A framework for space-efficient string kernels

String kernels are typically used to compare genome-scale sequences whose length makes alignment impractical, yet their computation is based on data structures that are either space-inefficient, or incur large slowdowns. We show that a number of exact string kernels, like the $k$-mer kernel, the substrings kernels, a number of length-weighted kernels, the minimal absent words kernel, and kernels with Markovian corrections, can all be computed in $O(nd)$ time and in $o(n)$ bits of space in addition to the input, using just a $\mathtt{rangeDistinct}$ data structure on the Burrows-Wheeler transform of the input strings, which takes $O(d)$ time per element in its output. The same bounds hold for a number of measures of compositional complexity based on multiple value of $k$, like the $k$-mer profile and the $k$-th order empirical entropy, and for calibrating the value of $k$ using the data

Practical private database queries based on a quantum key distribution protocol

Private queries allow a user Alice to learn an element of a database held by a provider Bob without revealing which element she was interested in, while limiting her information about the other elements. We propose to implement private queries based on a quantum key distribution protocol, with changes only in the classical post-processing of the key. This approach makes our scheme both easy to implement and loss-tolerant. While unconditionally secure private queries are known to be impossible, we argue that an interesting degree of security can be achieved, relying on fundamental physical principles instead of unverifiable security assumptions in order to protect both user and database. We think that there is scope for such practical private queries to become another remarkable application of quantum information in the footsteps of quantum key distribution.Comment: 7 pages, 2 figures, new and improved version, clarified claims, expanded security discussio

UVB radiation induced effects on cells studied by FTIR spectroscopy

We have made a preliminary analysis of the results about the eVects on tumoral cell line (lymphoid T cell line Jurkat) induced by UVB radiation (dose of 310 mJ/cm^2) with and without a vegetable mixture. In the present study, we have used two techniques: Fourier transform infrared spectroscopy (FTIR) and flow cytometry. FTIR spectroscopy has the potential to provide the identiWcation of the vibrational modes of some of the major compounds (lipid, proteins and nucleic acids) without being invasive in the biomaterials. The second technique has allowed us to perform measurements of cytotoxicity and to assess the percentage of apoptosis. We already studied the induction of apoptotic process in the same cell line by UVB radiation; in particular, we looked for correspondences and correlations between FTIR spetroscopy and flow cytometry data finding three highly probable spectroscopic markers of apoptosis (Pozzi et al. in Radiat Res 168:698-705, 2007). In the present work, the results have shown significant changes in the absorbance and spectral pattern in the wavenumber protein and nucleic acids regions after the treatments

Postprocessing for quantum random number generators: entropy evaluation and randomness extraction

Quantum random-number generators (QRNGs) can offer a means to generate information-theoretically provable random numbers, in principle. In practice, unfortunately, the quantum randomness is inevitably mixed with classical randomness due to classical noises. To distill this quantum randomness, one needs to quantify the randomness of the source and apply a randomness extractor. Here, we propose a generic framework for evaluating quantum randomness of real-life QRNGs by min-entropy, and apply it to two different existing quantum random-number systems in the literature. Moreover, we provide a guideline of QRNG data postprocessing for which we implement two information-theoretically provable randomness extractors: Toeplitz-hashing extractor and Trevisan's extractor.Comment: 13 pages, 2 figure

Order-Revealing Encryption and the Hardness of Private Learning

An order-revealing encryption scheme gives a public procedure by which two ciphertexts can be compared to reveal the ordering of their underlying plaintexts. We show how to use order-revealing encryption to separate computationally efficient PAC learning from efficient $(\epsilon, \delta)$-differentially private PAC learning. That is, we construct a concept class that is efficiently PAC learnable, but for which every efficient learner fails to be differentially private. This answers a question of Kasiviswanathan et al. (FOCS '08, SIAM J. Comput. '11). To prove our result, we give a generic transformation from an order-revealing encryption scheme into one with strongly correct comparison, which enables the consistent comparison of ciphertexts that are not obtained as the valid encryption of any message. We believe this construction may be of independent interest.Comment: 28 page

Determinants of adults' intention to vaccinate against pandemic swine flu

This article has been made available through the Brunel Open Access Publishing Fund.This article has been made available through the Brunel Open Access Publishing Fund.Background: Vaccination is one of the cornerstones of controlling an influenza pandemic. To optimise vaccination rates in the general population, ways of identifying determinants that influence decisions to have or not to have a vaccination need to be understood. Therefore, this study aimed to predict intention to have a swine influenza vaccination in an adult population in the UK. An extension of the Theory of Planned Behaviour provided the theoretical framework for the study. Methods: Three hundred and sixty two adults from the UK, who were not in vaccination priority groups, completed either an online (n = 306) or pen and paper (n = 56) questionnaire. Data were collected from 30th October 2009, just after swine flu vaccination became available in the UK, and concluded on 31st December 2009. The main outcome of interest was future swine flu vaccination intentions. Results: The extended Theory of Planned Behaviour predicted 60% of adults’ intention to have a swine flu vaccination with attitude, subjective norm, perceived control, anticipating feelings of regret (the impact of missing a vaccination opportunity), intention to have a seasonal vaccine this year, one perceived barrier: “I cannot be bothered to get a swine flu vaccination” and two perceived benefits: “vaccination decreases my chance of getting swine flu or its complications” and “if I get vaccinated for swine flu, I will decrease the frequency of having to consult my doctor,” being significant predictors of intention. Black British were less likely to intend to have a vaccination compared to Asian or White respondents. Conclusions: Theoretical frameworks which identify determinants that influence decisions to have a pandemic influenza vaccination are useful. The implications of this research are discussed with a view to maximising any future pandemic influenza vaccination uptake using theoretically-driven applications.This article is available through the Brunel Open Access Publishing Fund

RGS2 expression predicts amyloid-β sensitivity, MCI and Alzheimer's disease: genome-wide transcriptomic profiling and bioinformatics data mining

Alzheimer's disease (AD) is the most frequent cause of dementia. Misfolded protein pathological hallmarks of AD are brain deposits of amyloid-β (Aβ) plaques and phosphorylated tau neurofibrillary tangles. However, doubts about the role of Aβ in AD pathology have been raised as Aβ is a common component of extracellular brain deposits found, also by in vivo imaging, in non-demented aged individuals. It has been suggested that some individuals are more prone to Aβ neurotoxicity and hence more likely to develop AD when aging brains start accumulating Aβ plaques. Here, we applied genome-wide transcriptomic profiling of lymphoblastoid cells lines (LCLs) from healthy individuals and AD patients for identifying genes that predict sensitivity to Aβ. Real-time PCR validation identified 3.78-fold lower expression of RGS2 (regulator of G-protein signaling 2; P=0.0085) in LCLs from healthy individuals exhibiting high vs low Aβ sensitivity. Furthermore, RGS2 showed 3.3-fold lower expression (P=0.0008) in AD LCLs compared with controls. Notably, RGS2 expression in AD LCLs correlated with the patients' cognitive function. Lower RGS2 expression levels were also discovered in published expression data sets from postmortem AD brain tissues as well as in mild cognitive impairment and AD blood samples compared with controls. In conclusion, Aβ sensitivity phenotyping followed by transcriptomic profiling and published patient data mining identified reduced peripheral and brain expression levels of RGS2, a key regulator of G-protein-coupled receptor signaling and neuronal plasticity. RGS2 is suggested as a novel AD biomarker (alongside other genes) toward early AD detection and future disease modifying therapeutics

A Formal Study of the Privacy Concerns in Biometric-Based Remote Authentication Schemes

With their increasing popularity in cryptosystems, biometrics have attracted more and more attention from the information security community. However, how to handle the relevant privacy concerns remains to be troublesome. In this paper, we propose a novel security model to formalize the privacy concerns in biometric-based remote authentication schemes. Our security model covers a number of practical privacy concerns such as identity privacy and transaction anonymity, which have not been formally considered in the literature. In addition, we propose a general biometric-based remote authentication scheme and prove its security in our security model

Securing computation against continuous leakage

30th Annual Cryptology Conference, Santa Barbara, CA, USA, August 15-19, 2010. ProceedingsWe present a general method to compile any cryptographic algorithm into one which resists side channel attacks of the only computation leaks information variety for an unbounded number of executions. Our method uses as a building block a semantically secure subsidiary bit encryption scheme with the following additional operations: key refreshing, oblivious generation of cipher texts, leakage resilience re-generation, and blinded homomorphic evaluation of one single complete gate (e.g. NAND). Furthermore, the security properties of the subsidiary encryption scheme should withstand bounded leakage incurred while performing each of the above operations. We show how to implement such a subsidiary encryption scheme under the DDH intractability assumption and the existence of a simple secure hardware component. The hardware component is independent of the encryption scheme secret key. The subsidiary encryption scheme resists leakage attacks where the leakage is computable in polynomial time and of length bounded by a constant fraction of the security parameter.Israel Science Foundation (710267)United States-Israel Binational Science Foundation (710613)National Science Foundation (U.S.) (6914349)Weizmann KAMAR Gran