On the local behavior of spaces of range image patches

We focus on the quantitative and local topological properties of range images. We consider the spaces M_m of m × m high-contrast patches of range images for m=?3, 5, 7, 9, 11. Using computational topological tools to analyze range image patches, we detect that M₃ (M₉, M₁₁) has core subsets with the topology of a circle, M₃, M₅, M₇, M₉ and that M₁₁ have some subspaces with the topology of a Klein bottle. We also discover that the largest subspace with the Klein bottle’s topology decreases as the measurements of patches increase, which generalizes the results in the paper of H. Adams and G. Carlsson, and demonstrates properties among optical images and range image patches, which are more similar than those established by Lee et al.

     

Dual Inhibition of Pyruvate Dehydrogenase Complex and Respiratory Chain Complex Induces Apoptosis by a Mitochondria-Targeted Fluorescent Organic Arsenical in vitro and in vivo

Based on the potential therapeutic value in targeting mitochondria and the fluorophore tracing ability, a fluorescent mitochondria-targeted organic arsenical PDT-PAO-F16 was fabricated, which not only visualized the cellular distribution, but also exerted anti-cancer activity in vitro and in vivo via targeting pyruvate dehydrogenase complex (PDHC) and respiratory chain complexes in mitochondria. In details, PDT-PAO-F16 mainly accumulated into mitochondria within hours and suppressed the activity of PDHC resulting in the inhibition of ATP synthesis and thermogenesis disorder. Moreover, the suppression of respiratory chain complex I and IV accelerated the mitochondrial dysfunction leading to caspase family-dependent apoptosis. In vivo, the acute promyelocytic leukemia was greatly alleviated in the PDT-PAO-F16 treated group in APL mice model. Our results demonstrated the organic arsenical precursor with fluorescence imaging and target-anticancer efficacy is a promising anticancer drug.     

Lipase‐catalyzed synthesis of aliphatic poly(β‐thioether ester) with various methylene group contents: thermal properties,crystallization and degradation

A series of novel aliphatic poly(β‐thioether ester)s with various methylene group contents were prepared by direct lipase‐catalyzed polycondensation of the monomer with an acid‐labile β‐thiopropionate group. The polycondensation reaction using immobilized lipase B from Candida antarctica was carried out in diphenyl ether at 90 °C. Poly(β‐thioether ester)s with high molecular weights of 20 500–57 000 Da and narrow polydispersities in the range 1.40–1.48 were obtained. Thermogravimetric analysis, differential scanning calorimetry and wide‐angle X‐ray diffraction were used to investigate the thermal properties and crystal structures of these polyesters. All the poly(β‐thioether ester)s were semicrystalline polymers and thermally stable up to at least 200 °C. In vitro degradation studies showed that they can rapidly degrade under acidic conditions by the hydrolysis of the β‐thiopropionate groups, suggesting their potential as acid‐degradable polymeric materials. © 2019 Society of Chemical Industry     

Design and synthesis of side-chain optimized poly(2,6-dimethyl-1,4-phenylene oxide)-g-poly(styrene sulfonic acid) as proton exchange membrane for fuel cell applications: Balancing the water-resistance and the sulfonation degree

Side-chain optimized poly (2,6-dimethyl-1,4-phenylene oxide)-g-poly (styrene sulfonic acid) (PPO-g-PSSA) is designed with balanced water-resistance and sulfonation degree. The PPO-g-PSSA is synthesized by controlled atom-transfer radical polymerization (ATRP) from brominated poly (2,6-dimethyl-1,4-phenylene oxide) (PPO-xBr) and ethyl styrene-4-sulfonate and followed by hydrolysis. A series of PPO-g-PSSA are prepared possessing different bromination degree (x) of PPO-xBr and polymerization degree (m) of the side-chains and the water-resistances of the fabricated membranes are investigated. The results show that a PPO-g-PSSA at relatively low x (x < 0.2) and high m (m > 4) exhibits good balance between the water-resistance and the sulfonation degree. Namely, it displays suitable proton conductivity with compromised water-resistance. Moreover, a maximum ion exchange capacity (IEC) of 3.24 mmol g^?1 is reached without the sacrifice of water-resistance. In addition, PPO-g-0.08PSSA-13 and PPO-g-0.14PSSA-4 are chosen characterized by thermogravimetric analysis, proton conductivities and mechanical properties. At 90% RH, the optimized PPO-g-0.08PPSA-13 possesses a proton conductivity of 37.9 mS cm^?1 at 40 °C and 45.5 mS cm^?1 at 95 °C, respectively.     

Fabrication of direct Z-scheme FeIn2S4/Bi2WO6 hierarchical heterostructures with enhanced photocatalytic activity for tetracycline hydrochloride photodagradation

A series of direct Z-scheme FeIn₂S₄/Bi₂WO₆ hierarchical heterostructures with intimate interface contacts were synthesized by in-situ growth route and characterized by systematical analyses. All as-prepared FeIn₂S₄/Bi₂WO₆ nanocomposites showed significantly enhanced photocatalytic activity towards photodegradation for the removal of tetracycline hydrochloride (TCH) in comparison with individual FeIn₂S₄ and Bi₂WO₆. Meanwhile, the highest photocatalytic degradation activity can be achieved by modulating adding amount of FeIn₂S₄ in FeIn₂S₄/Bi₂WO₆ nanocomposites and the optimized component ratio of FeIn₂S₄ to Bi₂WO₆ is determined to be 10 wt%. The enhanced photocatalytic activity could be ascribed to efficient separation between photogenerated holes and electrons based on the construction of direct Z-scheme system. The high photocatalytic stability of resultant 10 wt% FeIn₂S₄/Bi₂WO₆ nanocomposites was revealed through six successive recycling reactions. The main intermediate generated during TCH photodegradation was explored by HPLC-MS. Besides, the direct Z-scheme photocatalytic mechanism was confirmed by band position analysis, electron spin resonance (ESR) and active species capture experiment.     

基于深度学习的视频跟踪研究进展综述

近年来深度学习迅猛发展，颠覆了语音识别、图像分类、文本理解等领域的算法设计思路。深度学习因其具备强大的特征提取能力，在图像识别领域的成绩尤为突出。然而深度学习与视频监控领域的结合并不多，由于深度模型具有多层网络结构，算法复杂度大，训练和更新模型时比较耗时，很难满足实时性要求。回顾了深度学习的发展史，介绍了最近10年来国内外深度学习主要模型，论述了基于深度学习的目标跟踪算法，指出了各算法的优缺点，最后对当前该领域存在的问题和发展前景进行了总结和展望。     

Headspace fingerprinting approach to identify the major pathway influencing volatile patterns of vinasse-cured duck processed by high pressure,as well as its impact on physicochemical and sensory attributes

As a decisive attribute, flavour could be influenced by HP treatments through multiple physical and chemical pathways within the high pressure (HP)-assisted meat curing process. This investigation aimed to identify the major pathway influencing volatile flavour patterns of two representative vinasse-cured duck (VCD) products with HP treatments (150–300 MPa/15 min), including wet and dry types, by employing headspace fingerprinting as an untargeted approach. Results suggested that HP treatments greatly lowered moisture contents and increased Warner-Bratzler shear force and thiobarbituric acid reactive substances of the cured samples. According to multivariate models, the volatile flavour patterns of the HP-processed VCD could be clearly separated from the unprocessed samples, but the VCD pressurised at different intensities represented similar volatile fingerprinting, which was validated by e-nose analysis. The discriminant analysis (OPLS-DA) model outlined vinasse-derived ethanol, acetic acid, 3-methyl-1-butanol, 2-methyl-1-butanol, phenethyl alcohol and 2-methyl-3-octanone as the major discriminant aromas across the unpressurised and pressurised samples.