TEMPO氧化修饰的天然多糖纳米纤维增强复合材料及其功能化研究进展

纤维素和几丁质具有相似的结构，是自然界中储量丰富的两类天然多糖。经2, 2, 6, 6-四甲基哌啶氮氧化物(TEMPO)氧化修饰制备的纤维素和几丁质纳米纤维，不仅具有多糖类物质的良好亲水性、生物可降解性、生物相容性及丰富的官能团(羟基、羧基、乙酰氨基和氨基等)所带来的特定化学性质，而且还具有纳米纤维的纳米尺寸效应、大比表面积、高表面活性、高结晶度和手性液晶相结构等特点，已成为生物质纳米材料领域的研究重点之一。本文对TEMPO氧化修饰制备天然多糖纳米纤维的方法及剥离机制进行了总结，同时重点综述了TEMPO氧化修饰的天然多糖纳米纤维在薄膜、凝胶、导电、医用、电磁屏蔽及环境等复合材料的增强和功能升级等方面的研究进展，强调了纤维素和几丁质纳米纤维的官能团及纳米尺寸在复合材料中的增效机制。最后，对天然多糖纳米纤维的发展方向及其在各领域应用的机遇与挑战进行了展望。     

基于全U网络的混凝土路面裂缝检测算法

针对现有的混凝土裂缝检测算法在各种复杂环境中检测精度不够、鲁棒性不强的问题,根据深度学习理论和U-net模型,提出一种全U型网络的裂缝检测算法。首先,依照原U-net模型路线构建网络;然后,在每个池化层后都进行一次上采样,恢复其在池化层之前的特征图规格,并将其与池化之前的卷积层进行融合,将融合之后的特征图作为新的融合层与原U-net网络上采样之后的网络层进行融合;最后,为了验证算法的有效性,在测试集中进行实验。结果表明,所提算法的平均精确率可达到83.48%,召回率为85.08%,F1为84.11%,相较于原U-net分别提升了1.48%,4.68%和3.29%,在复杂环境中也能提取完整裂缝,保证了裂缝检测的鲁棒性。     

Designing optical glasses by machine learning coupled with a genetic algorithm

Engineering new glass compositions have experienced a sturdy tendency to move forward from (educated) trial-and-error to data- and simulation-driven strategies. In this work, we developed a computer program that combines data-driven predictive models (in this case, neural networks) with a genetic algorithm to design glass compositions with desired combinations of properties. First, we induced predictive models for the glass transition temperature (T_g) using a dataset of 45,302 compositions with 39 different chemical elements, and for the refractive index (n_d) using a dataset of 41,225 compositions with 38 different chemical elements. Then, we searched for relevant glass compositions using a genetic algorithm informed by a design trend of glasses having high n_d (1.7 or more) and low T_g (500 °C or less). Two candidate compositions suggested by the combined algorithms were selected and produced in the laboratory. These compositions are significantly different from those in the datasets used to induce the predictive models, showing that the used method is indeed capable of exploration. Both glasses met the constraints of the work, which supports the proposed framework. Therefore, this new tool can be immediately used for accelerating the design of new glasses. These results are a stepping stone in the pathway of machine learning-guided design of novel glasses.     

Effect of Drosophila suzukii on Blueberry VOCs: Chemical Cues for a Pupal Parasitoid,Trichopria anastrephae

Journal of Chemical Ecology - Biocontrol agents such as parasitic wasps use long-range volatiles and host-associated cues from lower trophic levels to find their hosts. However, this chemical...     

Deduction of a facile method to construct Antheraea mylitta silk fibroin/gelatin blend films for prospective biomedical applications

Blend films of two types (I and II) were prepared by mixing Antheraea mylitta silk fibroin (AMF) and gelatin solution in various blend ratios via the solution casting method. Two different crosslinkers, namely glutaraldehyde and genipin, were used during blend preparation. The structural characteristics and thermal properties of the blend films were examined by Fourier transform infrared (FTIR) spectroscopy, X‐ray diffraction (XRD), Thermogravimetric analysis (TGA) and Diffrential scanning calorimetery (DSC). The FTIR spectra showed conformational alterations in type I blend films while type II films attained high β‐sheet crystallinity. The XRD diffractograms presented a high degree of crystallinity in type II blend films compared to type I, which showed an almost amorphous structure. Further, thermal and biological studies were conducted on type II films. According to the TGA thermograms, the degradation temperature of the crosslinked blend films shifted compared to pure gelatin and pure AMF films. Partial miscibility of the two components was indicated by DSC thermograms of the blends. The high water uptake capacity of type II blend films was found to imitate hydrogel behaviour. The blend films did not show any toxicity in 3‐(4,5‐dimethylthiazol‐2‐yl)‐2,5‐diphenyl tetrazolium bromide (MTT) assay and supported L929 fibroblast cell spreading and proliferation. The biodegradation of the blend films was significantly faster than the pure silk film. © 2020 Society of Industrial Chemistry     

Suggestions to the article: medical professionalism research characteristics and hotspots

Scientometrics - The article published on 5 July 2021 is well-written and of interest. However, some improvements could be made, such as ten Tables/Figures can be shortened to highlight the focused...     

外军地面无人装备发展现状与趋势研究

随着通信、计算机、人工智能和传感器等技术的飞速发展与广泛应用，地面无人装备日趋活跃在作战、搜救和消防等多种军民用任务场景中。对于军事领域而言，地面无人装备是陆军和其他地面作战部队迈向无人化、智能化战场的核心装备，将在未来陆战场各类作战任务中发挥不可替代的作用。通过对外军各类典型地面无人装备发展现状进行深入分析，总结出该装备领域的发展特点与趋势，对地面无人装备发展有一定的借鉴意义。     

Synthesis,characterization and magnetic properties of polythiophene/SrFe12-x(ZrZn)0.5xO19 nanocomposite as a microwave absorber

Ferrites are an important group of magnetic materials which are used as absorbers. The incorporation of ferrite and conducting polymer achieves great enhancement in microwave absorption properties. The nanocomposites of hexagonal ferrites embedded by conducting polymers such as polypyrrole, polyaniline and polythiophene (PTH) have been paid much attention. In the present study, strontium hexagonal ferrite doped by Zr and Zn with the final formula of SrFe_12-x(ZrZn)_0.5xO19 considering x = 0.9 and embedded by PTH was produced to achieve a nanocomposite with the highest microwave absorbing ability. In this study, after synthesis of SrFe₁₂O₁₉(ZrZn)_0.5xO19 and PTH, the nanocomposite was prepared by in situ polymerization. Wrapping the ferrite particles and PTH chains could form nanocomposite properly, and therefore acceptable interactions were observable between SrFe_12-x(ZrZn)_0.5xO19ferrite particles and PTH polymer chains in the composites. Assessing the X-ray diffraction (XRD) patterns of SrFe_12-x(ZrZn)_0.5xO19, PTH, and PTH/SrFe_12-x(ZrZn)_0.5xO19 nanocomposite indicated that the PTH characteristic peak shifts slightly and its peak intensity reduces, which may be attribute to the coating of PTH polymer chains onto SrFe_12-x(ZrZn)_0.5xO19 particles. We revealed also lower magnetic properties in the obtained nanocomposite. The morphological assessment also suggested that PTH could effectively coat the SrFe_12-x(ZrZn)_0.5xO19 particles. The synergistic effect of SrFe_12-x(ZrZn)_0.5xO19 particle plus PTH leads to microwave absorption percentage higher than 95% by PTH/SrFe_12-x(ZrZn)_0.5xO19 nanocomposite. Overall, nanocomposite creating by coupling interaction between SrFe_12-x(ZrZn)_0.5xO19 particles (x = 0.9) and PTH can effectively lead to achieve the highest rate of absorption of electromagnetic waves.     

Nanoraspberry-like palladium/spongy nickel oxide for electrooxidation of five light fuels

The spongy nickel oxide (SNO) was synthesized the solution combustion method. The SNO was selected as a promoter to boost the catalytic activity of nanoraspberry-like palladium (NRPd) toward electrooxidation of five light fuels (LFs): methanol, ethanol, formaldehyde, formic acid, and ethylene glycol. The X-ray powder diffraction, Fourier-transform infrared spectroscopy (FT-IR), scanning electron microscopy, and field emission scanning electron microscope techniques were used for the materials characterization. In comparison with nonpromoted Pd, the NRPd-SNO electrocatalyst shown an excellent efficiency in parameters like the electrochemical active surface area and anti-CO poisoning behavior. The turnover data and the parameters, including reaction order, activation energy, and the coefficients of electron transfer and diffusion, were evaluated for the each process of LFs electrooxidation. The outcome for NRPd-SNO activity toward LFs electrooxidation was compared to some reported electrodes. The SNO increases the removal of intermediates created in the oxidation of LFs that can poison the surface of palladium catalyst. This is due to the presence of the lattice oxygens in SNO structure and Ni switching between its high and low valances. The compatibility of the adsorption process of LFs on the surface of the NRPd-SNO catalyst with different isotherms was determined by studying the Tafel polarization and calculating the surface coverage.