Select, Link and Rank: Diversified Query Expansion and Entity Ranking using Wikipedia

A search query, being a very concise grounding of user intent, could potentially have many possible interpretations. Search engines hedge their bets by diversifying top results to cover multiple such possibilities so that the user is likely to be satisfied, whatever be her intended interpretation. Diversified Query Expansion is the problem of diversifying query expansion suggestions, so that the user can specialize the query to better suit her intent, even before perusing search results. We propose a method, Select-Link-Rank, that exploits semantic information from Wikipedia to generate diversified query expansions. SLR does collective processing of terms and Wikipedia entities in an integrated framework, simultaneously diversifying query expansions and entity recommendations. SLR starts with selecting informative terms from search results of the initial query, links them to Wikipedia entities, performs a diversity-conscious entity scoring and transfers such scoring to the term space to arrive at query expansion suggestions. Through an extensive empirical analysis and user study, we show that our method outperforms the state-of-the-art diversified query expansion and diversified entity recommendation techniques.

Energy efficiency analysis of rank-1 Ricean fading MIMO channels

This paper studies the energy efficiency (EE) of a point-to-point rank-1 Ricean fading multiple-input-multiple-output (MIMO) channel. In particular, a tight lower bound and an asymptotic approximation for the EE of the considered MIMO system are presented, under the assumption that the channel is unknown at the transmitter and perfectly known at the receiver. Moreover, the effects of different system parameters, namely, transmit power, spectral efficiency (SE), and number of transmit and receive antennas, on the EE are analytically investigated. An important observation is that, in the high signal-to-noise ratio regime and with the other system parameters fixed, the optimal transmit power that maximizes the EE increases as the Ricean-K factor increases. On the contrary, the optimal SE and the optimal number of transmit antennas decrease as K increases.

Enzyme-induced Aggregation of Plasmonic Nanoparticles for the Development of Label-free and Ultrasensitive Detection of Bacterial DNA

Sensitive detection of pathogens is critical to ensure the safety of food supplies and to prevent bacterial disease infection and outbreak at the first onset. While conventional techniques such as cell culture, ELISA, PCR, etc. have been used as the predominant detection workhorses, they are however limited by either time-consuming procedure, complicated sample pre-treatment, expensive analysis and operation, or inability to be implemented at point-of-care testing. Here, we present our recently developed assay exploiting enzyme-induced aggregation of plasmonic gold nanoparticles (AuNPs) for label-free and ultrasensitive detection of bacterial DNA. In the experiments, AuNPs are first functionalized with specific, single-stranded RNA probes so that they exhibit high stability in solution even under high electrolytic condition thus exhibiting red color. When bacterial DNA is present in a sample, a DNA-RNA heteroduplex will be formed and subsequently prone to the RNase H cleavage on the RNA probe, allowing the DNA to liberate and hybridize with another RNA strand. This continuously happens until all of the RNA strands are cleaved, leaving the nanoparticles ‘unprotected’. The addition of NaCl will cause the ‘unprotected’ nanoparticles to aggregate, initiating a colour change from red to blue. The reaction is performed in a multi-well plate format, and the distinct colour signal can be discriminated by naked eye or simple optical spectroscopy. As a result, bacterial DNA as low as pM could be unambiguously detected, suggesting that the enzyme-induced aggregation of AuNPs assay is very easy to perform and sensitive, it will significantly benefit to development of fast and ultrasensitive methods that can be used for disease detection and diagnosis.

Endonuclease Controlled Aggregation of Gold Nanoparticles for the Ultrasensitive Detection of Pathogenic Bacterial DNA

The development of an ultrasensitive biosensor for the low-cost and on-site detection of pathogenic DNA could transform detection capabilities within food safety, environmental monitoring and clinical diagnosis. Herein, we present an innovative approach exploiting endonuclease-controlled aggregation of plasmonic gold nanoparticles (AuNPs) for label-free and ultrasensitive detection of bacterial DNA. The method utilizes RNA-functionalized AuNPs which form DNA-RNA heteroduplex structures through specific hybridization with target DNA. Once formed, the DNA-RNA heteroduplex is susceptible to RNAse H enzymatic cleavage of the RNA probe, allowing the target DNA to liberate and hybridize with another RNA probe. This continuously happens until all of the RNA probes are cleaved, leaving the nanoparticles unprotected and thus aggregated upon exposure to a high electrolytic medium. The assay is ultrasensitive, allowing the detection of target DNA at femtomolar level by simple spectroscopic analysis (40.7 fM and 2.45 fM as measured by UV-vis and dynamic light scattering (DLS), respectively). The target DNA spiked food matrix (chicken meat) is also successfully detected at a concentration of 1.2 pM (by UV-vis) or 18.0 fM (by DLS). In addition to the ultra-high sensitivity, the total analysis time of the assay is less than 3 hours, thus demonstrating its practicality for food analysis.