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Katılım finans ekosistemi son yıllarda oldukça geniş bir coğrafyada kabul görmüştür. Bu durum sadece Müslüman ülkeler ile sınırlı kalmayıp Müslüman olmayan ülkeleri de içine almıştır. Katılım finans ürünlerine olan ilginin arka planında ise geleneksel muadillerine göre bu ürünlerin doğaları gereği faizsizlik prensipleri üzerine inşa edilmeleri ve güçlü bir yapıya sahip olmaları yatmaktadır. Katılım finans ürünleri içerisinde en fazla ilgiyi ise varlık temelli yapısıyla Katılım Sermaye Piyasası ürünlerinden sukuk görmektedir. Sukuk, muadili olarak görülen tahvillerden çok farklı bir yapıya sahiptir. Tahviller, içerisinde herhangi bir dayanak varlık bulundurmayan ve tahvil sahiplerine belirli tarihte anapara ve faiz ödemeyi taahhüt eden borç senetleridir. Sukuk ise varlığa dayalı bir menkul kıymetleştirme işlemi olup sukuk sahiplerine anapara ve kâr taahhüdünde bulunmayan bir enstrümandır. 1970 yılının sonunda kullanılmaya başlayan sukuk enstrümanının büyüme hacmi yıllar itibariyle devasa boyutlara ulaşmıştır. Sukuk piyasalarının son on yıldaki büyüme ivmesi ise katılım finansın finansal piyasalardaki pazar payının artmasında önemli bir rol oynamaktadır. Dünya piyasalarında sukuk ihraçları 2014-2021 döneminde 107 milyar dolardan 188 milyar dolara yükselmiştir. 2022 yılında sukuk ihraçlarının katılım finans ekosisteminden aldığı pay %25 seviyelerine ulaşmıştır. Bu payda 2021 yılında en yüksek hacmi ise %33,5 pay ile Suudi Arabistan, %25 pay ile Malezya ve %15 pay ile Endonezya oluşturmaktadır. Türkiye’nin ise global sukuk piyasalarında %6.9 payı bulunmaktadır. Sukuk, faizsiz bir şekilde tasarrufların değerlendirilmesi ve fon sağlaması hedefleri doğrultusunda kullanılan bir enstrümandır. Toplum yararına olan büyük projelerin finansmanına katkı sağlamak için tasarlanmış bu finansal araç, hem özel hem de kamu projeleri için çeşitli finansman fırsatları sunmanın yanı sıra bireylerinin bu sürece katılmaları hususunda imkânlar sunmaktadır. Özellikle katılım bankaları tarafından gerçekleştirilen sukuk ihraçları ciddi rağbet görmektedir. Bu rağbet katılım bankaları tarafından ihraç edilen sukuk hacimlerine de yansımaktadır. Sukuk ihraçları 2015-2022 döneminde 2.5 milyar ₺’den 83 milyar ₺’ye ulaşmıştır. Bu bağlamda çalışmada katılım bankaları açısından önemli bir gelir kaynağı olan sukuk ihraçlarının katılım bankalarının finansal performanslarını nasıl etkilediği araştırılmıştır. Bu amaca yönelik katılım bankalarının finansal performans göstergesi olarak aktif kârlılık (ROA) ve özsermaye kârlılığı (ROE) ele alınmıştır. 2015Q1-2023Q2 dönemine ait çeyreklik veriler kullanılarak panel veri analizi yöntemi ile incelenmiştir. Ele alınan veriler Türkiye Katılım Bankaları Birliği (TKBB), Banka faaliyet raporları, Türkiye İstatistik Kurumu (TÜİK) ve Türkiye Cumhuriyet Merkez Bankası Elektronik Veri Dağıtım Sistemi (EVDS)’nden temin edilmiştir. Ayrıca banka büyüklüğü, enflasyon, döviz kurları, GDP (Gayrisafi yurtiçi hasıla büyüme oranı), faiz oranları ve işsizlik değişkenleri de analizlerde kullanılmıştır. Bulgulara göre sukuk ihraçlarının, banka büyüklüğü ve enflasyonun katılım bankalarının finansal performanslarını pozitif yönde etkilediği; takipteki krediler ve döviz kurlarının negatif yönde etkilediği görülmüştür. GDP, faiz oranları ve işsizlik değişkenlerinin ise istatistiksel olarak anlamlı olmadığı tespit edilmiştir. Bulgular neticesinde elde edilen sonuçlar literatürde yer alan (Saad ve Haniff, 2013; Mimouni vd., 2019; Ho ve Mohd-Raff, 2019; Ergün, 2020; Al-Harbi,2020; Hidayat vd., 2021; Bouhider, 2021, Le vd., 2022; Ledhem, 2022; Akın ve Duramaz, 2022) çalışma sonuçları ile örtüşmektedir. Analiz sonuçlarına göre, küresel düzeyde önemli bir enstrüman haline gelen sukuk ihraçlarının katılım bankalarının finansal performansı üzerinde pozitif bir rol oynadığı görülmektedir. Bu yüzden sukuk ihraçlarının artırılmasının yanı sıra, yeşil sukuk ve mavi sukuk gibi sukuk türlerinin yaygınlaştırılmasının katılım bankaları açısından önemli bir finansal ürün niteliği taşıyabileceği ifade edilebilir.

Abstract T cell exhaustion is a hallmark of cancer and persistent infections, marked by inhibitory receptor upregulation, diminished cytokine secretion, and impaired cytolytic activity. Terminally exhausted T cells are steadily replenished by a precursor population (Tpex), but the metabolic principles governing Tpex maintenance and the regulatory circuits that control their exhaustion remain incompletely understood. Using a combination of gene-deficient mice, single-cell transcriptomics, and metabolomic analyses, we show that mitochondrial insufficiency is a cell-intrinsic trigger that initiates the functional exhaustion of T cells. At the molecular level, we find that mitochondrial dysfunction causes redox stress, which inhibits the proteasomal degradation of hypoxia-inducible factor 1α (HIF-1α) and promotes the transcriptional and metabolic reprogramming of Tpex cells into terminally exhausted T cells. Our findings also bear clinical significance, as metabolic engineering of chimeric antigen receptor (CAR) T cells is a promising strategy to enhance the stemness and functionality of Tpex cells for cancer immunotherapy.

The promising results of transcatheter aortic valve replacement (TAVR) over the past two decades indicate an expansion of the patient cohort toward patients with intermediate or low surgical risk. Since some complications of TAVR have already been minimized, subclinical leaflet thrombosis (SLT) has gained importance in recent years. SLT is manifested by a thrombotic layer on the prosthetic leaflets that gradually reduces leaflet motion. The resulting decrease in functionality of the TAVR causes a need for re-intervention. The origin of SLT and approaches to prevent SLT are still unexplored. For this reason, we have developed an in silicomodel that can be used during the design development process of TAVR devices to estimate the thrombosis risk of the implant. Based on passive scalar transport, hemodynamic metrics are used to quantify platelet activation and aggregation which are associated with the formation of thrombosis. In conjunction with a numerical simulation model considering the fluid-structure interaction between the blood mimicking fluid and the TAVR implanted in an aortic root, the thrombosis risk can be modeled. The simulation model can be used to calculate the three-dimensional flow structures within the native sinus and neo-sinus and also provides the ability to derive metrics to assess the risk of thrombosis. We demonstrated that this in silicomodel is a time-effective tool to assess thrombosis risk in TAVR product development.

The aim of this research is to determine the effect of curriculum literacy levels of primary school English teachers on the official and functional curriculum practices. In line with this purpose, an explanatory sequential design was used and qualitative data supplemented quantitative insights. The study was carried out in various primary schools on the European Side of Istanbul in the second semester of the 2021-2022 academic year. The participants of the study consisted of 98 English teachers for the quantitative part. For the qualitative part, six teachers were selected by the maximum variation sampling method. The quantitative data of the study were collected with the Curriculum Literacy Scale. Standard deviation, mean and independent groups t-test were used in the analysis of quantitative data. Qualitative data were analysed using the descriptive analysis method through the In-Class Program Compatibility Observation Form. In the analysis of the data, a classification was made for the cognitive process and the knowledge dimensions of Bloom's revised taxonomy for the objectives. In the teaching process and evaluation elements, a comparison was made with the relevant items of the primary school English curriculum. Quantitative results show notably high curriculum literacy levels among primary school English teachers, particularly in reading. Qualitative findings reveal that highly curriculum-literate teachers are better aligned with the official curriculum, while lower literacy levels yield greater compatibility in learning experiences. The study concludes that higher curriculum literacy corresponds to better curriculum alignment among teachers.

Biofluid mechanics play an important role in the study of the mechanism of cardiovascular diseases and in the development of new implants. For the assessment of hydrodynamic parameters, experimental methods as well as in-silico approaches can be used, such as particle image velocimetry (PIV) and Deep Learning, respectively. Challenges for PIV are the optical access to the region of interest, and time consumption for measuring and post-processing analysis in particular for three dimensional flow. To overcome these limitations state-of-the-art deep learning algorithms could be utilized to augment spatially coarse resolved flow fields. In this study, we demonstrate the use of Physics Informed Neural Networks (PINN) to augment PIV measurement data. To demonstrate a combined workflow, we investigate the flow of a Newtonian fluid through a simplified aneurysm under laminar conditions. Generation of synthetic PIV particle images of a single measurement plane and the corresponding PIV vector calculations were performed as the basis for the PINN algorithm. Based on the Navier-Stokes equations the PINN reconstructs the entire 3D flow field and pressure distribution inside the aneurysm. We observed qualitative agreements between ground through data and PINN predictions. Nevertheless, there are substantial differences in the quantitative, locally resolved comparison of the flow metrics, despite the generally tendency for the PINN algorithm to correctly augment the flow field.

Severe aortic valve stenosis has been successfully treated with minimally invasive transcatheter aortic valve replacement (TAVR) for more than 20 years. The therapy is applied to an increasing cohort of patients. Nevertheless, paravalvular leakage (PVL) remains one of the main complications after TAVR implantation reducing safety and efficacy of the implant. To improve TAVR performance, virtual patient cohorts can be used to generate a significant amount of data with biologically varying conditions comparable to clinically realworld data. For this purpose, in silico models need to be established which are used to evaluate the possible occurrence of PVL. When establishing in silico models, the question between simplification to reduce computational effort and still valid information from the model must always be clarified. Thus, we investigated the comparability between steadystate and transient PVL measurements as an input parameter for simulations in virtual cohorts. A clinically established TAVR was implanted into different annulus models and tested in a steady-state back-flow test bench and in a pulse duplicator system. As a result, leakage rates were compared and assumptions for the in silico models were derived. Although the trend of PVL is comparable in steady-state and transient conditions, absolute values differ making it difficult to extract generalized assumptions. Especially when PVL increased, e.g. in a larger implantation diameter or in an imperfect annulus, the variation also increased up to 50% of the measured value.

Objective: Diffuse large B-cell lymphoma (DLBCL) is a biologically heterogeneous disease that is classified into germinal center B-cell (GCB) and non-GCB subtypes, which are prognostically different. The Hans algorithm is the most widely used tool based on CD10, BCL6, and MUM1 expression, but some cases with the non-GCB phenotype are still known to be misclassified. In this study, we investigate the extent to which GCET1, HGAL, and LMO2 protein expressions reflect GCB phenotype together with their roles in determining the GCB phenotype of DLBCL and their contributions to the performance of the Hans algorithm. Materials and Methods: Sixty-five cases of DLBCL-not otherwise specified, 40 cases of follicular lymphoma (FL), and 19 non-GC-derived lymphoma cases were included in this study. The DLBCL cases were grouped as CD10+ (Group A) or only MUM1+ (Group B), and the remaining cases constituted the intermediate group (Group C). GCET1, HGAL, and LMO2 expressions were evaluated. Results: In the FL group, GCET1, HGAL, and LMO2 were positive in 85%, 77.5%, and 100% of the cases, respectively. Among the non-GCderived lymphoma cases, all three markers were negative in cases of small lymphocytic lymphoma, plasmablastic lymphoma, peripheral T-cell lymphoma, and anaplastic large cell lymphoma. GCET1 and HGAL were negative in cases of marginal zone lymphoma (MZL) and mantle cell lymphoma (MCL). Two of the 3 MZL and 2 of the 4 MCL cases were positive for LMO2. In the DLBCL group, the number of cases with GCET1, HGAL, and LMO2 positivity was 18 (90%), 17 (85%), and 20 (100%), respectively, in Group A and 0 (0%), 2 (13.3%), and 2 (13.3%), respectively, in Group B. Considering these rates, when the cases in the intermediate group were evaluated, it was concluded that 13 cases typed as non-GCB according to the Hans algorithm may have the GCB phenotype. Conclusion: GCET1, HGAL, and LMO2 are highly sensitive markers for determining the germinal center cell phenotype and can increase the accuracy of the subclassification of DLBCL cases, especially for cases that are negative for CD10.

The development of technology and the globalization of financial markets have increased the volatility in financial markets and caused the emergence of risks and uncertainties that have not been previously encountered. Since traditional econometric models cannot fully explain this volatility, nonlinear conditional variance models such as ARCH, GARCH, EGARCH and TARCH are used today. From this point of view, this study aims to determine the most explanatory model that fund managers who are considering investing in the Borsa Istanbul 100 (BIST 100) Index, and academicians doing research on this subject, can use in estimating the BIST 100 Index return volatility. For this purpose, ARCH and GARCH models, as symmetric models, and EGARCH and TARCH models, as asymmetric nonlinear conditional models, are included in the econometric analysis by using the end-of-day values of 2657 observations belonging to the 04.01.2010-28.07.2020 period. According to the empirical results of the study, the TARCH model, which has the highest level of explanatory power, gives the most successful results among related models in revealing BIST 100 Index return volatility.

The purpose of this research was to compare mental and physical practice on acquisition of basketball free shot. Forty inexperienced boys were selected randomly by a revised questionnaire of motor imagery-making of Hall and Martin (1977). They were divided into 2 groups; an experimental group and a control one. Group one carried out the whole practice sessions practically. Group two carried out the whole sessions regarding to the mental practice being achieved as internal imagery. The results showed that the mental practices have significant impact on acquisition of basketball free shot.

The main aim of this research was to reveal relationship between distress tolerance levels of university students according to different variables. The study sample consisted of 600 students in 2017-2018 academic years at Ataturk University in Erzurum, Turkey. In the study the "Distress Tolerance" Scale was conducted. It was developed by Simons et al. (2005) and its verification and validation in Turkish was conducted by Sargin et al (2012). SPSS 21 package program was used to analyze the data. In the analysis of data; frequency distribution was used in determination of demographic characteristics, the Independent Samples T test was used in examination of relationship between two independent variables and distress tolerance level, the one way ANOVA analysis test was used in examination of relationship between more than two variables and the distress tolerance levels. All these tests were analyzed in SPSS 21 package program and the significance was evaluated at p <0.05 level. According to the findings, it was determined that there was a significant difference between the students' distress tolerance levels and sports activity. It was observed that the students who were doing sports activities have higher distress tolerance level than those were not doing sportive activities. No significant difference was found between the distress tolerance level and gender, grade level and family structure. As a result of the fact that sports activities have a positive effect on the distress tolerance level, it is recommended that students be given opportunity to make different sports activities, by raising their awareness about the sports activity in order to increase the distress tolerance in learning process or the course of life However, it is also recommended to carry out studies to identify different variables that may have an impact on distress tolerance.

Objective: In this study, we aimed to investigate the physiological biodistribution pattern of 68Ga- DOTATATE and DOTANOC using standardized uptake value (SUV) parameters (maximum and mean) in nontumorous tissues on positron emission tomography/computed tomography (PET/CT) images. Methods: Images of 40 patients (female, n=23 and male, n=17; mean age, 52.50+-15.82 years) who had undergone 68Ga-DOTA labeled (TATE or NOC) PET/CT imaging with the diagnosis of GEPneuroendocrine tumor (NET), non-GEP-NET and thyroid cancer were retrospectively evaluated. SUVmax and SUVmean measurements were performed from areas of physiologic uptake including pituitary gland, parotid and submandibular gland, palatine tonsils, thyroid, lungs, blood pool, thymus, lymph nodes, liver, pancreas (from head, body and tail parts), spleen, stomach, both adrenal gland, kidney, small bowel and colon, bone marrow, prostate, glandular breast tissue and muscle tissue. Results: The highest uptake for 68Ga-DOTATATE and 68Ga-DOTATANOC was noted in the spleen, adrenal, kidney, liver, pituitary gland and head of the pancreas, respectively. Lung, muscle, blood pool, bone marrow, lymph node and breast showed low uptake (SUVmax-mean