A New Approach to Query Segmentation for Relevance Ranking in Web Search

Abstract In this paper, we try to determine how best to improve state-ofthe-art methods for relevance ranking in web searching by query segmentation. Query segmentation is meant to separate the input query into segments, typically natural language phrases. We propose employing the re-ranking approach in query segmentation, which first employs a generative model to create the top k candidates and then employs a discriminative model to re-rank the candidates to obtain the final segmentation result. The method has been widely utilized for structure prediction in natural language processing, but has not been applied to query segmentation, as far as we know. Furthermore, we propose a new method for using the results of query segmentation in relevance ranking, which takes both the original query words and the segmented query phrases as units of query representation. We investigate whether our method can improve three relevance models, namely n-gram BM25, key n-gram model and term dependency model, within the framework of learning to rank. Our experimental results on large scale web search datasets show that our method can indeed significantly improve relevance ranking in all three cases

Spin-dependent thermoelectric transport through double quantum dots

We study thermoelectric transport through double quantum dots system with spin-dependent interdot coupling and ferromagnetic electrodes by means of the non-equilibrium Green function in the linear response regime. It is found that the thermoelectric coefficients are strongly dependent on the splitting of interdot coupling, the relative magnetic configurations and the spin polarization of leads. In particular, the thermoelectric efficiency can achieve considerable value in parallel configuration when the effective interdot coupling and tunnel coupling between QDs and the leads for spin-down electrons are small. Moreover, the thermoelectric efficiency increases with the intradot Coulomb interactions increasing and can reach very high value at an appropriate temperature. In the presence of the magnetic field, the spin accumulation in leads strongly suppresses the thermoelectric efficiency and a pure spin thermopower can be obtained.Comment: 5 figure

CGMP: cloud-assisted green multimedia processing

With continued advancements of mobile computing and communications, emerging novel multimedia services and applications have attracted lots of attention and been developed for mobile users, such as mobile social network, mobile cloud medical treatment, mobile cloud game. However, because of limited resources on mobile terminals, it is of great challenge to improve the energy efficiency of multimedia services. In this paper, we propose a cloud-assisted green multimedia processing architecture (CGMP) based on mobile cloud computing. Specifically, the tasks of multimedia processing with energy-extensive consumption can be offloaded to the cloud, and the face recognition algorithm with improved principal component analysis and nearest neighbor classifier is realized on CGMP based cloud platform. Experimental results show that the proposed scheme can effectively save the energy consumption of the equipment

Rad9 plays an important role in DNA mismatch repair through physical interaction with MLH1

Rad9 is conserved from yeast to humans and plays roles in DNA repair (homologous recombination repair, and base-pair excision repair) and cell cycle checkpoint controls. It has not previously been reported whether Rad9 is involved in DNA mismatch repair (MMR). In this study, we have demonstrated that both human and mouse Rad9 interacts physically with the MMR protein MLH1. Disruption of the interaction by a single-point mutation in Rad9 leads to significantly reduced MMR activity. This disruption does not affect S/M checkpoint control and the first round of G2/M checkpoint control, nor does it alter cell sensitivity to UV light, gamma rays or hydroxyurea. Our data indicate that Rad9 is an important factor in MMR and carries out its MMR function specifically through interaction with MLH1

Live-cell imaging of alkyne-tagged small biomolecules by stimulated Raman scattering

Sensitive and specific visualization of small biomolecules in living systems is highly challenging. We report stimulated Raman-scattering imaging of alkyne tags as a general strategy for studying a broad spectrum of small biomolecules in live cells and animals. We demonstrate this technique by tracking alkyne-bearing drugs in mouse tissues and visualizing de novo synthesis of DNA, RNA, proteins, phospholipids and triglycerides through metabolic incorporation of alkyne-tagged small precursors

Primary tumor site specificity is preserved in patient-derived tumor xenograft models

Patient-derived tumor xenograft (PDX) mouse models are widely used for drug screening. The underlying assumption is that PDX tissue is very similar with the original patient tissue, and it has the same response to the drug treatment. To investigate whether the primary tumor site information is well preserved in PDX, we analyzed the gene expression profiles of PDX mouse models originated from different tissues, including breast, kidney, large intestine, lung, ovary, pancreas, skin, and soft tissues. The popular Monte Carlo feature selection method was employed to analyze the expression profile, yielding a feature list. From this list, incremental feature selection and support vector machine (SVM) were adopted to extract distinctively expressed genes in PDXs from different primary tumor sites and build an optimal SVM classifier. In addition, we also set up a group of quantitative rules to identify primary tumor sites. A total of 755 genes were extracted by the feature selection procedures, on which the SVM classifier can provide a high performance with MCC 0.986 on classifying primary tumor sites originated from different tissues. Furthermore, we obtained 16 classification rules, which gave a lower accuracy but clear classification procedures. Such results validated that the primary tumor site specificity was well preserved in PDX as the PDXs from different primary tumor sites were still very different and these PDX differences were similar with the differences observed in patients with tumor. For example, VIM and ABHD17C were highly expressed in the PDX from breast tissue and also highly expressed in breast cancer patients

Homogenization Pressure and Temperature Affect Protein Partitioning and Oxidative Stability of Emulsions

The oxidative stability of 10 % fish oil-in-water emulsions was investigated for emulsions prepared under different homogenization conditions. Homogenization was conducted at two different pressures (5 or 22.5 MPa), and at two different temperatures (22 and 72 °C). Milk proteins were used as the emulsifier. Hence, emulsions were prepared with either a combination of α-lactalbumin and β-lactoglobulin or with a combination of sodium caseinate and β-lactoglobulin. Results showed that an increase in pressure increased the oxidative stability of emulsions with caseinate and β-lactoglobulin, whereas it decreased the oxidative stability of emulsions with α-lactalbumin and β-lactoglobulin. For both types of emulsions the partitioning of proteins between the interface and the aqueous phase appeared to be important for the oxidative stability. The effect of pre-heating the aqueous phase with the milk proteins prior to homogenization did not have any clear effect on lipid oxidation in either of the two types of emulsions. (Résumé d'auteur