镁合金废料的回收

在镁合金零部件生产过程中，特别是在压力铸造生产中，产生出来的废料以及使用后报废的镁合金零件逐渐增多。出于成本和环境因素的考虑，必须对这与日俱增的镁合金废料进行有效回收。本文以生产占90％的镁合金零部件压力铸造为主线，介绍镁合金废料回收的经济分析，镁合金废料的来源和分类、现行回收技术的现状及发展趋势。并介绍香港生产力促进局和重庆硕龙科技公司最近研究开发的一种新型镁合金废料现场精炼回收系统。     

Active hashing and its application to image and text retrieval

In recent years, hashing-based methods for large-scale similarity search have sparked considerable research interests in the data mining and machine learning communities. While unsupervised hashing-based methods have achieved promising successes for metric similarity, they cannot handle semantic similarity which is usually given in the form of labeled point pairs. To overcome this limitation, some attempts have recently been made on semi-supervised hashing which aims at learning hash functions from both metric and semantic similarity simultaneously. Existing semi-supervised hashing methods can be regarded as passive hashing since they assume that the labeled pairs are provided in advance. In this paper, we propose a novel framework, called active hashing, which can actively select the most informative labeled pairs for hash function learning. Specifically, it identifies the most informative points to label and constructs labeled pairs accordingly. Under this framework, we use data uncertainty as a measure of informativeness and develop a batch mode algorithm to speed up active selection. We empirically compare our method with a state-of-the-art passive hashing method on two benchmark data sets, showing that the proposed method can reduce labeling cost as well as overcome the limitations of passive hashing.     

Ketamine effects on the urogenital system--changes in the urinary bladder and sperm motility

Different doses of ketamine (10 mg/kg, 20 mg/kg, 30 mg/kg, 40 mg/kg, 50 mg/kg, and 60 mg/kg) were injected i.p. (I.P.), respectively, to male ICR mice to determine the optimal dosage for chronic administration. At and above 40 mg/kg I.P. injection, mice had almost no hindlimb movement during swimming test. Subsequently, 30 mg/kg was used as the dose for the study in the toxicity of long-term ketamine administration on urinary bladder and sperm motility. The treatment group were subdivided into two (n = 10 each group); one received daily ketamine treatment i.p. for 3 months and another group for 6 months. Corresponding number of mice in control groups (n = 5 each group) received saline injection instead of ketamine. Terminal dUTP nick and labeling (TUNEL) study and Sirius red staining were carried out on the sectioned slides of the urinary bladders to study the degree of apoptosis in both epithelium and muscular layers of the urinary bladder and the relative thickness of the muscular layers in this organ was also computed. Apoptosis in the bladder epithelium was observed initially in the 3-month ketamine treated mice and the number of apoptotic cells was significantly different (P < 0.05) between the 3-month and 6-month ketamine treated mice and the control. The relative thickness of muscular layers in the bladder wall also decreased significantly (P < 0.05) when the 6-month treated mice and the control were compared. Sirius red staining revealed increase of collagen in the urinary bladder of the treated mice, most evidently 6 months after ketamine treatment. In addition, the sperm motility was studied and there was a statistically significant difference between the control and ketamine treated groups in the percentages of sperms which were motile (P < 0.05). This suggested that the chronic administration of ketamine affected the genital system as well.     

Robust path-based spectral clustering

Spectral clustering and path-based clustering are two recently developed clustering approaches that have delivered impressive results in a number of challenging clustering tasks. However, they are not robust enough against noise and outliers in the data. In this paper, based on M-estimation from robust statistics, we develop a robust path-based spectral clustering method by defining a robust path-based similarity measure for spectral clustering under both unsupervised and semi-supervised settings. Our proposed method is significantly more robust than spectral clustering and path-based clustering. We have performed experiments based on both synthetic and real-world data, comparing our method with some other methods. In particular, color images from the Berkeley segmentation data set and benchmark are used in the image segmentation experiments. Experimental results show that our method consistently outperforms other methods due to its higher robustness.     

A scalable kernel-based semisupervised metric learning algorithm with out-of-sample generalization ability

In recent years, metric learning in the semisupervised setting has aroused a lot of research interest. One type of semisupervised metric learning utilizes supervisory information in the form of pairwise similarity or dissimilarity constraints. However, most methods proposed so far are either limited to linear metric learning or unable to scale well with the data set size. In this letter, we propose a nonlinear metric learning method based on the kernel approach. By applying low-rank approximation to the kernel matrix, our method can handle significantly larger data sets. Moreover, our low-rank approximation scheme can naturally lead to out-of-sample generalization. Experiments performed on both artificial and real-world data show very promising results.     

Approximations and reducts with covering generalized rough sets

The covering generalized rough sets are an improvement of traditional rough set model to deal with more complex practical problems which the traditional one cannot handle. It is well known that any generalization of traditional rough set theory should first have practical applied background and two important theoretical issues must be addressed. The first one is to present reasonable definitions of set approximations, and the second one is to develop reasonable algorithms for attributes reduct. The existing covering generalized rough sets, however, mainly pay attention to constructing approximation operators. The ideas of constructing lower approximations are similar but the ideas of constructing upper approximations are different and they all seem to be unreasonable. Furthermore, less effort has been put on the discussion of the applied background and the attributes reduct of covering generalized rough sets. In this paper we concentrate our discussion on the above two issues. We first discuss the applied background of covering generalized rough sets by proposing three kinds of datasets which the traditional rough sets cannot handle and improve the definition of upper approximation for covering generalized rough sets to make it more reasonable than the existing ones. Then we study the attributes reduct with covering generalized rough sets and present an algorithm by using discernibility matrix to compute all the attributes reducts with covering generalized rough sets. With these discussions we can set up a basic foundation of the covering generalized rough set theory and broaden its applications.     

Determinants of the inhibitory action of purified 14-kDa phospholipases A2 on cell-free prothrombinase complex

It has been suggested (Kini, R. R., and Evans, H. J. (1987) J. Biol. Chem. 262, 14402-14407) that the anticoagulant activity of members of the 14-kDa phospholipase A2 (PLA2) family depends on the presence of basic residues within a variable surface region (residues 54-77) distinct from both the conserved catalytic machinery and surface sites mediating the antibacterial action of these enzymes (see Weiss, J., Inada, M., Elsbach, P., and Crowl, R. M. (1994) J. Biol. Chem. 269, 26331-26337). To further define the determinants of the anticoagulant activity of PLA2, we have analyzed the inhibitory effects of purified native and recombinant PLA2 on cell-free prothrombinase. Both native and recombinant wild-type pig pancreas (net charge -1) and human "secretory" PLA2 (net charge +15) produced similar dose-dependent inhibition of prothrombinase activity that was significantly less potent than a toxic PLA2 purified from snake venom. Site-specific mutations that either increased or decreased PLA2 activity toward bactericidal/permeability-increasing protein-treated Escherichia coli by up to 50-fold had no effect on antiprothrombinase activity. In contrast, substitution of Arg for Asp-59/Gly for Ser-60 in the pig PLA2 increased antiprothrombinase activity by 5-10-fold without affecting catalytic activity toward a range of phospholipid substrates or antibacterial activity. Comparison of antiprothrombinase activity of catalytically active and inactive forms of the PLA2 and under a range of phospholipid conditions revealed that the potent antiprothrombinase activity of native toxic venom PLA2 and of the D59R.S60G mutant pancreatic PLA2 reflect combined catalytic and noncatalytic actions, the latter apparently dependent on basic residues at discrete surface sites in the enzyme.