The LSST AGN Data Challenge: Selection methods

Development of the Rubin Observatory Legacy Survey of Space and Time (LSST) includes a series of Data Challenges (DC) arranged by various LSST Scientific Collaborations (SC) that are taking place during the projects preoperational phase. The AGN Science Collaboration Data Challenge (AGNSCDC) is a partial prototype of the expected LSST AGN data, aimed at validating machine learning approaches for AGN selection and characterization in large surveys like LSST. The AGNSC-DC took part in 2021 focusing on accuracy, robustness, and scalability. The training and the blinded datasets were constructed to mimic the future LSST release catalogs using the data from the Sloan Digital Sky Survey Stripe 82 region and the XMM-Newton Large Scale Structure Survey region. Data features were divided into astrometry, photometry, color, morphology, redshift and class label with the addition of variability features and images. We present the results of four DC submitted solutions using both classical and machine learning methods. We systematically test the performance of supervised (support vector machine, random forest, extreme gradient boosting, artificial neural network, convolutional neural network) and unsupervised (deep embedding clustering) models when applied to the problem of classifying/clustering sources as stars, galaxies or AGNs. We obtained classification accuracy 97.5% for supervised and clustering accuracy 96.0% for unsupervised models and 95.0% with a classic approach for a blinded dataset. We find that variability features significantly improve the accuracy of the trained models and correlation analysis among different bands enables a fast and inexpensive first order selection of quasar candidatesComment: Accepted by ApJ. 21 pages, 14 figures, 5 table

Hepatitis B Outbreak Among Men Who Have Sex with Men in the Autonomous Province of Vojvodina, Serbia

** From Crossref via Jisc Publications Router.The European Centre for Disease Prevention and Control reported that there were 2896 acute hepatitis B cases in 24 EU/EEA countries in 2013.1 The incidence ranged from 0.1 cases per 100,000 in France and Portugal to 4.3 per 100,000 in Latvia, with a male-to-female ratio of 2.2:1 in EU/EEA countries, and transmission among men who have sex with men (MSM) reported in 9.4% of all cases of acute hepatitis B.1 Some authors consider hepatitis B virus (HBV) infection to be endemic in the MSM population with the incidence 20 times higher in MSM than in the general population worldwide.2 However, data on HBV prevalence among MSM are available for only four EU/EEA countries.3 Six to ten percent of MSM infected with HBV worldwide are co-infected with HIV.4sch_iih5pub4999pub

Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection

ETERNITY I BESKRAJ QUALITY IN AGRICULTURE

This paper examines the evolution of the quality and quantity of the agriculture from the Neolithic to the green revolution. We analyzed the basic Quality factors in agriculture: the man, the four groups agroinovacija, namely : (1) live (cultivated plants and animals), (2) technical (tools), (3) Technology (Operations) and (4) agro as well as environmental conditions. All elemental factors of doing business in agriculture have the potential dvogubog fact: to increase and improve or reduce the extent and jeopardize quality production. In such a paradoxical relationship, man must seek and find those factors that the optimal effect on the sustainable growth of quality production, because its correctness is threatened today gall technology high yield, more in plants than in animals. It has been found that the validity of the process and the amount and quality of the product in agriculture can not be separated

Sulfur retention by ash during coal combustion. Part I. A model of char particle combustion

A model for the combustion of porous char particles as a basis for modeling the process of sulfur retention by ash during coal combustion is developed in this paper. The model belongs to the microscopic intrinsic models and describes the dynamic behavior of a porous char particle during comustion, taking into account temporal and spatial changes of all important physical properties of the char particle and various combustion parameters. The parametric analysis of the enhanced model shows that the model represents a good basis for the development of a model for the process of sulfur retention by ash during coal combustion. The model enables the prediction of the values of all parameters necessary for the introduction of reactions between sulfur compounds and mineral components in ash, primarily calcium oxide

Sulfur self-retention in ash a grain model approach

A developed overall model for sulfur self-retention in ash during coal particle combustion is presented in the paper. The total sulfur content in char, after devolatilization, is evaluated using a derived correlation. It is assumed that sulfur retention during char combustion occurs due to the reaction between SO2 and the active part of the Ca in the form of uniformly distributed CaO grains. Parametric analysis shows that the process is limited by solid diffusion through the product layer formed on the CaO grains and that the most important coal characteristics which influence sulfur self-retention are coal rank, content of sulfur forms, molar Ca/S ratio and particle radius. The model predicts relatively well the levels of the experimentally obtained values of SSR efficiencies, as well as the influence of temperature, particle size and the surrounding conditions

Specific approach for continuous air quality monitoring

Rapid industry development as well as increase of traffic volume across the world have resulted in air quality becoming one of the most important factors of everyday life. Air quality monitoring is the necessary factor for proper decision making regarding air pollution. An integral part of such investigations is the measurement of wind characteristics, as the wind is the most influential factor in turbulent pollution diffusion into the atmosphere. The most of the air pollution originates from combustion processes, so it is important to make quantitative, as well as qualitative analysis, as the sources of pollution can be very distant. In this paper, specific methodology for continuous wind, temperature and air quality data acquisition is presented. Comparison of the measured results is given, as well as the detailed presentation of the characteristics of the acquisition software used