Integrative analysis of the inter-tumoral heterogeneity of triple-negative breast cancer.

Triple-negative breast cancers (TNBC) lack estrogen and progesterone receptors and HER2 amplification, and are resistant to therapies that target these receptors. Tumors from TNBC patients are heterogeneous based on genetic variations, tumor histology, and clinical outcomes. We used high throughput genomic data for TNBC patients (n = 137) from TCGA to characterize inter-tumor heterogeneity. Similarity network fusion (SNF)-based integrative clustering combining gene expression, miRNA expression, and copy number variation, revealed three distinct patient clusters. Integrating multiple types of data resulted in more distinct clusters than analyses with a single datatype. Whereas most TNBCs are classified by PAM50 as basal subtype, one of the clusters was enriched in the non-basal PAM50 subtypes, exhibited more aggressive clinical features and had a distinctive signature of oncogenic mutations, miRNAs and expressed genes. Our analyses provide a new classification scheme for TNBC based on multiple omics datasets and provide insight into molecular features that underlie TNBC heterogeneity

Simulating the effect of in-nozzle cavitation on liquid atomisation using a three-phase model

The aim of this article is to present a fully compressible three-phase (liquid, vapor, air, and mixture) cavitation model and its application to the simulation of in-nozzle cavitation effects on liquid atomization. The model employs a combination of barotropic cavitation model with an implicit sharp interface capturing Volume of Fluid (VoF) approximation. The results from the simulation are compared against the experimental results obtained by (1) for injection of water into the air from a stepped nozzle. Large Eddy Simulation (LES) model is utilized for resolving turbulence. Simulations are performed for a condition where developing cavitation is observed. Model validation is achieved by qualitative comparison against the available images for the cavitation, spray pattern. The model predictions suggest that the experimentally observed void inside the nozzle is not purely vapor, but a mixture of both vapor and back-flowing air. The simulation also identified periodic air entrainment that occurs at developing cavitation condition which further improves primary atomization

Solar Power Prediction Using Machine Learning

This paper presents a machine learning-based approach for predicting solar power generation with high accuracy using a 99% AUC (Area Under the Curve) metric. The approach includes data collection, pre-processing, feature selection, model selection, training, evaluation, and deployment. High-quality data from multiple sources, including weather data, solar irradiance data, and historical solar power generation data, are collected and pre-processed to remove outliers, handle missing values, and normalize the data. Relevant features such as temperature, humidity, wind speed, and solar irradiance are selected for model training. Support Vector Machines (SVM), Random Forest, and Gradient Boosting are used as machine learning algorithms to produce accurate predictions. The models are trained on a large dataset of historical solar power generation data and other relevant features. The performance of the models is evaluated using AUC and other metrics such as precision, recall, and F1-score. The trained machine learning models are then deployed in a production environment, where they can be used to make real-time predictions about solar power generation. The results show that the proposed approach achieves a 99% AUC for solar power generation prediction, which can help energy companies better manage their solar power systems, reduce costs, and improve energy efficiency.Comment: 7 page

Timing Offset Calibration of CZTI instrument aboard ASTROSAT

The radio as well as the high energy emission mechanism in pulsars is yet not understood properly. A multi-wavelength study is likely to help in better understanding of such processes. The first Indian space-based observatory, ASTROSAT, has five instruments aboard, which cover the electromagnetic spectrum from infra-red (1300 $\AA$) to hard X-ray (380 KeV). Cadmium Zinc Telluride Imager (CZTI), one of the five instruments is a hard X-ray telescope functional over an energy range of 20-380 KeV. We aim to estimate the timing offset introduced in the data acquisition pipeline of the instrument, which will help in time alignment of high energy time series with those from two other ground-based observatories, viz. the Giant Meterwave Radio Telescope (GMRT) and the Ooty Radio Telescope (ORT). PSR B0531+21 is a well-studied pulsar with nearly aligned radio and hard X-ray pulse profiles. We use simultaneous observations of this pulsar with the ASTROSAT, the ORT and the GMRT. The pulsar was especially observed using the ORT with almost daily cadence to obtain good timing solutions. We also supplement the ORT data with archival FERMI data for estimation of timing noise. The timing offset of ASTROSAT instruments was estimated from fits to arrival time data at the ASTROSAT and the radio observatories. We estimate the offset between the GMRT and the ASTROSAT-CZTI to be -4716 $\pm$ 50 $\mu s$. The corresponding offset with the ORT was -29639 $\pm$ 50 $\mu s$. The offsets between the GMRT and Fermi-LAT -5368 $\pm$ 56 $\mu s$. (Abridged)Comment: 6 pages, 5 figures, 2 tables, Revised and Updated, accepted for publication in A&

Asymptotic behaviour of convex and column-convex lattice polygons with fixed area and varying perimeter

We study the inflated phase of two dimensional lattice polygons, both convex and column-convex, with fixed area A and variable perimeter, when a weight \mu^t \exp[- Jb] is associated to a polygon with perimeter t and b bends. The mean perimeter is calculated as a function of the fugacity \mu and the bending rigidity J. In the limit \mu -> 0, the mean perimeter has the asymptotic behaviour \avg{t}/4 \sqrt{A} \simeq 1 - K(J)/(\ln \mu)^2 + O (\mu/ \ln \mu) . The constant K(J) is found to be the same for both types of polygons, suggesting that self-avoiding polygons should also exhibit the same asymptotic behaviour.Comment: 10 pages, 3 figure

Numerical Investigations on Unsteady Flow past Two Identical Inline Square Cylinders Oscillating Transversely with Phase Difference

Two-dimensional numerical investigations have been carried out to study the temporal wake characteristics of laminar flow past two identical inline square cylinders performing transverse oscillations. Both the cylinders are forced to perform harmonic oscillations of same frequency and amplitude but with a phase difference. Computations are carried out using commercial software ANSYS Fluent 16.1 on a dynamically sliding mesh for fixed Reynolds number equal to 100. The oscillation frequency is varied from 0.4 to 1.6 times the frequency of vortex shedding behind a single stationary square cylinder. The amplitude of transverse oscillation is kept fixed equal to 0.4D (D = side of the cylinder). In addition, the effect of variation of inter-cylinder spacing has been investigated on wake interference which influences the modes of vortex shedding and resulting dynamic effects on the cylinders. Temporal signals as well as mean characteristics of lift and drag coefficients have been presented for different values of inter-cylinder spacing, phase difference between the two cylinders and frequency of oscillation