Mixture Models for Photometric Redshifts

Determining photometric redshifts to high accuracy is paramount to measure distances in wide-field cosmological experiments. With only photometric information at hand, photo-zs are prone to systematic uncertainties in the intervening extinction and the unknown underlying spectral-energy distribution of different astrophysical sources. Here, we aim to resolve these model degeneracies and obtain a clear separation between intrinsic physical properties of astrophysical sources and extrinsic systematics. We aim at estimates of the full photo-z probability distributions, and their uncertainties. We perform a probabilistic photo-z determination using Mixture Density Networks (MDN). The training data-set is composed of optical ($griz$) point-spread-function and model magnitudes and extinction measurements from the SDSS-DR15, and WISE midinfrared ($3.4 \mu$m and $4.6 \mu$m) model magnitudes. We use Infinite Gaussian Mixture models to classify the objects in our data-set as stars, galaxies or quasars, and to determine the number of MDN components to achieve optimal performance. The fraction of objects that are correctly split into the main classes is 94%. Our method improves the bias of photometric redshift estimation (i.e. the mean $\Delta z$ = (zp - zs)/(1 + zs)) by one order of magnitude compared to the SDSS photo-z, and decreases the fraction of $3 \sigma$ outliers (i.e. 3rms$(\Delta z) < \Delta z$). The relative, root-mean-square systematic uncertainty in our resulting photo-zs is down to 1.7% for low-redshift galaxies (zs $<$ 0.5). We have demonstrated the feasibility of machine-learning based methods that produce full probability distributions for photo-z estimates with a performance that is competitive with state-of-the art techniques. Our method can be applied to wide-field surveys where extinction can vary significantly across the sky and with sparse spectroscopic calibration samples.Comment: 14 pages, 9 figures, 7 tables, submitted to A&A 14/10/202

Development of a life cycle assessment tool for the assessment of food production systems within the energy, water and food nexus

© 2015 The Institution of Chemical Engineers.As the demand for services and products continues to increase in light of rapid population growth, the question of energy, water and food (EWF) security is of increasing importance. The systems representing the three resources are intrinsically connected and, as such, there is a need to develop assessment tools that consider their interdependences. Specifically when evaluating the environmental performance of a food production system, it is necessary to understand its life cycle. The objective of this paper is to introduce an integrated energy, water and food life cycle assessment tool that integrates EWF resources in one robust model and at an appropriate resolution. The nexus modelling tool developed is capable of providing an environmental assessment for food production systems utilising a holistic systems approach as described by a series of subsystems that constitute each of the EWF resources. A case study set in Qatar and characterised by an agriculture sub-system, which includes the production and application of fertilisers and the raising of livestock, a water sub-system represented by mechanical and thermal desalination processes and an energy sub-system, which includes fossil fuel in the form of combined cycle natural gas based energy production and solar renewable energy is used to illustrate the model function. For the nexus system analysed it is demonstrated that the food system is the largest contributor to global warming. The GWP can be reduced by up to 30% through the utilisation of solar energy to substitute fossil fuels, which, however, comes with a significant requirement for land investment

Simulation Analysis of a Power System Protection using Artificial Neural Network

There has been significant development in the area of neural network based power system protection in the previous decade. Neural network technology has been applied for various protective relaying functions including distance protection. The aim of this Paper is to develop a software module acting as a protective relay using neural network techniques. The Artificial Neural Network (ANN) software developed module employs the back-propagation method to recognize the waveform patterns of impedance in a transmission line. The input waveforms are generated using PSCAD. The generated waveforms then are used as training and testing data for the ANN software. The ANN software is simulated using the Neural Network Toolbox. The design has been tested for different fault conditions including different fault resistances and fault inception angles. The test results show that the relay is able to detect faults in lesser time as compared to conventional relay algorithms.DOI:http://dx.doi.org/10.11591/ijece.v3i1.193

Quantitative Analysis of Cardiomyocyte Dynamics with Optical Coherence Phase Microscopy

Spectral domain optical coherence microscopy (OCM) is an interferometric imaging technique for three-dimensional reconstruction of biological samples. Phase sensitive implementation of OCM has generally been in common path interferometer configuration to obtain high phase stability, wh ich limits the numerical aperture of the imaging optics and the transverse resolution. Here, we describe the implemen tation of optical coherence phase microscope in asymmetric Linnik interferometer configuration, which provides phase stability of 0.5 milliradians along with high spatial resolution. Three-dimensional structural images and dynamic displacement images ob tained from spontaneously active cardiomyocytes demonstrate that the phase information could potentially be used for quantitative analysis of contraction dynamics, spatially resolved to sub-cellular structures

Quantitative microarray profiling of DNA-binding molecules

A high-throughput Cognate Site Identity (CSI) microarray platform interrogating all 524 800 10-base pair variable sites is correlated to quantitative DNase I footprinting data of DNA binding pyrrole-imidazole polyamides. An eight-ring hairpin polyamide programmed to target the 5 bp sequence 5'-TACGT-3' within the hypoxia response element (HRE) yielded a CSI microarray-derived sequence motif of 5'-WWACGT-3' (W = A,T). A linear beta-linked polyamide programmed to target a (GAA)_3 repeat yielded a CSI microarray-derived sequence motif of 5'-AARAARWWG-3' (R = G,A). Quantitative DNase I footprinting of selected sequences from each microarray experiment enabled quantitative prediction of K_a values across the microarray intensity spectrum

Transcatheter closure of coronary artery fistulae: A literature review

Coronary artery fistulae (CAFs) are anomalous connections that bypass the myocardial capillary bed between 1 or more coronary arteries and other cardiac chambers or other vessels. These fistulae are usually asymptomatic and are, thus, diagnosed incidentally. However, larger CAFs can cause various symptoms such as angina, exertional dyspnea, syncope, palpitation, and even sudden cardiac death. Treatment options include surgical closure and percutaneous transcatheter closure (TCC) with comparable safety and efficacy. The choice of device in TCC depends on the anatomic characteristics of the CAF, the age and size of the patient, the size of the occluded vessel, the appropriate size of the catheter to be used, and the tortuosity of the catheter course to reach the intended point. Herein, we present 4 cases treated via TCC and then offer an in-depth discussion regarding this coronary artery anomaly. © 2020, Tech Science Press. All rights reserved

Changes in particulate matter concentrations at different altitudinal levels with environmental dynamics

Ambient air quality is defined not only by the source strength but a variety of meteorological parameters as well. In the current study, ambient concentrations of PM along with temperature and relative humidity levels were monitored at seven different locations of Pakistan. A DustTrak DRX (Model 8533, TSI Inc.) was employed for twenty four hours real time monitoring of particulate matter at the selected sites. A considerable variation was observed in the 24 hour trend of particulate matter (PM) at different locations owing to variation in meteorological conditions due to different altitudes and seasons, and natural and anthropogenic sources in the vicinity. The highest average concentrations of PM2.5 (407μg/m3 were observed at highest elevation (Makra Peak, Shogran, 3089 m) while lowest averages (102 μg/m3) were obtained at the seaside (Hawks Bay, Karachi, 0 m).On the other hand PMTotal fraction exhibited highest levels at site B (506 μg/m3) and lowest at Site A (121 μg/m3).Correlation factors were determined for PM and meteorological parameters at each location. More research needs to be conducted to have a comprehensive knowledge about the physical parameters controlling particulate dispersal at different altitudes within the country

Changes in particulate matter concentrations at different altitudinal levels with environmental dynamics

Ambient air quality is defined not only by the source strength but a variety of meteorological parameters as well. In the current study, ambient concentrations of PM along with temperature and relative humidity levels were monitored at seven different locations of Pakistan. A DustTrak DRX (Model 8533, TSI Inc.) was employed for twenty four hours real time monitoring of particulate matter at the selected sites. A considerable variation was observed in the 24 hour trend of particulate matter (PM) at different locations owing to variation in meteorological conditions due to different altitudes and seasons, and natural and anthropogenic sources in the vicinity. The highest average concentrations of PM2.5 (407 mu g/m(3)) were observed at highest elevation (Makra Peak, Shogran, 3089 m) while lowest averages (102 mu g/m(3)) were obtained at the seaside (Hawks Bay, Karachi, 0 m). On the other hand PMTotal fraction exhibited highest levels at site B (506 mu g/m(3)) and lowest at Site A (121 mu g/m(3)). Correlation factors were determined for PM and meteorological parameters at each location. More research needs to be conducted to have a comprehensive knowledge about the physical parameters controlling particulate dispersal at different altitudes within the country

Effect of glucose, lactate and pyruvate concentrations on in vitro growth of goat granulosa cell

Carbohydrates are among the most influential of the numerous components of culture medium that affect metabolism and developmental potential. Glucose, lactate and pyruvate are required for the growth of oocytes and other follicular cells in vitro. The aim of this study was to determine the effects of different concentrations of glucose, lactate and pyruvate on promoting DNA synthesis of granulosa cells in a serum-free medium. Effects of glucose (0.75, 1.5 or 3 mM), pyruvate (0.1 or 0.33 mM) and Llactate (3, 6 or 12 mM) concentrations in the maturation medium on the relative granulosa cell growth during metaphase II (MII) were examined in a 3 × 2 × 3 factorial design. The greatest relative granulosa cell growth response (p&lt;0.05) was observed in the presence of 1.5 mM glucose and 0.33 mM pyruvate or in 6 mM lactate and 0.33 mM pyruvate. Increasing pyruvate concentrations from 0.1 to 0.33 mM resulted in an increase in DNA synthesis in granulosa cells. In conclusion, the results of this study showed that increasing glucose and pyruvate concentrations in the maturation medium increased the growth of goat granulosa cells.Key word: Energy substrate, granulosa cell growth, methyl-3H-thymidine, goat