Clonal dominance defines metastatic dissemination in pancreatic cancer

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Dynamics Analysis of Castor Hulling in the Process of Air-and-Screen Cleaning

The air-and-screen cleaning mechanism of castor hulling is analyzed in this paper. And the numeric expression equations of the castor dynamics analysis are established. The correlation of floating speeds vp, air speeds w, the direction angle of airflow velocity β, the direction angle of vibration δ, the friction angle ϕ, the slip coefficient, the fell coefficient and the jumping coefficient are analyzed

Conjugation in Euplotes raikovi (Protista, Ciliophora): New Insights into Nuclear Events and Macronuclear Development from Micronucleate and Amicronucleate Cells

Ciliates form a distinct group of single‐celled eukaryotes that host two types of nuclei (micro and macronucleus) in the same cytoplasm and have a special sexual process known as conjugation, which involves mitosis, meiosis, fertilization, nuclear differentiation, and development. Due to their high species diversity, ciliates have evolved different patterns of nuclear events during conjugation. In the present study, we investigate these events in detail in the marine species Euplotes raikovi. Our results indicate that: (i) conjugation lasts for about 50 hours, the longest stage being the development of the new macronucleus (ca. 36 hours); (ii) there are three prezygotic micronuclear divisions (mitosis and meiosis I and II) and two postzygotic synkaryon divisions; and (iii) a fragment of the parental macronucleus fuses with the new developing macronucleus. In addition, we describe for the first time conjugation in amicronucleate E. raikovi cells. When two amicronucleate cells mate, they separate after about 4 hours without evident nuclear changes; when one amicronucleate cell mates with a micronucleate cell, the micronucleus undergoes regular prezygotic divisions to form migratory and stationary pronuclei, but the two pronuclei fuse in the same cell. In the amicronucleate cell, the parental macronucleus breaks into fragments, which are then recovered to form a new functional macronucleus. These results add new information on the process of conjugation in both micronucleate and amicronucleate Euplotes cells

Dynamics Analysis of Castor Hulling in the Process of Air-and-Screen Cleaning

The air-and-screen cleaning mechanism of castor hulling is analyzed in this paper. And the numeric expression equations of the castor dynamics analysis are established. The correlation of floating speeds vp, air speeds w, the direction angle of airflow velocity β, the direction angle of vibration δ, the friction angle ϕ, the slip coefficient, the fell coefficient and the jumping coefficient are analyzed

Design and Implementation of Intelligent EOD System Based on Six-Rotor UAV

Explosive ordnance disposal (EOD) robots can replace humans that work in hazardous environments to ensure worker safety. Thus, they have been widely developed and deployed. However, existing EOD robots have some limitations in environmental adaptation, such as a single function, slow action speed, and limited vision. To overcome these shortcomings and solve the uncertain problem of bomb disposal on the firing range, we have developed an intelligent bomb disposal system that integrates autonomous unmanned aerial vehicle (UAV) navigation, deep learning, and other technologies. For the hardware structure of the system, we design an actuator constructed by a winch device and a mechanical gripper to grasp the unexploded ordnance (UXO), which is equipped under the six-rotor UAV. The integrated dual-vision Pan-Tilt-Zoom (PTZ) pod is applied in the system to monitor and photograph the deployment site for dropping live munitions. For the software structure of the system, the ground station exploits the YOLOv5 algorithm to detect the grenade targets for real-time video and accurately locate the landing point of the grenade. The operator remotely controls the UAV to grasp, transfer, and destroy grenades. Experiments on explosives defusal are performed, and the results show that our system is feasible with high recognition accuracy and strong maneuverability. Compared with the traditional mode of explosives defusal, the system can provide decision-makers with accurate information on the location of the grenade and at the same time better mitigate the potential casualties in the explosive demolition process

Photoluminescence manipulation in two-dimensional transition metal dichalcogenides

Two-dimensional transition metal dichalcogenides (TMDCs) have been regarded as an intriguing platform for exploring novel physical phenomena and optoelectronic devices due to their excitonic emission characteristics derived from the atomic thin thickness and reduced dielectric screening effect. Notably, monolayer TMDCs with a direct bandgap exhibiting strong photoluminescence (PL) are promising candidates for the light-emitting devices, while the interlayer excitons in heterostructures hold great potential for the photonic chips and optical communication applications. However, the non-ideal photoluminescent intensity and quality due to the ultrathin thickness and high defect density of experimentally obtained monolayer TMDCs limit the further development for the light-emission applications. Here, we summarize the research progress on the PL manipulation of the excitonic emission in TMDCs, where the PL intensity enhancement and emission wavelength regulation are included. The concept and characteristics of excitons are overviewed firstly, followed by the discussion on the evaluation and characterization of excitonic emission. The state-of-the-art progress on the manipulation of the neutral excitons and interlayer excitons PL are then summarized. Finally, the challenges and prospects are proposed

A Proposal for Lodging Judgment of Rice Based on Binocular Camera

Rice lodging is a crucial problem in rice production. Lodging during growing and harvesting periods can decrease rice yields. Practical lodging judgment for rice can provide effective reference information for yield prediction and harvesting. This article proposes a binocular camera-based lodging judgment method for rice in real-time. As a first step, the binocular camera and Inertial Measurement Unit (IMU) were calibrated. Secondly, Census and Grayscale Level cost features are constructed for stereo matching of left and right images. The Cross-Matching Cost Aggregation method is improved to compute the aggregation space in the LAB color space. Then, the Winner-Takes-All algorithm is applied to determine the optimal disparity for each pixel. A disparity map is constructed, and Multi-Step Disparity Refinement is applied to the disparity map to generate the final one. Finally, coordinate transformation obtains 3D world coordinates corresponding to pixels. IMU calculates the real-time pose of the binocular camera. A pose transformation is applied to the 3D world coordinates of the rice to obtain its 3D world coordinates in the horizontal state of the camera (pitch and roll angles are equal to 0). Based on the distance between the rice and the camera level, thresholding was used to determine whether the region to be detected belonged to lodging rice. The disparity map effect of the proposed matching algorithm was tested on the Middlebury Benchmark v3 dataset. The results show that the proposed algorithm is superior to the widely used Semi-Global Block Matching (SGBM) stereo-matching algorithm. Field images of rice were analyzed for lodging judgments. After the threshold judgment, the lodging region results were accurate and could be used to judge rice lodging. By combining the algorithms with binocular cameras, the research results can provide practical technical support for yield estimation and intelligent control of rice harvesters

TCNet: Transformer Convolution Network for Cutting-Edge Detection of Unharvested Rice Regions

Cutting-edge detection is a critical step in mechanized rice harvesting. Through visual cutting-edge detection, an algorithm can sense in real-time whether the rice harvesting process is along the cutting-edge, reducing loss and improving the efficiency of mechanized harvest. Although convolutional neural network-based models, which have strong local feature acquisition ability, have been widely used in rice production, these models involve large receptive fields only in the deep network. Besides, a self-attention-based Transformer can effectively provide global features to complement the disadvantages of CNNs. Hence, to quickly and accurately complete the task of cutting-edge detection in a complex rice harvesting environment, this article develops a Transformer Convolution Network (TCNet). This cutting-edge detection algorithm combines the Transformer with a CNN. Specifically, the Transformer realizes a patch embedding through a 3 × 3 convolution, and the output is employed as the input of the Transformer module. Additionally, the multi-head attention in the Transformer module undergoes dimensionality reduction to reduce overall network computation. In the Feed-forward network, a 7 × 7 convolution operation is used to realize the position-coding of different patches. Moreover, CNN uses depth-separable convolutions to extract local features from the images. The global features extracted by the Transformer and the local features extracted by the CNN are integrated into the fusion module. The test results demonstrated that TCNet could segment 97.88% of the Intersection over Union and 98.95% of the Accuracy in the unharvested region, and the number of parameters is only 10.796M. Cutting-edge detection is better than common lightweight backbone networks, achieving the detection effect of deep convolutional networks (ResNet-50) with fewer parameters. The proposed TCNet shows the advantages of a Transformer combined with a CNN and provides real-time and reliable reference information for the subsequent operation of rice harvesting