A Personalised Ranking Framework with Multiple Sampling Criteria for Venue Recommendation

Recommending a ranked list of interesting venues to users based on their preferences has become a key functionality in Location-Based Social Networks (LBSNs) such as Yelp and Gowalla. Bayesian Personalised Ranking (BPR) is a popular pairwise recommendation technique that is used to generate the ranked list of venues of interest to a user, by leveraging the user's implicit feedback such as their check-ins as instances of positive feedback, while randomly sampling other venues as negative instances. To alleviate the sparsity that affects the usefulness of recommendations by BPR for users with few check-ins, various approaches have been proposed in the literature to incorporate additional sources of information such as the social links between users, the textual content of comments, as well as the geographical location of the venues. However, such approaches can only readily leverage one source of additional information for negative sampling. Instead, we propose a novel Personalised Ranking Framework with Multiple sampling Criteria (PRFMC) that leverages both geographical influence and social correlation to enhance the effectiveness of BPR. In particular, we apply a multi-centre Gaussian model and a power-law distribution method, to capture geographical influence and social correlation when sampling negative venues, respectively. Finally, we conduct comprehensive experiments using three large-scale datasets from the Yelp, Gowalla and Brightkite LBSNs. The experimental results demonstrate the effectiveness of fusing both geographical influence and social correlation in our proposed PRFMC framework and its superiority in comparison to BPR-based and other similar ranking approaches. Indeed, our PRFMC approach attains a 37% improvement in MRR over a recently proposed approach that identifies negative venues only from social links

Microgravimetric immunosensor for direct detection of aerosolized influenza A virus particles.

The development and characterization of a quartz crystal microbalance (QCM) sensor for the direct detection of aerosolized influenza A virions is reported. Self-assembled monolayers (SAMs) of mercaptoundecanoic acid (MUA) are formed on QCM gold electrodes to provide a surface amenable for the immobilization of anti-influenza A antibodies using NHS/EDC coupling chemistry. The surface-bound antibody provides a selective and specific sensing interface for the capture of influenza virions. A nebulizer is used to create aerosolized samples and is directly connected to a chamber housing the antibody-modified crystal ("immunochip"). Upon exposure to the aerosolized virus, the interaction between the antibody and virus leads to a dampening of the oscillation frequency of the quartz crystal. The magnitude of frequency change is directly related to virus concentration. Control experiments using aerosols from chicken egg allantoic fluid and an anti-murine antibody based immunosensor confirm that the observed signal originates from specific viral binding on the chip surface. Step-by-step surface modification of MUA assembly, antibody attachment, and antibody-virus interaction are characterized by atomic force microscopy (AFM) imaging analysis. Using the S/N = 3 principle, the limit of detection is estimated to be 4 virus particles/mL. The high sensitivity and real-time sensing scheme presented here can play an important role in the public health arena by offering a new analytical tool for identifying bio-contaminated areas and assisting in timely patient diagnosis

The Effect of Plant Water Storage on Water Fluxes within the Coupled Soil–Plant System

In addition to buffering plants from water stress during severe droughts, plant water storage (PWS) alters many features of the spatio-temporal dynamics of water movement in the soil–plant system. How PWS impacts water dynamics and drought resilience is explored using a multi-layer porous media model

A cross-sectional study of predatory publishing emails received by career development grant awardees

OBJECTIVE: To investigate the scope of academic spam emails (ASEs) among career development grant awardees and the factors associated with the amount of time spent addressing them. DESIGN: A cross-sectional survey of career development grant investigators via an anonymous online survey was conducted. In addition to demographic and professional information, we asked investigators to report the number of ASEs received each day, how they determined whether these emails were spam and time they spent per day addressing them. We used bivariate analysis to assess factors associated with the amount of time spent on ASEs. SETTING: An online survey sent via email on three separate occasions between November and December 2016. PARTICIPANTS: All National Institutes of Health career development awardees funded in the 2015 fiscal year. MAIN OUTCOME MEASURES: Factors associated with the amount of time spent addressing ASEs. RESULTS: A total of 3492 surveys were emailed, of which 206 (5.9%) were returned as undeliverable and 96 (2.7%) reported an out-of-office message; our overall response rate was 22.3% (n=733). All respondents reported receiving ASEs, with the majority (54.4%) receiving between 1 and 10 per day and spending between 1 and 10 min each day evaluating them. The amount of time respondents reported spending on ASEs was associated with the number of peer-reviewed journal articles authored (p<0.001), a history of publishing in open access format (p<0.01), the total number of ASEs received (p<0.001) and a feeling of having missed opportunities due to ignoring these emails (p=0.04). CONCLUSIONS: ASEs are a common distraction for career development grantees that may impact faculty productivity. There is an urgent need to mitigate this growing problem

MINRES-QLP: a Krylov subspace method for indefinite or singular symmetric systems

CG, SYMMLQ, and MINRES are Krylov subspace methods for solving symmetric systems of linear equations. When these methods are applied to an incompatible system (that is, a singular symmetric least-squares problem), CG could break down and SYMMLQ's solution could explode, while MINRES would give a least-squares solution but not necessarily the minimum-length (pseudoinverse) solution. This understanding motivates us to design a MINRES-like algorithm to compute minimum-length solutions to singular symmetric systems. MINRES uses QR factors of the tridiagonal matrix from the Lanczos process (where R is upper-tridiagonal). MINRES-QLP uses a QLP decomposition (where rotations on the right reduce R to lower-tridiagonal form). On ill-conditioned systems (singular or not), MINRES-QLP can give more accurate solutions than MINRES. We derive preconditioned MINRES-QLP, new stopping rules, and better estimates of the solution and residual norms, the matrix norm, and the condition number.Comment: 26 pages, 6 figure

Nondiffusive spin dynamics in a two-dimensional electron gas

We describe measurements of spin dynamics in the two-dimensional electron gas in GaAs=GaAlAs quantum wells. Optical techniques, including transient spin-grating spectroscopy, are used to probe the relaxation rates of spin polarization waves in the wave vector range from zero to 6 x 104 cm-1. We find that the spin polarization lifetime is maximal at a nonzero wave vector, in contrast with expectations based on ordinary spin diffusion, but in quantitative agreement with recent theories that treat diffusion in the presence of spin-orbit couplin