Showing papers by "Romanian Academy published in 2016"

Variational Methods for Nonlocal Fractional Problems

Abstract: This book provides researchers and graduate students with a thorough introduction to the variational analysis of nonlinear problems described by nonlocal operators. The authors give a systematic treatment of the basic mathematical theory and constructive methods for these classes of nonlinear equations, plus their application to various processes arising in the applied sciences. The equations are examined from several viewpoints, with the calculus of variations as the unifying theme. Part I begins the book with some basic facts about fractional Sobolev spaces. Part II is dedicated to the analysis of fractional elliptic problems involving subcritical nonlinearities, via classical variational methods and other novel approaches. Finally, Part III contains a selection of recent results on critical fractional equations. A careful balance is struck between rigorous mathematics and physical applications, allowing readers to see how these diverse topics relate to other important areas, including topology, functional analysis, mathematical physics, and potential theory.

The implications of oxidative stress and antioxidant therapies in Inflammatory Bowel Disease: Clinical aspects and animal models

Abstract: Inflammatory bowel disease (IBD), including Crohn's disease (CD) and ulcerative colitis (UC), is a chronic inflammatory disorder characterized by alternating phases of clinical relapse and remission. The etiology of IBD remains largely unknown, although a combination of patient's immune response, genetics, microbiome, and environment plays an important role in disturbing intestinal homeostasis, leading to development and perpetuation of the inflammatory cascade in IBD. As chronic intestinal inflammation is associated with the formation of reactive oxygen and reactive nitrogen species (ROS and RNS), oxidative and nitrosative stress has been proposed as one of the major contributing factor in the IBD development. Substantial evidence suggests that IBD is associated with an imbalance between increased ROS and decreased antioxidant activity, which may explain, at least in part, many of the clinical pathophysiological features of both CD and UC patients. Hereby, we review the presently known oxidant and antioxidant mechanisms involved in IBD-specific events, the animal models used to determine these specific features, and also the antioxidant therapies proposed in IBD patients.

Galaxy And Mass Assembly: accurate panchromatic photometry from optical priors using lambdar

Abstract: We present the Lambda Adaptive Multi-Band Deblending Algorithm in R (LAMBDAR), a novel code for calculating matched aperture photometry across images that are neither pixel- nor PSF-matched, using prior aperture definitions derived from high resolution optical imaging. The development of this program is motivated by the desire for consistent photometry and uncertainties across large ranges of photometric imaging, for use in calculating spectral energy distributions. We describe the program, specifically key features required for robust determination of panchromatic photometry: propagation of apertures to images with arbitrary resolution, local background estimation, aperture normalisation, uncertainty determination and propagation, and object deblending. Using simulated images, we demonstrate that the program is able to recover accurate photometric measurements in both high-resolution, low-confusion, and low-resolution, high-confusion, regimes. We apply the program to the 21-band photometric dataset from the Galaxy And Mass Assembly (GAMA) Panchromatic Data Release (PDR; Driver et al. 2016), which contains imaging spanning the far-UV to the far-IR. We compare photometry derived from LAMBDAR with that presented in Driver et al. (2016), finding broad agreement between the datasets. Nonetheless, we demonstrate that the photometry from LAMBDAR is superior to that from the GAMA PDR, as determined by a reduction in the outlier rate and intrinsic scatter of colours in the LAMBDAR dataset. We similarly find a decrease in the outlier rate of stellar masses and star formation rates using LAMBDAR photometry. Finally, we note an exceptional increase in the number of UV and mid-IR sources able to be constrained, which is accompanied by a significant increase in the mid-IR colour-colour parameter-space able to be explored.

GAMA/H-ATLAS: a meta-analysis of SFR indicators – comprehensive measures of the SFR–M* relation and cosmic star formation history at z < 0.4

Abstract: We present a meta-analysis of star-formation rate (SFR) indicators in the GAMA survey, producing 12 different SFR metrics and determining the SFR-M* relation for each. We compare and contrast published methods to extract the SFR from each indicator, using a well-defined local sample of morphologically-selected spiral galaxies, which excludes sources which potentially have large recent changes to their SFR. The different methods are found to yield SFR-M* relations with inconsistent slopes and normalisations, suggesting differences between calibration methods. The recovered SFR-M* relations also have a large range in scatter which, as SFRs of the targets may be considered constant over the different timescales, suggests differences in the accuracy by which methods correct for attenuation in individual targets. We then recalibrate all SFR indicators to provide new, robust and consistent luminosity-to-SFR calibrations, finding that the most consistent slopes and normalisations of the SFR-M* relations are obtained when recalibrated using the radiation transfer method of Popescu et al. These new calibrations can be used to directly compare SFRs across different observations, epochs and galaxy populations. We then apply our calibrations to the GAMA II equatorial dataset and explore the evolution of star-formation in the local Universe. We determine the evolution of the normalisation to the SFR-M* relation from 0 < z < 0.35 - finding consistent trends with previous estimates at 0.3 < z < 1.2. We then provide the definitive z < 0.35 Cosmic Star Formation History, SFR-M* relation and its evolution over the last 3 billion years.

Applying Dijkstra algorithm for solving neutrosophic shortest path problem

Abstract: The selection of shortest path problem is one the classic problems in graph theory. In literature, many algorithms have been developed to provide a solution for shortest path problem in a network. One of common algorithms in solving shortest path problem is Dijkstra's algorithm. In this paper, Dijkstra's algorithm has been redesigned to handle the case in which most of parameters of a network are uncertain and given in terms of neutrosophic numbers. Finally, a numerical example is given to explain the proposed algorithm.

Urinary Biomarkers in the Assessment of Early Diabetic Nephropathy

Abstract: Diabetic nephropathy (DN) is a frequent and severe complication of diabetes mellitus (DM). Its diagnosis in incipient stages may allow prompt interventions and an improved prognosis. Towards this aim, biomarkers for detecting early DN can be used. Microalbuminuria has been proven a remarkably useful biomarker, being used for diagnosis of DN, for assessing its associated condition—mainly cardiovascular ones—and for monitoring its progression. New researches are pointing that some of these biomarkers (i.e., glomerular, tubular, inflammation markers, and biomarkers of oxidative stress) precede albuminuria in some patients. However, their usefulness is widely debated in the literature and has not yet led to the validation of a new “gold standard” biomarker for the early diagnosis of DN. Currently, microalbuminuria is an important biomarker for both glomerular and tubular injury. Other glomerular biomarkers (transferrin and ceruloplasmin) are under evaluation. Tubular biomarkers in DN seem to be of a paramount importance in the early diagnosis of DN since tubular lesions occur early. Additionally, biomarkers of inflammation, oxidative stress, podocyte biomarkers, and vascular biomarkers have been employed for assessing early DN. The purpose of this review is to provide an overview of the current biomarkers used for the diagnosis of early DN.

Multiplicity of solutions for a class of quasilinear Kirchhoff system involving the fractional p-Laplacian

Abstract: In this paper, we investigate the multiplicity of solutions for a p-Kirchhoff system driven by a nonlocal integro-differential operator with zero Dirichlet boundary data. As a special case, we consider the following fractional p-Kirchhoff system {(∑i=1k[ui]s,pp)θ−1(−Δ)psuj(x)=λj|uj|q−2uj+∑i≠jβij|ui|m|uj|m−2ujin Ω,uj=0in RN\Ω, where , , , , is an open bounded subset of with Lipschitz boundary , N > ps with , is the fractional p-Laplacian, and for , . When and for all , two distinct solutions are obtained by using the Nehari manifold method. When and for all or and for all , the existence of infinitely many solutions is obtained by applying the symmetric mountain pass theorem. To our best knowledge, our results for the above system are new in the study of Kirchhoff problems.

How Hard Can It Be? Estimating the Difficulty of Visual Search in an Image

Abstract: We address the problem of estimating image difficulty defined as the human response time for solving a visual search task. We collect human annotations of image difficulty for the PASCAL VOC 2012 data set through a crowd-sourcing platform. We then analyze what human interpretable image properties can have an impact on visual search difficulty, and how accurate are those properties for predicting difficulty. Next, we build a regression model based on deep features learned with state of the art convolutional neural networks and show better results for predicting the groundtruth visual search difficulty scores produced by human annotators. Our model is able to correctly rank about 75% image pairs according to their difficulty score. We also show that our difficulty predictor generalizes well to new classes not seen during training. Finally, we demonstrate that our predicted difficulty scores are useful for weakly supervised object localization (8% improvement) and semi-supervised object classification (1% improvement).

Galaxy And Mass Assembly (GAMA): M*-Re relations of z = 0 bulges, discs and spheroids

Abstract: We perform automated bulge + disc decomposition on a sample of ~7500 galaxies from the Galaxy And Mass Assembly (GAMA) survey in the redshift range of 0.002

Role of MicroRNA in Endothelial Dysfunction and Hypertension

Abstract: Purpose of Review Hypertension is either a cause or a consequence of the endothelial dysfunction and a major risk factor for cardiovascular disease (CVD). In vitro and in vivo studies established that microRNAs (miRNAs) are decisive for endothelial cell gene expression and function in various pathological conditions associated with CVD. This review provides an overview of the miRNA role in controlling the key connections between endothelial dysfunction and hypertension.

Tracing the influence of Mediterranean climate on Southeastern Europe during the past 350,000 years

Abstract: Loess-palaeosol sequences are valuable archives of past environmental changes. Although regional palaeoclimatic trends and conditions in Southeastern Europe have been inferred from loess sequences, large scale forcing mechanisms responsible for their formation have yet to be determined. Southeastern Europe is a climatically sensitive region, existing under the strong influence of both Mediterranean and continental climates. Establishment of the spatial and temporal evolution and interaction of these climatic areas is essential to understand the mechanisms of loess formation. Here we present high-resolution grain-size, environmental magnetic, spectrophotometric and geochemical data from the Stalac section in the Central Balkans (Serbia) for the past ~350,000 years. The goal of this study is to determine the influence of the Mediterranean climate during this period. Data show that the Central Balkans were under different atmospheric circulation regimes, especially during Marine Isotope Stages 9 and 7, while continental climate prevailed further north. We observe a general weakening of the Mediterranean climate influence with time. Our data suggest that Marine Isotope Stage 5 was the first interglacial in the Central Balkans that had continental climate characteristics. This prominent shift in climatic conditions resulted in unexpectedly warm and humid conditions during the last glacial.

Galaxy And Mass Assembly (GAMA): stellar mass growth of spiral galaxies in the cosmic web

Abstract: We look for correlated changes in stellar mass and star formation rate (SFR) along filaments in the cosmic web by examining the stellar masses and UV-derived SFRs of 1799 ungrouped and unpaired spiral galaxies that reside in filaments. We devise multiple distance metrics to characterize the complex geometry of filaments, and find that galaxies closer to the cylindrical centre of a filament have higher stellar masses than their counterparts near the periphery of filaments, on the edges of voids. In addition, these peripheral spiral galaxies have higher SFRs at a given mass. Complementing our sample of filament spiral galaxies with spiral galaxies in tendrils and voids, we find that the average SFR of these objects in different large-scale environments are similar to each other with the primary discriminant in SFR being stellar mass, in line with previous works. However, the distributions of SFRs are found to vary with large-scale environment. Our results thus suggest a model in which in addition to stellar mass as the primary discriminant, the large-scale environment is imprinted in the SFR as a second-order effect. Furthermore, our detailed results for filament galaxies suggest a model in which gas accretion from voids on to filaments is primarily in an orthogonal direction. Overall, we find our results to be in line with theoretical expectations of the thermodynamic properties of the intergalactic medium in different large-scale environments.

Semantic Video Segmentation by Gated Recurrent Flow Propagation

Abstract: Semantic video segmentation is challenging due to the sheer amount of data that needs to be processed and labeled in order to construct accurate models. In this paper we present a deep, end-to-end trainable methodology to video segmentation that is capable of leveraging information present in unlabeled data in order to improve semantic estimates. Our model combines a convolutional architecture and a spatio-temporal transformer recurrent layer that are able to temporally propagate labeling information by means of optical flow, adaptively gated based on its locally estimated uncertainty. The flow, the recognition and the gated temporal propagation modules can be trained jointly, end-to-end. The temporal, gated recurrent flow propagation component of our model can be plugged into any static semantic segmentation architecture and turn it into a weakly supervised video processing one. Our extensive experiments in the challenging CityScapes and Camvid datasets, and based on multiple deep architectures, indicate that the resulting model can leverage unlabeled temporal frames, next to a labeled one, in order to improve both the video segmentation accuracy and the consistency of its temporal labeling, at no additional annotation cost and with little extra computation.

Green Synthesis Methods of CoFe2O4 and Ag-CoFe2O4 Nanoparticles Using Hibiscus Extracts and Their Antimicrobial Potential

Abstract: The cobalt ferrite CoFe2O4 and silver-cobalt ferrite Ag-CoFe2O4 nanoparticles were obtained through self-combustion and wet ferritization methods using aqueous extracts of Hibiscus rosa-sinensis flower and leaf. X-ray diffraction, scanning electron microscopy, Fourier transform infrared spectroscopy, and magnetic measurements were used for the characterization of the obtained oxide powders. The antimicrobial activity of the cobalt ferrite and silver-cobalt ferrite nanoparticles against Gram-positive and Gram-negative bacteria, as well as fungal strains, was investigated by qualitative and quantitative assays. The most active proved to be the Ag-CoFe2O4 nanoparticles, particularly those obtained through self-combustion using hibiscus leaf extract, which exhibited very low minimal inhibitory concentration values 0.031–0.062 mg/mL against all tested microbial strains, suggesting their potential for the development of novel antimicrobial agents.

Variations in the expression of TIMP1, TIMP2 and TIMP3 in cutaneous melanoma with regression and their possible function as prognostic predictors.

Abstract: Regression in melanoma is a frequent biological event of uncertain prognostic value as the lesion exhibits heterogeneous phenotypical features, both at the morphological and immunohistochemical level. In the present study, we examined the expression of tissue inhibitors of metalloproteinases (TIMP1, TIMP2 and TIMP3) in melanoma with regression. We specifically examined the expression levels of these TIMPs in regressed components (RC) and non-regressed components (NRC) of the tumor and compared their expression levels with those in non-regressed melanomas. We found that TIMP1 was overexpressed in the NRC of melanomas with partial regression (PR) compared with the NRC in melanomas with segmental regression (SR) (P=0.011). TIMP2 was overexpressed in the NRC of melanomas with PR compared with the NRC in melanomas with SR (PR/SR, P=0.009); or compared with the NRC in melanomas with simultaneous SR-PR (P=0.002); or compared with melanomas without regression (absence of regression) (P=0.037). Moreover, TIMP3 was overexpressed in the NRC of all melanomas with SR as compared to the RC component (P=0.007). Our findings on the differential expression of TIMP1, TIMP2 and TIMP3 in melanomas with regression support the hypothesis that the morphological differences identified in the melanoma regression spectrum may have a correlation with prognosis. This may explain the controversial findings within the literature concerning the biological and prognostic role of regression in melanoma.

An institutional theory of the informal economy: some lessons from the United Kingdom

Abstract: Purpose – The purpose of this paper is to propose a new way of explaining participation in the informal economy as resulting from the asymmetry between the codified laws and regulations of a society’s formal institutions (government morality) and the norms, values and beliefs of the population that constitute its informal institutions (societal morality). The proposition is that the greater the asymmetry between government morality and societal morality, the greater is the propensity to participate in the informal economy. Design/methodology/approach – To evaluate this institutional asymmetry theory, the results are reported of 1,306 face-to-face interviews conducted during 2013 in the UK. Findings – The finding is a strong correlation between the degree of institutional asymmetry (measured by tax morale) and participation in the informal economy. The lower the tax morale, the greater is the propensity to participate in the informal economy. Using ordered logistic regression analysis, tax morale is not fo...