University of the Aegean

About: University of the Aegean is a education organization based out in Mytilene, Greece. It is known for research contribution in the topics: Population & Context (language use). The organization has 2818 authors who have published 8100 publications receiving 179275 citations. The organization is also known as: UAEG.

Occurrence patterns of pharmaceuticals in water and wastewater environments

Abstract: The occurrence of pharmaceuticals and their metabolites and transformation products in the environment is becoming a matter of concern, because these compounds, which may have adverse effects on living organisms, are extensively and increasingly used in human and veterinary medicine and are released continuously into the environment. A variety of pharmaceuticals have been detected in many environmental samples worldwide. Their occurrence has been reported in sewage-treatment-plant effluents, surface water, seawater, groundwater, soil, sediment and fish. This paper provides an overview of recent scientific research on the sources, occurrence, and fate of pharmaceuticals in water and wastewater.

Pharmaceutical residues in environmental waters and wastewater: current state of knowledge and future research

Abstract: Pollution from pharmaceuticals in the aquatic environment is now recognized as an environmental concern in many countries. This has led to the creation of an extensive area of research, including among others: their chemical identification and quantification; elucidation of transformation pathways when present in wastewater-treatment plants or in environmental matrices; assessment of their potential biological effects; and development and application of advanced treatment processes for their removal and/or mineralization. Pharmaceuticals are a unique category of pollutants, because of their special characteristics, and their behavior and fate cannot be simulated with other chemical organic contaminants. Over the last decade the scientific community has embraced research in this specific field and the outcome has been immense. This was facilitated by advances in chromatographic techniques and relevant biological assays. Despite this, a number of unanswered questions exist and still there is much room for development and work towards a more solid understanding of the actual consequences of the release of pharmaceuticals in the environment. This review tries to present part of the knowledge that is currently available with regard to the occurrence of pharmaceutical residues in aquatic matrices, the progress made during the last several years on identification of such compounds down to trace levels, and of new, previously unidentified, pharmaceuticals such as illicit drugs, metabolites, and photo-products. It also tries to discuss the main recent findings in respect of the capacity of various treatment technologies to remove these contaminants and to highlight some of the adverse effects that may be related to their ubiquitous existence. Finally, socioeconomic measures that may be able to hinder the introduction of such compounds into the environment are briefly discussed.

A License Plate-Recognition Algorithm for Intelligent Transportation System Applications

Abstract: In this paper, a new algorithm for vehicle license plate identification is proposed, on the basis of a novel adaptive image segmentation technique (sliding concentric windows) and connected component analysis in conjunction with a character recognition neural network. The algorithm was tested with 1334 natural-scene gray-level vehicle images of different backgrounds and ambient illumination. The camera focused in the plate, while the angle of view and the distance from the vehicle varied according to the experimental setup. The license plates properly segmented were 1287 over 1334 input images (96.5%). The optical character recognition system is a two-layer probabilistic neural network (PNN) with topology 108-180-36, whose performance for entire plate recognition reached 89.1%. The PNN is trained to identify alphanumeric characters from car license plates based on data obtained from algorithmic image processing. Combining the above two rates, the overall rate of success for the license-plate-recognition algorithm is 86.0%. A review in the related literature presented in this paper reveals that better performance (90% up to 95%) has been reported, when limitations in distance, angle of view, illumination conditions are set, and background complexity is low

Measuring bee diversity in different european habitats and biogeographical regions

Abstract: Bee pollinators are currently recorded with many different sampling methods. However, the relative performances of these methods have not been systematically evaluated and compared. In response to the strong need to record ongoing shifts in pollinator diversity and abundance, global and regional pollinator initiatives must adopt standardized sampling protocols when developing large-scale and long-term monitoring schemes. We systematically evaluated the performance of six sampling methods (observation plots, pan traps, standardized and variable transect walks, trap nests with reed internodes or paper tubes) that are commonly used across a wide range of geographical regions in Europe and in two habitat types (agricultural and seminatural). We focused on bees since they represent the most important pollinator group worldwide. Several characteristics of the methods were considered in order to evaluate their performance in assessing bee diversity: sample coverage, observed species richness, species richness estimators, collector biases (identified by subunit-based rarefaction curves), species composition of the samples, and the indication of overall bee species richness (estimated from combined total samples). The most efficient method in all geographical regions, in both the agricultural and seminatural habitats, was the pan trap method. It had the highest sample coverage, collected the highest number of species, showed negligible collector bias, detected similar species as the transect methods, and was the best indicator of overall bee species richness. The transect methods were also relatively efficient, but they had a significant collector bias. The observation plots showed poor performance. As trap nests are restricted to cavity-nesting bee species, they had a naturally low sample coverage. However, both trap nest types detected additional species that were not recorded by any of the other methods. For large-scale and long-term monitoring schemes with surveyors with different experience levels, we recommend pan traps as the most efficient, unbiased, and cost-effective method for sampling bee diversity. Trap nests with reed internodes could be used as a complementary sampling method to maximize the numbers of collected species. Transect walks are the principal method for detailed studies focusing on plant-pollinator associations. Moreover, they can be used in monitoring schemes after training the surveyors to standardize their collection skills.