YOLSO: You Only Look Small Object

Small object detection is challenging and far from satisfactory. Most general object detectors suffer from two critical issues with small objects: (1) Feature extractor based on classification network cannot express the characteristics of small objects reasonably due to insufficient appearance information of targets and a large amount of background interference around them. (2) The detector requires a much higher location accuracy for small objects than for general objects. This paper proposes an effective and efficient small object detector YOLSO to address the above problems. For feature representation, we analyze the drawbacks in previous backbones and present a Half-Space Shortcut(HSSC) module to build a background-aware backbone. Furthermore, a coarse-to-fine Feature Pyramid Enhancement(FPE) module is introduced for layer-wise aggregation at a granular level to enhance the semantic discriminability. For loss function, we propose an exponential L1 loss to promote the convergence of regression, and a focal IOU loss to focus on prime samples with high classification confidence and high IOU. Both of them significantly improves the location accuracy of small objects. The proposed YOLSO sets state-of-the-art results on two typical small object datasets, MOCOD and VeDAI, at a speed of over 200 FPS. In the meantime, it also outperforms the baseline YOLOv3 by a wide margin on the common COCO dataset.     

AQP3 Increases Intercellular Cohesion in NSCLC A549 Cell Spheroids through Exploratory Cell Protrusions

Tumor cell aggregation is critical for cell survival following the loss of extracellular matrix attachment and dissemination. However, the underlying mechanotransduction of clustering solitary tumor cells is poorly understood, especially in non-small cell lung cancers (NSCLC). Here, we examined whether cell surface protrusions played an important role in facilitating the physical contact between floating cells detached from a substrate. We employed poly-2-hydroxyethyl methacrylate-based 3D culture methods to mimic in vivo tumor cell cluster formation. The suprastructural analysis of human NSCLC A549 cell spheroids showed that finger-like protrusions clung together via the actin cytoskeleton. Time-lapse holotomography demonstrated that the finger-like protrusions of free-floating cells in 3D culture displayed exploratory coalescence. Global gene expression analysis demonstrated that the genes in the organic hydroxyl transport were particularly enriched in the A549 cell spheroids. Particularly, the knockdown of the water channel aquaporin 3 gene (AQP3) impaired multicellular aggregate formation in 3D culture through the rearrangement of the actomyosin cytoskeleton. Moreover, the cells with reduced levels of AQP3 decreased their transmigration. Overall, these data indicate that cell detachment-upregulated AQP3 contributes to cell surface protrusions through actomyosin cytoskeleton remodeling, causing the aggressive aggregation of free-floating cells dependent on the property of the substratum and collective metastasis.     

Diphenyl-Methane Based Thyromimetic Inhibitors for Transthyretin Amyloidosis

Thyromimetics, whose physicochemical characteristics are analog to thyroid hormones (THs) and their derivatives, are promising candidates as novel therapeutics for neurodegenerative and metabolic pathologies. In particular, sobetirome (GC-1), one of the initial halogen-free thyromimetics, and newly synthesized IS25 and TG68, with optimized ADME-Tox profile, have recently attracted attention owing to their superior therapeutic benefits, selectivity, and enhanced permeability. Here, we further explored the functional capabilities of these thyromimetics to inhibit transthyretin (TTR) amyloidosis. TTR is a homotetrameric transporter protein for THs, yet it is also responsible for severe amyloid fibril formation, which is facilitated by tetramer dissociation into non-native monomers. By combining nuclear magnetic resonance (NMR) spectroscopy, computational simulation, and biochemical assays, we found that GC-1 and newly designed diphenyl-methane-based thyromimetics, namely IS25 and TG68, are TTR stabilizers and efficient suppressors of TTR aggregation. Based on these observations, we propose the novel potential of thyromimetics as a multi-functional therapeutic molecule for TTR-related pathologies, including neurodegenerative diseases.     

Boosting the hydrogenation activity of dibenzyltoluene catalyzed by Mg-based metal hydrides

Hydrogenation of dibenzyltoluene (DBT) is of great significance for the application in liquid organic hydrogen carriers (LOHCs). We successfully develop Mg-based metal hydrides (Mg₂NiH₄, MgH₂, and LaH₃) reactive ball-milling for the hydrogenation of DBT. Mg-based metal hydrides milled with 500 min exhibit the best catalytic activity, the hydrogen uptake of DBT can reach 4.63 wt% at the first 4 h and finally achieve 5.70 wt% through 20 h, which is the first time to use hydrogen storage material as a catalyst for the hydrogenation of DBT. The excellent catalytic hydrogenation performance of Mg-based metal hydrides mostly originates from numerous catalytic activity centers formed at the surfaces of Mg₂NiH₄ nanoparticles in the MgH₂ matrix. Inspired by this mechanism, more general metal hydrides can be explored for catalyzing the hydrogenation of LOHCs. The new application of Mg-based metal hydrides is beneficial to developing efficient LOHC based hydrogen storage systems and offers novel insights to hydride-based catalysts.     

Some picture fuzzy Bonferroni mean operators with their application to multicriteria decision making

In this paper, we extend the Bonferroni mean (BM) operator with the picture fuzzy numbers (PFNs) to propose novel picture fuzzy aggregation operators and demonstrate their application to multicriteria decision making (MCDM). On the basis of the algebraic operational rules of PFNs and BM, we introduce some aggregation operators: the picture fuzzy Bonferroni mean, the picture fuzzy normalized weighted Bonferroni mean, and the picture fuzzy ordered weighted Bonferroni mean. Then, a new picture fuzzy MCDM method is proposed with the help of the proposed operators. Lastly, a practical application of proposed model is given to verify the developed model and related results of the proposed model is compared with the results of the existing models to indicate its applicability.     

Synthesis and in vitro bioactivity assessment of injectable bioglass−organic pastes for bone tissue repair

The aim of this work was to study the bioactivity of systems based on a clinically tested bioactive glass (BG) particulates (mol%: 4.33 Na₂O−30.30 CaO−12.99 MgO−45.45 SiO₂−2.60 P₂O₅−4.33 CaF₂) and organic carriers. The cohesiveness of injectable bone graft products is of high relevance when filling complex volumetric bone defects. With this motivation behind, BG particulates with mean sizes within 11−14 μm were mixed in different proportions with glycerol (G) and polyethylene glycol (PEG) as organic carriers and the mixtures were fully injectable exhibiting Newtonian flow behaviors. The apatite forming ability was investigated using X-ray diffraction and field emission scanning electron microscopy under secondary electron mode after immersion of samples in simulated body fluid (SBF) for time durations varying between 12 h and 7 days. The results obtained revealed that in spite of the good adhesion of glycerol and PEG carriers to glass particles during preparation stage, they did not hinder the exposure of bioactive glass particulates to the direct contact with SBF solution. The results confirmed the excellent bioactivity in vitro for all compositions expressed by high biomineralization rates with the formation of crystalline hydroxyapatite being identified by XRD after 12 h of immersion in SBF solution.     

Multicellular Tumor Spheroids (MCTS) as a 3D In Vitro Evaluation Tool of Nanoparticles

Multicellular tumor spheroid models (MCTS) are often coined as 3D in vitro models that can mimic the microenvironment of tissues. MCTS have gained increasing interest in the nano‐biotechnology field as they can provide easily accessible information on the performance of nanoparticles without using animal models. Considering that many countries have put restrictions on animals testing, which will only tighten in the future as seen by the recent developments in the Netherlands, 3D models will become an even more valuable tool. Here, an overview on MCTS is provided, focusing on their use in cancer research as most nanoparticles are tested in MCTS for treatment of primary tumors. Thereafter, various types of nanoparticles—from self‐assembled block copolymers to inorganic nanoparticles, are discussed. A range of physicochemical parameters including the size, shape, surface chemistry, ligands attachment, stability, and stiffness are found to influence nanoparticles in MCTS. Some of these studies are complemented by animal studies confirming that lessons from MCTS can in part predict the behaviour in vivo. In summary, MCTS are suitable models to gain additional information on nanoparticles. While not being able to replace in vivo studies, they can bridge the gap between traditional 2D in vitro studies and in vivo models.     

Attribute Allocation and Retrieval Scheme for Large-Scale Sensor Networks

Wireless sensor network is an emerging technology that enables remote monitoring of large geographical regions. In this paper, we address the problem of distributing attributes over such a large-scale sensor network so that the cost of data retrieval is minimized. The proposed scheme is a data-centric storage scheme where the attributes are distributed over the network depending on the correlations between them. The problem addressed here is similar to the Allocation Problem of distributed databases. In this paper, we have defined the Allocation Problem in the context of sensor networks and have proposed a scheme for finding a good distribution of attributes to the sensor network. We also propose an architecture for query processing given such a distribution of attributes. We analytically determine the conditions under which the proposed architecture is beneficial and present simulation results to demonstrate the same. To the best of our knowledge, this is the first attempt to determine an allocation of attributes over a sensor network based on the correlations between attributes.     

超细Fe3O4粒子表面包覆酞菁钴性质研究

本文研究了合成载氧体的金属有机化学液相淀积法制造工艺，所得产物经ＴＥＭ、ＸＰＳ、Ｍｏｓｓ－ｂａｕｅｒ谱和Ｂ－Ｈ仪等手段，研究了它的结构和磁性能。实验表明，酞青钴以薄层形式包覆在Ｆｅ＿３Ｏ＿４的表面，封闭了Ｆｅ＿３Ｏ＿４的表面孔洞，稳定了Ｆｅ＿３Ｏ＿４的物相，增强了磁性能。