含硫氰酸盐、硫化物固体废物中总氰化合物测定方法

实验建立了含硫氰酸盐、硫化物固体废物中总氰化合物的测定方法,采用硝酸银滴定法、异烟酸-吡唑啉酮分光光度法分别测定总氰化合物含量高、低的样品。通过条件实验优化了前处理方式、称样量和干扰去除方法。该方法测定结果的相对标准偏差为0.43%～1.33%,加入标准物质回收率为91.5%～101.5%,精密度和准确度良好,符合测定要求。     

MnS夹杂物诱发钢材点蚀综述

MnS夹杂物诱发钢材点蚀,对钢材服役寿命、工作生产安全和社会经济发展产生巨大危害。首先,分析了MnS夹杂物诱发钢材点蚀的机理,包括电偶腐蚀机理、S和Cl-协同作用机理、封闭区域加速点蚀机理、贫铬区机理和微缝隙机理;其次,汇总了MnS夹杂物大小、形貌、分布,Cl-浓度、温度和应力对MnS夹杂物诱发钢材点蚀的影响;然后,总结了钢材防腐蚀的常用措施;最后,展望了防止MnS夹杂物诱发钢材点蚀的未来研究方向。     

几种重氮氨基类新显色剂的合成及其与镉（Ⅱ）显色反应的研究

3种重氮氨基类新显色剂的合成及其与镉(Ⅱ)的显色反应。在表面活性剂 Triton X-100存在下,3种试剂均与镉(Ⅱ)生成络合比为3:1的红色络合物。其表观摩尔吸光系数在1.80×10~5以上。镉量在0～12μg/25mL 符合比尔定律。并对3种试剂的性能与结构的关系作了比较。将其中一种试剂(BPDAA)用于废水中痕量镉的测定,结果满意。     

火焰原子吸收光谱法测定高纯石英粉中痕量钙

系统地研究了用空气——乙炔火焰原子吸收光谱分析法测定高纯石英粉中钙的最佳条件，建立了14％的乙醇作为增感剂，在2％盐酸介质中，0．4％ LaCl3溶液作为释放剂，用塞曼火焰原子吸收法测定的可行性方案，探讨了共存元素对钙的干扰及其消除。方法操作简便快速，干扰少，方法相对标准偏差小于3％，适用于日常分析石英粉中的杂质。     

用于虚拟现实的360度视频编码技术新进展*

随着虚拟现实技术不断发展,360度视频编码开始成为研究热点。应用于虚拟现实的360度视频与传统的视频相比分辨率更高,编码数据量更大,在实际应用中面临传输带宽有限的瓶颈,编码效率问题有待解决。归纳分析了国际标准组织联合视频研究组（joint video exploration team, JVET）正在制定的360度视频编码投影变换技术及其编码优化方法,综合对比了各变换技术的编码性能。根据当前最新研究成果,对下一步研究需要解决的问题进行了探讨总结,给出未来的研究方向和思路。     

Improvement of Microwave Loss Tangent and Tunability of Ba0.55Sr0.45TiO3/MgO Composites Using the Heterogeneous Precipitation Method

Ba_0.55Sr_0.45TiO₃/MgO composites were successfully prepared by the heterogeneous precipitation method and their structural, surface morphological, tunable properties, and dielectric properties at microwave frequency were systemically investigated. Compared with the sample prepared by the traditional solid-state method, the sample prepared by the heterogeneous precipitation method exhibits a smaller grain size, more uniform microstructure, higher tunability, and lower microwave loss, and these properties are very beneficial to the development of the microwave tunable devices application. Moreover, the effects of La₂O₃ doping on the dielectric and tunable properties of BST/MgO composites are investigated. The result shows that the La³⁺-doped sample has higher tunability and lower microwave loss than the undoped one.     

Augment low-field intra-operative MRI with preoperative MRI using a hybrid non-rigid registration method

Background

Preoperatively acquired diffusion tensor image (DTI) and blood oxygen level dependent (BOLD) have been proved to be effective in providing more anatomical and functional information; however, the brain deformation induced by brain shift and tumor resection severely impairs the correspondence between the image space and the patient space in image-guided neurosurgery.

Method

To address the brain deformation, we developed a hybrid non-rigid registration method to register high-field preoperative MRI with low-field intra-operative MRI in order to recover the deformation induced by brain shift and tumor resection. The registered DTI and BOLD are fused with low-field intra-operative MRI for image-guided neurosurgery.

Results

The proposed hybrid registration method was evaluated by comparing the landmarks predicted by the hybrid registration method with the landmarks identified in the low-field intra-operative MRI for 10 patients. The prediction error of the hybrid method is 1.92 ± 0.54 mm, and the compensation accuracy is 74.3 ± 5.0%. Compared to the landmarks far from the resection region, those near the resection region demonstrated a higher compensation accuracy (P-value = .003) although these landmarks had larger initial displacements.

Conclusions

The proposed hybrid registration method is able to bring preoperatively acquired BOLD and DTI into the operating room and compensate for the deformation to augment low-field intra-operative MRI with rich anatomical and functional information.     

A Framework for Moving Least Squares Method with Total Variation Minimizing Regularization

In this paper, we propose a computational framework to incorporate regularization terms used in regularity based variational methods into least squares based methods. In the regularity based variational approach, the image is a result of the competition between the fidelity term and a regularity term, while in the least squares based approach the image is computed as a minimizer to a constrained least squares problem. The total variation minimizing denoising scheme is an exemplary scheme of the former approach with the total variation term as the regularity term, while the moving least squares method is an exemplary scheme of the latter approach. Both approaches have appeared in the literature of image processing independently. By putting schemes from both approaches into a single framework, the resulting scheme benefits from the advantageous properties of both parties. As an example, in this paper, we propose a new denoising scheme, where the total variation minimizing term is adopted by the moving least squares method. The proposed scheme is based on splitting methods, since they make it possible to express the minimization problem as a linear system. In this paper, we employed the split Bregman scheme for its simplicity. The resulting denoising scheme overcomes the drawbacks of both schemes, i.e., the staircase artifact in the total variation minimizing based denoising and the noisy artifact in the moving least squares based denoising method. The proposed computational framework can be utilized to put various combinations of both approaches with different properties together.     

二维多层次的云服务可靠性评估方法研究

针对云服务业务流程管理的特点, 给出了云服务的组合实现框架; 依据随机Petri网的建模理论, 探讨了组合云服务流程网模型的细粒度建模方法; 根据动态多变的用户需求, 设计了二维多层次的云服务组合可靠性动态评估框架, 并给出了马尔可夫过程和等值约简的两种可靠性计算方法。应用示例分析结果表明, 该方法具有较好的动态适应性和灵活性, 能有效满足云服务的可靠性评估需求。