Massively scalable density based clustering (DBSCAN) on the HPCC systems big data platform

Dealing with large samples of unlabeled data is a key challenge in today’s world, especially in applications such as traffic pattern analysis and disaster management. DBSCAN, or density based spatial clustering of applications with noise, is a well-known density-based clustering algorithm. Its key strengths lie in its capability to detect outliers and handle arbitrarily shaped clusters. However, the algorithm, being fundamentally sequential in nature, proves expensive and time consuming when operated on extensively large data chunks. This paper thus presents a novel implementation of a parallel and distributed DBSCAN algorithm on the HPCC Systems platform. The algorithm seeks to fully parallelize the algorithm implementation by making use of HPCC Systems optimal distributed architecture and performing a tree-based union to merge local clusters. The proposed approach* was tested both on synthetic as well as standard datasets (MFCCs Data Set) and found to be completely accurate. Additionally, when compared against a single node setup, a significant decrease in computation time was observed with no impact to accuracy. The parallelized algorithm performed eight times better for higher number of data points and takes exponentially lesser time as the number of data points increases

EMC ASPECTS OF TURBULENCE HEATING OBSERVER (THOR) SPACECRAFT

Turbulence Heating ObserveR (THOR) is a spacecraft mission dedicated to the study of plasma turbulence in near-Earth space. The mission is currently under study for implementation as a part of ESA Cosmic Vision program. THOR will involve a single spinning spacecraft equipped with state of the art instruments capable of sensitive measurements of electromagnetic fields and plasma particles. The sensitive electric and magnetic field measurements require that the spacecraft-generated emissions are restricted and strictly controlled; therefore a comprehensive EMC program has been put in place already during the study phase. The THOR study team and a dedicated EMC working group are formulating the mission EMC requirements state of its EMC requirements

Modulation of FGF pathway signaling and vascular differentiation using designed oligomeric assemblies

Many growth factors and cytokines signal by binding to the extracellular domains of their receptors and driving association and transphosphorylation of the receptor intracellular tyrosine kinase domains, initiating downstream signaling cascades. To enable systematic exploration of how receptor valency and geometry affect signaling outcomes, we designed cyclic homo-oligomers with up to 8 subunits using repeat protein building blocks that can be modularly extended. By incorporating a de novo-designed fibroblast growth factor receptor (FGFR)-binding module into these scaffolds, we generated a series of synthetic signaling ligands that exhibit potent valency- and geometry-dependent Ca2+ release and mitogen-activated protein kinase (MAPK) pathway activation. The high specificity of the designed agonists reveals distinct roles for two FGFR splice variants in driving arterial endothelium and perivascular cell fates during early vascular development. Our designed modular assemblies should be broadly useful for unraveling the complexities of signaling in key developmental transitions and for developing future therapeutic applications

Reduced Gray to White Matter Tissue Intensity Contrast in Schizophrenia

BACKGROUND: While numerous structural magnetic resonance imaging (MRI) studies revealed changes of brain volume or density, cortical thickness and fibre integrity in schizophrenia, the effect of tissue alterations on the contrast properties of neural structures has so far remained mostly unexplored. METHODS: Whole brain high-resolution MRI at 3 Tesla was used to investigate tissue contrast and cortical thickness in patients with schizophrenia and healthy controls. RESULTS: Patients showed significantly decreased gray to white matter contrast in large portions throughout the cortical mantle with preponderance in inferior, middle, superior and medial temporal areas as well as in lateral and medial frontal regions. The extent of these intensity contrast changes exceeded the extent of cortical thinning. Further, contrast changes remained significant after controlling for cortical thickness measurements. CONCLUSIONS: Our findings clearly emphasize the presence of schizophrenia related brain tissue changes that alter the imaging properties of brain structures. Intensity contrast measurements might not only serve as a highly sensitive metric but also as a potential indicator of a distinct pathological process that might be independent from volume or thickness alterations

Activated carbon from banana peel: an emerging biobased material for adsorption of diclofenac

International audienc

Massively scalable density based clustering (DBSCAN) on the HPCC systems big data platform

&lt;span id="docs-internal-guid-919b015d-7fff-56da-f81d-8f032097bce2"&gt;&lt;span&gt;Dealing with large samples of unlabeled data is a key challenge in today’s world, especially in applications such as traffic pattern analysis and disaster management. DBSCAN, or density based spatial clustering of applications with noise, is a well-known density-based clustering algorithm. Its key strengths lie in its capability to detect outliers and handle arbitrarily shaped clusters. However, the algorithm, being fundamentally sequential in nature, proves expensive and time consuming when operated on extensively large data chunks. This paper thus presents a novel implementation of a parallel and distributed DBSCAN algorithm on the HPCC Systems platform. The algorithm seeks to fully parallelize the algorithm implementation by making use of HPCC Systems optimal distributed architecture and performing a tree-based union to merge local clusters. The proposed approach* was tested both on synthetic as well as standard datasets (MFCCs Data Set) and found to be completely accurate. Additionally, when compared against a single node setup, a significant decrease in computation time was observed with no impact to accuracy. The parallelized algorithm performed eight times better for higher number of data points and takes exponentially lesser time as the number of data points increases.&lt;/span&gt;&lt;/span&gt;</jats:p

Combination of coagulation-adsorption by using new activated carbon from banana peel for diclofenac removal in surface water

International audienc