The influence of volume fraction of amorphous phase on corrosion resistance of Mg67Zn 29Ca 4 alloy

The aim of this study was to investigate the structure and corrosion resistance of amorphous, amorphous‐crystalline, and crystalline Mg₆₇Zn₂₉Ca₄ alloy for biodegradable applications. This paper presents a preparation method and results of the structural characterization and corrosion resistance analysis of the material. Samples were prepared in the form of 3 mm diameter rods. The structure of the alloy was examined with the use of X‐ray diffractometry and scanning electron microscopy. The thermal properties of the samples were examined with differential scanning calorimetry (DSC). Results of DSC analysis were used to determine heat treatment temperatures, allowing to obtain different fractures of crystalline phase in the material. Corrosion resistance of heat‐treated samples was investigated by immersion tests and electrochemical measurements performed in the simulated body fluid. The X‐ray diffraction results confirmed that the prepared Mg₆₇Zn₂₉Ca₄ alloy's structure is fully amorphous. After heat treatment, samples with different fractions of amorphous phase in the structure were obtained. Immersion tests of the samples showed that the structure significantly influenced corrosion resistance in examined materials. It should be pointed out, that certain amounts of crystalline phase in amorphous matrix can greatly improve the corrosion resistance of Mg₆₇Zn₂₉Ca₄ alloy.     

Transport Map sampling with PGD model reduction for fast dynamical Bayesian data assimilation

The motivation of this work is to address real-time sequential inference of parameters with a full Bayesian formulation. First, the proper generalized decomposition (PGD) is used to reduce the computational evaluation of the posterior density in the online phase. Second, Transport Map sampling is used to build a deterministic coupling between a reference measure and the posterior measure. The determination of the transport maps involves the solution of a minimization problem. As the PGD model is quasi-analytical and under a variable separation form, the use of gradient and Hessian information speeds up the minimization algorithm. Eventually, uncertainty quantification on outputs of interest of the model can be easily performed due to the global feature of the PGD solution over all coordinate domains. Numerical examples highlight the performance of the method.     

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。     

基于多尺度双线性卷积神经网络的多角度下车型精细识别

针对多角度下车辆出现一定的尺度变化和形变导致很难被准确识别的问题，提出基于多尺度双线性卷积神经网络（MS-B-CNN）的车型精细识别模型。首先，对双线性卷积神经网络（B-CNN）算法进行改进，提出MS-B-CNN算法对不同卷积层的特征进行了多尺度融合，以提高特征表达能力；此外，还采用基于中心损失函数与Softmax损失函数联合学习的策略，在Softmax损失函数基础上分别对训练集每个类别在特征空间维护一个类中心，在训练过程中新增加样本时，网络会约束样本的分类中心距离，以提高多角度情况下的车型识别的能力。实验结果显示，该车型识别模型在CompCars数据集上的正确率达到了93.63%，验证了模型在多角度情况下的准确性和鲁棒性。     

结合优化支持向量机与K-means++的工控系统入侵检测方法

针对工业控制系统传统单一检测算法模型对不同攻击类型检测率和检测速度不佳的问题，提出一种优化支持向量机和K-means++算法结合的入侵检测模型。首先利用主成分分析法（PCA）对原始数据集进行预处理，消除其相关性；其次在粒子群优化（PSO）算法的基础上加入自适应变异过程避免在训练的过程中陷入局部最优解；然后利用自适应变异粒子群优化（AMPSO）算法优化支持向量机的核函数和惩罚参数；最后利用密度中心法改进K-means算法与优化后的支持向量机组合成入侵检测模型，从而实现工业控制系统的异常检测。实验结果表明，所提方法在检测速度和对各类攻击的检测率上得到明显提升。     

Fair‐Weather Friends: Evidence of Lipoxin Dysregulation in Neurodegeneration

Lipoxins (LXs) are autacoids, specialized proresolving lipid mediators (SPMs) acting locally in a paracrine or autocrine fashion. They belong to a complex superfamily of dietary small polyunsaturated fatty acid (PUFA)–metabolites, which direct potent cellular responses to resolve inflammation and restore tissue homeostasis. Together, these SPM activities have been intensely studied in systemic inflammation and acute injury or infection, but less is known about LX signaling and activities in the central nervous system. LXs are derived from arachidonic acid, an omega‐6 PUFA. In addition to well‐established roles in systemic inflammation resolution, they have increasingly become implicated in regulating neuroinflammatory and neurodegenerative processes. In particular, chronic inflammation plays a central role in Alzheimer's disease (AD) etiology, and dysregulated LX production and activities have been reported in a variety of AD rodent models and clinical tissue samples, yet with complex and sometimes conflicting results. In addition, reduced LX production following retinal injury has been reported recently by the authors, and an intriguing direct neuronal activity promoting survival and homeostasis in retinal and cortical neurons is demonstrated. Here, the authors review and clarify this growing literature and suggest new research directions to further elaborate the role of lipoxins in neurodegeneration.     

Structure and phase-composition of Ti-doped gas atomized Raney-type Ni catalyst precursor alloys

Raney-type Ni precursor alloys containing 75 at.% Al and doped with 0, 0.75, 1.5 and 3.0 at.% Ti have been produced by a gas atomization process. The resulting powders have been classified by size fraction with subsequent investigation by powder XRD, SEM and EDX analysis. The undoped powders contain, as expected, the phases Ni₂Al₃, NiAl₃ and an Al-eutectic. The Ti-doped powders contain an additional phase with the TiAl₃ DO₂₂ crystal structure. However, quantitative analysis of the XRD results indicate a far greater fraction of the TiAl₃ phase is present than could be accounted for by a simple mass balance on Ti. This appears to be a (Ti_xNi_1−x)Al₃ phase in which higher cooling rates favour small x (low Ti-site occupancy by Ti atoms). SEM and EDX analysis reveal that virtually all the available Ti is contained within the TiAl₃ phase, with negligible Ti dissolved in either the Ni₂Al₃ or NiAl₃ phases.     

Human mobility synthesis using matrix and tensor factorizations

Human mobility prediction is of great advantage in route planning and schedule management. However, mobility data is a high-dimensional dataset in which multi-context prediction is difficult in a single model. Mobility data can usually be expressed as a home event, a work event, a shopping event and a traveling event. Previous works have only been able to learn and predict one type of mobility event and then integrate them. As the tensor model has a strong ability to describe high-dimensional information, we propose an algorithm to predict human mobility in tensors of location context data. Using the tensor decomposition method, we extract human mobility patterns with multiple expressions and then synthesize the future mobility event based on mobility patterns. The experiment is based on real-world location data and the results show that the tensor decomposition method has the highest accuracy in terms of prediction error among the three methods. The results also prove the feasibility of our multi-context prediction model.     

水提法提取—电感耦合等离子体质谱法测定婴幼儿配方奶粉中的碘

用水提取婴幼儿奶粉中的碘,亚铁氰化钾和乙酸锌盐析法沉淀蛋白,过滤后可以得到澄清处理液。用电感耦合等离子体质谱对提取样液进行测定,130Te作为内标物进行定量分析。该方法简便快捷,检出限为0.10 mg/kg加标回收率为90.8%~109%,相关系数0.999,精密度试验RSD2%。