<?xml version="1.0" encoding="UTF-8"?><rdf:RDF xmlns="http://purl.org/rss/1.0/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/">
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<title>İstatistik Bölümü Koleksiyonu</title>
<link>https://hdl.handle.net/20.500.12809/236</link>
<description/>
<items>
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<rdf:li rdf:resource="https://hdl.handle.net/20.500.12809/11221"/>
<rdf:li rdf:resource="https://hdl.handle.net/20.500.12809/11207"/>
<rdf:li rdf:resource="https://hdl.handle.net/20.500.12809/11032"/>
<rdf:li rdf:resource="https://hdl.handle.net/20.500.12809/10997"/>
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<dc:date>2026-06-28T09:44:51Z</dc:date>
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<item rdf:about="https://hdl.handle.net/20.500.12809/11221">
<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>
<dc:date>2026-01-01T00:00:00Z</dc:date>
</item>
<item rdf:about="https://hdl.handle.net/20.500.12809/11207">
<title>Regularized Cox Models Versus Deep Survival Networks in Low Events-per-Variable Regimes: A Benchmark Across Censoring Levels</title>
<link>https://hdl.handle.net/20.500.12809/11207</link>
<description>Regularized Cox Models Versus Deep Survival Networks in Low Events-per-Variable Regimes: A Benchmark Across Censoring Levels
Yılmaz, Ersin
Survival analysis on biomedical data has seen quick methodological growth, but practitioners face limited guidance on which family of methods to prefer when censoring rates are high or the ratio of predictors to events is unsuitable. This paper presents a systematic benchmark of six survival models-the classical Cox model, lasso-penalized Cox, the Bayesian elastic net Cox model (BEN-Cox), random survival forests, DeepSurv, and Cox-Time-across three publicly available datasets (METABRIC, SUPPORT, and TCGA-BRCA) under controlled censoring regimes. The experimental grid scans events-per-variable (EPV) ratios from 0.6 to 7.6 and censoring rates from 33% to 86%. Performance is evaluated using Harrell's concordance index, time-dependent concordance, the integrated Brier score, and the calibration slope, with statistical comparisons carried out by paired Wilcoxon signed-rank tests with Holm correction. Three main findings are obtained. First, BEN-Cox, lasso-Cox, and random survival forests form a narrow top tier in discrimination, with pooled C -index values within 0.003 of each other, while DeepSurv and Cox-Time do not reach this tier in any configuration. Second, calibration separates models that discrimination does not: BEN-Cox achieves the lowest integrated Brier score in all six configurations, while lasso-Cox produces calibration slopes closest to one on the high-dimensional datasets; deep models and the unpenalized Cox model are systematically overconfident. Third, increasing censoring widens the gap between the regularized top tier and the deep architectures without changing which model family is preferred. An empirical partition of the (c, EPV) plane summarizes these observations. Because the entire grid falls below the classical EPV threshold of ten, the partition documents the low-EPV regime in which regularized models dominate but does not identify the boundary at which deep models may become competitive.
</description>
<dc:date>2026-01-01T00:00:00Z</dc:date>
</item>
<item rdf:about="https://hdl.handle.net/20.500.12809/11032">
<title>Testicular involvement of Brucellosis: A 10-year, multicentre study</title>
<link>https://hdl.handle.net/20.500.12809/11032</link>
<description>Testicular involvement of Brucellosis: A 10-year, multicentre study
Güler Dinçer, Nevin; Çelik, Mehmet; Akgül, Fethiye; Alkan, Sevil; Altındağ, Sevin
Introduction: The genito-urinary system is one of the most common areas of involvement in brucellosis. To present the epidemiological, clinical, and laboratory characteristics of patients with testicular involvement associated with brucellosis, together with the diagnostic and therapeutic approaches.&#13;
Methodology: Patients followed up for brucellosis-related testicular involvement between January 2012 and November 2022 were included in the study. Brucellosis is defined as the production of Brucella spp. in cultures, or clinical symptoms together with the serum standard tube agglutination test titer of ≥ 1/160. Inflammation in scrotal Doppler ultrasonography was based on testicular involvement.&#13;
Results: A retrospective evaluation was made of the data of 194 patients with brucellosis-related testicular involvement. The rate of determination of testicular involvement in brucellosis was 2.57%. The most affected patients were determined in the 16-30 years age range. On presentation, brucellosis was in the acute stage in 83.7% of patients. The most common symptoms on presentation were swelling and/or pain in the testes (86.6%). In the patients where a spermiogram could be performed, oligospermia was determined in 41.7%, and aspermia in 8.3%. When the testicular involvement of brucellosis was evaluated, epididymo-orchitis was present at the rate of 55.7%, epididymitis at 27.3%, and testis abscess at 5.1%.&#13;
Conclusions: Although epididymo-orchitis was the most frequently determined form of involvement in this study, there was also seen to be a significant number of patients presenting with epididymitis. Male patients presented with the clinical status of brucellosis should be questioned about swelling and pain in the testes to avoid overlooking testicular involvement.
</description>
<dc:date>2023-01-01T00:00:00Z</dc:date>
</item>
<item rdf:about="https://hdl.handle.net/20.500.12809/10997">
<title>Modified Local Linear Estimators in Partially Linear Additive Models with Right-Censored Data Based on Different Censorship Solution Techniques</title>
<link>https://hdl.handle.net/20.500.12809/10997</link>
<description>Modified Local Linear Estimators in Partially Linear Additive Models with Right-Censored Data Based on Different Censorship Solution Techniques
Yılmaz, Ersin; Aydın, Dursun; Ahmed, Syed Ejaz
This paper introduces a modified local linear estimator (LLR) for partially linear additive models (PLAM) when the response variable is subject to random right-censoring. In the case of modeling right-censored data, PLAM offers a more flexible and realistic approach to the estimation procedure by involving multiple parametric and nonparametric components. This differs from the widely used partially linear models that feature a univariate nonparametric function. The LLR method is employed to estimate unknown smooth functions using a modified backfitting algorithm, delivering a non-iterative solution for the right-censored PLAM. To address the censorship issue, three approaches are employed: synthetic data transformation (ST), Kaplan-Meier weights (KMW), and the kNN imputation technique (kNNI). Asymptotic properties of the modified backfitting estimators are detailed for both ST and KMW solutions. The advantages and disadvantages of these methods are discussed both theoretically and practically. Comprehensive simulation studies and real-world data examples are conducted to assess the performance of the introduced estimators. The results indicate that LLR performs well with both KMW and kNNI in the majority of scenarios, along with a real data example
</description>
<dc:date>2023-01-01T00:00:00Z</dc:date>
</item>
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