Analysis of Phytochemical Composition of Camellia oleifera Oil and Evaluation of its Anti-Inflammatory Effect in Lipopolysaccharide-Stimulated RAW 264.7 Macrophages

In China, Camellia oleifera oil (COO) is not only a common edible oil but also a traditional remedy widely applied to ameliorate a variety of illnesses associated with inflammation, such as mouth ulcers, thrush, eczema, etc. However, there has been a lack of relevant biological research on the anti-inflammatory capacity of COO, and the specific bioactive lipid phytochemicals contributing to the anti-inflammatory effect need further research. In this study, the RAW 264.7 macrophages model was used to investigate the anti-inflammatory capacity of COO. Our data showed that 33–200 μg/mL COO markedly inhibited the lipopolysaccharide lipopolysaccharide (LPS)-stimulated nitric oxide (NO.) secretion via the suppression of Nos2 and Cox-2 expression. The enzyme immunoassay confirmed that COO also exhibited a strong suppressive effect on the expression of proinflammatory cytokines such as Tnf-α and Il-6. To further explore the correlation between the anti-inflammatory effects and the lipid phytochemicals in COO, 10 samples were collected and screened for their chemical compositions. It was interestingly demonstrated that the polyphenol extracts of COO play a vital role in its anti-inflammatory properties. In addition, an oil-in-water (O/W) emulsion-based system was also developed to deliver the liposoluble COO into the cells, and the feasibility of this system was confirmed. Our research confirms the anti-inflammatory potential of COO and highlights that the main functional ingredient is polyphenol extracts. This may provide a scientific basis for the comprehensive utilization and development of COO and related functional foods.     

Distributed learning consensus control based on neural networks for heterogeneous nonlinear multiagent systems

This paper considers a novel distributed iterative learning consensus control algorithm based on neural networks for the control of heterogeneous nonlinear multiagent systems. The system's unknown nonlinear function is approximated by suitable neural networks; the approximation error is countered by a robust term in the control. Two types of control algorithms, both of which utilize distributed learning laws, are provided to achieve consensus. In the provided control algorithms, the desired reference is considered to be an unknown factor and then estimated using the associated learning laws. The consensus convergence is proven by the composite energy function method. A numerical simulation is ultimately presented to demonstrate the efficacy of the proposed control schemes.     

铜基化合物的可见光催化研究进展

与传统贵金属光催化剂相比，铜基光催化剂具有价格低廉、绿色环保、反应条件温和、光催化活性可调节等优势，受到合成化学家们广泛关注。本文简述了铜基催化剂的光催化历史，回顾了近五年来铜基化合物在可见光催化领域的研究成果与进展，总结了铜基催化剂的独立光催化机理与协同光催化机理；简要阐述了铜催化剂在不同类型反应中的应用，重点讨论了铜(Ⅰ)催化剂在烯烃官能化、碳-碳偶联、碳-杂偶联、原位催化等反应中的应用研究，表明铜基化合物在光催化合成领域具有很大的应用潜力。对未来的研究工作进行了展望，指出拓展催化剂的反应适用性、探索催化剂的氧化还原能力、进一步开发催化剂在手性合成中的应用将是该领域的研究重点。     

Detecting Cysteine in Bioimaging with a Near-Infrared Probe Based on a Novel Fluorescence Quenching Mechanism

Near-infrared (NIR) fluorescent probes are very significant for detecting cysteine in biological systems. Herein, we report a highly selective and sensitive NIR turn-on fluorescent probe (BDP-NIR) based on BODIPY with large Stokes shift (105 nm) for detecting Cys. We clarified the sensing mechanism based on the different thiol-induced S_NAr substitution/rearrangement reaction of the probe with cysteine and homocysteine/glutathione, which leads to the corresponding amino- and thiol-BODIPY dyes with distinct photophysical properties. Moreover, a novel mechanism of fluorescence quenching was demonstrated by density functional theory calculation. The reason for the fluorescence quenching of the probe might be intersystem crossing (from singlet to triplet excited state). Moreover, BDP-NIR had a high linear dynamic range of 0–500 μM, which was promising for detecting cysteine quantificationally. Significantly, BDP-NIR was capable of sensing endogenous cysteine in living cells and in vivo.     

潮流能水平轴水轮机在剪切来流下的水动力分析

采用基于计算流体力学方法的全尺度数值模拟计算,建立了适用于潮流能水轮机模拟的剪切来流环境,通过数值计算结果,对潮流能水轮机随时间变化的宏观力和流场特征进行了系统分析,探索水轮机在复杂工况下的水动力特性规律。结果表明,水轮机整个叶轮的总体平均受力在剪切流工况中未受到明显影响; 单个叶片的瞬态轴向力系数和瞬态轴向扭矩系数在旋转周期内出现了明显的周期性变化,且周期性变化幅值随转速增大而增大; 非定常的瞬时轴向扭矩和力的周期性振荡容易引起单个叶片的结构性振动,可能对水轮机的机械结构造成影响。     

某含锌锡多金属硫化矿石锌浮选试验研究

某含锌锡多金属硫化矿石Zn、Sn、Fe、S含量分别为6.04%、1.05%、29.33%、19.08%，锌主要以铁闪锌矿、闪锌矿的形式存在，锡主要以锡石的形式存在，铁主要以黄铁矿、磁黄铁矿等形式存在，其中的金属矿物共生关系密切，相互包裹现象普遍。为确保不影响后续选锡，对锌浮选流程进行了试验研究。结果表明：矿石在磨矿细度为-0.074 mm占80%的情况下，采用预先脱硫—锌硫混浮再分离流程处理，在选择硫酸铜为锌矿物活化剂、丁基黄药为捕收剂、松醇油为起泡剂、石灰为黄铁矿抑制剂的情况下，经1段脱硫、2粗1扫锌硫混浮、1粗2精锌硫分离，锌硫分离精选尾矿与锌硫混浮扫选精矿2次精选后锌硫分离，最终获得锌精矿Zn品位47.06%、回收率90.76%，试验指标良好。     

山东栖霞—大柳行地区金矿找矿靶区地质评价及优选

栖霞—大柳行地区位于胶东中部栖霞—蓬莱金矿成矿带内，是胶东重要的金成矿区，成矿条件优越。为了对圈定靶区进行优选分类，通过对该区地质背景、找矿靶区评价、找矿靶区优选方面展开综合研究，并结合勘查工作程度和矿业权设置情况，划分出3类预测区，选定了5个靶区为今后优先部署勘查工作的方向。     

Influence of Si-Doping on the Performance of InGaN/GaN Multiple Quantum Well Solar Cells

Semiconductors - The performance of InGaN/GaN multiple quantum well (MQW) solar cells with five different Si-doping concentrations, namely 0, 4 × 1017 cm–3, 1 × 1018 cm–3, 3...