Measurement of the Effective Diffusivity in Porous Media by the Diffusion Cell Method

There has been a vast amount of investigation in the field of experimental and theoretical treatments of the effective diffusivity in porous media for more than half of a century [1-4]. The effective diffusivity is required for several reasons [5]; for example, during catalyst formulation, active species can be laid down precisely or with specified concentration profiles on a porous matrix or support. In experimental work on heterogeneous reactions an effective diffusivity is needed to obtain the value of the Thiele modulus and hence to determine the intrinsic reaction kinetics. In reactor design the diffusivity is needed to evaluate the Thiele modulus, which can then be an aid in predicting reaction rates for heterogeneous systems. In addition, a simple and quick testing method could be used as a screening or quality control procedure during catalyst manufacture.

     

ANALYSIS OF THE INITIAL STAGES.OF ENZYME IMMOBILIZATION IN POROUS SOLIDS

This work considers the initial stages of enzyme immobilization in solids with pores of much greater diameter than the enzyme molecule. The enzyme immobilization rate is assumed during this time to be first-order with respect to the enzyme concentration in the pore fluid. An analytical solution for this model is obtained using finite Sturm-Liouville integral transforms. Asymptotic expressions for the case of large reservoirs of immobilizing fluid are also determined by application of a multiscale perturbation analysis.     

（英）基于新型双模圆谐振腔的高选择性毫米波滤波器

提出了一种新颖的高选择性毫米波带通滤波器及其设计方法.在圆谐振腔的侧壁加入槽型微扰结构,通过调节微扰小槽的角度可以控制滤波器带外传输零点的位置,从而实现了带宽可调、高选择性的双模圆谐振腔带通滤波器.根据该滤波器结构、理论分析和仿真设计基础,研制了在V波段滤波器样品并进行了测试.实验结果与方正吻合得良好.与传统双模圆腔滤波器相比,所提出的滤波器不需要额外的调节结构,其设计方法简单,选择特性高,结构紧凑,具有一定的工程价值用于高性能平面化毫米波滤波器的设计.     

Association of serum alkaline phosphatase and bone mineral density in maintenance hemodialysis patients

Recent studies indicate that serum alkaline phosphatase (AlkPhos), a surrogate of high turnover bone disease, is associated with coronary artery calcification and death risk in maintenance hemodialysis (MHD) patients. The association between AlkPhos and bone mineral density (BMD) is not well studied. We studied the association between AlkPhos and dual‐energy X‐ray absorptiometry‐assessed BMD in a group of MHD patients in Southern California. In 154 MHD patients, aged 55.3 ± 13.6 years, including 42% women, 38% Hispanics, 42% African Americans, and 55% diabetics, the mean serum AlkPhos was 121 ± 63 U/L (median: 101, Q_25–75: 81–141); 36% had AlkPhos≥120 U/L and 50% had a total T‐score≤?1. Whereas the total BMD did not correlate with age (r=0.01, P=0.99) or body mass index (r=0.10, P=0.22), it correlated negatively with AlkPhos (r=?0.25, P=0.002), including after multivariate adjustment (r=?0.24, P=0.003). The proportion of patients with a high coronary artery calcification score>400 was incrementally higher across worsening BMD tertiles (P trend=0.04). The BMD was significantly worse in MHD patients with serum AlkPhos≥120 U/L compared with <120 U/L (1.01 ± 0.016 vs. 1.08 ± 0.013 g/cm², respectively, P<0.001). The multivariate adjusted odds ratio of AlkPhos≥120 U/L for having a total T‐score相似文献   

ASYMPTOTIC MATCHING PRINCIPLE TO CHEMICAL ENGINEERING PROBLEMS

A matching principle is developed for a class of initial value problems for which the degenerate problems have either a zero or nonzero Jacobian. Detailed derivation of the appropriate set of initial conditions which apply to the outer expansion is also provided. The use of the technique is illustrated by way of two reactions engineering examples.     

CLS-Miner: efficient and effective closed high-utility itemset mining

High-utility itemset mining (HUIM) is a popular data mining task with applications in numerous domains. However, traditional HUIM algorithms often produce a very large set of high-utility itemsets (HUIs). As a result, analyzing HUIs can be very time consuming for users. Moreover, a large set of HUIs also makes HUIM algorithms less efficient in terms of execution time and memory consumption. To address this problem, closed high-utility itemsets (CHUIs), concise and lossless representations of all HUIs, were proposed recently. Although mining CHUIs is useful and desirable, it remains a computationally expensive task. This is because current algorithms often generate a huge number of candidate itemsets and are unable to prune the search space effectively. In this paper, we address these issues by proposing a novel algorithm called CLS-Miner. The proposed algorithm utilizes the utility-list structure to directly compute the utilities of itemsets without producing candidates. It also introduces three novel strategies to reduce the search space, namely chain-estimated utility co-occurrence pruning, lower branch pruning, and pruning by coverage. Moreover, an effective method for checking whether an itemset is a subset of another itemset is introduced to further reduce the time required for discovering CHUIs. To evaluate the performance of the proposed algorithm and its novel strategies, extensive experiments have been conducted on six benchmark datasets having various characteristics. Results show that the proposed strategies are highly efficient and effective, that the proposed CLS-Miner algorithmoutperforms the current state-ofthe- art CHUD and CHUI-Miner algorithms, and that CLSMiner scales linearly.