Toward Malaria Risk Prediction in Afghanistan Using Remote Sensing

Malaria causes more than one million deaths every year worldwide, with most of the mortality in Sub-Saharan Africa. It is also a significant public health concern in Afghanistan, with approximately 60% of the population, or nearly 14 million people, living in a malaria-endemic area. Malaria transmission has been shown to be dependent on a number of environmental and meteorological variables. For countries in the tropics and the subtropics, rainfall is normally the most important variable, except for regions with high altitude where temperature may also be important. Afghanistan s diverse landscape contributes to the heterogeneous malaria distribution. Understanding the environmental effects on malaria transmission is essential to the effective control of malaria in Afghanistan. Provincial malaria data gathered by Health Posts in 23 provinces during 2004-2007 are used in this study. Remotely sensed geophysical parameters, including precipitation from TRMM, and surface temperature and vegetation index from MODIS are used to derive the empirical relationship between malaria cases and these geophysical parameters. Both neural network methods and regression analyses are used to examine the environmental dependency of malaria transmission. And the trained models are used for predicting future transmission. While neural network methods are intrinsically more adaptive for nonlinear relationship, the regression approach lends itself in providing statistical significance measures. Our results indicate that NDVI is the strongest predictor. This reflects the role of irrigation, instead of precipitation, in Afghanistan for agricultural production. The second strongest prediction is surface temperature. Precipitation is not shown as a significant predictor, contrary to other malarious countries in the tropics or subtropics. With the regression approach, the malaria time series are modelled well, with average R2 of 0.845. For cumulative 6-month prediction of malaria cases, the average provincial accuracy reaches 91%. The developed predictive and early warning capabilities support the Third Strategic Approach of the WHO EMRO Malaria Control and Elimination Plan

First observation of 54Zn and its decay by two-proton emission

The nucleus 54Zn has been observed for the first time in an experiment at the SISSI/LISE3 facility of GANIL in the quasi-fragmentation of a 58Ni beam at 74.5 MeV/nucleon in a natNi target. The fragments were analysed by means of the ALPHA-LISE3 separator and implanted in a silicon-strip detector where correlations in space and time between implantation and subsequent decay events allowed us to generate almost background free decay spectra for about 25 different nuclei at the same time. Eight 54Zn implantation events were observed. From the correlated decay events, the half-life of 54Zn is determined to be 3.2 +1.8/-0.8 ms. Seven of the eight implantations are followed by two-proton emission with a decay energy of 1.48(2) MeV. The decay energy and the partial half-life are compared to model predictions and allow for a test of these two-proton decay models.Comment: 4 pages, 4 figures, accepted for publication in PR

Beta-decay branching ratios of 62Ga

Beta-decay branching ratios of 62Ga have been measured at the IGISOL facility of the Accelerator Laboratory of the University of Jyvaskyla. 62Ga is one of the heavier Tz = 0, 0+ -> 0+ beta-emitting nuclides used to determine the vector coupling constant of the weak interaction and the Vud quark-mixing matrix element. For part of the experimental studies presented here, the JYFLTRAP facility has been employed to prepare isotopically pure beams of 62Ga. The branching ratio obtained, BR= 99.893(24)%, for the super-allowed branch is in agreement with previous measurements and allows to determine the ft value and the universal Ft value for the super-allowed beta decay of 62Ga

Q-value of the superallowed beta decay of Ga-62

Masses of the radioactive isotopes 62Ga, 62Zn and 62Cu have been measured at the JYFLTRAP facility with a relative precision of better than 18 ppb. A Q_EC value of (9181.07 +- 0.54) keV for the superallowed decay of 62Ga is obtained from the measured cyclotron frequency ratios of 62Ga-62Zn, 62Ga-62Ni and 62Zn-62Ni ions. The resulting Ft-value supports the validity of the conserved vector current hypothesis (CVC). The mass excess values measured were (-51986.5 +-1.0) keV for 62Ga, (-61167.9 +- 0.9) keV for 62Zn and (-62787.2 +- 0.9) keV for 62Cu.Comment: 12 pages, 3 figures, 2 tables, submitted to Phys. Lett. B. v2: added acknowledgement

Extended investigation of superdeformed bands in 151,152^{151,152}Tb nuclei

A detailed study of known and new SD bands in Tb isotopes has been performed with the use of the EUROBALL IV -ray array. The high-statistics data set has allowed for the extension of known SD bands at low and high spins by new -ray transitions. These transitions, as it turns out, correspond to the rotational frequencies where the principal superdeformed gaps (Z=66,N=86) close giving rise to up- or down-bending mechanisms. This enables to attribute the underlying theoretical configurations with much higher confidence as compared to the previous identifications. Five new SD bands have been discovered, three of them assigned to the 152Tb and the two others to the 151Tb nuclei. Nuclear mean-field calculations have been used to interpret the structure of known SD bands as well as of the new ones in terms of nucleonic configurations

Nutrition and lung cancer: a case control study in Iran

Background: Despite many prospective and retrospective studies about the association of dietary habit and lung cancer, the topic still remains controversial. So, this study aims to investigate the association of lung cancer with dietary factors. Method: In this study 242 lung cancer patients and their 484 matched controls on age, sex, and place of residence were enrolled between October 2002 to 2005. Trained physicians interviewed all participants with standardized questionnaires. The middle and upper third consumer groups were compared to the lower third according to the distribution in controls unless the linear trend was significant across exposure groups. Result: Conditional logistic regression was used to evaluate the association with lung cancer. In a multivariate analysis fruit (Ptrend < 0.0001), vegetable (P = 0.001) and sunflower oil (P = 0.006) remained as protective factors and rice (P = 0.008), bread (Ptrend = 0.04), liver (P = 0.004), butter (Ptrend = 0.04), white cheese (Ptrend < 0.0001), beef (Ptrend = 0.005), vegetable ghee (P < 0.0001) and, animal ghee (P = 0.015) remained as risk factors of lung cancer. Generally, we found positive trend between consumption of beef (P = 0.002), bread (P < 0.0001), and dairy products (P < 0.0001) with lung cancer. In contrast, only fruits were inversely related to lung cancer (P < 0.0001). Conclusion: It seems that vegetables, fruits, and sunflower oil could be protective factors and bread, rice, beef, liver, dairy products, vegetable ghee, and animal ghee found to be possible risk factors for the development of lung cancer in Iran

Spatial distribution estimation of malaria in northern China and its scenarios in 2020, 2030, 2040 and 2050

© 2016 The Author(s). Background: Malaria is one of the most severe parasitic diseases in the world. Spatial distribution estimation of malaria and its future scenarios are important issues for malaria control and elimination. Furthermore, sophisticated nonlinear relationships for prediction between malaria incidence and potential variables have not been well constructed in previous research. This study aims to estimate these nonlinear relationships and predict future malaria scenarios in northern China. Methods: Nonlinear relationships between malaria incidence and predictor variables were constructed using a genetic programming (GP) method, to predict the spatial distributions of malaria under climate change scenarios. For this, the examples of monthly average malaria incidence were used in each county of northern China from 2004 to 2010. Among the five variables at county level, precipitation rate and temperature are used for projections, while elevation, water density index, and gross domestic product are held at their present-day values. Results: Average malaria incidence was 0.107 per annum in northern China, with incidence characteristics in significant spatial clustering. A GP-based model fit the relationships with average relative error (ARE) = 8.127 % for training data (R2 = 0.825) and 17.102 % for test data (R2 = 0.532). The fitness of GP results are significantly improved compared with those by generalized additive models (GAM) and linear regressions. With the future precipitation rate and temperature conditions in Special Report on Emission Scenarios (SRES) family B1, A1B and A2 scenarios, spatial distributions and changes in malaria incidences in 2020, 2030, 2040 and 2050 were predicted and mapped. Conclusions: The GP method increases the precision of predicting the spatial distribution of malaria incidence. With the assumption of varied precipitation rate and temperature, and other variables controlled, the relationships between incidence and the varied variables appear sophisticated nonlinearity and spatially differentiation. Using the future fluctuated precipitation and the increased temperature, median malaria incidence in 2020, 2030, 2040 and 2050 would significantly increase that it might increase 19 to 29 % in 2020, but currently China is in the malaria elimination phase, indicating that the effective strategies and actions had been taken. While the mean incidences will not increase even reduce due to the incidence reduction in high-risk regions but the simultaneous expansion of the high-risk areas