Quadrupole deformation in Λ\Lambda-hypernuclei

Shapes of light normal nuclei and $\Lambda$-hypernuclei are investigated using relativistic mean field approach. The FSUGold parametrization is used for this purpose. The addition of a $\Lambda$ is found to change the shape of the energy surface towards prolate. The deformation in a $\Lambda$-hypernucleus, when the hyperon is in the first excited state, is also discussed. The effect of the inclusion of the hyperon on the nuclear radius is generally small with one exception

Ground states and excited states of hypernuclei in Relativistic Mean Field approach

Hypernuclei have been studied within the framework of Relativistic Mean Field theory. The force FSU Gold has been extended to include hyperons. The effective hyperon-nucleon and nucleon-nucleon interactions have been obtained by fitting experimental energies in a number of hypernuclei over a wide range of mass. Calculations successfully describe various features including hyperon separation energy and single particle spectra of single-\Lambda hypernuclei throughout the periodic table. We also extend this formalism to double-\Lambda hypernuclei.Comment: 16 pages,3 figure

Generation of Test Vectors for Sequential Cell Verification

For Application Specific Integrated Circuits (ASIC) and System-on-Chip (SOC) designs, Cell - Based Design (CBD) is the most prevalent practice as it guarantees a shorter design cycle, minimizes errors and is easier to maintain. In modern ASIC design, standard cell methodology is practiced with sizable libraries of cells, each containing multiple implementations of the same logic functionality, in order to give the designer differing options based on area, speed or power consumption. For such library cells, thorough verification of functionality and timing is crucial for the overall success of the chip, as even a small error can prove fatal due to the repeated use of the cell in the design. Both formal and simulation based methods are being used in the industry for cell verification. We propose a method using the latter approach that generates an optimized set of test vectors for verification of sequential cells, which are guaranteed to give complete Single Input Change transition coverage with minimal redundancy. Knowledge of the cell functionality by means of the State Table is the only prerequisite of this procedure

Evaluation of Important Treatment Parameters in Supraphysiological Thermal Therapy of Human Liver Cancer HepG2 Cells

This study was aimed at simulating the effect of various treatment parameters like heating rate (HR), peak temperature (PT) and hold/total treatment time on the viability of human liver cancer HepG2 cells subjected to different thermal therapy conditions. The problem was approached by investigating the injury kinetics obtained using experimentally measured viability of the cells, heated to temperatures of 50–70°C for 0–9 min at HRs of 100, 200, 300 and 525°C min(−1). An empirical expression obtained between the activation energy (E) and HR was extended to obtain the E values over a broad range of HRs from 5 to 600°C min(−1) that mimic the actual conditions encountered in a typical thermal therapy protocol. Further, the effect of the HR (5–600°C min(−1)) and PT (50–85°C) on the cell survival was studied over a range of hold times. A significant drop in survival from 90% to 0% with the simultaneous increase in HR and PT was observed as the hold time increased from 0 to 5 min. For complete cell death, the hold time increased with the increase in the HR for a given PT, while the total time showed presence of minima for 60, 65 and 70°C at HRs of 50, 100 and 200°C min(−1), respectively

Generalized Holographic Cosmology

We consider general black hole solutions in five-dimensional spacetime in the presence of a negative cosmological constant. We obtain a cosmological evolution via the gravity/gauge theory duality (holography) by defining appropriate boundary conditions on a four-dimensional boundary hypersurface. The standard counterterms are shown to renormalize the bare parameters of the system (the four-dimensional Newton's constant and cosmological constant). We discuss the thermodynamics of cosmological evolution and present various examples. The standard brane-world scenarios are shown to be special cases of our holographic construction.Comment: 15 pages, 5 figure

Real-time, noise and drift resilient formaldehyde sensing at room temperature with aerogel filaments

Formaldehyde, a known human carcinogen, is a common indoor air pollutant. However, its real-time and selective recognition from interfering gases remains challenging, especially for low-power sensors suffering from noise and baseline drift. We report a fully 3D-printed quantum dot/graphene-based aerogel sensor for highly sensitive and real-time recognition of formaldehyde at room temperature. By optimising the morphology and doping of the printed structures, we achieve a record-high response of 15.23 percent for 1 parts-per-million formaldehyde and an ultralow detection limit of 8.02 parts-per-billion consuming only 130 uW power. Based on measured dynamic response snapshots, we also develop an intelligent computational algorithm for robust and accurate detection in real time despite simulated substantial noise and baseline drift, hitherto unachievable for room-temperature sensors. Our framework in combining materials engineering, structural design and computational algorithm to capture dynamic response offers unprecedented real-time identification capabilities of formaldehyde and other volatile organic compounds at room temperature.Comment: Main manuscript: 21 pages, 5 figure. Supplementary: 21 pages. 13 Figures, 2 tabl

MODEL FOR LAND COVER ESTIMATION USING UNSUPERVISED MACHINE LEARNING ON GOOGLE MAPS COLOR IMAGES

Remote sensing data and satellite images are broadly used for land cover information. There are so many challenges to classify pixels on the basis of features and characteristics. Generally it is pixel classification that required the count of pixels for certain area of interest. In the proposed model, we are applying unsupervised machine learning to classify the content of the input images on the basis of pixels intensity. The study aims to compare classification accuracy of different landscape characteristics like water, forest, urban, agricultural areas, transport network and other classes adapted from CORINE (Coordination of information on the environment) nomenclature. To fulfil the aim of the model, accessing data from Google map using Google static API service which creates a map based on URL parameters sent through a standard HTTP (Hyper Text Transfer Protocol) request and returns the map as an image which can be display on any graphical user interface platform. The Google Static Maps API returns an image either in GIF, PNG or JPEG format in response to an HTTP request. To identify different land cover/use classes using k-means clustering. The model is dynamic in nature that describes the clustering as well formulate the area of the concerned class or clustered fields