Real-Time Vehicle Detection from Short-range Aerial Image with Compressed MobileNet

Vehicle detection from short-range aerial image faces challenges including vehicle blocking, irrelevant object interference, motion blurring, color variation etc., leading to the difficulty to achieve high detection accuracy and real-time detection speed. In this paper, benefiting from the recent development in MobileNet family network engineering, we propose a compressed MobileNet which is not only internally resistant to the above listed challenges but also gains the best detection accuracy/speed tradeoff when comparing with the original MobileNet. In a nutshell, we reduce the bottleneck architecture number during the feature map downsampling stage but add more bottlenecks during the feature map plateau stage, neither extra FLOPs nor parameters are thus involved but reduced inference time and better accuracy are expected. We conduct experiment on our collected 5-k short-range aerial images, containing six vehicle categories: truck, car, bus, bicycle, motorcycle, crowded bicycles and crowded motorcycles. Our proposed compressed MobileNet achieves 110 FPS (GPU), 31 FPS (CPU) and 15 FPS (mobile phone), 1.2 times faster and 2% more accurate (mAP) than the original MobileNet

Progress of research on PD-1/PD-L1 in leukemia

Leukemia cells prevent immune system from clearing tumor cells by inducing the immunosuppression of the bone marrow (BM) microenvironment. In recent years, further understanding of the BM microenvironment and immune landscape of leukemia has resulted in the introduction of several immunotherapies, including checkpoint inhibitors, T-cell engager, antibody drug conjugates, and cellular therapies in clinical trials. Among them, the programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) axis is a significant checkpoint for controlling immune responses, the PD-1 receptor on tumor-infiltrating T cells is bound by PD-L1 on leukemia cells. Consequently, the activation of tumor reactive T cells is inhibited and their apoptosis is promoted, preventing the rejection of the tumor by immune system and thus resulting in the occurrence of immune tolerance. The PD-1/PD-L1 axis serves as a significant mechanism by which tumor cells evade immune surveillance, and PD-1/PD-L1 checkpoint inhibitors have been approved for the treatment of lymphomas and varieties of solid tumors. However, the development of drugs targeting PD-1/PD-L1 in leukemia remains in the clinical-trial stage. In this review, we tally up the basic research and clinical trials on PD-1/PD-L1 inhibitors in leukemia, as well as discuss the relevant toxicity and impacts of PD-1/PD-L1 on other immunotherapies such as hematopoietic stem cell transplantation, bi-specific T-cell engager, chimeric antigen receptor T-cell immunotherapy

Sulfur-Based Electrodes that Function via Multielectron Reactions for Room-Temperature Sodium-Ion Storage

Emerging rechargeable sodium-ion storage systems—sodium-ion and room-temperature sodium–sulfur (RT-NaS) batteries—are gaining extensive research interest as low-cost options for large-scale energy-storage applications. Owing to their abundance, easy accessibility, and unique physical and chemical properties, sulfur-based materials, in particular metal sulfides (MSx) and elemental sulfur (S), are currently regarded as promising electrode candidates for Na-storage technologies with high capacity and excellent redox reversibility based on multielectron conversion reactions. Here, we present current understanding of Na-storage mechanisms of the S-based electrode materials. Recent progress and strategies for improving electronic conductivity and tolerating volume variations of the MSx anodes in Na-ion batteries are reviewed. In addition, current advances on S cathodes in RT-NaS batteries are presented. We outline a novel emerging concept of integrating MSx electrocatalysts into conventional carbonaceous matrices as effective polarized S hosts in RT-NaS batteries as well. This comprehensive progress report could provide guidance for research toward the development of S-based materials for the future Na-storage techniques

Lotus rhizome-like S/N-C with embedded WS2 for superior sodium storage

Sodium-ion batteries (SIBs) hold great promise as power sources because of their low cost and decent electrochemical behavior. Nevertheless, the poor rate performance and long-term cycling capability of anode materials in SIBs still impede their practical application in smart grids and electric vehicles. Herein, we design a delicate method to embed WS2 nanosheets into lotus rhizome-like heteroatom-doped carbon nanofibers with abundant hierarchical tubes inside, forming WS2@sulfur and nitrogen-doped carbon nanofibers (WS2@S/N-C). The WS2@S/N-C nanofibers exhibit a large discharge capacity of 381 mA h g-1 at 100 mA g-1, excellent rate capacity of 108 mA h g-1 at 30 A g-1, and a superior capacity of 175 mA h g-1 at 5 A g-1 after 1000 cycles. The excellent performance of WS2@S/N-C is ascribed to the synergistic effects of WS2 nanosheets, contributing to larger interlayer spacing, and the stable lotus rhizome-like S/N-C nanofiber frameworks which alleviate the mechanical stress. Moreover, the WS2@S/N-C electrode shows obvious pseudocapacitive properties at 1 mV s-1 with a capacitive contribution of 86.5%. In addition, density functional theory calculations further indicate that the WS2@S/N-C electrode is very favorable for Na storage. This novel synthetic strategy is a promising method for synthesizing other electrode materials for rechargeable batteries in the future

Effects of Seed Size and Sand Burial on Germination and Early Growth of Seedlings for Coastal <i>Pinus thunbergii</i> Parl. in the Northern Shandong Peninsula, China

This paper examines the effects of seed size and the depth of sand burial on seed germination and seedling development for Pinus thunbergii. Parl. Seeds from 20- to 30-year old trees grown in the coastal area of Yantai were divided into three size categories (large, medium, and small). The seeds were sown in pots with different depth of sand, and their germination and seedling growth during the first month were investigated. Results showed that large seeds possessed the highest 1000-seed weight and soluble sugar concentration. Large and medium seeds had a higher germination rate, germination index, vigor index, and seedling biomass than small seeds. With the increase in seed size, root mass ratio, root/shoot ratio, specific root length, and specific root area decreased, whereas leaf mass ratio increased. Sand burial depth significantly influenced seed germination and seedling growth, and the highest germination rate and seedling biomass were achieved with 2&#8211;3 cm sand burial. We also found that seedling biomass was positively related to germination rate, germination index, and vigor index, but was negatively related to mean germination time. Moreover, seedling biomass was negatively correlated with root mass ratio and root/shoot ratio, but positively correlated with leaf mass ratio, specific root length, and specific root area. The results suggest that seed size and sand burial depth are key factors in the regeneration of the coastal P. thunbergii forest

BIFRNet: A Brain-Inspired Feature Restoration DNN for Partially Occluded Image Recognition

The partially occluded image recognition (POIR) problem has been a challenge for artificial intelligence for a long time. A common strategy to handle the POIR problem is using the non-occluded features for classification. Unfortunately, this strategy will lose effectiveness when the image is severely occluded, since the visible parts can only provide limited information. Several studies in neuroscience reveal that feature restoration which fills in the occluded information and is called amodal completion is essential for human brains to recognize partially occluded images. However, feature restoration is commonly ignored by CNNs, which may be the reason why CNNs are ineffective for the POIR problem. Inspired by this, we propose a novel brain-inspired feature restoration network (BIFRNet) to solve the POIR problem. It mimics a ventral visual pathway to extract image features and a dorsal visual pathway to distinguish occluded and visible image regions. In addition, it also uses a knowledge module to store classification prior knowledge and uses a completion module to restore occluded features based on visible features and prior knowledge. Thorough experiments on synthetic and real-world occluded image datasets show that BIFRNet outperforms the existing methods in solving the POIR problem. Especially for severely occluded images, BIRFRNet surpasses other methods by a large margin and is close to the human brain performance. Furthermore, the brain-inspired design makes BIFRNet more interpretable

The effects of diverse microbial community structures, driven by arbuscular mycorrhizal fungi inoculation, on carbon release from a paddy field

Arbuscular mycorrhizal fungi (AMF) play a key role in regulating the carbon cycle in terrestrial ecosystems. However, there is little information on how AMF inoculation affects the carbon fluxes of paddy fields, which are major sources of global carbon emissions. We, therefore, designed an experiment to study the effects of AMF inoculation on methane and carbon dioxide emissions from a paddy field. Results showed that: (1) Among the tested factors, the C/N ratio was the main environmental determinant of microbial community structure in the investigated soil; (2) compared with traditional fertilisation (control), the soil C/N ratio increased by 2.1~15.2% and 1.4~10.5% as a result of AMF application alone (M) or in combination with mineral fertiliser (FM) throughout the growing season, respectively. This change shifted microbial community composition to higher G+/G- bacterial and fungal/bacterial ratios; (3) the microbial community change favoured soil carbon retention. Methane (CH4) emission peaks were reduced by 59.4% and 76.0% versus control in the M treatment and by 52.5% and 29.4% in the FM treatment in the midseason and end-of-season drainage periods, and CO2 emission peaks were reduced by 70.1% and 52.3% in the M plots and by 55.4% and 66.4% in the FM plots

S/N-doped carbon nanofibers affording Fe7S8 particles with superior sodium storage

2020 Iron sulfides draw much attention as electrode candidates for sodium-ion batteries (SIBs) due to the rich chemical stoichiometries and high capacity. However, they usually exhibit poor cycling performance due to the large volume change during sodiation/desodiation process. In this work, we embed Fe7S8 nanoparticles into sulfur, nitrogen-doped carbon (S/N-C) nanofibers through electrospinning/sulfurization processes. The heteroatom doped carbon matrixes could effectively protect the Fe7S8 from structural collapse, obtaining a stable cycling performance. Moreover, the conductive matrixes with 1D structure can facilitate the diffusion of electrons, leading to good rate capability. As results, the as-designed Fe7S8@S/N-C nanofibers present a discharge capacity of 347 m Ah g−1 after 150 cycles at 1 A g−1 and a high rate capacity of 220 m Ah g−1 at 5 A g−1 in virtue of unique structural characteristics