Quantum noise in the electromechanical shuttle: Quantum master equation treatment

We consider a type of quantum electromechanical system, known as the shuttle system, first proposed by Gorelik [Phys. Rev. Lett. 80, 4526 (1998)]. We use a quantum master equation treatment and compare the semiclassical solution to a full quantum simulation to reveal the dynamics, followed by a discussion of the current noise of the system. The transition between tunneling and shuttling regime can be measured directly in the spectrum of the noise. (c) 2006 American Institute of Physics.

Comparison of cultures from rectoanal-junction mucosal swabs and feces for detection of Escherichia coli 0157 in dairy heifers

Fecal culture for Escherichia coli 0157:H7 was compared to rectoanal mucosal swab (RAMS) culture in dairy heifers over a 1-year period. RAMS enrichment culture was as sensitive as fecal culture using immunomagnetic separation (IMS) (P = 0.98, as determined by a chi-square test). RAMS culture is less costly than fecal IMS culture and can yield quantitative data.

Document re-ranking by generality in bio-medical information retrieval

Document ranking is an important process in information retrieval (IR). It presents retrieved documents in an order of their estimated degrees of relevance to query. Traditional document ranking methods are mostly based on the similarity computations between documents and query. In this paper we argue that the similarity-based document ranking is insufficient in some cases. There are two reasons. Firstly it is about the increased information variety. There are far too many different types documents available now for user to search. The second is about the users variety. In many cases user may want to retrieve documents that are not only similar but also general or broad regarding a certain topic. This is particularly the case in some domains such as bio-medical IR. In this paper we propose a novel approach to re-rank the retrieved documents by incorporating the similarity with their generality. By an ontology-based analysis on the semantic cohesion of text, document generality can be quantified. The retrieved documents are then re-ranked by their combined scores of similarity and the closeness of documents’ generality to the query’s. Our experiments have shown an encouraging performance on a large bio-medical document collection, OHSUMED, containing 348,566 medical journal references and 101 test queries.

A web recommendation technique based on probabilistic latent semantic analysis

Web transaction data between Web visitors and Web functionalities usually convey user task-oriented behavior pattern. Mining such type of click-stream data will lead to capture usage pattern information. Nowadays Web usage mining technique has become one of most widely used methods for Web recommendation, which customizes Web content to user-preferred style. Traditional techniques of Web usage mining, such as Web user session or Web page clustering, association rule and frequent navigational path mining can only discover usage pattern explicitly. They, however, cannot reveal the underlying navigational activities and identify the latent relationships that are associated with the patterns among Web users as well as Web pages. In this work, we propose a Web recommendation framework incorporating Web usage mining technique based on Probabilistic Latent Semantic Analysis (PLSA) model. The main advantages of this method are, not only to discover usage-based access pattern, but also to reveal the underlying latent factor as well. With the discovered user access pattern, we then present user more interested content via collaborative recommendation. To validate the effectiveness of proposed approach, we conduct experiments on real world datasets and make comparisons with some existing traditional techniques. The preliminary experimental results demonstrate the usability of the proposed approach.

Genomic and proteomic analysis of synaptic protein expression in the brains of human alcoholics

Alcoholism results in changes in the human brain which reinforce the cycle of craving and dependency, and these changes are manifest in the pattern of expression of mRNA and proteins in key cells and brain areas. Long-term alcohol abuse also results in damage to selected regions of the cortex. We have used cDNA microarrays to show that less than 1% of mRNA transcripts differ signifi cantly between cases and controls in the susceptible area and that the expression profi le of a subset of these transcripts is suffi cient to distinguish alcohol abusers from controls. In addition, we have utilized a 2D gel proteomics based approach to determine the identity of proteins in the superior frontal cortex (SFC) of the human brain that show differential expression in controls and long term alcohol abusers. Overall, 182 proteins differed by the criterion of > 2-fold between case and control samples. Of these, 139 showed signifi cantly lower expression in alcoholics, 35 showed signifi cantly higher expression, and 8 were new or had disappeared. To date 63 proteins have been identifi ed. The expression of one family of proteins, the synucleins, has been further characterized using Real Time PCR and Western Blotting. The expression of alpha-synuclein mRNA was signifi cantly lower in the SFC of alcoholics compared with the same area in controls (P = 0.01) whereas no such difference in expression was found in the motor cortex. The expression of beta- and gamma- synuclein were not signifi cantly different between alcoholics and controls. In contrast, the pattern of alphasynuclein protein expression differs from that of the corresponding RNA transcript. Because of the key role of synaptic proteins in the pathogenesis of alcoholism, we are developing 2-D DIGE based techniques to quantify expression changes in synaptosomes prepared from the SFC of controls and alcoholics.