NH_3-OH体系中共沉淀法同时回收钕铁硼废料中Nd-Pr-Co-Fe

为了避免回收单一钕铁硼废料中有价元素带来的操作复杂和资源浪费等问题,本研究采用共沉淀法共沉淀出钕铁硼废料中的有价元素Me(Nd,Pr,Co,Fe),制备可用于生产再生钕铁硼的原料;根据质量守恒和同时平衡原理,采用MATLAB软件建立Me(Nd,Pr,Co,Fe)-OH--NH3热力学模型,绘制lg[Me]-p H曲线模拟共沉淀工艺,并根据模拟结果确立了共沉淀工艺;模拟和实验的结果表明:根据lg[Me]-p H模拟结果可以确立一步共沉淀法的p H:6~10,Fe3+比Fe2+更易于沉淀完全;在上述条件下获得的共沉淀粉末主相均为Nd,Pr,Co,Fe的化合物,且有价元素的百分比含量均大于99.4%;其中,当p H值在8左右时回收率最高,在该条件下金属元素Me(Nd,Pr,Co,Fe)的沉淀效率分别为:98.7%,99.9%,93.6%,99.9%。该结果也表明共沉淀法工艺不仅高效,而且所制备的共沉淀粉末可以满足制备二次钕铁硼的需要。     

Isolated hepatic tuberculosis mimicking liver tumors in a dialysis patient

Cases of isolated hepatic tuberculosis (TB) are rare. The diagnosis is often delayed or missed because of nonspecific symptoms and laboratory findings. Besides, the disease is extremely rare even in a country where TB is an alarming public health problem. This report demonstrates the difficulty in correctly diagnosing local hepatic TB. We report the case of a 62‐year‐old male patient with end‐stage renal disease treated with hemodialysis, who developed 2 months of abdominal distension and general anorexia, with hyperechoic hepatic lesions on ultrasound. Computed tomography suspected multiple liver tumors. The liver biopsy finally led to the diagnosis of TB of the liver without other involvements. We conclude that isolated hepatic TB is one of the rare forms of extrapulmonary TB in dialysis patients. A greater awareness of this rare clinical entity may prevent needless surgical interventions.     

靶面激光光斑尺寸原位测量的研究

提供了一种简便易行的靶面激光光斑尺寸原位测量的方法。从高斯光束的横向光强分布特性出发,建立了激光烧蚀斑半径与辐照激光能量、光斑尺寸、烧蚀阈值间的关系式,模拟分析发现辐照激光光斑尺寸对烧蚀斑半径随辐照能量变化曲线有较大影响。对于脉宽为2 ms,波长为1064 nm的激光,实验测量了不同能量激光辐照下相纸烧蚀斑半径,并用推导出的关系式拟合测量数据,获得了靶面处光斑尺寸和样品烧蚀阈值。同时,也测量了不同位置处的光斑尺寸和样品烧蚀阈值,对高斯光束束腰位置和样品烧蚀阈值的光斑尺寸效应进行了验证。研究结果表明该技术结果可靠,简单高效。该技术可以为高能激光与固体物质相互作用的基础研究和激光加工等应用领域中实现简单方便地测量靶面光斑尺寸提供帮助。     

V2O5/RGO/Pt nanocomposite on oxytetracycline degradation and pharmaceutical effluent detoxification

The cover image is based on the Research Article V₂O₅/RGO/Pt nanocomposite on oxytetracycline degradation and pharmaceutical effluent detoxification by Mohan, H et al., DOI: 10.1002/jctb.6238 .

     

ATSP:时态网络可视化的自适应时间片划分方法

现有的时态网络可视化方法大多采用等量时间片来可视化网络的演变，不利于时态模式的快速挖掘和发现。为此，根据时态网络固有的特征提出自适应时间片划分方法（Adaptive Time Slice Partition method，ATSP）。在时态网络的两种表示方式（基于事件的表示方式和基于快照的表示方式）的基础上，构建了ATSP的基础模型，同时提出了一种改进模型用来描述事件间隔时间服从长尾分布的时态网络。为了实现时间片的不等量划分，针对探索任务的不同提出了基于时态模式的ATSP规则和基于中心节点的ATSP规则，并提出了实现算法--层次划分算法（Hierarchical Partition algorithm，HP）和增量划分算法（Incremental Partition algorithm，IP）。实验结果表明，ATSP方法比传统的时间片划分方法更能准确地表示网络的时态特征，且该方法应用于可视化时，能有效归纳并展示网络的特征，明显提高了视觉分析的效率。     

基于粒子群优化和支持向量机的花粉浓度预测模型

为了提高花粉浓度预报的准确率，解决现有花粉浓度预报准确率不高的问题，提出了一种基于粒子群优化（PSO）算法和支持向量机（SVM）的花粉浓度预报模型。首先，综合考虑气温、气温日较差、相对湿度、降水量、风力、日照时数等多种气象要素，选择与花粉浓度相关性较强的气象要素构成特征向量；其次，利用特征向量与花粉浓度数据建立SVM预测模型，并使用PSO算法找出最优参数；然后利用最优参数优化花粉浓度预测模型；最后，使用优化后的模型对花粉未来24 h浓度进行预测，并与未优化的SVM、多元线性回归法（MLR）、反向神经网络（BPNN）作对比。此外使用优化后的模型对某市南郊观象台和密云两个站点进行逐日花粉浓度预测。实验结果表明，相比其他预报方法，所提方法能有效提高花粉浓度未来24 h预测精度，并具有较高的泛化能力。     

Electrocatalytic activity of LaSr3Fe3O10 and LaSr3Fe3O10-GO towards oxygen reduction reaction in alkaline medium

Oxygen reduction reaction(ORR) plays a critical role in many energy conversion and storage processes.Therein, a comparative study of the electrocatalytic activity for ORR in 0.1 mol/L KOH solution was conducted using layered perovskite-like LaSr_3 Fe_3 O_(10) and LaSr3 Fe_3 O_(10)-graphene oxide(GO) composite as electrodes. Linear sweep voltammetry(LSV) results show that the LaSr3 Fe_3 O_(10)-GO hybrid exhibits higher current density, a more positive onset potential(-0.15 V vs. Hg/HgO) in comparison with LaSr_3 Fe_3 O_(10).The value of the overall transferred electrons for both catalysts implies a dominant two electron process for ORR. Both catalysts under alkalic conditions exhibit a two-step Tafel slope, suggesting a change in the reaction mechanism for ORR. The composite electrode exhibits a higher ORR current density, but inferior durability performances in relative to the LaSr_3 Fe_3 O_(10) electrode.     

Backtesting portfolio value-at-risk with estimated portfolio weights

This article theoretically and empirically analyzes backtesting portfolio value-at-risk (VaR) with estimation risk in an intrinsically multi-variate framework. It particularly takes into account the estimation of portfolio weights in forecasting portfolio VaR and its impact on backtesting. It shows that the estimation risk from estimating portfolio weights and that from estimating the multi-variate dynamic model make the existing methods in a univariate framework inapplicable. It proposes a general theory to quantify estimation risk applicable to the present problem and suggests practitioners a simple but effective way to implement valid inference to overcome the effect of estimation risk in backtesting portfolio VaR. In particular, we apply our theory to the efficient mean-variance-skewness portfolio for a multi-variate generalized autoregressive conditional heteroscedasticity model with multi-variate general hyperbolic distributed innovations. Some Monte Carlo simulations and an empirical application demonstrate the merits of our method.     

Se doped nickel-molybdenum bimetal sulfide with enhanced electrochemical activity for hydrogen evolution reaction

In this work, we synthesized Se doped MoS₂@Ni₃S₂ with nanosheets coated nanorods structure supported on Ni foam (MoNiSeS). Firstly, MoS₂@Ni₃S₂ (MoNiS) nanorods was synthesized by hydrothermal method. After selenization treatment, MoSe₂ successfully formed on the edge of MoS₂ nanosheets and particle Ni₃S₂ transformed into NiSe, in which MoSe₂ and NiSe acted as new phase in MoNiSeS. The obtained MoNiSeS only needs a low overpotential of 68 mV to reach the current density of 10 mA cm^?2, and has a low Tafel plots of 72.77 mV dec^?1 and good electrochemical durability, whose electrochemical activity is much better than that of MoNiS and NiSeS, implying the introduction of Mo and Se is beneficial to improve the electrocatalytic performance of NiS for HER. In addition, the proper amount of Mo source, which has an effect on the morphology of product, has also been investigated. For MoNiSeS, the typical nanosheets coated nanarods expose more active sites and the synergic effects is good to the improvement of the catalytic activity. Meanwhile, WNiSeS has also been prepared using the same method and the corresponding results show that the electrochemical activity of WNiSeS is much better than that of NiSeS, proving the universality of this strategy.