Ahi Evran University

About: Ahi Evran University is a education organization based out in Kırşehir, Turkey. It is known for research contribution in the topics: Density functional theory & Ab initio. The organization has 842 authors who have published 2270 publications receiving 21904 citations.

The dynamic impact of renewable energy consumption on CO2 emissions: A revisited Environmental Kuznets Curve approach

Abstract: This paper considers a revisited Environmental Kuznets Curve (EKC) hypothesis with potential impact of renewable energy consumption on environmental quality. To this end, paper aims at investigating the validity of the EKC hypothesis employing the dependent variable of CO2 emissions and regressors of GDP, quadratic GDP and renewable energy consumption. This paper, hence, analyzes this revisited EKC hypothesis to observe if (i) there exists an inverted-U shaped relationship between environmental quality (in terms of CO2 emissions), per capita income and per capita income squared and (ii) there exists a negative causality from renewables to CO2 emissions within EKC model. Paper employs a panel data set of 17 OECD countries over the period 1977–2010 and launches panel FMOLS and panel DOLS estimations. The findings support the EKC hypothesis for the panel and indicate that GDP per capita and GDP per capita squared have the impacts on CO2 emissions positively and negatively, respectively, and that renewable energy consumption yields negative impact on CO2 emissions. Another remark of this paper is that the validity of EKC does not depend on income level of individual countries of panel in which EKC hypothesis holds. Eventually, paper argues that if countries carry out (i) policies, i.e., for fair and easy access to the electricity from renewable sources and (ii) policies to increase renewables supply through i.e. improved renewable energy technologies, they will be able to contribute to combating global warming problem as they increase their GDP’s.

The Faces of Fungi database: fungal names linked with morphology, phylogeny and human impacts

Abstract: Taxonomic names are key links between various databases that store information on different organisms. Several global fungal nomenclural and taxonomic databases (notably Index Fungorum, Species Fungorum and MycoBank) can be sourced to find taxonomic details about fungi, while DNA sequence data can be sourced from NCBI, EBI and UNITE databases. Although the sequence data may be linked to a name, the quality of the metadata is variable and generally there is no corresponding link to images, descriptions or herbarium material. There is generally no way to establish the accuracy of the names in these genomic databases, other than whether the submission is from a reputable source. To tackle this problem, a new database (FacesofFungi), accessible at www.facesoffungi.org (FoF) has been established. This fungal database allows deposition of taxonomic data, phenotypic details and other useful data, which will enhance our current taxonomic understanding and ultimately enable mycologists to gain better and updated insights into the current fungal classification system. In addition, the database will also allow access to comprehensive metadata including descriptions of voucher and type specimens. This database is user-friendly, providing links and easy access between taxonomic ranks, with the classification system based primarily on molecular data (from the literature and via updated web-based phylogenetic trees), and to a lesser extent on morphological data when molecular data are unavailable. In FoF species are not only linked to the closest phylogenetic representatives, but also relevant data is provided, wherever available, on various applied aspects, such as ecological, industrial, quarantine and chemical uses. The data include the three main fungal groups (Ascomycota, Basidiomycota, Basal fungi) and fungus-like organisms. The FoF webpage is an output funded by the Mushroom Research Foundation which is an NGO with seven directors with mycological expertise. The webpage has 76 curators, and with the help of these specialists, FoF will provide an updated natural classification of the fungi, with illustrated accounts of species linked to molecular data. The present paper introduces the FoF database to the scientific community and briefly reviews some of the problems associated with classification and identification of the main fungal groups. The structure and use of the database is then explained. We would like to invite all mycologists to contribute to these web pages.

Outline of Fungi and fungus-like taxa

Abstract: This article provides an outline of the classification of the kingdom Fungi (including fossil fungi. i.e. dispersed spores, mycelia, sporophores, mycorrhizas). We treat 19 phyla of fungi. These are Aphelidiomycota, Ascomycota, Basidiobolomycota, Basidiomycota, Blastocladiomycota, Calcarisporiellomycota, Caulochytriomycota, Chytridiomycota, Entomophthoromycota, Entorrhizomycota, Glomeromycota, Kickxellomycota, Monoblepharomycota, Mortierellomycota, Mucoromycota, Neocallimastigomycota, Olpidiomycota, Rozellomycota and Zoopagomycota. The placement of all fungal genera is provided at the class-, order- and family-level. The described number of species per genus is also given. Notes are provided of taxa for which recent changes or disagreements have been presented. Fungus-like taxa that were traditionally treated as fungi are also incorporated in this outline (i.e. Eumycetozoa, Dictyosteliomycetes, Ceratiomyxomycetes and Myxomycetes). Four new taxa are introduced: Amblyosporida ord. nov. Neopereziida ord. nov. and Ovavesiculida ord. nov. in Rozellomycota, and Protosporangiaceae fam. nov. in Dictyosteliomycetes. Two different classifications (in outline section and in discussion) are provided for Glomeromycota and Leotiomycetes based on recent studies. The phylogenetic reconstruction of a four-gene dataset (18S and 28S rRNA, RPB1, RPB2) of 433 taxa is presented, including all currently described orders of fungi.

Synthesis optimization and characterization of chitosan-coated iron oxide nanoparticles produced for biomedical applications

Abstract: The chitosan-coated magnetic nanoparticles (CS MNPs) were in situ synthesized by cross-linking method. In this method; during the adsorption of cationic chitosan molecules onto the surface of anionic magnetic nanoparticles (MNPs) with electrostatic interactions, tripolyphosphate (TPP) is added for ionic cross-linking of the chitosan molecules with each other. The characterization of synthesized nanoparticles was performed by X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS/ESCA), Fourier transform infrared spectroscopy (FTIR), transmission electron microscopy (TEM), dynamic light scattering (DLS), thermal gravimetric analysis (TGA), and vibrating sample magnetometry (VSM) analyses. The XRD and XPS analyses proved that the synthesized iron oxide was magnetite (Fe3O4). The layer of chitosan on the magnetite surface was confirmed by FTIR. TEM results demonstrated a spherical morphology. In the synthesis, at higher NH4OH concentrations, smaller sized nanoparticles were obtained. The average diameters were generally between 2 and 8 nm for CS MNPs in TEM and between 58 and 103 nm in DLS. The average diameters of bare MNPs were found as around 18 nm both in TEM and DLS. TGA results indicated that the chitosan content of CS MNPs were between 15 and 23 % by weight. Bare and CS MNPs were superparamagnetic. These nanoparticles were found non-cytotoxic on cancer cell lines (SiHa, HeLa). The synthesized MNPs have many potential applications in biomedicine including targeted drug delivery, magnetic resonance imaging (MRI), and magnetic hyperthermia.