Hitit University is a university in Çorum, Turkey, founded in 2006. The university was affiliated to Gazi University before splitting into an independent university, with existing educational units affiliated to this newly founded university in 2006.Hitit University comprises three institutes, eight faculties, two schools and seven vocational schools. The university provides education to 6,263 short cycle students, 8,245 bachelor students, 1,214 master's degree students and 116 PhD students through 592 academic staff and 347 administrative staff..
Pesticide residues are not only present in fresh fruits and vegetables but can also be detected in processed food products. In this study, 109 pomegranate juice samples from Turkey were analyzed for 225 multi-residue-type pesticides and five highly polar substances using liquid chromatography-tandem mass spectrometry (LC-MS/ MS). A total of eight different pesticides were detected, two of which were unauthorized. Phosphonic acid was the most frequently detected compound (96.3 %), followed by glyphosate (17.4 %) and chlorate (13.8 %). Under the worst-case scenario, hazard index (HI) values were calculated at 0.0014 for adults and 0.0043 for children, indicating that pesticide exposure from pomegranate juice consumption does not pose a significant health risk. Chlorate (33 %), boscalid (29 %), and phosphonic acid (17 %) were identified as the primary contributors to the cumulative HI values in both population groups. Nevertheless, the detection of non-authorized pesticides, such as chlorate, raises concerns regarding agricultural practices and regulatory compliance. These results provide essential data on the occurrence and levels of multi-residue and highly polar pesticides in processed pomegranate juice and support evidence-based assessments for regulatory compliance and consumer safety.
Over time, catastrophes have increasingly caused significant material and human losses. Effective logistics management in humanitarian aid is crucial to minimizing these impacts. Infrastructure damage from disasters introduces uncertainties that must be considered when routing trucks for relief item delivery. This study proposes a Mixed Integer Programming model for the Two-Echelon Vehicle Routing Problem in Humanitarian Aid Logistics (2E-VRP-HAL) to minimize total travel time. An earthquake scenario in Kartal, Istanbul is used to demonstrate the model's accuracy and applicability while accounting for road closures. A diverse fleet, including trucks and pedestrians, addresses delivery challenges, with handover stations enabling access to unreachable areas. To address larger problem instances, a set partitioning approach is used to cluster demand points, followed by a MIP-based local search heuristic to refine the results. Numerical analysis shows up to 15.83
We report the preparation and characterization of an Organic Field-Effect Transistor (OFET) gas sensor based on a hybrid active layer composed of Nickel Phthalocyanine (NiPc) and beta-phase borophene prepared via physical exfoliation. The electrical properties and time-dependent stability of NiPc:Borophene hybrid OFETs were evaluated. According to the root I-D-V-G analysis obtained from transfer measurements, the device exhibits ambipolar behavior, with threshold voltages approximately V-th p= - 40.8 V and V-th,V-= + 40.8 V the on/off current ratio is similar to 1.0 x 10(6) in both polarities. To assess the long-term electrical stability of the prepared NiPc:Borophene NiPc: Borophene hybrid OFETs, time-dependent bias-stress measurements were investigated. Under negative bias-stress measurements, the change in Delta V-T increased significantly (Delta V-T = 0.195 V at 10(3) s, and 0.336 V at 10(4) s); the mobility stability was 98,7 % at 10(3) s, and 97,5 % at 10(4) s; and the normalized current (I-D/I-D0) was 0.92 % at 10(3) s, and 0.86 % at 10(Han et al., 2018(4)). Beside these, under positive bias-stress measurements, the change in Delta V-T remained limited (Delta V-T = 0.045 V at 10(3) s, and 0.077 V at 10(4) s); the mobility stability was 99,6 % at 10(3) s, and 99,2 % at 10(4) s; and the I-D/I-D0 was 0.97 % at 10(3) s, and 0.95 % at 10(Han et al., 2018(4)). Because the changes in mobility and normalized current values were limited, it was concluded that the overall performance of the OFETs was maintained under long-term stress. Gas sensing performance was evaluated for NO2, NH3, and ethanol at room temperature. The sensitivities were found to be 21.39 % ppm(-1) for NO2, 5.84 % ppm(-1) for NH3, and 4.07 % ppm(-1) for ethanol. The highest slope for NO2 is consistent with its electron-withdrawing nature, which increases the hole density in the p-type channel and strongly triggers current or resistance changes. LOD values drop to as low as 0.13 ppm for NO2; NH3 and ethanol are 0.62 ppm and 1.10 ppm, respectively. The peak response to NO2 is maintained at similar to 25 % for three consecutive cycles, with no significant shift between cycles. This demonstrates the sensor's strong reproducibility and reversible adsorption-desorption capabilities. The NiPc:Borophene hybrid OFET sensor shows promise for use in low-power, scalable, and highly responsive environmental monitoring systems.
Variations in the branching pattern of the aortic arch are highly diverse and are often encountered incidentally during routine computed tomography angiography scans. This study aimed to determine the prevalence of variations in aortic arch branching patterns in the Turkish population using computed tomography angiography (CTA) images. CTA images of 1000 patients (500 males, 500 females) who presented to the radiology clinic for various indications between May 2018 and June 2024 were evaluated. The branching variations of the aortic arch were classified into seven main types. The relationship between aortic arch branching pattern variations and sex was assessed using the Chi-square test. A normal branching pattern (Type 1) was observed in 853 of the 1000 cases, while variations were found in 147 cases. The most common variation was Type 2, in which the brachiocephalic trunk and the left common carotid artery originate from a common trunk, observed in 8.3
Age-related macular degeneration (AMD) is a leading cause of vision loss in older adults. Detecting AMD early can prevent the irreversible damage caused in later stages. Most existing methods detect drusens as a preliminary step for AMD detection, which is quite challenging as the drusens are present alongside other exudates in the retina. This paper presents a system for early diagnosis of dry AMD that does not rely on detecting drusens and integrates handcrafted features with machine learning and image processing techniques. The system performs several image processing tasks, including pre-processing a color fundus photograph of the retina, macula detection, Region-of-Interest (RoI) selection around the macula, and feature extraction from the RoI. Several texture and color features of the macula region are extracted and analyzed using t-test and ReliefF feature selection algorithms. Supervised classification techniques such as Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Naïve Bayes Classifier (NBC), and Multi-Layer Perceptron (MLP) are trained on the selected features with stratified 10-fold cross-validation to classify retinal images as normal or AMD. The system’s performance is evaluated based on accuracy, error, recall, specificity, precision, and F1-score. Classifiers are trained and tested on three feature sets: texture, color, and a combination of both. The proposed system achieves excellent results with texture features and the SVM classifier, attaining accuracies of 98.89% and 95.43% on the STARE and ODIR datasets, respectively.
