A New Approach to Free-form Cluster Lens Modeling Inspired by the JPEG Image Compression Method

Large scale structure and cosmolog

Wigner Crystals in the lowest Landau level at low filling factors

We report on results of finite-size numerical studies of partially filled lowest Landau level at low electron filling factors. We find convincing evidence suggesting that electrons form Wigner Crystals at sufficiently low filling factors, and the critical filling factor is close to 1/7. At nu=1/7 we find the system undergoes a phase transition from Wigner Crystal to the incompressible Laughlin state when the short-range part of the Coulomb interaction is modified slightly. This transition is either continuous or very weakly first order.Comment: 5 papges RevTex with 8 eps figures embedded in the tex

Angiotensin-converting enzyme (ACE) inhibition in type 2, diabetic patients – interaction with ACE insertion/deletion polymorphism

Angiotensin-converting enzyme (ACE) insertion(I)/deletion (D) polymorphism may modify the effect of inhibition of the renin–angiotensin–aldosterone system (RAAS) on survival and cardiorenal outcomes in type 2, diabetes. A consecutive cohort of 2089 Chinese type 2 diabetic patients with mean (±standard deviation) age of 59.7±13.1 years were genotyped for this polymorphism by polymerase chain reaction method and were followed prospectively for a median period of 44.6 (interquartile range: 23.7, 57.5) months. Clinical outcomes, including all-cause mortality, cardiovascular and renal end points, were examined. The frequency for I allele was 67.1 and 32.9% for D allele, with observed genotype frequencies of 45.8, 42.6, and 11.6% for 3, DI and DD, respectively. ACE DD polymorphism was an independent predictor for renal end point with hazard ratio (HR) (95% confidence interval) of 1.72 (1.16, 2.56), but not for cardiovascular end point or mortality. After controlling for confounding factors, including ACE I/D genotype, the usage of RAAS inhibitors was associated with reduced risk of mortality (HR 0.34 (0.23, 0.50)) and renal end point (HR 0.55 (0.40, 0.75)). On subgroup analysis, the beneficial effects on survival (II vs DI vs DD: HR 0.29 (0.16, 0.51) vs 0.25 (0.14, 0.46) vs 1.33 (0.41, 4.31)) and renoprotection (II vs DI vs DD: 0.52 (0.30, 0.90) vs 0.43 (0.25, 0.72) vs 0.95 (0.43, 2.12)) were most evident in II and DI carriers. In conclusion, inhibition of RAAS was associated with reduced risk of mortality and occurrence of renal end point in Chinese type 2 diabetic patients. These benefits were most evident among II and DI carriers

Structural optimisation of random discontinuous fibre composites: Part 1 – Methodology

This paper presents a finite element model to optimise the fibre architecture of components manufactured from discontinuous fibre composites. An optimality criterion method has been developed to maximise global component stiffness, by determining optimum distributions for local section thickness and preform areal mass. The model is demonstrated by optimising the bending performance of a flat plate with three holes. Results are presented from a sensitivity study to highlight the level of compromise in stiffness optimisation caused by manufacturing constraints associated with the fibre deposition method, such as the scale of component features relative to the fibre length

Bezoekersonderzoek De Tijdtrap (Markthal, Rotterdam)

Archaeological Heritage Managemen

Annotation of Allosteric Compounds to Enhance Bioactivity Modeling for Class A GPCRs

Proteins often have both orthosteric and allosteric binding sites. Endogenous ligands, such as hormones and neurotransmitters, bind to the orthosteric site, while synthetic ligands may bind to orthosteric or allosteric sites, which has become a focal point in drug discovery. Usually, such allosteric modulators bind to a protein noncompetitively with its endogenous ligand or substrate. The growing interest in allosteric modulators has resulted in a substantial increase of these entities and their features such as binding data in chemical libraries and databases. Although this data surge fuels research focused on allosteric modulators, binding data is unfortunately not always clearly indicated as being allosteric or orthosteric. Therefore, allosteric binding data is difficult to retrieve from databases that contain a mixture of allosteric and orthosteric compounds. This decreases model performance when statistical methods, such as machine learning models, are applied. In previous work we generated an allosteric data subset of ChEMBL release 14. In the current study an improved text mining approach is used to retrieve the allosteric and orthosteric binding types from the literature in ChEMBL release 22. Moreover, convolutional deep neural networks were constructed to predict the binding types of compounds for class A G protein-coupled receptors (GPCRs). Temporal split validation showed the model predictiveness with Matthews correlation coefficient (MCC) = 0.54, sensitivity allosteric = 0.54, and sensitivity orthosteric = 0.94. Finally, this study shows that the inclusion of accurate binding types increases binding predictions by including them as descriptor (MCC = 0.27 improved to MCC = 0.34; validated for class A GPCRs, trained on all GPCRs). Although the focus of this study is mainly on class A GPCRs, binding types for all protein classes in ChEMBL were obtained and explored. The data set is included as a supplement to this study, allowing the reader to select the compounds and binding types of interest.Medicinal Chemistr

Experimental and analytical investigation on flexural behaviour of RC beams strengthened with NSM CFRP prestressed concrete prisms

This investigation aims to study the flexural behaviour of reinforced concrete (RC) beams strengthened with near-surface mounted (NSM) carbon fibre reinforced polymer prestressed concrete prisms (CFRP-PCPs). Eight RC beams were tested under monotonic loading until the failure load was reached. One beam was un-strengthened to act as a control beam. The other seven beams were strengthened with non-prestressed or prestressed NSM CFRP-PCPs. The effects of bond length, prestress level, and concrete type of the CFRP-PCPs on the flexural capacity, flexural crack and deflection are discussed in this paper. The results indicate that the flexural capacity of RC beams strengthened with NSM CFRP-PCPs was greater than the control beam. An obvious improvement was discovered in the crack resistance when the RC beams were strengthened with prestressed NSM CFRP-PCPs. The strengthened beams showed a higher first-cracking, yielding, and ultimate load as the bond length and prestress level of CFRP-PCPs increased up to a critical level. The beams strengthened with CFRP-PCPs, which were cast with ultra-high performance concrete (UHPC), exhibited greater load capacity than the corresponding beams with epoxy resin mortar. The analytical model of flexural response for the NSM CFRP-PCPs strengthening beams is presented. The analytical results are in good agreement with the experimental results, which revealed the NSM CFRP-PCPs is an effective technique for flexural strengthening of the RC beams

Linking drug target and pathway activation for effective therapy using multi-task learning

Despite the abundance of large-scale molecular and drug-response data, the insights gained about the mechanisms underlying treatment efficacy in cancer has been in general limited. Machine learning algorithms applied to those datasets most often are used to provide predictions without interpretation, or reveal single drug-gene association and fail to derive robust insights. We propose to use Macau, a bayesian multitask multi-relational algorithm to generalize from individual drugs and genes and explore the interactions between the drug targets and signaling pathways' activation. A typical insight would be: "Activation of pathway Y will confer sensitivity to any drug targeting protein X". We applied our methodology to the Genomics of Drug Sensitivity in Cancer (GDSC) screening, using gene expression of 990 cancer cell lines, activity scores of 11 signaling pathways derived from the tool PROGENy as cell line input and 228 nominal targets for 265 drugs as drug input. These interactions can guide a tissue-specific combination treatment strategy, for example suggesting to modulate a certain pathway to maximize the drug response for a given tissue. We confirmed in literature drug combination strategies derived from our result for brain, skin and stomach tissues. Such an analysis of interactions across tissues might help target discovery, drug repurposing and patient stratification strategies.Medicinal Chemistr