An Improved Private Mechanism for Small Databases

We study the problem of answering a workload of linear queries $\mathcal{Q}$, on a database of size at most $n = o(|\mathcal{Q}|)$ drawn from a universe $\mathcal{U}$ under the constraint of (approximate) differential privacy. Nikolov, Talwar, and Zhang~\cite{NTZ} proposed an efficient mechanism that, for any given $\mathcal{Q}$ and $n$, answers the queries with average error that is at most a factor polynomial in $\log |\mathcal{Q}|$ and $\log |\mathcal{U}|$ worse than the best possible. Here we improve on this guarantee and give a mechanism whose competitiveness ratio is at most polynomial in $\log n$ and $\log |\mathcal{U}|$, and has no dependence on $|\mathcal{Q}|$. Our mechanism is based on the projection mechanism of Nikolov, Talwar, and Zhang, but in place of an ad-hoc noise distribution, we use a distribution which is in a sense optimal for the projection mechanism, and analyze it using convex duality and the restricted invertibility principle.Comment: To appear in ICALP 2015, Track

Analysis of genetic variation in different banana (Musa species) variety using random amplified polymorphic DNAs (RAPDs)

The banana (Musa acuminata Colla) is considered as an important crop plant due to its high economic value as good dietary source. Here, we analyze the genetic relationship of four different banana varieties that are cultivated in south India. Random amplified polymorphic DNAs (RAPDs) fingerprinting of these banana varieties (Grand Naine, Red Banana, Nendran and Rasthali) carried out by three primers (OPA-19, OPB-18, OPD-16) led to DNA amplification. 43.47% of the amplification products weremonomorphic (common to all the genotypes), whereas 30.43% were unique, but only 26.08% revealed the relationship between these genotypes

Utilizing Computational Complexity to Protect Cryptocurrency against Quantum Threats: A Review

Digital currency is primarily designed on problems that are computationally hard to solve using traditional computing techniques. However, these problems are now vulnerable due to the computational power of quantum computing. For the postquantum computing era, there is an immense need to reinvent the existing digital security measures. Problems that are computationally hard for any quantum computation will be a possible solution to that. This research summarizes the current security measures and how the new way of solving hard problems will trigger the future protection of the existing digital currency from the future quantum threat

Do children's expectations about future physical activity predict their physical activity in adulthood?

BACKGROUND: Much of the population fails to meet recommended physical activity (PA) levels, but there remains considerable individual variation. By understanding drivers of different trajectories, interventions can be better targeted and more effective. One such driver may be a person's physical activity identity (PAI)-the extent to which a person perceives PA as central to who they are. METHODS: Using survey information and a unique body of essays written at age 11 from the National Child Development Study (N = 10 500), essays mentioning PA were automatically identified using the machine learning technique support vector classification and PA trajectories were estimated using latent class analysis. Analyses tested the extent to which childhood PAI correlated with activity levels from age 23 through 55 and with trajectories across adulthood. RESULTS: 42.2% of males and 33.5% of females mentioned PA in their essays, describing active and/or passive engagement. Active PAI in childhood was correlated with higher levels of activity for men but not women, and was correlated with consistently active PA trajectories for both genders. Passive PAI was not related to PA for either gender. CONCLUSIONS: This study offers a novel approach for analysing large qualitative datasets to assess identity and behaviours. Findings suggest that at as young as 11 years old, the way a young person conceptualizes activity as part of their identity has a lasting association with behaviour. Still, an active identity may require a supportive sociocultural context to manifest in subsequent behaviour

Streaming Algorithms for Submodular Function Maximization

We consider the problem of maximizing a nonnegative submodular set function $f:2^{\mathcal{N}} \rightarrow \mathbb{R}^+$ subject to a $p$-matchoid constraint in the single-pass streaming setting. Previous work in this context has considered streaming algorithms for modular functions and monotone submodular functions. The main result is for submodular functions that are {\em non-monotone}. We describe deterministic and randomized algorithms that obtain a $\Omega(\frac{1}{p})$-approximation using $O(k \log k)$-space, where $k$ is an upper bound on the cardinality of the desired set. The model assumes value oracle access to $f$ and membership oracles for the matroids defining the $p$-matchoid constraint.Comment: 29 pages, 7 figures, extended abstract to appear in ICALP 201

A framework for automatic semantic video annotation

The rapidly increasing quantity of publicly available videos has driven research into developing automatic tools for indexing, rating, searching and retrieval. Textual semantic representations, such as tagging, labelling and annotation, are often important factors in the process of indexing any video, because of their user-friendly way of representing the semantics appropriate for search and retrieval. Ideally, this annotation should be inspired by the human cognitive way of perceiving and of describing videos. The difference between the low-level visual contents and the corresponding human perception is referred to as the ‘semantic gap’. Tackling this gap is even harder in the case of unconstrained videos, mainly due to the lack of any previous information about the analyzed video on the one hand, and the huge amount of generic knowledge required on the other. This paper introduces a framework for the Automatic Semantic Annotation of unconstrained videos. The proposed framework utilizes two non-domain-specific layers: low-level visual similarity matching, and an annotation analysis that employs commonsense knowledgebases. Commonsense ontology is created by incorporating multiple-structured semantic relationships. Experiments and black-box tests are carried out on standard video databases for action recognition and video information retrieval. White-box tests examine the performance of the individual intermediate layers of the framework, and the evaluation of the results and the statistical analysis show that integrating visual similarity matching with commonsense semantic relationships provides an effective approach to automated video annotation

Bone marrow transplantation in AML, and socioeconomic class: a UK population-based cohort study

<p>Abstract</p> <p>Background</p> <p>We have previously shown that in the UK mortality in people with Acute Myeloid Leukaemia (AML) was nearly 50% greater among the most socio-economically deprived. The aim of this study was to determine whether AML patients from lower socioeconomic classes had a lower chance of receiving a bone marrow transplant.</p> <p>Methods</p> <p>Using Hospital Episode Statistics (HES) data, we identified all incident cases of AML admitted to UK hospitals between 1998 and 2007. We calculated the number of bone marrow transplantations undertaken in AML patients, stratifying our results by gender, age at diagnosis, year of diagnosis, degree of socioeconomic deprivation and co-morbidity. We used logistic regression to calculate odds ratios for bone marrow transplantation, adjusting for gender, age at diagnosis, year of diagnosis, degree of socioeconomic deprivation and co-morbidity score.</p> <p>Results</p> <p>We identified a total of 23 910 incident cases of AML over this 10-year time period, of whom 1 140 (4.8%) underwent BMT. Bone marrow transplantation declined with increasing socioeconomic deprivation (p for trend < 0.001) such that people in the most deprived socioeconomic quintile were 40% less likely to have a transplant than those in the most advantaged group (Odds Ratio 0.60, 95% confidence interval 0.49, 0.73), even after adjusting for gender, age at diagnosis, year of diagnosis and co-morbidity.</p> <p>Conclusion</p> <p>This large cohort study demonstrates that AML patients from lower socioeconomic classes are less likely to undergo bone marrow transplantation than their better off counter-parts.</p

Membranous nephropathy in the UK Biobank

Background Despite MN being one of the most common causes of nephrotic syndrome worldwide, its biological and environmental determinants are poorly understood in large-part due to it being a rare disease. Making use of the UK Biobank, a unique resource holding a clinical dataset and stored DNA, serum and urine for ~500,000 participants, this study aims to address this gap in understanding. Methods The primary outcome was putative MN as defined by ICD-10 codes occurring in the UK Biobank. Univariate relative risk regression modelling was used to assess the associations between the incidence of MN and related phenotypes with sociodemographic, environmental exposures, and previously described increased-risk SNPs. Results 502,507 patients were included in the study of whom 100 were found to have a putative diagnosis of MN; 36 at baseline and 64 during the follow-up. Prevalence at baseline and last follow-up were 72 and 199 cases/million respectively. At baseline, as expected, the majority of those previously diagnosed with MN had proteinuria, and there was already evidence of proteinuria in patients diagnosed within the first 5 years of follow-up. The highest incidence rate for MN in patients was seen in those homozygous for the high-risk alleles (9.9/100,000 person-years). Conclusion It is feasible to putatively identify patients with MN in the UK Biobank and cases are still accumulating. This study shows the chronicity of disease with proteinuria present years before diagnosis. Genetics plays an important role in disease pathogenesis, with the at-risk group providing a potential population for recall

Adolescent gambling behaviour, a single latent construct and indicators of risk: findings from a national survey of New Zealand high school students

This study explores underlying latent construct/s of gambling behaviour, and identifies indicators of “unhealthy gambling”. Data were collected from Youth’07 a nationally representative sample of New Zealand secondary school students (N = 9107). Exploratory factor analyses, item-response theory analyses, multiple indicators-multiple causes, and differential item functioning analyses were used to assess dimensionality of gambling behaviour, underlying factors, and indicators of unhealthy gambling. A single underlying continuum of gambling behaviour was identified. Gambling frequency and ‘gambling because I can’t stop’ were most strongly associated with unhealthy gambling. Gambling to ‘feel better about myself’ and to ‘forget about things’ provided the most precise discriminants of unhealthy gambling. Multivariable analyses found that school connectedness was associated with lower levels of unhealthy gambling