Neuroprotective and Anti-Inflammatory Effects of Evernic Acid in an MPTP-Induced Parkinson’s Disease Model

Oxidative stress, mitochondrial dysfunction, and neuroinflammation are strongly associated with the pathogenesis of Parkinson’s disease (PD), which suggests that anti-oxidative and anti-inflammatory compounds might provide an alternative treatment for PD. Here, we evaluated the neuroprotective effects of evernic aid (EA), which was screened from a lichen library provided by the Korean Lichen Research Institute at Sunchon National University. EA is a secondary metabolite generated by lichens, including Ramalina, Evernia, and Hypogymnia, and several studies have described its anticancer, antifungal, and antimicrobial effects. However, the neuroprotective effects of EA have not been studied. We found that EA protected primary cultured neurons against 1-methyl-4-phenylpyridium (MPP⁺)-induced cell death, mitochondrial dysfunction, and oxidative stress, and effectively reduced MPP⁺-induced astroglial activation by inhibiting the NF-κB pathway. In vivo, EA ameliorated MPTP-induced motor dysfunction, dopaminergic neuronal loss, and neuroinflammation in the nigrostriatal pathway in C57BL/6 mice. Taken together, our findings demonstrate that EA has neuroprotective and anti-inflammatory effects in PD models and suggest that EA is a potential therapeutic candidate for PD.     

AP2M1 Supports TGF-β Signals to Promote Collagen Expression by Inhibiting Caveolin Expression

The extracellular matrix (ECM) is important for normal development and disease states, including inflammation and fibrosis. To understand the complex regulation of ECM, we performed a suppressor screening using Caenorhabditis elegans expressing the mutant ROL-6 collagen protein. One cuticle mutant has a mutation in dpy-23 that encodes the μ2 adaptin (AP2M1) of clathrin-associated protein complex II (AP-2). The subsequent suppressor screening for dpy-23 revealed the lon-2 mutation. LON-2 functions to regulate body size through negative regulation of the tumor growth factor-beta (TGF-β) signaling pathway responsible for ECM production. RNA-seq analysis showed a dominant change in the expression of collagen genes and cuticle components. We noted an increase in the cav-1 gene encoding caveolin-1, which functions in clathrin-independent endocytosis. By knockdown of cav-1, the reduced TGF-β signal was significantly restored in the dpy-23 mutant. In conclusion, the dpy-23 mutation upregulated cav-1 expression in the hypodermis, and increased CAV-1 resulted in a decrease of TβRI. Finally, the reduction of collagen expression including rol-6 by the reduced TGF-β signal influenced the cuticle formation of the dpy-23 mutant. These findings could help us to understand the complex process of ECM regulation in organism development and disease conditions.     

中国石油工业上游发展面临的挑战与未来科技攻关方向

石油和天然气是全球和中国最重要的一次能源。石油工业的生存发展是由油气资源、市场、技术和社会政治经济环境等要素决定的，其中，技术进步是最活跃和最关键的因素之一。中国已成为全球油气生产消费大国，中国石油工业上游的发展也高度依赖石油科技的进步。中国石油工业已形成了先进完整的理论技术研发和装备制造体系，支撑了油气产量持续稳产和增产。未来是中国社会经济发展的关键期，石油工业必将面对重大挑战与新的技术需求，大力实施国家创新战略，发展具有国际领先水平的新一代勘探开发理论技术，支撑油气产业发展，保障国家油气能源安全。中国石油工业上游在未来面临的重大挑战与技术需求包括：①满足中国未来现代化建设的巨大油气需求和保障油气供应安全，这当中必须加大中国油气勘探开发，同时进一步扩大全球及"一带一路"油气投资与生产；②实现中国石油长期稳产2×10⁸t/a以上；③实现中国天然气产量上升至3 000×10⁸m³/a并长期稳产；④发展海洋及深水油气勘探开发先进技术与装备；⑤形成新一代石油工程服务技术装备和数字化转型。中国石油工业上游未来的科技攻关方向和研发重点包括：①先进的石油大幅度提高采收率技术；②大气田勘探与复杂气田提高采收率技术；③非常规油气勘探开发技术；④海洋及深水油气勘探开发技术及装备；⑤"一带一路"油气勘探开发技术；⑥新一代石油工程服务技术装备和数字化转型。     

基于多特征融合的电影推荐系统

协同过滤算法（CF）根据用户-物品的评分矩阵做推荐，未考虑物品自身属性。本文将MovieLens数据集上的电影属性，作为影响推荐结果的因素，融合电影的简介、评论、评分、导演和演员等多种因素，进行推荐。使用CNN（卷积神经网络）和Word2Vec（Word to Vector,词向量模型）处理电影简介；使用AFINN（Finn rup Nielsen情感词典）处理评论，并对结果进行映射；对导演和演员数据进行建模，得到该因素下的预测评分，最后将各因素下的结果进行加权融合，通过调整权重，得到最佳效果。经验证，该方法的推荐性能优于传统的CF算法。     

凝胶型99Mo-99mTc发生器研究现状

与裂变型⁹⁹Mo-^99mTc发生器相比，凝胶型⁹⁹Mo-^99mTc发生器制备^99mTc具有工艺简单、产生的放射性废物容易处理、对环境影响小等优点。本文主要论述了凝胶型⁹⁹Mo-^99mTc发生器与裂变型⁹⁹Mo-99mTc发生器的区别，堆照生产⁹⁹Mo原料和凝胶材料的研究进展，凝胶结构以及凝胶组分等多种条件因素对凝胶型⁹⁹Mo-^99mTc发生器性能的影响等，并对低比活度⁹⁹Mo生产^99mTc的研究进展进行综述。     

Evaluation of adult and offspring thiamine deficiency in salmonine species from Lake Ontario

Thiamine Deficiency Complex (TDC) is an ongoing problem impacting salmonine health in various waterbodies, including Lake Ontario. The prevalence of TDC has been variable and explanations for differences are limited. In the current study, thiamine concentrations were measured in eggs, liver tissue, and muscle tissue sampled from brown trout (Salmo trutta), Chinook salmon (Oncorhynchus tshawytscha), coho salmon (O. kisutch), lake trout (Salvelinus namaycush), and steelhead trout (O. mykiss) that were collected from Lake Ontario and its surrounding tributaries. The occurrence of TDC was measured for each species based on TDC-induced offspring mortality rates under laboratory conditions. TDC-induced offspring mortality was observed for all species except brown trout. For affected species, egg free thiamine (Th) was consistently low compared to lake trout collected from Lake Superior that are considered thiamine replete. In addition, species with the lowest percentages of Th in their eggs were the most susceptible to TDC, suggesting that limited thiamine reserves in the form of Th may cause TDC-induced offspring mortality. Lastly, our results show that egg thiamine concentrations have yearly variation and increased for all species throughout the study. Reasons for such variation are undetermined; but, if egg thiamine concentrations continue to increase, the impacts of TDC on these salmonine species may lessen. Future monitoring is needed for determining if thiamine concentrations are increasing and the potential impacts that may have on the entire Lake Ontario fishery.     

A robust locating multi-optima approach for damage identification of plate-like structures

This paper proposes a robust optimization approach for multiple damage identification of plate-like structures. Different from traditional particle swarm optimizations (PSOs), a combined PSO and niche technique (NPSO) is proposed to solve multimodal optimization problems, with the full consideration of subswarm creation, merging and absorbing mechanism. As a hypersensitive parameter to damage, the curvature mode shape is adopted to construct the objective function. Case studies are conducted to investigate the effectiveness and robustness of the algorithm on multi-damage identification. Simulation results show that the proposed algorithm exhibits robust search performance on identifying damage locations accurately with good convergence behavior. It is hoped that this study can provide guidance on robust damage detection, especially when the structure is subject to multiple damages and external disturbances.     

移动边缘计算环境下的动态资源分配策略

在通讯设备爆炸式增长的时代,移动边缘计算作为5G通讯技术的核心技术之一,对其进行合理的资源分配显得尤为重要。移动边缘计算的思想是把云计算中心下沉到基站部署(边缘云),使云计算中心更加靠近用户,以快速解决计算资源分配问题。但是,相对于大型的云计算中心,边缘云的计算资源有限,传统的虚拟机分配方式不足以灵活应对边缘云的计算资源分配问题。为解决此问题,提出一种根据用户综合需求变化的动态计算资源和频谱分配算法(DRFAA),采用"分治"策略,并将资源模拟成"流体"资源进行分配,以寻求较大的吞吐量和较低的传输时延。实验仿真结果显示,动态计算资源和频谱分配算法可以有效地降低用户与边缘云之间的传输时延,也可以提高边缘云的吞吐量。     

基于种群划分与变异策略的粒子群优化算法

粒子群算法因其形式比较简洁，参数设置灵活，操作简便易行，并且能够快速收敛，从而引起广泛关注。但是传统的粒子群算法也有缺陷：收敛速度慢以及容易陷入局部最优等。针对这些问题，本文借鉴小生境的方法，在进化初始阶段，对种群进行划分，将初始种群分为子种群，对不同的子种群进行不同的变异策略；在进化过程中，针对不同的子种群，设置不同的惯性权重因子ω，用来增强全局搜索能力与局部搜索能力。实验结果表明，本文提出的算法较传统的粒子群算法具有较快的收敛性以及找寻的全局最优解更接近真实解集，收敛精度比较高。     

基于改进耦合增强随机共振的滚动轴承故障诊断

针对强背景噪声下经典随机共振方法对滚动轴承故障特征提取效果差的问题,提出了一种基于改进耦合增强随机共振的滚动轴承故障诊断方法。首先,利用一个定参双稳系统和一个变参双稳系统构成耦合随机共振系统,外部输入直接作用于定参双稳系统;然后,通过调节变参双稳系统参数和耦合系数实现耦合系统的随机共振控制,并借助遗传算法实现控制参数的自适应选取。实验和工程应用验证了所提方法的有效性和优越性。