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<title>Rektörlüğe Bağlı Birimler</title>
<link>https://hdl.handle.net/20.500.12809/6</link>
<description>Other Units</description>
<pubDate>Fri, 03 Jul 2026 15:31:20 GMT</pubDate>
<dc:date>2026-07-03T15:31:20Z</dc:date>
<item>
<title>Grey water footprint of pharmaceuticals and personal care products discharged via urban wastewater</title>
<link>https://hdl.handle.net/20.500.12809/11241</link>
<description>Grey water footprint of pharmaceuticals and personal care products discharged via urban wastewater
Stejskalova, Lada; Ansorge, Libor; Rosendorf, Pavel; Fiala, Daniel; hernysh, Yelizaveta
Urban wastewater is a significant source of micro- and macropollutants in aquatic ecosystems, posing a high potential risk to drinking water sources. Pharmaceuticals and personal care products (PPCPs) are widely recognized as contaminants of emerging concern, although their relative burden compared to traditional pollutants remains insufficiently quantified. This study presents a comprehensive assessment of 92 micropollutants together with conventional pollution represented by nutrients and organic pollutants across 19 municipalities in the catchment of the largest Czech drinking water reservoir. More than one hundred 24-hour composite measurements were analysed. The Grey Water Footprint methodology integrates ecotoxicological thresholds, enabling a consistent comparison across PPCPs, nutrients, and organic pollution. Results reveal that the most critical micropollutants released from centralized wastewater treatment plants are Ibuprofen or Diclofenac, depending on treatment technology and plant size. However, nitrogen remains the dominant stressor approximately one kilometer downstream of urban discharges. These findings highlight that despite the increasing attention to micropollutants, conventional pollutants still account for the largest share of pollution in recipients. The methodological framework applied in this study allows stakeholders to compare the risks of different types of pollutants in a specific region. It offers a transferable tool for prioritizing contaminants and treatments, and guiding local wastewater management strategies under the EU Water Framework Directive, risk assessments under the revised Urban Wastewater Treatment Directive, and beyond.
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<pubDate>Thu, 01 Jan 2026 00:00:00 GMT</pubDate>
<guid isPermaLink="false">https://hdl.handle.net/20.500.12809/11241</guid>
<dc:date>2026-01-01T00:00:00Z</dc:date>
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<item>
<title>ASSESSMENT OF METAL CONTAMINATION AND ASSOCIATED ECOLOGICAL AND HEALT RISKS IN CREEKS DISCHARGING INTO GOKOVA BAY, TURKİYE</title>
<link>https://hdl.handle.net/20.500.12809/11221</link>
<description>ASSESSMENT OF METAL CONTAMINATION AND ASSOCIATED ECOLOGICAL AND HEALT RISKS IN CREEKS DISCHARGING INTO GOKOVA BAY, TURKİYE
Genç, Tuncer Okan; Yılmaz, Fevzi; Yılmaz, Ersin; Yıldız, Dilek; Kabanka, Göktuğ
This study presents a comprehensive assessment of metal contamination and associated ecological and human health risks in three freshwater systems (Azmak, Ak &amp; ccedil;ap &amp; imath;nar, and &amp; Ccedil;etibeli Creeks) discharging into G &amp; ouml;kova Bay, a Special Environmental Protection Area on the southwestern coast of T &amp; uuml;rkiye. Surface water and sediment samples were collected monthly from six stations between April 2023 and March 2024, and concentrations of Fe, Cu, Mn, Zn, and Cd were determined using atomic absorption spectrometry. Sediment contamination was evaluated using the Contamination Factor (CF), Enrichment Factor (EF), Geoaccumulation Index (Igeo), and Potential Ecological Risk Index (ER and RI), while non-carcinogenic and carcinogenic risks were assessed through Average Daily Dose (ADD), Hazard Quotient (HQ), Hazard Index (HI), and Cancer Risk (CR) according to U.S. Environmental Protection Agency methodologies. Multivariate statistical analyses, including Spearman correlation, principal component analysis, and non-parametric tests, were employed to identify spatial and seasonal patterns. Sediment concentrations followed the order Fe &gt; Mn &gt; Zn &gt; Cu &gt; Cd, with Cd exhibiting exceptionally high levels (mean: 8.75 mg kg(-1)), substantially exceeding international sediment quality guidelines. Cd showed very high contamination (CF = 89.35), extreme enrichment (EF = 455.05), and strong geoaccumulation (Igeo = 5.77), indicating severe anthropogenic input. The overall ecological risk index (RI = 2688.42) revealed a very high ecological risk, overwhelmingly driven by Cd. Spatial analyses identified Ak &amp; ccedil;ap &amp; imath;nar downstream station as the principal contamination hotspot, whereas seasonal variation was limited except for Cd, which peaked during spring. Human health risk assessment indicated that sediment ingestion poses significant non-carcinogenic risks, particularly for children (HI = 181.34), and carcinogenic risk from Cd exposure in children (CR = 6.25 x 10(-4)) exceeded the acceptable threshold recommended by the USEPA.
</description>
<pubDate>Thu, 01 Jan 2026 00:00:00 GMT</pubDate>
<guid isPermaLink="false">https://hdl.handle.net/20.500.12809/11221</guid>
<dc:date>2026-01-01T00:00:00Z</dc:date>
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<item>
<title>A Hybrid Nanomaterial-Based Electrochemical Sensor for Melatonin Measurement in Human Saliva: A Diagnostic Tool for Anxiety Disorder</title>
<link>https://hdl.handle.net/20.500.12809/11220</link>
<description>A Hybrid Nanomaterial-Based Electrochemical Sensor for Melatonin Measurement in Human Saliva: A Diagnostic Tool for Anxiety Disorder
Özyurt, Vasfiye Hazal; Çaylayık, Nil Su; Çitil, Burak Ekrem; Türkiş, Fulden Cantaş; Anık, Ülkü
Since the diagnosis of anxiety disorder is primarily based on questionnaires, accurate identification of the disorder can be challenging. Melatonin has been identified as a potential biomarker for the detection of anxiety disorders. By targeting this biomarker, it will be possible to get more accurate results and diagnose anxiety disorder more properly. In this study, a carbon screen-printed electrode modified with multi-walled carbon nanotube-gold-platinum (MWCNT-Au-Pt) nanocomposite-based electrochemical sensor was developed for the detection of melatonin. To enhance the sensor's performance, key experimental parameters-including the amount of MWCNT-Au-Pt nanoparticle and the pH of the solution-were systematically optimized. The sensor exhibited two linear response ranges for melatonin: from 0.5 to 50 &amp; micro;M with a limit of detection (LOD) of 0.23 &amp; micro;M, and from 100 to 1000 &amp; micro;M with an LOD of 2.14 &amp; micro;M. The sensor's specificity was evaluated in the presence of potential interfering substances. It was subsequently applied successfully to the detection of melatonin in 25 real human saliva samples. As a result, the first MWCNT-Au-Pt modified electrochemical sensor for melatonin detection, which will lead to proper anxiety disorder diagnosis, was fabricated.
</description>
<pubDate>Thu, 01 Jan 2026 00:00:00 GMT</pubDate>
<guid isPermaLink="false">https://hdl.handle.net/20.500.12809/11220</guid>
<dc:date>2026-01-01T00:00:00Z</dc:date>
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<item>
<title>The Role of Media Literacy in Online Information: Searching Strategies</title>
<link>https://hdl.handle.net/20.500.12809/10220</link>
<description>The Role of Media Literacy in Online Information: Searching Strategies
Tatar, İsmail; Şahin, Yusuf Levent; Doğan, Ezgi
Along with the spread of Web 2.0 technologies, individuals' habits such as learning, socializing, and getting information have changed rapidly. A lot of information, the accuracy of which cannot be trusted, is available in the web, and it becomes difficult to choose useful, relevant, and accurate information. This pollution is also present in the media. The abilities to choose messages in the media, to look at these messages critically, and to produce your own messages are considered among the 21st-century skills. These reasons bring media literacy (ML) and online information searching strategies (OISS) to the agenda. The processes of ML and OISS have interrelated features. Therefore, it is important and necessary to examine these concepts together. Based on this necessity, the aim of the study was to determine the role of ML in OISS. To this end, the data were collected from 1809 pre-service teachers using the OISS inventory and the ML level determination scale. Data were analyzed by descriptive statistics, MANOVA, and multiple regression analysis. According to the results, pre-service teachers' ML and OISS levels were above the moderate level. ML and OISS vary significantly according to the type of websites. In conclusion, ML was revealed as a predictor variable that could explain OISS at a rate of 33.2%. © 2022 Research Group Education and Virtual Learning (GREAV)
</description>
<pubDate>Sat, 01 Jan 2022 00:00:00 GMT</pubDate>
<guid isPermaLink="false">https://hdl.handle.net/20.500.12809/10220</guid>
<dc:date>2022-01-01T00:00:00Z</dc:date>
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