Identification of source areas of polycyclic aromatic hydrocarbons in Ulsan, South Korea, using hybrid receptor models and the conditional bivariate probability function

This study identifies the emission source areas for the atmospheric polycyclic aromatic hydrocarbons (PAHs) detected in Ulsan, South Korea. To achieve this, in addition to a conditional bivariate probability function...

Automated glaucoma detection from fundus images using wavelet-based denoising and machine learning

Glaucoma is a domineering and irretrievable neurodegenerative eye disease produced by the optical nerve head owed to extended intra-ocular stress inside the eye. Recognition of glaucoma is an essential job for ophthalmologists. In this paper, we propose a methodology to classify fundus images into normal and glaucoma categories. The proposed approach makes use of image denoising of digital fundus images by utilizing a non-Gaussian bivariate probability distribution function to model the statistics of wavelet coefficients of glaucoma images. The traditional image features were extracted followed by the popular feature selection algorithm. The selected features are then fed to the least square support vector machine classifier employing various kernel functions. The comparison result shows that the proposed approach offers maximum classification accuracy of nearly 91.22% over the existing best approaches.

Assessing internal changes in the future structure of dry–hot compound events: the case of the Pyrenees

Impacts upon vulnerable areas such as mountain ranges may become greater under a future scenario of adverse climatic conditions. In this sense, the concurrence of long dry spells and extremely hot temperatures can induce environmental risks such as wildfires, crop yield losses or other problems, the consequences of which could be much more serious than if these events were to occur separately in time (e.g. only long dry spells). The present study attempts to address recent and future changes in the following dimensions: duration (D), magnitude (M) and extreme magnitude (EM) of compound dry–hot events in the Pyrenees. The analysis focuses upon changes in the extremely long dry spells and extremely high temperatures that occur within these dry periods in order to estimate whether the internal structure of the compound event underwent a change in the observed period (1981–2015) and whether it will change in the future (2006–2100) under intermediate (RCP4.5, where RCP is representative concentration pathway) and high (RCP8.5) emission scenarios. To this end, we quantified the changes in the temporal trends of such events, as well as changes in the bivariate probability density functions for the main Pyrenean regions. The results showed that to date the risk of the compound event has increased by only one dimension – magnitude (including extreme magnitude) – during the last few decades. In relation to the future, increase in risk was found to be associated with an increase in both the magnitude and the duration (extremely long dry spells) of the compound event throughout the Pyrenees during the spring under RCP8.5 and in the northernmost part of this mountain range during summer under this same scenario.

Method for quantitative assessment of protective immunity against SARS-CoV-2, its duration and antibody dynamics

The level and duration of protective immunity are often analyzed qualitatively or semi-quantitatively. The same strategy is applied to the analysis of antibody dynamics. At some point in time t after exposure or immunization, the presence of immunity against the infection is inferred from the level of specific antibodies by comparing it to a reference value. This approach does not account for the stochastic nature of human disease after exposure to a pathogen. At the same time, it is not fully clear what antibody level should be considered protective. The aim of this study was to develop a mathematical model for quantitative determination of protective immunity against SARS-CoV-2 and its duration. We demonstrate that the problem of describing protective immunity in quantitative terms can be broken down into 2 interrelated problems: describing the quantitative characteristics of a pathogen’s virulence (in our case, the pathogen is SARS-CoV-2) and describing the dynamics of antibody titers in a biological organism. Below, we provide solutions for these problems and identify parameters of the model which describes such dynamics. Using the proposed model, we offer a theoretical solution to the problem of protective immunity and its duration. We also note that in order to quantitatively determine the studied parameters in a homogenous population group, it is necessary to know 5 parameters of the bivariate probability density function for correlated continuous random variables: the infective dose of the pathogen and the antibody titer at which the disease develops and which are still unknown.

Assessing internal changes in the future structure of Dry-Hot compound events. The case of the Pyrenees

Impacts upon vulnerable areas such as mountain ranges may become greater under a future scenario of adverse climatic conditions. In this sense, the concurrence of long dry spells and extremely hot temperatures can induce environmental risks such as wildfires, crop yield losses or other problems, the consequences of which could be much more serious than if these events were to occur separately in time (e.g. only long dry spells). The present study attempts to address recent and future changes in the following dimensions: duration (D), magnitude (M) and extreme magnitude (EM) of compound Dry-Hot events in the Pyrenees. The analysis focuses upon changes in the extremely long dry spells and extremely high temperatures that occur within these dry periods, in order to estimate whether the internal structure of the compound event underwent a change in the observed period (1981–2015) and whether it will change in the future (2011–2100) under intermediate (RCP4.5) and high (RCP8.5) emission scenarios. To this end, we quantified the changes in the temporal trends of such events, as well as changes in the bivariate probability density functions for the main Pyrenean regions. The results showed that to date the risk of the compound event has increased by only one dimension –magnitude (including extreme magnitude) – during the last few decades. In relation to the future, increased in risk was found to be associated with an increase both in the magnitude and the duration (extremely long dry spells) of the compound event, mainly in the eastern and southern regions of the Pyrenees.