Kocaeli University Research Information System
Not a member yet
80615 research outputs found
Sort by
Clinical Characteristics and Predictors of Antiviral Treatment Duration in Hospitalized Patients with Ulcerative Colitis-Associated Cytomegalovirus Colitis, Including Biologic Therapy
No full textCytomegalovirus (CMV) colitis is a significant entity in hospitalized patients with ulcerative colitis, particularly during immunosuppressive therapy. The factors associated with antiviral treatment duration remain incompletely defined. This retrospective cohort study included hospitalized adult patients with ulcerative colitis and immunohistochemically confirmed CMV colitis. Baseline demographic, clinical, endoscopic, and laboratory characteristics were evaluated for the cohort and stratified by antiviral treatment duration of ≤14 days and >14 days. Correlation analyses were performed between tissue CMV polymerase chain reaction (PCR) viral load and laboratory parameters. Receiver operating characteristic analysis identified a tissue CMV PCR cut-off associated with prolonged antiviral therapy. The study included 52 patients (median age, 41.5 years; 65.4% male). Fourteen patients received biologic therapy and were younger and had higher C-reactive protein levels than those who did not receive biologics. Tissue CMV PCR viral load was higher in patients who received antiviral therapy for >14 days. The analysis identified a tissue CMV PCR cut-off value of 162,000 IU/mg, with an area under the curve of 0.69, sensitivity of 70.4%, and specificity of 76.0%. Tissue CMV PCR viral load showed a weak negative correlation with serum albumin levels (Spearman ’s r = −0.34, p < 0.05). Tissue CMV PCR viral load is associated with antiviral treatment duration and may help identify patients with ulcerative colitis–associated CMV colitis who require prolonged therapy
WEB 2.0 DESTEKLİ UYGULAMALARIN İLKOKUL ÖĞRENCİLERİNİN AKADEMİK BAŞARI VE ÜÇ BOYUTLU GEOMETRİK DÜŞÜNME BECERİLERİNE ETKİSİ
No full textBu araştırma, 3. sınıf matematik dersinde “Geometrik Şekiller ve Cisimler” konusundaki kazanımlara uygun olarak hazırlanan Web 2.0 uygulamalarının ilkokul öğrencilerinin akademik başarılarına ve Üç Boyutta Geometrik Düşünme becerilerine etkisini incelemek amacıyla yapılmıştır. Araştırmanın örneklemini Kocaeli ilinde bulunan bir devlet ilkokulunda öğrenim görmekte olan 29 deney, 28 kontrol grubu olmak üzere toplamda 57 öğrenci oluşturmaktadır. Nicel araştırma yöntemlerinden biri olan ön test-son test kontrol gruplu yarı deneysel desenin kullanıldığı bu çalışmada öğrencilere veri toplama aracı olarak “Geometrik Şekiller ve Cisimler Başarı (GŞCB) Testi” ve “Üç Boyutta Geometrik Düşünme (ÜBGD) Testi ” her iki gruba ön test ve son test olarak uygulanmıştır. Araştırmanın deney grubunda, araştırmacı tarafından hazırlanan Web 2.0 uygulamaları ile dersler 2 hafta (10 ders saati) süresince yürütülmüş, kontrol grubunda ise aynı ünite geleneksel öğretim metodu ile eşit sürede tamamlanılması sağlanmıştır. Uygulama öncesi ve sonrasında elde edilen verilerin normal dağılıma uyup uymadığının belirlenmesi için çarpıklık, basıklık kriterleri incelemesi yapılmıştır. Öğrencilerin Geometrik Şekiller ve Cisimler Başarı Testi’nden aldıkları puanlar bağımsız örneklemler t-testi ve bağımlı örneklemler t-testi ile analiz edilmiştir. Analiz sonuçlarına göre, deney ve kontrol grubu öğrencilerinin GŞCB Başarı Testi son test puanları arasında deney grubu lehine anlamlı düzeyde bir farklılık gösterdiği ve Web 2.0 araçlarının kullanılmasının Geometri ünitesindeki “Geometrik Cisimler ve Şekiller Konusu” üzerindeki öğrenci başarısını arttırdığı görülmüştür. ÜBGD son test puanları arasında yapılan bağımsız gruplar t testi sonucunda, deney ve kontrol grupları arasında istatistiksel olarak deney grubu lehine anlamlı düzeyde yüksek olması Web 2.0 destekli öğretim uygulamalarının öğrencilerin üç boyutlu geometrik düşünme becerilerini geliştirmede geleneksel öğretim yöntemlerine kıyasla daha etkili olduğunu kanıtlamaktadır. </p
Dişli Üretiminde Termal Davranışların Performansa Etkilerinin Sayısal ve Deneysel İncelenmesi
No full textLabel-Free Detection of 2,4-Dinitrotoluene Using a Laser-Induced Graphene Based Chemiresistive Sensor
No full textThe rapid and sensitive detection of nitroaromatic explosives is of paramount importance for both security and environmental monitoring. In this study, a label-free chemiresistive sensor based on laser-induced graphene (LIG) was developed for the selective detection of 2,4-dinitrotoluene (DNT). LIG films were directly fabricated on polyimide substrates via a single-step laser writing process, resulting in porous and conductive surfaces without additional modification. The structural, chemical, and electrical properties of the fabricated materials were comprehensively evaluated using scanning electron microscopy (SEM), X-ray diffraction (XRD), Raman spectroscopy, Fourier transform infrared (FTIR) spectroscopy, X-ray photoelectron spectroscopy (XPS). The electrical properties were characterized by current–voltage (I–V) measurements using a Kelvin (pseudofour-point) configuration. SEM revealed a porous morphology formed during laser scribing, while XRD and Raman spectroscopy confirmed multilayer graphene (∼5 layers) with relatively low defect density. FTIR spectroscopy indicated residual oxygen-containing functional groups, and XPS verified DNT adsorption. The fabricated films exhibited a uniform electrical conductivity of 1545 S/m. By employing these films, a chemiresistive sensor was developed, which demonstrated a response toward DNT, achieving an estimated detection limit (LOD) of 3.79%, corresponding to 2.4 × 10–9 M. Strong selectivity was observed against structurally related interferents such as nitrotoluene, toluene, and ethanol. These results demonstrated that LIG-based flexible sensors provide a low-cost, scalable, and selective platform for explosive detection with promising applications in security and environmental monitoring
Multi-group overlapping weighted random forests
No full textThis paper introduces an enhanced random forest framework that partitions trees into overlapping subsets, allowing each tree to contribute to multiple groups. Each group acts as a base classifier, producing predictions through internal voting, while a weighted inter-group vote combines these outputs according to each group’s reliability. A particle swarm optimization algorithm jointly determines the optimal number of groups, their composition, and associated weights, enabling efficient exploration of the configuration space. Experiments on twenty five UCI benchmark datasets show that the proposed method consistently improves accuracy, robustness, and generalization
Associations between urban health indicators and COVID-19 vaccine uptake in Türkiye
No full textIntroduction: Understanding structural and contextual factors behind COVID-19 vaccine uptake is essential for designing equitable immunization strategies. In Türkiye, a centrally coordinated campaign with notable regional variation offered an opportunity to explore how provincial characteristics influenced vaccine coverage. Methods: This ecological study analyzes monthly full vaccination coverage (two doses) across 81 provinces and explores its association with 26 indicators grouped into six domains: health system capacity, healthcare utilization, population characteristics, economic indicators, urban environment, and socio-cultural factors. Domain-specific composite indices were created using standardized scores. Bivariate correlations and multiple linear regression models—adjusted for the proportion of the population aged 65 and older—were conducted. Results: The proportion of the elderly population emerged as the most consistent predictor of vaccination uptake. Health system capacity was strongly associated with higher vaccination rates in the early months (β = 0.581 in February; β = 0.192 in March), emphasizing the role of public sector readiness. From March onward, healthcare utilization was a more stable determinant (β = 0.260 to 0.345), reflecting the importance of familiarity with and trust in health services. Socio-cultural factors—including education, women’s economic participation, and civic engagement—showed strong and sustained associations (β = 0.439 to 0.722). In contrast, population, economic, and urban environmental indicators showed weaker or inconsistent relationships. Conclusion: Provinces with stronger public healthcare infrastructure and engaged communities achieved more equitable vaccine coverage. Türkiye’s experience underscores the importance of resilient, trusted primary care systems in driving immunization success. Future studies should investigate intra-provincial disparities to support more locally responsive public health strategies
Letter to the Editor re “Evaluating the utility of ChatGPT in enhancing parental education and clinical support in hypospadias care”
No full textIdentifying future risk factors of uncontrolled asthma control: the TAAR study perspective
No full textObjective: Risk factors associated with asthma symptom control is crucial for disease management. This study aimed to determine the risk factors of patients with uncontrolled asthma and to examine the relationship with their geographical patterns. Methods: This cross-sectional study was conducted at 36 centers across Turkey. Future risk factors (FRFs) such as exposure to triggers/allergens and inadequate or poor inhalation technique, etc., were identified based on the Global Initiative for Asthma (GINA) guidelines. The associations between FRFs and demographic and clinical characteristics, geographical regions, and levels of asthma control were analyzed. Results: The study included 2,053 adult asthma patients. At least one FRF was identified in 1576(76.8%) patients. The most common FRFs were exposure to allergens/triggers (n: 664; 32.3%), impaired asthma symptom control (n: 540; 26.3%), and eosinophilia (n: 526; 25.6%). Regarding regional differences, the most prevalent FRFs in the Marmara region were exposure to allergens/triggers and frequent use of short-acting beta-2 agonists (>3 boxes/year). In contrast, eosinophilia was more common in the Southeastern region, while inadequate or poor inhalation technique, noncompliance with treatment, and psychosocial or socioeconomic problems were more frequently observed in the Eastern Anatolia region. Asthma control was achieved in 79.5% of patients without any FRFs; however, this rate decreased significantly to 25% among patients with more than four FRFs. Conclusions: This study demonstrates that FRFs in asthma vary according to demographic and disease characteristics, as well as geographical distribution. An increased number of FRFs was associated with asthma control. However, an individualized approach remains essential for achieving optimal asthma management
Magnitude Scaling and Real-Time Performance Assessment for an ElarmS-Based Early Warning System: The Case of the 2025 Silivri (Istanbul) Earthquake (Mw = 6.2)
No full textFeatured Application: The proposed Pd-based regional scaling model enhances the real-time performance of ElarmS-type EEW systems, improving alert reliability and response time across the Marmara Region. This study develops and evaluates a regionally calibrated magnitude scaling and early warning framework based on the ElarmS–EPIC algorithm using the 23 April 2025 Silivri (Istanbul) Earthquake (Mw = 6.2) scenario. A comprehensive dataset comprising the mainshock and its aftershocks was used to derive local regression relationships between earthquake magnitude (Mw) and the peak displacement amplitude ((Formula presented.)) and predominant period ((Formula presented.)) parameters. Replay simulations were conducted to assess real-time performance, and the results of the regional models were compared with those of the default EPIC configuration. The results indicate that the (Formula presented.) -based magnitude estimation model produces faster and more stable results than the (Formula presented.) -based approach, significantly improving accuracy and operational reliability. The region-specific (Formula presented.) –Mw scaling provided higher consistency with catalog magnitudes compared to the default EPIC relationships. The calculated distribution of warning times shows that the system can provide actionable warning times of 5–9 s in districts near the epicenter (e.g., Silivri, Avcılar, Beylikdüzü) and 20–50 s in more distant districts and city centers (e.g., Kadıköy, Pendik, Bursa, Sakarya). These values demonstrate that a regionally optimized early warning system can provide critical decision-making time for automatic safety systems and emergency responses in the densely populated Marmara Region. Overall, this study emphasizes the importance of regional calibration in improving earthquake early warning (EEW) performance in Türkiye. The findings show that the success of EEW systems depends on station density, network latency, data transmission speed, processing capacity, and algorithmic optimization. The proposed (Formula presented.) -based regional framework provides a scientifically robust and operationally applicable foundation for future EEW implementations in Istanbul and the Marmara Region