TiO_2薄膜光催化降解甲基橙反应动力学研究

以甲基橙为模型污染物、TiO2薄膜为光催化剂,在自制的光催化反应器上进行了光催化降解反应实验,主要研究了甲基橙初始浓度(c0)和紫外光光照强度(I)对其光催化降解反应的影响。结果表明,该降解反应可用一级反应动力学方程进行描述,反应速率常数(k)与c0及光强I的关系分别为:k∝c0-1 4和k∝I0.65。     

接种固氮菌对纤维素分解过程的影响

从纤维素分解菌与联合固氮菌的接种配比,研究了混合培养对滤纸分解的影响。试验共设6个处理样,总接种量均为10%(V/V):处理Ⅰ,2%固氮菌+8%纤维素分解菌;处理Ⅱ,4%固氮菌+6%纤维素分解菌;处理Ⅲ,6%固氮菌+4%纤维素分解菌;处理Ⅳ,10%纤维素分解菌;处理Ⅴ,10%固氮菌;CK(空白对照)。结果显示:与处理Ⅳ相比,处理Ⅰ、Ⅱ的CMC酶活力及处理Ⅰ、Ⅱ、Ⅲ的滤纸分解率有明显提高。接种固氮菌的各处理样中,培养液中氮素含量与CK相比均有显著提高(P<0.05),且培养过程中pH值比较平稳,而未接种固氮菌处理培养液的氮素则低于CK,pH急剧降低。所有处理样中,接种2%固氮菌效果最佳,培养192h,其CMC酶活力与滤纸分解率比处理Ⅳ分别提高43.4%、240%;与处理Ⅴ相比,固氮菌数有显著增加(P<0.05),培养液中氮含量提高28.0%。     

以高活性度石灰为原料制备纳米碳酸钙的研究

采用间歇鼓泡碳化法，通过对碳化反应温度、灰乳体积质量、搅拌转速、气体分布器开孔直径、消化浆液陈化时间等影响因素的控制，得到了用高活性度石灰为原料制备纳米碳酸钙的优化工艺条件，制得了平均粒径为15～40nm的纳米碳酸钙产品。     

气相法改性纳米二氧化硅表面

采用硅烷偶联剂A-151处理的纳米二氧化硅粒子，具有良好的疏水性，并且反应副产物没有腐蚀性，有利于保护设备和环境保护。分别用表面羟基数、亲油化度等性能来表征改性纳米二氧化硅的效果。红外光谱分析表明A-151确实已经和纳米二氧化硅表明的羟基发生了化学反应，通过透射电镜研究发现改性后纳米二氧化硅在乙醇中达到纳米级的分散。     

生物质秸秆墙材—新型墙材的发展方向

秸秆是第二大“森林”资源，将秸秆制备成墙材，既找到大量秸秆资源化的出路，也填补了墙材即将面临短缺的难题。综述了生物质秸秆墙材的研究进展，讨论了目前秸秆墙材研究与应用中存在的问题，探讨了秸秆墙材将来研究的趋势。     

硼酸在润滑油添加剂领域的应用现状

硼元素引入润滑油添加剂中可改善和提高油品的抗磨性能以及热稳定性能等。硼元素是通过硼酸与碱性化合物反应而引入添加剂分子上的，因而，硼酸已逐步成为润滑油添加剂的重要原料之一。介绍了硼酸在润滑油添加剂中的应用现状，包括含硼清净剂、含硼分散剂、含硼极压抗磨剂、含硼防锈剂。主要介绍了世界各大石油公司生产含硼润滑油添加剂的商品牌号、合成方法等。指出随着中国汽车工业的发展，环保、节能法规的不断出台与执行力度的加大，含硼等环保、节能型润滑油添加剂将得到广泛的使用，其中硼化丁二酰亚胺市场潜力巨大。     

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.     

Prediction of multicomponent adsorption equilibrium of gas mixtures including supercritical components

A new model to predict the adsorption equilibrium of mixtures containing supercritical components was presented. The difference in the adsorption mechanism between the supercritical components and the condensable components was accounted for in the new model. Lateral interaction in the adsorbed phase was also considered in the local isotherm. The new model was verified by the experimental data of the mixture CH₄/CO₂/C₂H₆ on activated carbon JX101 collected for 283-313 K and pressures up to . It was also verified with the experimental data published previously in literature. Considerable improvement in the prediction precision was achieved in using the new model to predict the adsorption of mixtures on activated carbon.     

Automatic inpainting by removing fence-like structures in RGBD images

Recent inpainting techniques usually require human interactions which are labor intensive and dependent on the user experiences. In this paper, we introduce an automatic inpainting technique to remove undesired fence-like structures from images. Specifically, the proposed technique works on the RGBD images which have recently become cheaper and easier to obtain using the Microsoft Kinect. The basic idea is to segment and remove the undesired fence-like structures by using both depth and color information, and then adapt an existing inpainting algorithm to fill the holes resulting from the structure removal. We found that it is difficult to achieve a satisfactory segmentation of such structures by only using the depth channel. In this paper, we use the depth information to help identify a set of foreground and background strokes, with which we apply a graph-cut algorithm on the color channels to obtain a more accurate segmentation for inpainting. We demonstrate the effectiveness of the proposed technique by experiments on a set of Kinect images.     

A memetic algorithm for the capacitated m-ring-star problem

The Capacitated m-Ring-Star Problem (CmRSP) models a network topology design problem in the telecommunications industry. In this paper, we propose to solve this problem using a memetic algorithm that includes a crossover operation, a mutation operation, a local search involving three neighborhood operators, and a population selection strategy that maintains population diversity. Our approach generates the best known solutions for 131 out of 138 benchmark instances, improving on the previous best solutions for 24 of them, and exhibits more advantages on large benchmark instances when compared with the best existing approach. Additionally, all existing algorithms for this problem in literature assume that the underlying graph of the problem instance satisfies the triangle inequality rule; our approach does not require this assumption. We also generated a new set of 36 larger test instances based on a digital data service network price structure to serve as a new benchmark data set for future researchers.