NOVEL MECHANISMS IN THE REGULATION OF PERINUCLEAR ACTIN ASSEMBLY

Ph.DPH.D. IN MECHANOBIOLOGY (FOS

Sea-Surface Object Detection Based on Electro-Optical Sensors: A Review

Sea-surface object detection is critical for navigation safety of autonomous ships. Electrooptical (EO) sensors, such as video cameras, complement radar on board in detecting small obstacle sea-surface objects. Traditionally, researchers have used horizon detection, background subtraction, and foreground segmentation techniques to detect sea-surface objects. Recently, deep learning-based object detection technologies have been gradually applied to sea-surface object detection. This article demonstrates a comprehensive overview of sea-surface object-detection approaches where the advantages and drawbacks of each technique are compared, covering four essential aspects: EO sensors and image types, traditional object-detection methods, deep learning methods, and maritime datasets collection. In particular, sea-surface object detections based on deep learning methods are thoroughly analyzed and compared with highly influential public datasets introduced as benchmarks to verify the effectiveness of these approaches. The arti

Mechanical stimulation induces formin-dependent assembly of a perinuclear actin rim

Proceedings of the National Academy of Sciences of the United States of America11220E2595-E260

Size dependent effectiveness of engineering and administrative control strategies for both short- and long-range airborne transmission control

Ventilation is recognized as an effective mitigation strategy for long-range airborne transmission. However, a recent study by Li et al. revealed its potential impact on short-range airborne transmission as well. Our study extends their work by developing size-dependent transmission models for both short- and long-range airborne transmission and evaluates the impact of various control strategies, including ventilation. By adopting a recently determined mode-dependent viral load, we first analyzed the role of different sizes of droplets in airborne transmission. In contrast to models with a constant viral load where large droplets contain more viruses, our findings demonstrated that droplets ranging from ∼2–4 μm are more critical for short-range airborne transmission. Meanwhile, droplets in the ∼1–2 μm range play a significant role in long-range airborne transmission. Furthermore, our study indicates that implementing a size-dependent filtration/mask strategy considerably affects the rate of change (ROC) of virus concentration in relation to both distancing and ventilation. This underscores the importance of factoring in droplet size during risk assessment. Engineering controls, like ventilation and filtration, as well as administrative controls, such as distancing and masks, have different effectiveness in reducing virus concentration. Our findings indicate that high-efficiency masks can drastically reduce virus concentrations, potentially diminishing the impacts of other strategies. Given the size-dependent efficiency of filtration, ventilation has a more important role in reducing virus concentration than filtration, especially for long-range airborne transmission. For short-range airborne transmission, maintaining distance is far more effective than ventilation, and its effectiveness is largely unaffected by ventilation. However, the influence of ventilation on virus concentration and its variation with the distance mainly depend on the specific transmission model utilized. In sum, this research delineates the differential roles of droplet sizes and control strategies in both short- and long-range airborne transmission, offering valuable insights for future size-dependent airborne transmission control measures

Index system study on distributed InSAR formation system

TH-2 is the first close-range dual-satellite formation distributed InSAR satellite system in China, which enables China to establish global digital surface model and radar orthophoto acquisition capability. Addressing the need for rapid access to global elevation data (1∶50 000), this paper investigates the index system for satellite formation design, control and planning based on an integrated design concept in the context of the TH-2. This method establishes a demonstration model of formation technical index for three types of application requirements: image bypass overlap, interferometric imaging baseline and earth observation effectiveness, based on the full consideration of the coupling effect of technical index on system application performance. The proposed method integrates formation theory into engineering practice, which can achieve the goal of fast and efficient distributed SAR satellite formation system design and support the development of model equipment and ground operation and management system. The in-orbit results of TH-2 show that the proposed method is reasonable and feasible, and the performance indicators are accurately assigned

Weight-based Channel-model Matrix Framework provides a reasonable solution for EEG-based cross-dataset emotion recognition

Cross-dataset emotion recognition as an extremely challenging task in the field of EEG-based affective computing is influenced by many factors, which makes the universal models yield unsatisfactory results. Facing the situation that lacks EEG information decoding research, we first analyzed the impact of different EEG information(individual, session, emotion and trial) for emotion recognition by sample space visualization, sample aggregation phenomena quantification, and energy pattern analysis on five public datasets. Based on these phenomena and patterns, we provided the processing methods and interpretable work of various EEG differences. Through the analysis of emotional feature distribution patterns, the Individual Emotional Feature Distribution Difference(IEFDD) was found, which was also considered as the main factor of the stability for emotion recognition. After analyzing the limitations of traditional modeling approach suffering from IEFDD, the Weight-based Channel-model Matrix Framework(WCMF) was proposed. To reasonably characterize emotional feature distribution patterns, four weight extraction methods were designed, and the optimal was the correction T-test(CT) weight extraction method. Finally, the performance of WCMF was validated on cross-dataset tasks in two kinds of experiments that simulated different practical scenarios, and the results showed that WCMF had more stable and better emotion recognition ability.Comment: 18 pages, 12 figures, 8 table

Multi-Scale Object Detection Model for Autonomous Ship Navigation in Maritime Environment

Accurate detection of sea-surface objects is vital for the safe navigation of autonomous ships. With the continuous development of artificial intelligence, electro-optical (EO) sensors such as video cameras are used to supplement marine radar to improve the detection of objects that produce weak radar signals and small sizes. In this study, we propose an enhanced convolutional neural network (CNN) named VarifocalNet * that improves object detection in harsh maritime environments. Specifically, the feature representation and learning ability of the VarifocalNet model are improved by using a deformable convolution module, redesigning the loss function, introducing a soft non-maximum suppression algorithm, and incorporating multi-scale prediction methods. These strategies improve the accuracy and reliability of our CNN-based detection results under complex sea conditions, such as in turbulent waves, sea fog, and water reflection. Experimental results under different maritime conditions show that our method significantly outperforms similar methods (such as SSD, YOLOv3, RetinaNet, Faster R-CNN, Cascade R-CNN) in terms of the detection accuracy and robustness for small objects. The maritime obstacle detection results were obtained under harsh imaging conditions to demonstrate the performance of our network model

Relations of stellar mass between electron temperature-based metallicity of star-forming galaxies in a wide mass range

We select 947 star-forming galaxies from SDSS-DR7 with [O~{\sc iii}]$\lambda$4363 emission lines detected at a signal-to-noise {ratio }larger than 5$\sigma$. Their electron temperatures and direct oxygen abundances are {then }determined. {W}e compare the results from different methods. $t_2${, the} electron temperature in {the }low ionization region{,} estimated from $t_3${, that} in {the }high ionization region{,} {is} compared {using} three analysis relations between $t_2-t_3${. These} show obvious differences, which result in some different ionic oxygen abundances. The results of $t_3$, $t_2$, {$\rm O^{++}$/$\rm H^+$} and {$\rm O^{+}$/$\rm H^+$} derived by using methods from IRAF and literature are also compared. The ionic abundances $\rm O^{++}$/$\rm H^+$ {are} higher than $\rm O^{+}$/$\rm H^+$ for most cases. The{ different} oxygen abundances derived from $T_{\rm e}$ and the strong-line ratios show {a }clear discrepancy, which is more obvious following increasing stellar mass and strong-line ratio $R_{23}$. The sample{ of} galaxies from SDSS {with} detected [O~{\sc iii}]$\lambda$4363 have lower metallicites and higher {star formation rates}, {so} they may not be typical representatives of the whole{ population of} galaxies. Adopting data objects from {Andrews \& Martini}, {Liang et al.} and {Lee et al.} data, we derive new relations of stellar mass and metallicity for star-forming galaxies in a much wider stellar mass range: from $10^6\,M_\odot$ to $10^{11}\,M_\odot$.Comment: 16 pages, 11 figures, Accepted by Research in Astronomy and Astrophysic