1,246 research outputs found

    Availability, healthiness, and price of packaged and unpackaged foods in India: A cross-sectional study

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    Background: Vulnerable populations are the most prone to diet-related disease. The availability, healthiness, and price of foods have established associations with diet-related disease in communities. However, data describing this in India are sparse, particularly in urban slums and rural areas. Aim: To quantify and compare availability, healthiness, and price of packaged and unpackaged foods and beverages in India, and to identify opportunities to improve diets and health of vulnerable populations. Methods: Nutrition data and price were collected on foods and beverages available at 44 stores in urban, urban slum, and rural areas in four states in India between May and August 2018. Healthiness was assessed using the Australasian Health Star Rating system and product retail prices were examined. Comparisons in the findings were made across state, community area type, and adherence to current and draft Indian food labeling regulations. Results: Packaged foods and beverages (n = 1443, 89%) were more prevalent than unpackaged (n = 172, 11%). Unpackaged products were healthier than packaged (mean Health Star Rating = 3.5 vs 2.0; p < 0.001) and lower in price (median price per 100 g/ml: 13.42 Indian rupees vs 25.70 Indian rupees; p < 0.001), a pattern observed across most community area types and states. 96% of packaged products were compliant with current Indian labeling regulations but only 23% were compliant with proposed labeling regulations. Conclusions: Unpackaged products were on average much healthier and lower in price than packaged foods and beverages. Food policies that support greater availability, accessibility and consumption of unpackaged foods, while limiting consumption of packaged foods, have enormous potential for sustaining the health of the Indian population

    Probabilistic Clustering of Time-Evolving Distance Data

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    We present a novel probabilistic clustering model for objects that are represented via pairwise distances and observed at different time points. The proposed method utilizes the information given by adjacent time points to find the underlying cluster structure and obtain a smooth cluster evolution. This approach allows the number of objects and clusters to differ at every time point, and no identification on the identities of the objects is needed. Further, the model does not require the number of clusters being specified in advance -- they are instead determined automatically using a Dirichlet process prior. We validate our model on synthetic data showing that the proposed method is more accurate than state-of-the-art clustering methods. Finally, we use our dynamic clustering model to analyze and illustrate the evolution of brain cancer patients over time

    Mean population salt consumption in India: a systematic review

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    Background: Member states of the WHO, including India, have adopted a target 30% reduction in mean population salt consumption by 2025 to prevent noncommunicable diseases. Our aim was to support this initiative by summarizing existing data that describe mean salt consumption in India. Method: Electronic databases – MEDLINE via Ovid, EMBASE, CINAHL and the Cochrane Database of Systematic Reviews – were searched up to November 2015 for studies that reported mean or median dietary salt intake in Indian adults aged 19 years and older. Random effects meta-analysis was used to obtain summary estimates of salt intake. Results: Of 1201 abstracts identified, 90 were reviewed in full text and 21 were included: 18 cross-sectional surveys (n = 225 024), two randomized trials (n = 255) and one case–control study (n = 270). Data were collected between 1986 and 2014, and reported mean salt consumption levels were between 5.22 and 42.30 g/day. With an extreme outlier excluded, overall mean weighted salt intake was 10.98 g/day (95% confidence interval 8.57–13.40). There was significant heterogeneity between the estimates for contributing studies (I2 = 99.97%) (P homogeneity ≤0.001), which was likely attributable to the different measurement methods used and the different populations studied. There was no evidence of a change in intake over time (P trend = 0.08). Conclusion: The available data leave some uncertainty about exact mean salt consumption in India but there is little doubt that population salt consumption far exceeds the WHO-recommended maximum of 5 g per person per day

    A Secure Semi-Field System for the Study of Aedes aegypti

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    Novel vector control strategies require validation in the field before they can be widely accepted. Semi-field system (SFS) containment facilities are an intermediate step between laboratory and field trials that offer a safe, controlled environment that replicates field conditions. We developed a SFS laboratory and cage complex that simulates an urban house and yard, which is the primary habitat for Aedes aegypti, the mosquito vector of dengue in Cairns Australia. The SFS consists of a Quarantine Insectary Level-2 (QIC-2) laboratory, containing 3 constant temperature rooms, that is connected to two QIS-2 cages for housing released mosquitoes. Each cage contains the understory of a “Queenslander” timber house and associated yard. An automated air conditioning system keeps temperature and humidity to within 1°C and 5% RH of ambient conditions, respectively. Survival of released A. aegypti was high, especially for females. We are currently using the SFS to investigate the invasion of strains of Wolbachia within populations of A. aegypti

    A search for the decay modes B+/- to h+/- tau l

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    We present a search for the lepton flavor violating decay modes B+/- to h+/- tau l (h= K,pi; l= e,mu) using the BaBar data sample, which corresponds to 472 million BBbar pairs. The search uses events where one B meson is fully reconstructed in one of several hadronic final states. Using the momenta of the reconstructed B, h, and l candidates, we are able to fully determine the tau four-momentum. The resulting tau candidate mass is our main discriminant against combinatorial background. We see no evidence for B+/- to h+/- tau l decays and set a 90% confidence level upper limit on each branching fraction at the level of a few times 10^-5.Comment: 15 pages, 7 figures, submitted to Phys. Rev.

    Observation and study of baryonic B decays: B -> D(*) p pbar, D(*) p pbar pi, and D(*) p pbar pi pi

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    We present a study of ten B-meson decays to a D(*), a proton-antiproton pair, and a system of up to two pions using BaBar's data set of 455x10^6 BBbar pairs. Four of the modes (B0bar -> D0 p anti-p, B0bar -> D*0 p anti-p, B0bar -> D+ p anti-p pi-, B0bar -> D*+ p anti-p pi-) are studied with improved statistics compared to previous measurements; six of the modes (B- -> D0 p anti-p pi-, B- -> D*0 p anti-p pi-, B0bar -> D0 p anti-p pi- pi+, B0bar -> D*0 p anti-p pi- pi+, B- -> D+ p anti-p pi- pi-, B- -> D*+ p anti-p pi- pi-) are first observations. The branching fractions for 3- and 5-body decays are suppressed compared to 4-body decays. Kinematic distributions for 3-body decays show non-overlapping threshold enhancements in m(p anti-p) and m(D(*)0 p) in the Dalitz plots. For 4-body decays, m(p pi-) mass projections show a narrow peak with mass and full width of (1497.4 +- 3.0 +- 0.9) MeV/c2, and (47 +- 12 +- 4) MeV/c2, respectively, where the first (second) errors are statistical (systematic). For 5-body decays, mass projections are similar to phase space expectations. All results are preliminary.Comment: 28 pages, 90 postscript figures, submitted to LP0

    Evidence for an excess of B -> D(*) Tau Nu decays

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    Based on the full BaBar data sample, we report improved measurements of the ratios R(D(*)) = B(B -> D(*) Tau Nu)/B(B -> D(*) l Nu), where l is either e or mu. These ratios are sensitive to new physics contributions in the form of a charged Higgs boson. We measure R(D) = 0.440 +- 0.058 +- 0.042 and R(D*) = 0.332 +- 0.024 +- 0.018, which exceed the Standard Model expectations by 2.0 sigma and 2.7 sigma, respectively. Taken together, our results disagree with these expectations at the 3.4 sigma level. This excess cannot be explained by a charged Higgs boson in the type II two-Higgs-doublet model. We also report the observation of the decay B -> D Tau Nu, with a significance of 6.8 sigma.Comment: Expanded section on systematics, text corrections, improved the format of Figure 2 and included the effect of the change of the Tau polarization due to the charged Higg

    Search for the decay modes D^0 → e^+e^-, D^0 → μ^+μ^-, and D^0 → e^±μ∓

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    We present searches for the rare decay modes D^0→e^+e^-, D^0→μ^+μ^-, and D^0→e^±μ^∓ in continuum e^+e^-→cc events recorded by the BABAR detector in a data sample that corresponds to an integrated luminosity of 468  fb^(-1). These decays are highly Glashow–Iliopoulos–Maiani suppressed but may be enhanced in several extensions of the standard model. Our observed event yields are consistent with the expected backgrounds. An excess is seen in the D^0→μ^+μ^- channel, although the observed yield is consistent with an upward background fluctuation at the 5% level. Using the Feldman–Cousins method, we set the following 90% confidence level intervals on the branching fractions: B(D^0→e^+e^-)<1.7×10^(-7), B(D^0→μ^+μ^-) within [0.6,8.1]×10^(-7), and B(D^0→e^±μ^∓)<3.3×10^(-7)

    Probabilistic machine learning and artificial intelligence.

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    How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.The author acknowledges an EPSRC grant EP/I036575/1, the DARPA PPAML programme, a Google Focused Research Award for the Automatic Statistician and support from Microsoft Research.This is the author accepted manuscript. The final version is available from NPG at http://www.nature.com/nature/journal/v521/n7553/full/nature14541.html#abstract
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