基于上转换纳米粒子的低损伤神经界面技术

Optogenetics is a neuromodulation technology that combines light control technology with genetic technology, thus allowing the selective activation and inhibition of the electrical activity in specific types of neurons with millisecond time resolution. Over the past several years, optogenetics has become a powerful tool for understanding the organization and functions of neural circuits, and it holds great promise to treat neurological disorders. To date, the excitation wavelengths of commonly employed opsins in optogenetics are located in the visible spectrum. This poses a serious limitation for neural activity regulation because the intense absorption and scattering of visible light by tissues lead to the loss of excitation light energy and also cause tissue heating. To regulate the activity of neurons in deep brain regions, it is necessary to implant optical fibers or optoelectronic devices into target brain areas, which however can induce severe tissue damage. Non- or minimally-invasive remote control technologies that can manipulate neural activity have been highly desirable in neuroscience research. Upconversion nanoparticles (UCNPs) can emit light with a short wavelength and high frequency upon excitation by light with a long wavelength and low frequency. Therefore, UCNPs can convert low-frequency near-infrared (NIR) light into high-frequency visible light for the activation of light-sensitive proteins, thus indirectly realizing the NIR optogenetic system. Because NIR light has a large tissue penetration depth, UCNP-mediated optogenetics has attracted significant interest for deep-tissue neuromodulation. However, in UCNP-mediated in vivo optogenetic experiments, as the up-conversion efficiency of UCNPs is low, it is generally necessary to apply high-power NIR light to obtain up-converted fluorescence with energy high enough to activate a photosensitive protein. High-power NIR light can cause thermal damage to tissues, which seriously restricts the applications of UCNPs in optogenetic technology. Therefore, the exploration of strategies to increase the up-conversion efficiency, fluorescence intensity, and biocompatibility of UCNPs is of great significance to their wide applications in optogenetic systems. This review summarizes recent developments and challenges in UCNP-mediated optogenetics for deep-brain neuromodulation. We firstly discuss the correspondence between the parameters of UCNPs and employed opsins in optogenetic experiments, which mainly include excitation wavelengths, emission wavelengths, and luminescent lifetimes. Thereafter, we introduce the methods to enhance the conversion efficiency of UCNPs, including optimizing the structure of UCNPs and modifying the organic dyes in UCNPs. In addition, we also discuss the future opportunities in combining UCNP-mediated optogenetics with flexible microelectrode technology for the long-term detection and regulation of neural activity in the case of minimal injury.     

计算机分子模拟在分子印迹技术中的应用

传统的分子印迹技术对模板分子、功能单体、交联剂、致孔剂等的筛选往往依靠经验,常通过反复实验对合成条件进行优化,存在实验周期长、耗材量大等问题。计算机分子模拟技术的应用在实验过程中起到可预见性指导作用,可以实现精准识别位点的裁制、识别驱动力的设计,通过结合能等物化特征参数计算优化识别体系的稳定性,从而合理选择模板分子、功能单体、交联剂、致孔剂,优化聚合条件,以提高聚合物识别特异性和亲和力,缩短实验周期,更符合绿色化学的理念。本文简单介绍了计算机分子模拟技术,重点对其在分子印迹技术中的指导作用进行了综述,并对其在分子印迹技术中的应用进行了展望。     

翼型、机翼非定常运动模式下动态数值模拟

基于RANS方程,通过刚性动网格技术实现对翼型和机翼典型运动模式的描述,采用双时间推进方法和Roe空间离散格式对流场求解,构建了一个非定常气动计算平台;以NACA0012翼型为算倒进行了动态数值模拟可信度验证。数值模拟结果与试验数据吻合较好,升力和俯仰力矩的最大计算误差分别为3％和10％,表明了该平台的可靠性。另外,还数值模拟了M6机翼的动态非定常流场,并分析了两种湍流模型对非定常流场激波的捕捉能力。结果表明非定常流动中S-A湍流模型对激波的捕捉较B-L模型更敏感。文中开发的非定常计算平台对进一步解决三维复杂流场的流动问题有很高的工程应用价值。     

爆炸复合1Cr13Mo/45钢连铸辊工艺

鉴于目前连铸辊制造工艺存在的不足,以爆炸复合法制造1Cr13Mo/45钢复合轧辊,并以爆炸复合工艺为研究对象,采用超声波探伤和金相观察等方法,研究药厚和间隙大小对复合界面波形的影响.结果表明:药厚一定的情况下,间隙对复合轧辊界面波形的影响较大;而在间隙一定的情况下,药厚对复合轧辊界面波形的影响不明显.通过实验,获得了该...     

应用声发射技术的钢筋与混凝土粘结滑移特性研究

为研究钢筋与混凝土间的粘结滑移特性,分别对不同粘结长度的钢筋混凝土试件进行了拉拔试验,同时对粘结长度相同而钢筋外形不同的试件进行了比较试验.利用声发射技术采集相应波形信号,并对采集信号进行了小波去噪和Gabor小波时频分析.结果显示,各试件受力全过程均可分为完全粘结、局部脱粘、非线性滑移及残余粘结四个阶段;不同粘结长度...     

空间薄膜阵面结构褶皱的实验研究

阵面薄膜上的褶皱会显著影响航天器性能,褶皱控制也是薄膜航天器研发的难点。本文采用白光扫描技术,测试了一个正方形薄膜阵面结构在纯剪切作用下的褶皱特性。测试结果显示,随着剪切力的增大,结构膜面褶皱数增加,褶皱幅度增大,膜面平整度降低。随着膜面预应力的增大,膜面上的褶皱数略有增大,褶皱幅度有所减小,膜面平整度有所提高。测试结果还显示,膜面上粘结缝的存在、以及粘结缝与剪切力间的方位关系对膜面褶皱有复杂的影响。论文所得结论对薄膜阵面结构设计研发具有参考价值。     

D-最优设计的分部搜索数值构造方法

为了简化D-最优设计的过程,便于工程应用,提出了一种D-最优设计的数值构造方法——分部搜索数值构造方法。该方法以惯性器件测试为背景,以D-最优性为准则,将传统的D-最优设计分解为谱点寻优和测度寻优两个部分,降低了设计的复杂度,从而减少了运算量,又具有操作简单、思路清楚直观的特点,工程实用性强。提出并证明了相关的定理及推论,从理论上说明了这种构造方法的正确性。以陀螺加速度计误差模型系数辨识试验为例,运用此算法进行了D-最优设计。设计的结果证明了该方法的正确性,同直接搜索法相比,能将最小设计维数降低为原来的50%,提高了设计效率。     

能源节约型技术进步下碳关税对中国经济与环境的影响——基于动态递归可计算一般均衡模型

将动态递归的可计算一般均衡方法应用于碳关税征收影响的研究,建立了测算美国征收碳关税对中国经济与环境影响的动态递归可计算一般均衡模型,并在模型中引入技术进步参数以刻画能源节约型技术进步.模型以2007年作为基年,包含37个生产部门和7个国内国外账户.应用该模型模拟了2020年起美国征收碳关税,在税率从20美元每吨碳排放到80美元每吨碳排放的13种情景下,到2030年期间对我国碳排放和经济发展的不同影响,进而测算在不同的能源节约型技术进步条件下,碳关税对我国经济与环境影响的变动.     

Climate change and optimal energy technology R&D policy

Public policy response to global climate change presents a classic problem of decision making under uncertainty. Theoretical work has shown that explicitly accounting for uncertainty and learning in climate change can have a large impact on optimal policy, especially technology policy. However, theory also shows that the specific impacts of uncertainty are ambiguous. In this paper, we provide a framework that combines economics and decision analysis to implement probabilistic data on energy technology research and development (R&D) policy in response to global climate change. We find that, given a budget constraint, the composition of the optimal R&D portfolio is highly diversified and robust to risk in climate damages. The overall optimal investment into technical change, however, does depend (in a non-monotonic way) on the risk in climate damages. Finally, we show that in order to properly value R&D, abatement must be included as a recourse decision.     

隐性技术、贸易溢出和模仿策略

本文构建了一个扩展的南北贸易模型,将北方创新、南方模仿和进口产品隐性技术作为内生变量,分析进口国如何选择模仿策略以最大程度地获得进口产品的内生技术溢出效应.结果表明,进口产品中隐性技术含量会影响南方厂商的模仿策略:进口产品隐性技术含量低时,原始模仿是南方厂商的理性选择;进口产品隐性技术产量较高时,南方厂商的模仿策略取决于模仿的预期边际收益与单位模仿成本的对比关系:模仿的预期边际收益大于单位模仿成本时,内生模仿是南方厂商的最优选择,反之原始模仿.