Mercury DPM: fast, flexible particle simulations in complex geometries part II: applications

MercuryDPM is a particle-simulation software developed open-source by a global network of researchers. It was designed ​ab initio to simulate realistic geometries and materials, thus it contains several unique features not found in any other particle simulation software. These features have been discussed in a companion paper published in the DEM7 conference proceedings; here we present several challenging setups implemented in MercuryDPM ​ . Via these setups, we demonstrate the unique capability of the code to simulate and analyse highly complex geotechnical and industrial applications.These tups implemented include complex geometries such as (i) a screw conveyor, (ii) steady-state inflow conditions for chute flows, (iii) a confined conveyor belt to simulate a steady-state breaking wave, and(iii)aquasi-2D cylindrical slice to efficiently study shear flows.​MercuryDPM is also parallel, which we showcase via a multi-million particle simulations of a rotating drum. We further demonstrate how to simulate complex particle interactions, including: (i)deformable, charged clay particles; and (ii) liquid bridges and liquid migration in wet particulates, (iii) non-spherical particles implemented via superquadrics. Finally, we show how to analyse and complex systems using the unique micro-macro mapping (coarse-graining) tool MercuryCG

Comparative return of imports into the state of Negri Sembilan during the years, 1916 and 1915.

Supplement to the F.M.S Government Gazette, May 11th, 1917. It also contains 'Comparative return of exports into the state of Negri Sembilan during the years, 1916 and 1915'

Validity of diagnostic codes and laboratory measurements to identify patients with idiopathic acute liver injury in a hospital database

PurposeThe development and validation of algorithms to identify cases of idiopathic acute liver injury (ALI) are essential to facilitate epidemiologic studies on drug-induced liver injury. The aim of this study is to determine the ability of diagnostic codes and laboratory measurements to identify idiopathic ALI cases. MethodsIn this cross-sectional validation study, patients were selected from the hospital-based Utrecht Patient Oriented Database between 2008 and 2010. Patients were identified using (I) algorithms based on ICD-9-CM codes indicative of idiopathic ALI combined with sets of liver enzyme values (ALT>2x upper limit of normal (ULN); AST>1ULN+AP>1ULN+bilirubin>1ULN; ALT>3ULN; ALT>3ULN+bilirubin>2ULN; ALT>10ULN) and (II) algorithms based on solely liver enzyme values (ALT>3ULN+bilirubin>2ULN; ALT>10ULN). Hospital medical records were reviewed to confirm final diagnosis. The positive predictive value (PPV) of each algorithm was calculated. ResultsA total of 707 cases of ALI were identified. After medical review 194 (27%) patients had confirmed idiopathic ALI. The PPV for (I) algorithms with an ICD-9-CM code as well as abnormal tests ranged from 32% (13/41) to 48% (43/90) with the highest PPV found with ALT>2ULN. The PPV for (II) algorithms with liver test abnormalities was maximally 26% (150/571). ConclusionsThe algorithm based on ICD-9-CM codes indicative of ALI combined with abnormal liver-related laboratory tests is the most efficient algorithm for identifying idiopathic ALI cases. However, cases were missed using this algorithm, because not all ALI cases had been assigned the relevant diagnostic codes in daily practice. Copyright (c) 2015 John Wiley & Sons, Lt

Validity of diagnostic codes and laboratory measurements to identify patients with idiopathic acute liver injury in a hospital database

Purpose: The development and validation of algorithms to identify cases of idiopathic acute liver injury (ALI) are essential to facilitate epidemiologic studies on drug-induced liver injury. The aim of this study is to determine the ability of diagnostic codes and laboratory measurements to identify idiopathic ALI cases. Methods: In this cross-sectional validation study, patients were selected from the hospital-based Utrecht Patient Oriented Database between 2008 and 2010. Patients were identified using (I) algorithms based on ICD-9-CM codes indicative of idiopathic ALI combined with sets of liver enzyme values (ALT>2× upper limit of normal (ULN); AST>1ULN+AP>1ULN+bilirubin>1ULN; ALT>3ULN; ALT>3ULN+bilirubin>2ULN; ALT>10ULN) and (II) algorithms based on solely liver enzyme values (ALT>3ULN+bilirubin>2ULN; ALT>10ULN). Hospital medical records were reviewed to confirm final diagnosis. The positive predictive value (PPV) of each algorithm was calculated. Results: A total of 707 cases of ALI were identified. After medical review 194 (27%) patients had confirmed idiopathic ALI. The PPV for (I) algorithms with an ICD-9-CM code as well as abnormal tests ranged from 32% (13/41) to 48% (43/90) with the highest PPV found with ALT>2ULN. The PPV for (II) algorithms with liver test abnormalities was maximally 26% (150/571). Conclusions: The algorithm based on ICD-9-CM codes indicative of ALI combined with abnormal liver-related laboratory tests is the most efficient algorithm for identifying idiopathic ALI cases. However, cases were missed using this algorithm, because not all ALI cases had been assigned the relevant diagnostic codes in daily practice

Seasonal changes in gene expression represent cell-type composition in whole blood

Seasonal patterns in behavior and biological parameters are widespread. Here, we examined seasonal changes in whole blood gene expression profiles of 233 healthy subjects. Using weighted gene co-expression network analysis, we identified three co-expression modules showing circannual patterns. Enrichment analysis suggested that this signal stems primarily from red blood cells and blood platelets. Indeed, a large clinical database with 51 142 observations of blood cell counts over 3 years confirmed a corresponding seasonal pattern of counts of red blood cells, reticulocytes and platelets. We found no direct evidence that these changes are linked to genes known to be key players in regulating immune function or circadian rhythm. It is likely, however, that these seasonal changes in cell counts and gene expression profiles in whole blood represent biological and clinical relevant phenomena. Moreover, our findings highlight possible confounding factors relevant to the study of gene expression profiles in subjects collected at geographical locations with disparaging seasonality patterns

MercuryDPM: Fast, flexible particle simulations in complex geometries: Part B: Applications

MercuryDPM is a particle-simulation software developed open-source by a global network of researchers. It was designed ​ab initio to simulate realistic geometries and materials, thus it contains several unique features not found in any other particle simulation software. These features have been discussed in a companion paper published in the DEM7 conference proceedings; here we present several challenging setups implemented in MercuryDPM​. Via these setups, we demonstrate the unique capability of the code to simulate and analyse highly complex geotechnical and industrial applications. The setups implemented include complex geometries such as (i) a screw conveyor, (ii) steady-state inflow conditions for chute flows, (iii) a confined conveyor belt to simulate a steady-state breaking wave, and (iii) a quasi-2D cylindrical slice to efficiently study shear flows. ​MercuryDPM is also parallel, which we showcase via a multi-million particle simulations of a rotating drum. We further demonstrate how to simulate complex particle interactions, including: (i) deformable, charged clay particles; and (ii) liquid bridges and liquid migration in wet particulates, (iii) non-spherical particles implemented via superquadrics. Finally, we show how to analyse and complex systems using the unique micro-macro mapping (coarse-graining) tool MercuryCG