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BackgroundDiabetes stigma is recognized to negatively impact health-related outcomes for people living with type 2 diabetes (T2D), but there is a dearth of evidence among U.S. Latino adults with T2D. Our aim was to develop a Spanish-language translation of the Type 2 Diabetes Stigma Assessment Scale (DSAS-2) and examine its psychometric properties among U.S. Latino adults with T2D.MethodsThe translation was developed through a multi-step process, including a focus group with community health workers (n=5) and cognitive debriefing interviews with Latino adults with T2D (n=8). It was field-tested in an online survey of U.S. Latino adults with T2D, recruited via Facebook (October 2018 to June 2019). Exploratory factor analysis examined structural validity. Convergent and divergent validity were assessed by testing hypothesized correlations with measures of general chronic illness stigma, diabetes distress, depressive and anxiety symptoms, loneliness, and self-esteem.ResultsAmong 817 U.S. Latino adults with T2D who participated in the online survey, 517 completed the Spanish-language DSAS-2 (DSAS Spa-US) and were eligible for the study (mean age 54 ± 10 years, and 72% female). Exploratory factor analysis supported a single-factor solution (eigenvalue=8.20), accounting for 82% of shared variance among the 19 items, all loading ≥ 0.5. Internal consistency reliability was high (α=0.93). As expected, strong, positive correlations were observed between diabetes stigma and general chronic illness stigma (rs=0.65) and diabetes distress (rs=0.57); medium, positive correlations, between diabetes stigma and depressive (rs=0.45) and anxiety (rs=0.43) symptoms, and loneliness (rs=0.41); and a moderate negative correlation between diabetes stigma and self-esteem (rs=-0.50). There was no relationship between diabetes stigma and diabetes duration (rs=0.07, ns).ConclusionThe DSAS-2 Spa-US is a version of the DSAS-2, translated into Spanish, that has good psychometric properties for assessing diabetes stigma in U.S. Latino adults with T2D.

The assessment of alveolar bone loss, a crucial element of the periodontium, plays a vital role in the diagnosis of periodontitis and the prognosis of the disease. In dentistry, artificial intelligence (AI) applications have demonstrated practical and efficient diagnostic capabilities, leveraging machine learning and cognitive problem-solving functions that mimic human abilities. This study aims to evaluate the effectiveness of AI models in identifying alveolar bone loss as present or absent across different regions. To achieve this goal, alveolar bone loss models were generated using the PyTorch-based YOLO-v5 model implemented via CranioCatch software, detecting periodontal bone loss areas and labeling them using the segmentation method on 685 panoramic radiographs. Besides general evaluation, models were grouped according to subregions (incisors, canines, premolars, and molars) to provide a targeted evaluation. Our findings reveal that the lowest sensitivity and F1 score values were associated with total alveolar bone loss, while the highest values were observed in the maxillary incisor region. It shows that artificial intelligence has a high potential in analytical studies evaluating periodontal bone loss situations. Considering the limited amount of data, it is predicted that this success will increase with the provision of machine learning by using a more comprehensive data set in further studies.

Abstract Background We report a nosocomial outbreak caused by Burkholderia cepacia that occurred among six patients admitted in the medical and surgical intensive care unit between 04 March 2019 and 02 April 2019 in Istanbul, Turkey. Methods The outbreak investigation was launched on 11 March 2019 five days after the detection of B. cepacia in four different patients. We defined potential reservoirs and started environmental screening. We sampled the liquid solutions used in patient care activities. Pulse-field gel electrophoresis (PFGE) was performed to determine the genetic relatedness of environmental and patient samples. Results Burkholderia cepacia was isolated in tracheal aspiration cultures of six patients. Three out of six patients developed healthcare-associated pneumoniae due to B. cepacia. Environmental cultures in the ICUs revealed B. cepacia growth in 2% chlorhexidine-gluconate mouthwash solution that been used in the colonized patients as well as in samples obtained from the unused products. PFGE revealed the patient and a specific batch of chlorhexidine mouthwash solution samples had a 96% similarity. Conclusion Contamination of medical solutions used in critical patient care could cause outbreaks and should be detected early by infection control teams. Graphic abstract

ObjectiveThe purpose of this study was to investigate the impact of the COVID-19 pandemic on the quality of life of families of children with disabilities and the mediating roles of perceived social support, perceived parental self-efficacy, psychological health, psychological resilience, and perceived family burden on this relationship.BackgroundChildren with disabilities and their families are among the most affected populations from the restrictions imposed to prevent the spread of COVID-19 virus, as the special education and rehabilitation services they had been receiving were interrupted.MethodA correlational survey design was used to collect data from 824 parents of children with disabilities in Turkey. Path analysis was used to examine the direct and indirect effects of COVID-19 on family quality of life.ResultsResults indicated that COVID-19 had a significant total effect on family quality of life and perceived social support, parental self-efficacy and psychological resilience had a mediating role on the relationship between impact of the COVID-19 pandemic and family quality of life. Perceived social support was found to the strongest mediator of the relationship between the impact of COVID-19 and the family quality of life, while perceived family burden did not have a statistically significant association with these variables.ConclusionFamily quality of life for children with disabilities decreased as the impact of COVID-19 pandemic increased. Perceived social support, parental self-efficacy and psychological resilience had mediating roles in the relationship between the impact of the COVID-19 pandemic and family quality of life.ImplicationsCOVID-19 has resulted in disruption of special education and rehabilitation services for children with disabilities and their families. Changes in daily routines have brought up additional responsibilities to parents of children with disabilities. These additional responsibilities may adversely affect and increase the burden and stress families of children with disabilities experience. The high levels of stress in families negatively affect the welfare and quality of life and result in decreased parental attention to support their children. Findings of this study show the mediating link of perceived social support, parental self-efficacy and psychological resilience in the relationship between the impact of the COVID-19 pandemic and family quality of life. Policymakers and service providers should develop and implement specific care actions to support children with disabilities and their families during and after the pandemic.

Deep learning algorithms have lately been used for medical image processing, and they have showed promise in a range of applications. The purpose of this study was to develop and test computer-based diagnostic tools for evaluating masseter muscle segmentation on ultrasonography images.

Abstract Background Panoramic radiography is an imaging method for displaying maxillary and mandibular teeth together with their supporting structures. Panoramic radiography is frequently used in dental imaging due to its relatively low radiation dose, short imaging time, and low burden to the patient. We verified the diagnostic performance of an artificial intelligence (AI) system based on a deep convolutional neural network method to detect and number teeth on panoramic radiographs. Methods The data set included 2482 anonymized panoramic radiographs from adults from the archive of Eskisehir Osmangazi University, Faculty of Dentistry, Department of Oral and Maxillofacial Radiology. A Faster R-CNN Inception v2 model was used to develop an AI algorithm (CranioCatch, Eskisehir, Turkey) to automatically detect and number teeth on panoramic radiographs. Human observation and AI methods were compared on a test data set consisting of 249 panoramic radiographs. True positive, false positive, and false negative rates were calculated for each quadrant of the jaws. The sensitivity, precision, and F-measure values were estimated using a confusion matrix. Results The total numbers of true positive, false positive, and false negative results were 6940, 250, and 320 for all quadrants, respectively. Consequently, the estimated sensitivity, precision, and F-measure were 0.9559, 0.9652, and 0.9606, respectively. Conclusions The deep convolutional neural network system was successful in detecting and numbering teeth. Clinicians can use AI systems to detect and number teeth on panoramic radiographs, which may eventually replace evaluation by human observers and support decision making.

In this study, a special lower triangular matrix derived by combining Riesz matrix and Euler totient matrix is used to construct new Banach spaces. $\alpha-$,$\beta-$,$\gamma-$duals of the resulting spaces are obtained and some matrix operators are characterized. Finally by the aid of measure of non-compactness, the conditions for which a matrix operator on these spaces is compact are determined.

Multilayer networks represent multiple types of connections between the same set of nodes. Clearly, a multilayer description of a system adds value only if the multiplex does not merely consist of independent layers. In real-world multiplexes, it is expected that the observed inter-layer overlap may result partly from spurious correlations arising from the heterogeneity of nodes, and partly from true inter-layer dependencies. It is therefore important to consider rigorous ways to disentangle these two effects. In this paper, we introduce an unbiased maximum entropy model of multiplexes with controllable intra-layer node degrees and controllable inter-layer overlap. The model can be mapped to a generalized Ising model, where the combination of node heterogeneity and inter-layer coupling leads to the possibility of local phase transitions. In particular, we find that node heterogeneity favors the splitting of critical points characterizing different pairs of nodes, leading to link-specific phase transitions that may, in turn, increase the overlap. By quantifying how the overlap can be increased by increasing either the intra-layer node heterogeneity (spurious correlation) or the strength of the inter-layer coupling (true correlation), the model allows us to disentangle the two effects. As an application, we show that the empirical overlap observed in the International Trade Multiplex genuinely requires a nonzero inter-layer coupling in its modeling, as it is not merely a spurious result of the correlation between node degrees across different layers.

We consider the equivalence problem for first-order ordinary differential equations (ODEs) and recover the well-known result that any two first-order ODEs are equivalent under a point transformation by Cartan’s equivalence method. Curvature properties of some first-order and second-order ODEs motivate us to define the equivalence problem for such equations as the metric equivalence problem which defines the {e}-structure on the corresponding manifolds. Accordingly, we show that there are first-order ODEs and linear second-order ODEs which may not be equivalent under a class of fiber-preserving diffeomorphisms. [ABSTRACT FROM AUTHOR]

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Nanokompozit malzemeler, Ba2Bi2Co2Fe12O22 Nano Partiküllerin polianilin ve poliakrilonitril polimerler ile sentezlenmesi ile elde edilmiştir. Bu nanoyapıdaki kompozitler; yapısal, manyetik ve elektromanyetik soğurma özellikleri incelenmiştir. X-ışını analizinden nano yapılı partiküllerin kristal yapıya sahip olduğu ve Y tipi altıgen yapı gösterdiği görülmüştür. 878 ve 650 cm-1'de bu yapıya sahip olduğu IR ölçümlerinden de görülebilmektedir. Nanopartiküllerin Elektron Spin Rezonans deneyi oda sıcaklığında ölçülmüş ve oldukça geniş spektrum ve bölünme faktörü gösterilmiştir. Titreşim Örneği Manyetometre ölçümleri 10-50 ve oda sıcaklığında yapılmıştır. Nanopartiküllerin, manyetik kayıt medyası, mikrodalga teknolojilerinin uygulamaları kadar başarılı olduğu söylenebilir. Elektromanyetik absorpsiyon deneyleri, frekans bandında serbest alan yöntemi kullanılarak yaklaşık 5-20 GHz ölçülmüştür. 1,5 mm. kalınlığındaki elektromanyetik soğurucu numuneler için 6 GHz. genişliğinde ve 50 db. yansıma kaybı ölçülmüştür.

Din eğitimi faaliyetlerini geçmişiyle ve bugünüyle araştırma sorumluluğunu üstlenmiş bilim dalı din eğitimi bilimidir. Din eğitimi biliminin öncelikli görevi, araştırma sahasının sınırlarını netliğe kavuşturmaktır. Bunun için yapılması gereken ise din eğitimi olgusunu tanımlamaktır. Literatüre bakılırsa, bu amaçla yapılmış birçok tanımın olduğu görülecektir. Ne var ki bu tanımlar, din eğitiminin mahiyetinin ve kapsamının ne olduğu hususunda din eğitimi bilimcilerin uzlaşı içerisinde bulunmadıklarını göstermektedir. Bu çalışmada din eğitimi için yapılmış söz konusu tanımlar analiz edilip değerlendirilmiş ve yeni bir tanım önerisi ortaya konulmuştur. Tanımlama yapılırken objektif yaklaşım esas alınmış ve ‘nedir?’ sorusuna cevap aranmıştır. Din eğitimi için yapılmış tanımları değerlendirme ve yeni bir tanım geliştirme sürecinde tanımla ilgili ortaya konulmuş esaslar göz önünde bulundurulmuştur. Yapılan araştırmada din eğitimi için yapılmış normatif tanımların din eğitimi olgusunun neliğini ve kapsamını ifade etmekte yetersiz kaldığı, deskriptif tanımların ise söz konusu olguya dair bazı noktaları bulanık bıraktığı sonucuna ulaşılmıştır.

Bu çalışmada Anti Ayrımcı ve Çok Kültürlü eğitimin ne olduğu, alan yazında nasıl tanımlandığı, Anti Ayrımcı Programların ön koşullarının ne olduğu, hangi bileşenlerden oluştuğu, neleri hedeflediği ve hangi paydaşlardan yararlandığı yer almaktadır. Ayrıca Anti Ayrımcı Programlarda yer alan kişilerin ve uzmanların rol ve sorumluluklarının ne olduğu, bu programlar uygulanırken nelere dikkat edilmesi gerektiği açıklanmıştır. Bunların yanı sıra “Anti Ayrımcı Programların” okulöncesi sınıflarda uygulanmasının yarattığı avantajlar ve sınırlılıkları alan yazında yer alan görüşlere göre derlenmiş ve yorumlanmıştır. “Anti Ayrımcı Programların” okulöncesi sınıflarda uygulanmasının yarattığı avantajların ortak yönü olarak eğitim ortamlarında kültürel ve bireysel farklılıkların temsilinin artıyor olması ve buna bağlı olarak eğitim öğretim sürecinde hem sosyal hem akademik çıktıların olumlu etkilenmesi olarak görülebilir. “Anti Ayrımcı Programların” okulöncesi sınıflarda uygulanmasının yarattığı dezavantajların ise alan yazına göre daha çok içerik, materyal, süre ve bilinç eksikliği ekseninde yer aldığını söyleyebiliriz.

Objectives: The aim of this study was to detect alveolar bone loss from dental panoramic radiographic images using artificial intelligence systems. Material and Methods: A total of 2276 panoramic radiographic images were used in this study. While 1137 of them belong to cases with bone destruction, 1139 were periodontally healthy. The dataset is divided into three parts as training (n=1856) , validation (n=210) and testing set (n= 210). All images in the data set were resized to 1472x718 pixels before training. A random sequence was created using the open-source python programming language and OpenCV, NumPy, Pandas, and Matplotlib libraries effectively. A pre-trained Google Net Inception v3 CNN network was used for preprocessing and data sets were trained using transfer learning. Diagnostic performance was evaluated with the confusion matrix using sensivitiy, specificity, precision, accuracy and F1 score. Results: Of the 105 cases with bone loss, 99 were detected by the AI system. Sensitivity was 0.94, specificity 0.88, precision 0.89, accuracy 0.91 and F1 score 0.91. Conclusion: The convolutional neural network model is successful in determining periodontal bone losses. It can be used as a system to facilitate the work of physicians in diagnosis and treatment planning in the future.

Due to the fact that social networks are becoming more and more popular, many users are continuously active social networking users. Active users are constantly sharing what they see and think. Social network users follow the people they are interested in, comment on their messages and forward them to other people. In this way, there is a huge amount of data generated by users on social networks. Besides; in addition to textual sharing, image and video sharing are also available through mobile phones with a camera. In this study, text and image-based semantic inference methods in social networks were investigated. The advantages of different semantic inference methods are emphasized. Finally, information was given on what can be done in this area in the future.

In this study, loading of optimum leather fleshings was investigated with four identical batch reactors with different fleshings and treatment sludge ratios (0:1, 0.25:1, 0.35:1, 0.50:1) to contribute to the state of art of the biogas production from tannery solid wastes. Results showed that lipids-containing leather fleshings boosted the methane production potential. However, H2S inhibition and volatile fatty acids accumulation were the main concern in the anaerobic digestion of these wastes. The modified Gompertz model was applied to the batch tests data to determine the kinetic constants of anaerobic digestion of tannery solid wastes. It was calculated with the model outputs that the ultimate methane production potential and maximum methane production rate in reactors having mixing ratio of 0.35:1 and 0.5:1 (dry basis) were highly similar. 0.35 was found to be an optimum leather fleshing and treatment sludge ratio with a 54% more methane production potential than that of control reactor in this study.

Background and Study Aim. The aim of this study is to determine the effect of e-sports on physical activity level and body composition. Material and Methods. The athletes who participated in the study were 19.92± 2.21 years of age, 1.73±0.04 m body height and 78.35±6.52 kg body weight. A total of 137 athletes participated in the study, including 27 from Turkey, 47 from South Korea and 63 from the United States (USA). The data was collected by e-mail from the sports clubs. The athletes who representing their country in international competitions involved in the study. The data obtained were evaluated in the SPSS program. Results. According to the findings of the study, the body mass index (BMI) of e-sport athletes is 26.03±1.85, the number of physical activity steps is 6646±3400 and the daily e-sport hours are 9.34±1.12. The BMI was determined as USA 26.12, South Korea 26.02 and Turkey 25.84 respectively. The number of physical activity steps was identified as 5255 steps in the US, 7785 steps in South Korea and 7909 steps in Turkey. The daily e-sports hour is set at US 9.63 hours, Turkey 9.29 hours and South Korea 8.97 hours. In comparison of country-based athletes, there was a significant difference between physical activity level and daily e-sports hours at p

ABSTRACTBackground:The purpose of this in-vitro study was to evaluate the centering ability and the apical transportation of curved root canals after preparation with WaveOne Gold single-file reciprocating system with guidance of different glide path systems by using Cone-Beam Computed Tomography. Methods:Seventy-two extracted mandibular first molar teeth with curved mesial roots were selected for this study. Specimens were randomly divided into six experimental groups according to the root canal preparation (n = 12): Group G-File; Group One G; Group ProGlider; Group PathFile; Group K-files; and Group control. After forming a glide path, root canal preparation procedure was completed with WaveOne Gold primary instrument (#25). Cone-beam computed tomographic images of specimens were taken before and after root canal preparation procedure. Apical transportation and centering ability were evaluated at 1, 4, and 7 mm from the apical foramen. The data were statistically analyzed using the Kruskal Wallis test at a significance level of P = 0.05. Results:There were no significant differences among all experimental groups. (p > 0.05) Conclusion:Creating a glide path in curved root canals with either NiTi glide path files or stainless still manuel K-files before root canal preparation with WaveOne Gold Primary caused similar apical transportation and centering ability results with no glide path used group.

The egg structures of eight Dioctria species known in Turkey, i.e., D. abdominalis, D. arcana, D. cornuta, D. flavipennis, D. hermonensis, D. linearis, D. sudetica, D. valida were examined and described in detail, using the scanning electron microscope (SEM). The material was collected from various habitats such as watersides, forest areas and crop fields within Adana, Aksaray, Mersin, Nigde, Karaman and Konya provinces between 2006 and 2007. Dioctria eggs are characterized as: 1) ovoid in shape and brown in color; 2) operculum at the anterior pole of the egg; 3) one or two micropyles at the center of the operculum; 4) aeropyles scattered in the body region and operculum or only in the former. The eggs were photographed to provide useful information to the systematics of Dioctria genus.

This study was carried out to investigate the effect of static and dynamic core training on the performance of football players. In this study, static and dynamically applied core exercises were evaluated in terms of speed and agility in football players, and then their effects on anaerobic power tests, core stabilization tests and body composition were compared. While 10 of the 30 football players participating in the study were practicing dynamic core exercises and 10 of them were practicing static core exercises 2 days a week for about 9 weeks and 30 minutes a day, 10 athletes continued their football training with the other group athletes as control groups. The effects of the exercises, performed at the end of 9 weeks on performance, body composition, and core stabilization tests were compared in the pre and post-test in order (p lt;0.05). There is no significant difference in the height, body weight, body mass index parameters of 30 subjects (10 control, 10 static core, 10 dynamic core) belonging to the 3 groups participating in the study. Significant differences were found at waist level and hip circumference at the level of p lt;0.05 in comparisons between the first and last measurements of all anthropometric measurements. While there was a significant increase in the duration of leg lift, push-up, plank, shuttle, and isometric tests, a decrease was observed in the plank, shuttle and isometric test times in the control group. In the pre and post-test comparisons, 30 m speed, long jump, vertical jump, agility 550 and arrowhead agility tests showed a significant difference at p lt;0.05 level. It can be said that core studies should be included in training aimed at increasing performance in the football branch.