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Palimpsest Tarihi Yerleşimlerin “Kabuk, Gizli ve Kısmi Kabuk” Tipolojilerinin Değer Analizi İle Belirlenmesi
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A study on prep school EFL instructors' technological pedagogical content knowledge (TPACK) and self-efficacy
No full textEvaluation of the psychometric properties of the Turkish version of the Skin-to-Skin Contact Scale for nurses
No full textRationale: Skin-to-skin contact is the practice with the highest level of evidence that increases the growth, development, and healing rate of the newborn. Neonatal nurses are also the best practitioners of skin-to-skin contact. Aims: This study examined the psychometric properties of the Turkish version of the Skin-to-Skin Contact Scale for nurses. Methods: This descriptive, correlational, and cross-sectional study was carried out with 226 neonatal and pediatric nurses between July 2022 and July 2023. The data were collected using an online questionnaire, including a descriptive information form and a skin-to-skin contact scale for nurses. Data were analyzed by explanatory and confirmatory factor analysis, Cronbach's alpha, and item-total score analysis. Results: It was determined that the scale consisted of 20 items and four sub-dimensions and that those four sub-dimensions explained 53.01% of the total variance. All factor loads were higher than 0.30 in the explanatory and confirmatory factor analyses. All the fit indices were higher than 0.80, and the Root Mean Square Error of Approximation (RMSEA) was less than 0.080 in the confirmatory factor analysis. Cronbach's alpha was determined to be 0.89 for the total scale and greater than 0.70 for all sub-dimensions. Conclusions: The Skin-to-Skin Contact Scale for nurses was determined to be a valid and reliable measurement tool for Turkish nurses. It is recommended that the scale be used regularly in clinics to determine nurses' attitudes towards skin-to-skin contact
Analysis of risk factors for cancer-specific survival in neoadjuvant chemotherapy nonresponsive disease of muscle-invasive bladder cancer: A multicentre study from the Turkish Urooncology Association Bladder Tumor study group
No full textObjective: To investigate the risk factors affecting cancer-specific survival (CSS) in nonresponsive disease to neoadjuvant chemotherapy (NAC) among patients with muscle-invasive bladder cancer (MIBC) who were treated with NAC and radical cystectomy (RC). Methods: Patients with MIBC who underwent NAC and RC were retrospectively examined. By comparing clinical and pathological stages, patients whose pathological stage was lower than clinical stage were categorized as “NAC-responsive” and the remainder as “NAC-non-responsive.” Apart from pathologic staging, variables compared between groups included age, gender, Eastern Cooperative Oncology Group (ECOG) score, clinical stages, NAC type and cycle number, durations between MIBC diagnosis and NAC initiation and RC, presence of hydronephrosis, number of lymph nodes removed, and variant histology of urothelial bladder cancer. CSS analysis was performed by construction of Kaplan–Meier survival curves and multivariable Cox regression was performed to identify the prognosticators in the NAC-non-responsive-group. Results: Ninety-two patients were included with a mean age was 61.5 ± 8.5 years, of whom 84.8% were men. The NAC regimen used was predominantly gemcitabine-cisplatin (88%) and the median cycle number was 4. Fifty-six (60.9%) patients were NAC-non-responsive. There was a significantly lower proportion of patients receiving ≥4 cycles (46.4% vs. 66.7%) and a higher rate of patients with ECOG score ˃1 (33.9% vs. 11.1%) in the NAC-non-responsive-group compared to the NAC-responsive-group (both P < 0.05). Other variables were similar between groups. In multivariable analysis, only ypN+ was found to be an independent prognosticator for CSS in NAC-non-responsive-group (HR: 2.725, CI95%:1.017–7.303). Conclusion: Although higher ECOG scores and lower cycle numbers appears to be associated factors in NAC-non-responsive disease, only ypN(+) status was a prognosticator for CSS in this population
TÜRKİYE’DE BOŞANMA DAVALARININ ZAMAN SERİSİ ANALİZİ VE GELECEK TAHMİNLERİ: BOX-JENKİNS (ARIMA) YAKLAŞIMI
No full textBoşanma,TMK 4721’e göre evli olan kişilerin yasal olan evlilik birliğinin sonaerdirilmesi sürecidir. Boşanmanın artışlarının toplumsal, ekonomik, bireysel,psikolojik, hukuki ve kültürel birçok etkisi bulunmaktadır. Bu çalışmanın amacıTürkiye’de geçmişe yönelik açılan boşanma davası sayıları referans alınarakzaman serisi analizi yöntemleri ile geleceğe yönelik açılan boşanma davasayılarının tahminlerinin yapılmasıdır. Yöntem olarak Box-Jenkins (ARIMA)Yöntemi kullanılmıştır. Çalışmada Hukuk Mahkemelerine 2013-2022 yıllarıarasında yıl içinde açılan boşanma dava sayısı verileri istatistiksel olarakincelenmiştir. Veri yapısının aylık olması diğer bakışla zamana bağlı olmasıdaha önce boşanma dava sayısının Box-Jenkis yöntemine ile tahmin edilmemesisebebiyle yapılan analizin literatüre katkısının önemli olacağı sonucuna varılmıştır.Türkiye’de açılan boşanma dava sayılarının zaman serisi grafiği incelendiğindetrend ve mevsimselliğin olabileceği önsel bilgisine ulaşılmış ACF ve PACFgrafiklerine bakılarak trend ve mevsimsellik için fark alma işlemi yapılmıştır.Bakılan grafikler sonucu AR ve MA modelleri için denemeler yapılmış en uygun modelinARIMA (1,1,1)(1,1,0)12 olduğu sonucuna varılmıştır. Modelin p değerleri 0.05’tendaha küçük olduğundan AR1, MA1 ve SAR1 katsayıları istatistiksel olarak önemliçıkmıştır. Ayrıca, normalleştirilmiş Bayes bilgi kriteri değeri de 16 415olarak bulunmuştur. Türkiye’de son beş yılda ortalama 273 447 (2019-2023)boşanma davası açıldığı görülmüştür. 2023 yılında açılan dava sayısı 315 202 olarak tahmin edilmiş gerçekteise 295 187 davanın açıldığı görülmüştür. Elde edilen tahmin değeri %6.8 hataoranı ile çok yakın olarak tahmin edilmiştir. Boşanma davasının yıllaritibarıyla artacağı öngörülmüştür. 2024 yılında 336 309 olacağı 2025 yılındaise 359 445 davanın açılacağı tahmin edilmiştir.Divorce,according to the Turkish Civil Code No. 4721, is the process by which the legalunion of marriage between individuals is terminated. The increase in divorcerates has numerous social, economic, individual, psychological, legal, andcultural effects. The purpose of this study is to project the future number ofdivorce cases filed in Turkey using time series analysis methods, based on thehistorical data of filed divorce cases. The Box-Jenkins (ARIMA) Method wasemployed as the methodology. The study statistically analyzed the number ofdivorce cases filed annually in Civil Courts between 2013 and 2022. The factthat the data is monthly and thus time-dependent, combined with the lack ofprevious forecasts of divorce case numbers using the Box-Jenkins method,suggests that this analysis will significantly contribute to the literature. Uponexamining the time series graph of the number of divorce cases filed in Turkey,it was preliminarily determined that there might be trends and seasonality.After reviewing the ACF and PACF graphs, differencing was performed to accountfor these trends and seasonality. Following trials for AR and MA models basedon the examined graphs, it was concluded that the most suitable model was ARIMA(1,1,1)(1,1,0)12. Since the p-values of the model were found to be less than0.05, the coefficients for AR1, MA1, and SAR1 were statistically significant.Additionally, the normalized BayesianInformation Criterion value was found to be 16.415. It was observed that anaverage of 273 447 divorce cases were filed in Turkey over the past five years(2019-2023). The number of cases projected for 2023 was 315 202, whereas theactual number of cases filed was 295 187. The estimated value was very close tothe actual figure, with an error rate of 6.8%. It is forecasted that the numberof divorce cases will increase in the coming years, with 336 309 cases expectedto be filed in 2024 and 359 445 cases in 2025.</p
Predictors of static and dynamic balance control in kidney transplant recipients
No full textBackgroundWe aimed to evaluate balance control and lower extremity muscle strength in kidney transplant recipients (KTRs) including a comparison to a healthy control group and determine the predictors of static and dynamic balance control after kidney transplantation.MethodsIn this study 40 KTRs and 40 healthy controls were included. Balance control was assessed using the Biodex balance system. The static postural stability test (SPST) and clinical test of sensory integration and balance (CTSIB) were used to assess static balance control whereas the dynamic postural stability test (DPST) and limits of stability test (LOST) were used for dynamic balance control. Lower extremity muscle strength was measured with a hand-held dynamometer. Renal functions and laboratory findings of KTRs were recorded.ResultsAll the stability index scores of SPST and sway index in CTSIB were significantly higher in KTRs compared to healthy controls. The right anteroposterior stability index score in DPST and the reaction time in LOST were significantly higher whereas overall score in LOST and lower extremity muscle strength were significantly lower in KTRs. The linear regression analysis revealed that hemoglobin was the predictor of static balance control accounting for 11% of the variance and body weight was the predictor of dynamic balance control accounting for 34% of the variance.ConclusionBalance control, both static and dynamic, are impaired in KTRs as well as lower extremity muscle strength. Hemoglobin level is a predictor of static balance control whereas body weight is a predictor of dynamic balance control after kidney transplantation
Optimization of an integrated harvest, and process planning model in the agri-food industry
No full textIn this paper, an integrated harvest and production planning problem in the olive oil industry is addressed. The aim of the paper is to develop and optimize a mathematical model that integrates both olive harvest and olive oil production process. The objective is to maximize the total profit while determining quantity of olives harvested from several olive groves, quantity of olives purchased from external farmers, quantity of olive oil produced, and by-product management to handle hazardous effects of olive oil production. The problem is formulated as a mixed integer linear programming model (MILP). Maximization of profit consists of two components; total sales revenue and total cost including harvesting, purchasing, fixed and variable processing costs. Constraints on the system include harvest planning, harvest capacity, production planning, and processing constraints. The proposed MILP model incorporates several distinguishing characteristics of the problem such as ripeness of olives, olive oil quality, organic and conventional farming, and by-product management. A numerical experiment based on a real-world case study was presented to verify the effectiveness of the developed model. The results show that simultaneously considering harvesting and production processes can significantly assist the profitability of the olive oil supply chain. A scenario analysis is conducted by extending the base model to explore olive loss in the olive groves which can occur due to the severe climatic conditions.</p
Vibration-based Detection and Classification of Mechanical Defects in Induction Motor-driven Systems during the Starting Transient
No full textVibration analysis is considered the most common and effective means of detecting mechanical faults such as imbalance, misalignment, and looseness in induction motor driven systems. Most mechanical problems result in an increase in vibration at multiples of the rotor speed frequency (1x) making it difficult to discern the source of vibration. In case of a fault alarm, the maintenance engineer usually performs a walk-around test to identify the source of vibration for planning maintenance, and therefore, is exposed to safety risks. In this paper, a new remote and automated test method for identifying the source of mechanical vibration during the starting transient of induction motors is proposed. The level and speed-dependency of vibration during rotor acceleration are used for identifying imbalance from other mechanical defects that produce 1x vibration. Test results on a 380 V, 5.5 kW induction motor under mechanical defects are given for verification. It is shown that the proposed method can provide automated identification of the source of vibration enabling maintenance to be performed in a safe, low cost, and efficient manner. The data acquired and analyzed for the testing are described and shared through this paper