基于模糊谱聚类的不确定蛋白质相互作用网络功能模块挖掘

针对谱聚类融合模糊C-means（FCM）聚类的蛋白质相互作用（PPI）网络功能模块挖掘方法准确率不高、执行效率较低和易受假阳性影响的问题，提出一种基于模糊谱聚类的不确定PPI网络功能模块挖掘（FSC-FM）方法。首先，构建一个不确定PPI网络模型，使用边聚集系数给每一条蛋白质交互作用赋予一个存在概率测度，克服假阳性对实验结果的影响；第二，利用基于边聚集系数流行距离（FEC）策略改进谱聚类中的相似度计算，解决谱聚类算法对尺度参数敏感的问题，进而利用谱聚类算法对不确定PPI网络数据进行预处理，降低数据的维数，提高聚类的准确率；第三，设计基于密度的概率中心选取策略（DPCS）解决模糊C-means算法对初始聚类中心和聚类数目敏感的问题，并对预处理后的PPI数据进行FCM聚类，提高聚类的执行效率以及灵敏度；最后，采用改进的边期望稠密度（EED）对挖掘出的蛋白质功能模块进行过滤。在酵母菌DIP数据集上运行各个算法可知，FSC-FM与基于不确定图模型的检测蛋白质复合物（DCU）算法相比，F-measure值提高了27.92%，执行效率提高了27.92%；与在动态蛋白质相互作用网络中识别复合物的方法（CDUN）、演化算法（EA）、医学基因或蛋白质预测算法（MGPPA）相比也有更高的F-measure值和执行效率。实验结果表明，在不确定PPI网络中，FSC-FM适合用于功能模块的挖掘。     

发夹式换热器管束流致振动数值模拟研究

运用计算流体力学方法,采用ANSYS CFX软件对发夹式换热器的壳侧流场进行了三维数值模拟。流场计算中采用多孔介质模型对管束区域进行简化,分析了壳侧流场的速度分布,结果表明:直管段部分的流体湍流强度大于弯管段,且外层管束所在区域为高流速区,受流体冲刷严重。结合流场信息,通过功率谱生成随机激振力,采用ABAQUS软件模拟计算了湍流激振下管束的振动响应,结果显示管束的面外均方根位移远大于面内位移,且弯管部分的振动位移最大。该研究结果可为发夹式换热器的性能分析和优化设计提供参考和依据。     

Amine-containing olefin copolymer with CO2-switchable oil absorption and desorption

Global decrease in crude oil resources and frequent crude oil leaks cause the energy crisis and ecological pollution. The absorption and release of leaked crude oil through absorption materials are a necessary process for environmental protection and recycling. In this article, a CO₂-responsive olefin copolymer was obtained by copolymerization of styrene and an amine-containing olefin monomer. The structure of resultant copolymer was characterized by FTIR; thermal properties and CO₂-responsive morphology changes were determined by DSC/TGA and SEM, respectively. Copolymers had certain absorption capacity for toluene with absorption rate up to 180.0%. The absorbed toluene could be released upon CO₂ stimulation with desorption rate up to 84.6%. The CO₂-responsive copolymer could be regenerated through a simple heating process and showed stable absorption–desorption performance even after being recycled for 4 times. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47439.     

Fabrication of novel silicon carbide-based nanomaterials with unique hydrophobicity and microwave absorption property

Novel SiC-based nanomaterials, namely the nitrogen and aluminum co-doped SiC@SiO₂ core-shell nanowires and nitrogen-doped SiO₂/Al₂O₃ nanoparticles, have been fabricated through a facile thermal treatment process based on the chemical vapor deposition and vapor-liquid reaction. These nanomaterials show remarkable hydrophobicity with a water contact angle (CA) over 140°, which are aroused by the surface zigzag morphology of the nanostructures and the hydrocarbyl groups generated during the preparation process. Moreover the nanocomposites also exhibit relatively prominent microwave absorption (MA) properties in the frequency range of 2.0-18.0 GHz. The minimum reflection loss (RL) value as low as −23.68 dB can be observed at 14.16 GHz when the absorber thickness is 2.6 mm with a loading rate of 16.7 wt%. And the nanocomposites-based absorbent can achieve an effective absorption bandwidth (RL < −10 dB) of 4.48 GHz with the absorbent thickness of 2.5 mm. This enhanced microwave attenuation performance can be attributed to multiple polarizations and perfect impedance matching conditions, as well as multiple internal reflections. These marvelous properties make these N and Al co-doped SiC@SiO₂ core-shell nanowires and N-doped SiO₂/Al₂O₃ nanoparticles display extensive application potential as MA materials in harsh environment.     

Using electroencephalogram to continuously discriminate feelings of personal thermal comfort between uncomfortably hot and comfortable environments

Thermal comfort is an important factor for the design of buildings. Although it has been well recognized that many physiological parameters are linked to the state of thermal comfort or discomfort of humans, how to use physiological signal to judge the state of thermal comfort has not been well studied. In this paper, the feasibility of continuously determining feelings of personal thermal comfort was discussed by using electroencephalogram (EEG) signals in private space. In the study, 22 subjects were exposed to thermally comfortable and uncomfortably hot environments, and their EEG signals were recorded. Spectral power features of the EEG signals were extracted, and an ensemble learning method using linear discriminant analysis or support vector machine as a sub-classifier was used to build the discriminant model. The results show that an average discriminate accuracy of 87.9% can be obtained within a detection window of 60 seconds. This study indicates that it is feasible to distinguish whether a person feels comfortable or too hot in their private space by multi-channel EEG signals without interruption and suggests possibility for further applications in neuroergonomics.     

Transparent niobate glass-ceramics for optical limiting

The construction of nonlinear optical materials featuring asymmetric transmission of light is of great technological importance for various applications, including optical switching and optical power limiting. A significant challenge is the scalable fabrication of material candidates with good photochemical stability, high optical transmittance, and excellent optical limiting performance. Here, we present a nanocrystallization avenue for constructing hybrid optical limiting materials that exhibit ultrafast and robust optical limiting performance. The experimental results show that the controllable relaxation of a niobate glass may lead to the clustering of Nb-O units and contracting of the bandgap. It results in the notable improvement in nonlinear optical properties, including the enhanced saturation irradiance (380 GW/cm²), doubly increased nonlinear coefficient, and decreased limiting threshold (200 GW/cm²). Our results suggest a promising material that exhibits promising applications for protecting eyes and sensitive components from laser-induced damage.     

Research on Chromium Retrieval of Black Soil with Hyperspectral Imagery in Northeast of China#br#

According to the definition of spectral integral，a new spectral characteristic parameter，with the name Reversed Spectral Absorption Integral(RSAI)，is proposed and used to retrieve the chromium content based on the Partial Least Squares Regression(PLSR) model.The contrastive study with other traditional spectral characteristic parameters，including differential transformation，inverse transformation，absorption area，etc.indicates that(1) the first derivation of square root transformed model can predict the chromium content quantitatively in terms of spectral transformations.(2) the stability of the absorption area model is slightly poor，and the chromium content of samples can only be estimated roughly.(3) However，as to the inversed spectral absorption integral model，the adjustment determination coefficient(Ad-R²) of the modeling and verification is 0.73 and 0.77，while the Root Mean Squared Error(RMSE) is 2.63 mg/kg and 2.36 mg/kg respectively with Relative Percent Deviation(RPD) being 3.21，which shows that the RSAI model has excellent prediction ability.So，the inversed spectral absorption integral new model can improve the accuracy and stability used to retrieve the chromium content，which provides a new idea for monitoring the chromium contamination in soil.     

Facile synthesis of Co0.5Zn0.5Fe2O4 nanoparticles decorated reduced graphene oxide hybrid nanocomposites with enhanced electromagnetic wave absorption properties

Herein, reduced graphene oxide/cobalt-zinc ferrite (RGO/Co_0.5Zn_0.5Fe₂O₄) hybrid nanocomposites were fabricated by a facile hydrothermal strategy. Results revealed that the contents of RGO could affect the micromorphology, electromagnetic parameters and electromagnetic wave absorption properties. As the contents of RGO increased in the as-synthesized hybrid nanocomposites, the dispersibility of the particles was improved. Meanwhile, numerously ferromagnetic Co_0.5Zn_0.5Fe₂O₄ particles were evenly anchored on the wrinkled surfaces of flaky RGO. Besides, the obtained hybrid nanocomposites exhibited superior electromagnetic absorption in both X and Ku bands, which was achieved by adjusting the RGO contents and matching thicknesses. Significantly, when the content of RGO was 7.4 wt%, the binary nanocomposites showed the optimal reflection loss of -73.9 dB at a thickness of 2.2 mm and broadest effective absorption bandwidth of 6.0 GHz (12.0–18.0 GHz) at a thin thickness of merely 2.0 mm. The enhanced electromagnetic absorption performance was primarily attributed to the multiple polarization effects, improved conduction loss caused by electron migration, and magnetic loss derived from ferromagnetic Co_0.5Zn_0.5Fe₂O₄ nanoparticles. Our results could provide inspiration for manufacturing graphene-based hybrid nanocomposites as high-efficient electromagnetic wave absorbers.     

In vitro evaluation and in vivo performance of lyophilized gliclazide

Enhancement of the dissolution rate of the poorly water-soluble hypoglycemic agent, gliclazide, by the aid of lyophilization was investigated. Mannitol, sodium lauryl sulfate (SLS) and polyvinyl pyrrolidone (PVP-k-30) were employed in different weight ratios (43%, 56% and 64% w/w, respectively) as water-soluble excipients in the formulation. Lyophilized systems were found to exhibit extremely higher in vitro dissolution rate compared to the unprocessed drug powder. Solid state characterization of the lyophilized systems using X-ray powder diffraction, Fourier transform infrared spectroscopy and differential scanning calorimetry techniques revealed that dissolution enhancement was attributable to transformation of gliclazide from the crystalline to an amorphous state in the solid dispersion formed during the lyophilization process. The gastrointestinal absorption and hypoglycemic effect of the lyophilized gliclazide/SLS system were investigated following oral administration to Albino rabbits. C_max and area under the plasma concentration–time curve of gliclazide (AUC_0–12) after administration of the lyophilized formulations were significantly higher than those obtained after administration of the unprocessed gliclazide.     

The Critical Role of Passive Permeability in Designing Successful Drugs

Passive permeability is a key property in drug disposition and delivery. It is critical for gastrointestinal absorption, brain penetration, renal reabsorption, defining clearance mechanisms and drug-drug interactions. Passive diffusion rate is translatable across tissues and animal species, while the extent of absorption is dependent on drug properties, as well as in vivo physiology/pathophysiology. Design principles have been developed to guide medicinal chemistry to enhance absorption, which combine the balance of aqueous solubility, permeability and the sometimes unfavorable compound characteristic demanded by the target. Permeability assays have been implemented that enable rapid development of structure-permeability relationships for absorption improvement. Future advances in assay development to reduce nonspecific binding and improve mass balance will enable more accurately measurement of passive permeability. Design principles that integrate potency, selectivity, passive permeability and other ADMET properties facilitate rapid advancement of successful drug candidates to patients.