Distributed learning on 20 000+ lung cancer patients - The Personal Health Train.

Background And Purpose: Access to healthcare data is indispensable for scientific progress and innovation. Sharing healthcare data is time-consuming and notoriously difficult due to privacy and regulatory concerns. The Personal Health Train (PHT) provides a privacy-by-design infrastructure connecting FAIR (Findable, Accessible, Interoperable, Reusable) data sources and allows distributed data analysis and machine learning.

Predicting adsorptive removal of chlorophenol from aqueous solution using artificial intelligence based modeling approaches.

The research aims to develop artificial intelligence (AI)-based model to predict the adsorptive removal of 2-chlorophenol (CP) in aqueous solution by coconut shell carbon (CSC) using four operational variables (pH of solution, adsorbate concentration, temperature, and contact time), and to investigate their effects on the adsorption process. Accordingly, based on a factorial design, 640 batch experiments were conducted. Nonlinearities in experimental data were checked using Brock-Dechert-Scheimkman (BDS) statistics.

Influence of physico-chemical factors on leaching of chemical additives from aluminium foils used for packaging of food materials.

In recent years, the use of aluminium foils to wrap foodstuff and commodities has been increased to a great extent. Aluminium was found to leach out from the foil in different simulants particularly in distilled water, acidic and alkaline medium at 60 +/- 2 degrees C for 2 hours and 40 +/- 2 degrees C for 24 hours. The migration was found to be above the permissible limit as laid down by WHO guidelines, that is of 0.

Levels and distribution of persistent organochlorine pesticide residues in water and sediments of Gomti River (India)--a tributary of the Ganges River.

This study reports the concentration levels and distribution pattern of the persistent organochlorine pesticide (OCPs) residues in the water and bed-sediments of the Gomti River collected seasonally over a period of 2 years. The water and bed-sediment samples were collected from eight different sites and analyzed for aldrin, dieldrin, endrin, HCB, HCH isomers, DDT isomers/metabolites, endosulfan isomers (alpha and beta), endosulfan sulfate, heptachlor and its metabolites, alpha-chlordane, gamma-chlordane and methoxychlor. In the river water and sediments SigmaOCPs residues ranged between 2.

Distribution of polycyclic aromatic hydrocarbons in edible fish from Gomti river, India.

This study reports the levels and distribution patterns of selected polycyclic aromatic hydrocarbons (PAHs) in fish samples of the Gomti river, India, collected from three sites during the pre- and post-monsoon seasons of the years 2004-2005. In the fish muscles, SigmaPAHs ranged between 12.85 and 34.

Vertical characterization of soil contamination using multi-way modeling--a case study.

This study describes application of chemometric multi-way modeling approach to analyze the dataset pertaining to soils of industrial area with a view to assess the soil/sub-soil contamination, accumulation pathways and mobility of contaminants in the soil profiles. The three-way (sampling depths, chemical variables, sampling sites) dataset on heavy metals in soil samples collected from three different sites in an industrial area, up to a depth of 60 m each was analyzed using three-way Tucker3 model validated for stability and goodness of fit. A two component Tucker3 model, explaining 66.

Residues of organochlorine pesticides in fish from the Gomti river, India.

This study reports the levels and distribution patterns of some organochlorine pesticides (OCPs) in fish samples of the Gomti river, India, collected from three sites. In the fish muscles Sigma OCPs ranged between 2.58-22.

Liquid-phase adsorption of phenols using activated carbons derived from agricultural waste material.

Physical and chemical properties of activated carbons prepared from coconut shells (SAC and ATSAC) were studied. The adsorption equilibria and kinetics of phenol and 2,4-dichlorophenol from aqueous solutions on such carbons were then examined at three different temperatures (10, 25 and 40 degrees C). Adsorption of both phenol and 2,4-dichlorophenol increased with an increase in temperature.