Investigating some microbial pollution parameters of seawater and mussels (Mytilus galloprovincialis, Lamarck 1819) of sіnop Black Sea Coastal Zone, Turkey

The presence of coliforms bacteria is one of the most prevalent problems in terms of public health in marine ecosystems over the world. In this study were investigated the physico-chemical properties of seawater and the numbers of total aerobic, total coliform, fecal coliform, E. coli O157:H7 and fecal streptococci in seawater and mussel samples collected from Sinop environs between May and October 2011. The microbiological analysis of seawater samples showed that the difference between total coliform, fecal coliform and fecal streptococci numbers (p0.05) were not found significant. The difference between whole counting results for mussel samples taken from different sampling sites was not significant (p>0.05), too. Furthermore, the results of the screening assay for the presence of E. coli O157:H7 showed that the strain was not detected in neither seawater nor mussel samples. In conclusion, it was determined that fecal coliform and fecal streptococci counts in the seawater and mussel samples were higher than legal (Turkish Bathing Water and Quality of Fishery Products Regulation) limit values for some stations in Sinop coastal areas

Antimicrobial and antioxidant activities of medicinal plant Glycyrrhiza glabra var. glandulifera from different habitats

In this study, the antimicrobial and antioxidant activities of root methanolic extracts of Glycyrrhiza glabra var. glandulifera (Waldst. & Kit.) Boiss. (Fabaceae) were investigated. Plant samples were collected from different habitats in the East Mediterranean part of Turkey. The plant extracts were evaluated for antimicrobial activities against nine bacterial and two yeast strains using disc-diffusion and minimum inhibitory concentration methods. The antioxidant activity was determined by using the DPPH (1,1-diphenyl-2-picrylhydrazyl) method. The antimicrobial assays indicated that the plant root extracts were more effective against Gram-positive bacteria than against Gram-negative ones. In addition, the extracts had higher antimicrobial effect against Candida species than against bacteria. The extracts showed good antioxidant activity, with a median inhibitory concentration (IC50) in the range of 588 ± 0.86 µg/mL to 2190 ± 1.73 µg/mL. Results indicated that different environmental conditions in each habitat might affect the contents of chemical compounds and biological activity in the natural licorice populations of. This study also supported the traditional use of licorice and as well as suggested that it may also be its beneficial role in the treatment of other infections. The obtained results indicated that different environmental conditions in each habitat might affect the contents of chemical compounds and the biological activity in the natural licorice populations

Semantic Segmentation of High-Resolution Airborne Images with Dual-Stream DeepLabV3+

In geospatial applications such as urban planning and land use management, automatic detection and classification of earth objects are essential and primary subjects. When the significant semantic segmentation algorithms are considered, DeepLabV3+ stands out as a state-of-the-art CNN. Although the DeepLabV3+ model is capable of extracting multi-scale contextual information, there is still a need for multi-stream architectural approaches and different training approaches of the model that can leverage multi-modal geographic datasets. In this study, a new end-to-end dual-stream architecture that considers geospatial imagery was developed based on the DeepLabV3+ architecture. As a result, the spectral datasets other than RGB provided increments in semantic segmentation accuracies when they were used as additional channels to height information. Furthermore, both the given data augmentation and Tversky loss function which is sensitive to imbalanced data accomplished better overall accuracies. Also, it has been shown that the new dual-stream architecture using Potsdam and Vaihingen datasets produced 88.87% and 87.39% overall semantic segmentation accuracies, respectively. Eventually, it was seen that enhancement of the traditional significant semantic segmentation networks has a great potential to provide higher model performances, whereas the contribution of geospatial data as the second stream to RGB to segmentation was explicitly shown

Semantic Segmentation of High-Resolution Airborne Images with Dual-Stream DeepLabV3+

In geospatial applications such as urban planning and land use management, automatic detection and classification of earth objects are essential and primary subjects. When the significant semantic segmentation algorithms are considered, DeepLabV3+ stands out as a state-of-the-art CNN. Although the DeepLabV3+ model is capable of extracting multi-scale contextual information, there is still a need for multi-stream architectural approaches and different training approaches of the model that can leverage multi-modal geographic datasets. In this study, a new end-to-end dual-stream architecture that considers geospatial imagery was developed based on the DeepLabV3+ architecture. As a result, the spectral datasets other than RGB provided increments in semantic segmentation accuracies when they were used as additional channels to height information. Furthermore, both the given data augmentation and Tversky loss function which is sensitive to imbalanced data accomplished better overall accuracies. Also, it has been shown that the new dual-stream architecture using Potsdam and Vaihingen datasets produced 88.87% and 87.39% overall semantic segmentation accuracies, respectively. Eventually, it was seen that enhancement of the traditional significant semantic segmentation networks has a great potential to provide higher model performances, whereas the contribution of geospatial data as the second stream to RGB to segmentation was explicitly shown

Determining the Effects of Some Bacteria on Wooden Toys Treated with Antibacterial Protective Coatings

Several protective coatings enhanced by antimicrobial agents and/or pigments were considered for the wooden toy market: water-based matte varnish, an ultra-hygiene water-based matte varnish (WBV-UH), a polyurethane matte varnish (PUV), and an ultra-hygiene antiviral polyurethane matte varnish (PUV-UH), as well as a water-based dye (WBV 5%K), an ultra-hygiene water-based dye (WBV-UH 5%K), a polyurethane dye (PUV 5%K), and an ultra-hygiene polyurethane dye (PUV-UH 5%K), which contain 5% red nano-pigment (K). By utilizing 7 kinds of bacteria and 2 types of yeast that are commonly detected in routine, daily settings, the efficacy of the different protective coatings on wooden toy surface was investigated. The antibacterial and antimicrobial activities of the tested dye samples were based on the agar-well diffusion method. Ultimately, the study found that the addition of antimicrobial agents to several different protective coatings and dyes resulted in the presence of antimicrobial activity vs. the lack thereof with protective coatings and dyes alone. Additionally, some of the dyes with added antimicrobial agents were found to be effective against biofilm formation. Overall, the addition of pigment into the coating, alongside the addition of antimicrobial agents, proved to be highly effective in inhibiting growth and spread of microorganisms on wooden toy surface