Live Cancer Cell Classification Based on Quantitative Phase Spatial Fluctuations and Deep Learning With a Small Training Set

We present an analysis method that can automatically classify live cancer cells from cell lines based on a small data set of quantitative phase imaging data without cell staining. The method includes spatial image analysis to extract the cell phase spatial fluctuation map, derived from the quantitative phase map of the cell measured without cell labeling, thus without prior knowledge on the biomarker. The spatial fluctuations are indicative of the cell stiffness, where cancer cells change their stiffness as cancer progresses. In this paper, the quantitative phase spatial fluctuations are used as the basis for a deep-learning classifier for evaluating the cell metastatic potential. The spatial fluctuation analysis performed on the quantitative phase profiles before inputting them to the neural network was proven to increase the classification results in comparison to inputting the quantitative phase profiles directly, as done so far. We classified between primary and metastatic cancer cells and obtained 92.5% accuracy, in spite of using a small training set, demonstrating the method potential for objective automatic clinical diagnosis of cancer cells in vitro.

Temporal and Spatial Fluctuation of Noise Levels in the Closed Vicinity of Urban Roadways

Noise pollution is a very critical issue for a better quality of life in urban settings. This study has been conducted to investigate the temporal and spatial fluctuation of noise levels in the vicinity of urban roadways. A total of twelve sites have been covered, eight in residential area and four in commercial area for this study. The monitoring of noise levels in residential and commercial areas in the capital city of India, Delhi, has been carried out from 18th of July to 12th of August 2017 using Sound Level Meter (Larson & Davis 831). The monitoring has been done only on working days and in good weather condition as per standard procedure, special care has been taken to reduce the effects of wind. Temporal distribution shows that the noise level in morning at the residential area has been more than the prescribed standard and reached up to 84.8 dB (A) in comparison to the commercial areas which has been remains up to 79.46 dB (A). Spatial distribution revealed that the noise level at Ashram Chowk remains in the range of 75 to 80 dB (A) which is maximum in comparison to all other selected location of residential area followed by Moolchand which remains in the range of 70 to 75 dB (A). In commercial area the noise levels remain in the range of 65 to 70 dB (A) at Connaught Place outer Circle (CPOC), which is remain maximum among all selected location. The noise level exceeds the recommendation of CPCB at all eight locations of residential area and two locations of commercial area out of four. It can be concluded that the residential area near urban roadways remains more prone to noise pollution in comparison to commercial area. Planning and public knowledge about the long term noise risk may help in to relieve the noise risk in urban areas

Velocity fluctuations generated by the flow through a random array of spheres: a model of bubble-induced agitation

This work reports an experimental investigation of the flow through a random array of fixed solid spheres. The volume fraction of the spheres is 2 %, and the Reynolds number $Re$ based on the sphere diameter and the average flow velocity is varied from 120 to 1040. Using time and spatial averaging, the fluctuations have been decomposed into two contributions of different natures: a spatial fluctuation that accounts for the strong inhomogeneity of the flow around each sphere, and a time fluctuation that comes from the instability of the flow at large enough Reynolds numbers. The evolutions of these two contributions with the Reynolds number are different, so that their relative importance varies. However, when each is normalized by using its own variance and the integral length scales of the fluctuations, their spectra and probability density functions (PDFs) are almost independent of $Re$. The spatial fluctuation mostly comes from the velocity deficit in the wakes of the spheres, and is thus dominated by scales larger than one or two sphere diameters. It is found to be responsible for the asymmetry of the PDFs of the vertical fluctuations and of the major part of the anisotropy level between the vertical and the horizontal components of the fluctuations. The time fluctuation dominates at scales smaller than the integral length scale. It is isotropic and its PDFs, well described by an exponential distribution, are non-Gaussian. The spectra of the spatial and the time fluctuations both show an evolution as the power $-3$ of the wavenumber, but not exactly in the same subrange. All these properties are found in remarkable agreement with the results of both experimental investigations and large eddy simulations (LES) of a homogeneous bubble swarm. This confirms that the main mechanism responsible for the production of bubble-induced fluctuations is the interaction of the velocity disturbances caused by obstacles immersed in a flow and that the structure of this agitation is weakly dependent on the precise nature of the obstacles. The understanding and the modelling of the agitation generated by the motion of a dispersed phase, such as the bubble-induced agitation, therefore require one to distinguish between the roles of these two contributions.

Spatial Fluctuation Enhancement in Polymer Capacitors Using Immiscible Binary Mixtures

A control and utilizability of spatial fluctuations in polymer capacitors using immiscible binary mixtures are described. The spatial fluctuations for the device elements are of particular important for bioinspired multielemental network devices that is composed of elements with distributed electric property. Here we first report that spatial distribution of dielectric properties can be enhanced on the fabrication of SDDE using thermal processing that changes the morphology of immiscible PLLA/PCL binary mixture.