to autonomously perceive the operating environment and plan the trajectory of the object’s surface in order to perform surface cleaning tasks in a complex, unstructured environment. This study suggests an autonomous trajectory planning technique for cleaning an object’s surface based on RGB-D semantic segmentation, which enables the robotic arm to move the cleaning mechanism on the object’s surface smoothly and steadily and finish the cleaning process. More particularly, it contains the following: (1) A Double Attention Fusion Net (DAFNet) RGB-D semantic segmentation network is proposed, which successfully integrates color texture features and spatial structure features and enhances the semantic segmentation performance of indoor objects. This network is based on the dual attention mechanism (channel attention and spatial attention). (2) The trajectory planning algorithm for the robot arm is created, and the semantically segmented data is clustered using DBCSCAN. In order to achieve autonomous planning of the cleaning trajectory, the target subject is first extracted, and then the working trajectory of the robot arm is generated via the processes of edge detection, slicing, sampling, fitting, etc. We also compare the accuracy of DAFNet semantic segmentation and other algorithms on SUNRGBD and self-built datasets, experiment with trajectory generation for various objects, and evaluate the online surface cleaning procedure. According to the experimental findings, the DAFNet semantic segmentation model is more accurate than the current models. According to the online test, the trajectory generated has a good degree of smoothness and continuity, and the robotic arm is capable of completing the surface cleaning operation effectively.

As the cathode of lithium-ion batteries, carbon material has been the focus of research. At present, diverse investigations have been carried out on the lithium convergence behavior in the carbon material family. As a new carbon material, multilayer fullerenes have been shown in various experimental studies to have a high discharge rate as an electrode, indicating that onion-like carbon has the potential to release energy quickly. Materials and mechanical scientists are increasingly interested in lithium-ion batteries. In this paper, the molecular dynamics (MD) method was used to simulate the absorption of lithium ions by multilayer fullerenes. A model of five layers of fullerenes was established to compare the lithium-ion absorption rates of multiple layers of fullerenes at different lithium-ion concentrations. The effects of the lithium-ion diffusion rate on the results were considered. In addition, the effects of the number of lithium ions, the velocity, and the layer number of multilayer fullerenes on the structural behavior and stress were investigated thoroughly when the multilayer fullerenes adsorbed lithium ions.

Effective entrepreneurship education can not only cultivate students’ entrepreneurship awareness and inspire entrepreneurial potential, but also set up an entrepreneurial foundation and form entrepreneurial practice, but the current teaching system doesn’t have strong timeliness, due to the high interest of students and lack of rich teaching methods and means by college teachers. Taking “online + offline” entrepreneurship education courses as an example, an “online + offline” teaching mode based on case teaching method was developed in this paper. Based on curriculum theory, the author identified the attractive quality and must-be quality of this course by fully understanding students’ needs in the learning process of “online + offline” courses, and designed a questionnaire on the needs for the learning support services of “online + offline” course products, to understand the satisfaction degree of students corresponding to each need. At the same time, combined with the characteristics of the “online + offline” courses, by reference to the evaluation criteria of DEMATEL-ANP, course mentoring, communication, final exam, subtitles and video effect were taken as key indicators, to build an evaluation system to be used in this mode. Finally, the teaching practice proves that this mode can better increase students’ learning interest, expand the teaching content of entrepreneurship education course and improve students’ satisfaction with this course.

Batteries with conversion-type electrodes exhibit higher energy storage density but suffer much severer capacity fading than those with the intercalation-type electrodes. The capacity fading has been considered as the result of contact failure between the active material and the current collector, or the breakdown of solid electrolyte interphase layer. Here, using a combination of synchrotron X-ray absorption spectroscopy and in situ transmission electron microscopy, we investigate the capacity fading issue of conversion-type materials by studying phase evolution of iron oxide composited structure during later-stage cycles, which is found completely different from its initial lithiation. The accumulative internal passivation phase and the surface layer over cycling enforce a rate−limiting diffusion barrier for the electron transport, which is responsible for the capacity degradation and poor rate capability. This work directly links the performance with the microscopic phase evolution in cycled electrode materials and provides insights into designing conversion-type electrode materials for applications. Conversion electrodes possess high energy density but suffer a rapid capacity loss over cycling compared to their intercalation equivalents. Here the authors reveal the microscopic origin of the fading behavior, showing that the formation and augmentation of passivation layers are responsible.