Mass spectrometry imaging of latent fingerprints using titanium oxide development powder as an existing matrix

Recent research has focused on increasing the evidentiary value of latent fingerprints through chemical analysis. Although researchers have optimized the use of organic and metal matrices for matrix‐assisted laser desorption/ionization‐mass spectrometry imaging (MALDI‐MSI) of latent fingerprints, the use of development powders as matrices has not been fully investigated. Carbon forensic powder (CFP), a common nonporous development technique, was shown to be an efficient one‐step matrix; however, a high‐resolution mass spectrometer was required in the low mass range due to carbon clusters. Titanium oxide (TiO₂) is another commonly used development powder, especially for dark nonporous surfaces. Here, forensic TiO₂ powder is utilized as a single‐step development and matrix technique for chemical imaging of latent fingerprints without the requirement of a high‐resolution mass spectrometer. All studied compounds were successfully detected when TiO₂ was used as the matrix in positive mode, although, generally, the overall ion signals were lower than the previously studied CFP. TiO₂ provided quality mass spectrometry (MS) images of endogenous and exogenous latent fingerprint compounds. The subsequent addition of traditional matrices on top of the TiO₂ powder was ineffective for universal detection of latent fingerprint compounds. Forensic TiO₂ development powder works as an efficient single‐step development and matrix technique for MALDI‐MSI analysis of latent fingerprints in positive mode and does not require a high‐resolution mass spectrometer for analysis.     

在线社交网络控制实验的现状与展望

在线社交网络已发展成为一个独特的电子生态系统，其应用深刻影响着人们生活的方方面面。由于在线社交网络特性复杂，分析在线社交网络形成和变化中的规律成为当前计算机科学、社会学和物理学的一项挑战。传统上，在线社交网络实证研究主要采用计算机辅助的被动数据获取和分析方式。近年来，在真实大规模在线社交网络上直接进行控制实验从而主动获取数据并开展分析研究的方式广受关注。评述了这一领域的研究进展，包括：社交网络控制实验的主要研究模式；控制实验方法在社交网络结构、信息传播、行为和心理学等领域取得的主要成果以及主要实验工具的适用条件和局限性。最后，展望了人工智能技术在社交网络控制实验中的应用潜力，分析了智能算法对降低实验成本和提高实验效率的作用。     

Effect of nitrogen plasma treatment on the crystallinity and self‐bonding of polyetheretherketone (PEEK) for biomedical applications

Polyetheretherketone (PEEK) is a thermoplastic material with outstanding properties and high potential for biomedical applications, including hermetic encapsulation of active implantable devices. Different biomedical grade PEEK films with initial degree of crystallinity ranging from 8% to 32% (with or without mineral filling) were inspected. PEEK surfaces were treated with nitrogen RF plasma and the effects on materials crystallinity and self‐bonding were evaluated. In particular, the relationship between auto‐adhesive properties and crystalline content of PEEK before and after plasma treatment was examined. PEEK samples showed different bonding strength depending on their degree of crystallinity, with higher self‐bonding performance of mineral‐filled semi‐crystalline films. XRD did not show any modification of the PEEK microstructure as a result of plasma treatment, excluding a significant influence of crystallinity on the self‐bonding mechanisms. Nevertheless, plasma surface treatment successfully improved the self‐bonding strength of all the PEEK films tested, with larger increase in the case of semi‐crystalline unfilled materials. This could be interpreted to the increase in chain mobility that led to interfacial interpenetration of the amorphous phase.     

On-chip multiphoton Greenberger–Horne–Zeilinger state based on integrated frequency combs

One of the most important multipartite entangled states, Greenberger–Horne–Zeilinger state (GHZ), serves as a fundamental resource for quantum foundation test, quantum communication and quantum computation. To increase the number of entangled particles, significant experimental efforts should been invested due to the complexity of optical setup and the difficulty in maintaining the coherence condition for high-fidelity GHZ state. Here, we propose an ultra-integrated scalable on-chip GHZ state generation scheme based on frequency combs. By designing several microrings pumped by different lasers, multiple partially overlapped quantum frequency combs are generated to supply as the basis for on-chip polarization-encoded GHZ state with each qubit occupying a certain spectral mode. Both even and odd numbers of GHZ states can be engineered with constant small number of integrated components and easily scaled up on the same chip by only adjusting one of the pump wavelengths. In addition, we give the on-chip design of projection measurement for characterizing GHZ states and show the reconfigurability of the state. Our proposal is rather simple and feasible within the existing fabrication technologies and we believe it will boost the development of multiphoton technologies.     

基于平面度的燃料电池电化学性能模拟

 固体氧化物燃料电池的翘曲会影响电极-盖板界面的接触情况，从而影响电化学性能，对相关制造工艺提出了很大的挑战．为了分析燃料电池平面度对放电过程的影响，揭示其潜在的风险，我们建立了两个基于有限元法的仿真模型，对考虑平面度缺陷的燃料电池封装和放电进行分析．在对固体氧化物燃料电池进行平面度测量的基础上，首先建立了具有真实燃料电池翘曲特性的几何模型，分析封装过程中接触压力的分布情况．然后将接触电阻的仿真结果导入到三维多物理场耦合模型中，模拟具有平面度缺陷的燃料电池电化学性能．计算结果展示了燃料电池两侧封装过程中接触压力的分布情况．通过对比有接触电阻和无接触电阻的燃料电池电流密度，分析了电池与盖板的接触对放电过程的影响．结果表明，燃料电池的凹陷面较难达到满意的接触状态，需要比凸起面更大的封装压力．燃料电池表面接触电阻的变化将引起电流传导路径的变化，产生局部高电流或低电流．这项工作强调了在燃料电池中保持均匀分布的接触电阻的重要性，为今后的优化工作奠定了基础．     

Stochastic sensitivity analysis of coupled acoustic-structural systems under non-stationary random excitations

This paper presents a new sensitivity analysis method for coupled acoustic–structural systems subjected to non-stationary random excitations. The integral of the response power spectrum density (PSD) of the coupled system is taken as the objective function. The thickness of each structural element is used as a design variable. A time-domain algorithm integrating the pseudo excitation method (PEM), direct differentiation method (DDM) and high precision direct (HPD) integration method is proposed for the sensitivity analysis of the objective function with respect to design variables. Firstly, the PEM is adopted to transform the sensitivity analysis under non-stationary random excitations into the sensitivity analysis under pseudo transient excitations. Then, the sensitivity analysis equation of the coupled system under pseudo transient excitations is derived based on the DDM. Moreover, the HPD integration method is used to efficiently solve the sensitivity analysis equation under pseudo transient excitations in a reduced-order modal space. Numerical examples are presented to demonstrate the validity of the proposed method.     

Nowcasting Avalanches as Earthquakes and the Predictability of Strong Avalanches in the Olami-Feder-Christensen Model

Nowcasting earthquakes, suggested recently as a method to estimate the state of a fault and hence the seismic risk, is based on the concept of natural time. Here, we generalize nowcasting to a prediction method the merits of which are evaluated by means of the receiver operating characteristics. This new prediction method is applied to a simple (toy) model for the waiting (natural) time of the stronger earthquakes, real seismicity, and the Olami-Feder-Christensen earthquake model with interesting results revealing acceptable to excellent or even outstanding performance.     

Sparse Multicategory Generalized Distance Weighted Discrimination in Ultra-High Dimensions

Distance weighted discrimination (DWD) is an appealing classification method that is capable of overcoming data piling problems in high-dimensional settings. Especially when various sparsity structures are assumed in these settings, variable selection in multicategory classification poses great challenges. In this paper, we propose a multicategory generalized DWD (MgDWD) method that maintains intrinsic variable group structures during selection using a sparse group lasso penalty. Theoretically, we derive minimizer uniqueness for the penalized MgDWD loss function and consistency properties for the proposed classifier. We further develop an efficient algorithm based on the proximal operator to solve the optimization problem. The performance of MgDWD is evaluated using finite sample simulations and miRNA data from an HIV study.     

平面波输入下海水-海床-结构动力相互作用分析

海洋工程结构的地震反应分析是保证海洋工程结构地震安全的重要环节.由于其所处的复杂环境, 该问题涉及到流固耦合和土-结相互作用.本文基于海水、饱和海床、基岩流固耦合统一计算框架,采用Davidenkov模型和修正的Masing准则考虑饱和海床的非线性,在脉冲SV波垂直入射下, 进行了海域场地和海洋工程结构的动力响应分析. 首先,对比分析了线性自由场和非线性自由场输入情形的海域场地非线性反应,结果表明线性自由场输入时反应不合理,自由场分析和场地分析应该采用相一致的本构模型. 然后,对比分析了海床分别为线性和非线性情形时,海域场地以及海水-海床-结构体系的反应特征. 与线性海床情形相比,非线性对海床反应的影响主要由如下两方面因素控制: 一方面,非线性导致饱和海床模量减小, 饱和海床与基岩间的波阻抗比减小,由基岩到饱和海床间的反射系数和透射系数增加, 导致反应增大; 另一方面,非线性导致阻尼加大, 使海床反应减小. 对于本文算例而言,阻尼对非线性海床结果的影响占主导作用.      

小直径棒材超声横波检测仿真分析

采用超声水浸聚焦斜入射方式进行小棒材表面、近表缺陷检测时,声波在水/棒和棒/缺陷界面会发生反射、折射、散射、衍射及波形转换等一系列物理变换。此时缺陷可检性对声波入射条件十分敏感,常出现由于检测条件设置不当而导致缺陷漏检、误检的情况。为解决这一问题,本文针对小棒材超声斜入射检测中的主要参数——入射角和水距,开展声场及缺陷声响应仿真,研究检测参数对不同部位缺陷检测能力的影响,并对仿真结果进行试验验证。通过研究得到了检测水距、入射角度对缺陷检测能力的影响,并得到最优检测条件。试验验证结果表明研究制定的检测方案可有效检测出表面、近表面裂纹缺陷。