PEDIA: prioritization of exome data by image analysis.

PURPOSE: Phenotype information is crucial for the interpretation of genomic variants. So far it has only been accessible for bioinformatics workflows after encoding into clinical terms by expert dysmorphologists. METHODS: Here, we introduce an approach driven by artificial intelligence that uses portrait photographs for the interpretation of clinical exome data. We measured the value added by computer-assisted image analysis to the diagnostic yield on a cohort consisting of 679 individuals with 105 different monogenic disorders. For each case in the cohort we compiled frontal photos, clinical features, and the disease-causing variants, and simulated multiple exomes of different ethnic backgrounds. RESULTS: The additional use of similarity scores from computer-assisted analysis of frontal photos improved the top 1 accuracy rate by more than 20-89% and the top 10 accuracy rate by more than 5-99% for the disease-causing gene. CONCLUSION: Image analysis by deep-learning algorithms can be used to quantify the phenotypic similarity (PP4 criterion of the American College of Medical Genetics and Genomics guidelines) and to advance the performance of bioinformatics pipelines for exome analysis

LORONG LORONG NERAKA CU CHI: Perjuangan Hidup-Mati Gerilya Bawah Tanah Vietnam untuk Mengalahkan Adikuasa Amerika Serikat

xii ; 412 hlm; ilus;14 x 21 c

Simulation Tool for the Development of a Staged Combustion Pellet Stove Controller

Optimizing the combustion control concepts on a pellet stove with very low heat output is time-consuming and costly. In order to shorten the required laboratory test time, a 0-D transient tool was developed within the ERA-NET project “LowEmi-MicroStove”, which simulates a 4 kW pellet stove with staged combustion and heat transfer. This approach was chosen in order to greatly simplify the description of the combustion processes and so reduce the computational complexity and simulation time. The combustion of a bed of pellets is modeled as a superposition of the combustion cycles of individual pellets, assuming no interactions between pellets. A test setup was developed and used to determine the ignition and burning cycle of individual pellets. The description of the CO emissions behavior is based upon an empirically grounded relation which is in turn based on the air/fuel ratio and the combustion chamber temperature. For the validation of the 0-D simulation results, a test rig for a 4 kW pellet stove was built. Despite its simplistic approach, good agreement was found between the simulation and 4 kW pellet stove test results for the mean values and temporal fluctuations of flue gas temperature and oxygen and carbon monoxide content during start up, stable operation and load changes. The simulation could thus be used to quantify the effect of air flow rates and distribution as well as load changes on performance and draw conclusions regarding different process control strategies. A control strategy which can operate the stove at high temperatures near the air stoichiometric limit with acceptable CO emissions has been proven to be the most promising. Additionally, the model can be used to quantify the effects of variations in other process parameters, for example the impact of fluctuations in the pellet feed. Due to its effectiveness and simplicity, this model approach can be applied for the development of control strategies for other staged, pellet combustion systems

Simulation Tool for the Development of a Staged Combustion Pellet Stove Controller

Optimizing the combustion control concepts on a pellet stove with very low heat output is time-consuming and costly. In order to shorten the required laboratory test time, a 0-D transient tool was developed within the ERA-NET project “LowEmi-MicroStove”, which simulates a 4 kW pellet stove with staged combustion and heat transfer. This approach was chosen in order to greatly simplify the description of the combustion processes and so reduce the computational complexity and simulation time. The combustion of a bed of pellets is modeled as a superposition of the combustion cycles of individual pellets, assuming no interactions between pellets. A test setup was developed and used to determine the ignition and burning cycle of individual pellets. The description of the CO emissions behavior is based upon an empirically grounded relation which is in turn based on the air/fuel ratio and the combustion chamber temperature. For the validation of the 0-D simulation results, a test rig for a 4 kW pellet stove was built. Despite its simplistic approach, good agreement was found between the simulation and 4 kW pellet stove test results for the mean values and temporal fluctuations of flue gas temperature and oxygen and carbon monoxide content during start up, stable operation and load changes. The simulation could thus be used to quantify the effect of air flow rates and distribution as well as load changes on performance and draw conclusions regarding different process control strategies. A control strategy which can operate the stove at high temperatures near the air stoichiometric limit with acceptable CO emissions has been proven to be the most promising. Additionally, the model can be used to quantify the effects of variations in other process parameters, for example the impact of fluctuations in the pellet feed. Due to its effectiveness and simplicity, this model approach can be applied for the development of control strategies for other staged, pellet combustion systems

HIV/AIDS and the changing landscape of war in Africa

No description supplie

Mars Surface Diversity as Revealed by the OMEGA/Mars Express Observations

International audienceThe Observatoire pour la Minéralogie, l'Eau, les Glaces, et l'Activité (OMEGA) investigation, on board the European Space Agency Mars Express mission, is mapping the surface composition of Mars at a 0.3- to 5-kilometer resolution by means of visible-near-infrared hyperspectral reflectance imagery. The data acquired during the first 9 months of the mission already reveal a diverse and complex surface mineralogy, offering key insights into the evolution of Mars. OMEGA has identified and mapped mafic iron-bearing silicates of both the northern and southern crust, localized concentrations of hydrated phyllosilicates and sulfates but no carbonates, and ices and frosts with a water-ice composition of the north polar perennial cap, as for the south cap, covered by a thin carbon dioxide-ice veneer