Comparison of Mann-Kendall and innovative trend method (Şen trend) for monthly total precipitation (Middle Black Sea Region, Turkey)

The objective of this study is to determine possible trend in annual total precipitation based on Mann–Kendall (MK) and a novel method lately published by Şen. The novel method is used for trend analysis of annual total precipitation data recorded at Sinop, Samsun, Ordu, Corum, Amasya, and Tokat provinces in Turkey. This provinces are located in the central Black Sea region of Turkey. The novel Şen’s trend method is applied to this data. According to the Şen’s trend method, peak and low values of annual total precipitation of the six provinces demonstrate same trends (increasing, decreasing, or trendless time series) with the MK test. The study demonstrates that the Şen method can be used for identifying trend analysis of peak and low values of annual total precipitation data. According to the MK trend test, annual total precipitations demonstrate increasing trend for Sinop, Ordu and Tokat provinces while Şen’s method indicates increasing trend in Sinop, Amasya and Tokat in Turkey. As a result, Şen’s method provides an important advantage in terms of especially in all ranges graphically clarification of the data evaluation phase

Prediction using step-wise L1, L2 regularization and feature selection for small data sets with large number of features

<p>Abstract</p> <p>Background</p> <p>Machine learning methods are nowadays used for many biological prediction problems involving drugs, ligands or polypeptide segments of a protein. In order to build a prediction model a so called training data set of molecules with measured target properties is needed. For many such problems the size of the training data set is limited as measurements have to be performed in a wet lab. Furthermore, the considered problems are often complex, such that it is not clear which molecular descriptors (features) may be suitable to establish a strong correlation with the target property. In many applications all available descriptors are used. This can lead to difficult machine learning problems, when thousands of descriptors are considered and only few (e.g. below hundred) molecules are available for training.</p> <p>Results</p> <p>The CoEPrA contest provides four data sets, which are typical for biological regression problems (few molecules in the training data set and thousands of descriptors). We applied the same two-step training procedure for all four regression tasks. In the first stage, we used optimized L1 regularization to select the most relevant features. Thus, the initial set of more than 6,000 features was reduced to about 50. In the second stage, we used only the selected features from the preceding stage applying a milder L2 regularization, which generally yielded further improvement of prediction performance. Our linear model employed a soft loss function which minimizes the influence of outliers.</p> <p>Conclusions</p> <p>The proposed two-step method showed good results on all four CoEPrA regression tasks. Thus, it may be useful for many other biological prediction problems where for training only a small number of molecules are available, which are described by thousands of descriptors.</p

Use of a biopolymer for road pavement subgrade

This paper presents an extensive series of laboratory works and a prediction model on the design of a road pavement subgrade with Xanthan Gum (XG) biopolymer. The experimental works were carried out using mixtures of conventional aggregate for road pavement construction and XG at the ratios of 0%, 1%, 2%, and 5%, by dry weight. Unconfined compressive strength (UCS) and California bearing ratio (CBR) tests were conducted during the experimental works at the end of the various curing periods (4, 8, 16, and 32 days). An example of an improvement in the UCS values for a specimen with 5% XG addition tested at the end of 4-daycuring yields about a 200% increment by the end of a 32-daycuring. The CBR values of clean aggregates were found to be increased by about 300% by 5% XG addition for all curing periods applied. Furthermore, the energy absorption capacity of the aggregates was observed to be increased significantly by both XG inclusion and curing period. Moreover, scaled conjugate gradient (SCG) training algorithm-based models developed for the prediction of CBR and UCS test results displayed a very high estimation performance with the regression coefficients of R-2 = 0.967 and R-2 = 0.987, respectively. Evidently, XG biopolymer is provably of use as an alternative inclusion in road pavement subgrades constructed with conventional aggregates

The psycho-social needs of displaced Syrian youth in Turkish schools:A qualitative study

This study investigates major challenges encountered by Syrian refugee youth in public high schools in Turkey, focusing on three sources of assessment: the refugee students themselves and their parents and educators. Based on qualitative interpretive research methodology, twenty-three individual semi-structured interviews were conducted. The study simultaneously hears the voices of the Syrian refugee students as well as those of their parents, teachers, and principals. Making friends among Turkish peers, social integration in school and the host society, discrimination, feeling lonely or even depressed, and other displacement problems are the crucial issues identified by this study. While most of the teachers and principals interviewed focused more on academic problems as the main reason for the deterioration of the majority of Syrian youth's education, refugee students and their parents claimed that the psycho-social challenges are more difficult and thus problematic. © 2021 Birlesik Dunya Yenilik Arastirma ve Yayincilik Merkezi. All rights reserved

Podwójne znakowanie immunologiczne CD133 i Ki-67 wskazuje na ich istotną współlokalizację w podtypie włóknistym oponiaków

Background and purpose A unique molecular and/or cellular marker for meningiomas, the most common intracranial tumours, has not been identified yet. Material and methods We investigated the co-localization fraction of CD133/Ki-67 in meningioma tissue array slide composed of 80 meningioma tissue samples of various histological variants. CD133 – a cell membrane stem cell marker – was previously proved to be associated with the initiation and progression of intracerebral gliomas and medulloblastomas. Results Immunohistochemical co-localization of CD133/Ki-67 was significantly higher in fibroblastic variant than in meningothelial and transitional subtypes. However, since there were only 3 atypical and 1 malignant meningioma spots in the tumour tissue array slide, it is difficult to draw a firm conclusion regarding the actual co-localization percentage and persistence of CD133/Ki-67 in atypical and malignant meningiomas. Conclusions Far higher co-staining percentage of CD133/Ki-67 in fibroblastic meningioma samples compared to meningothelial subtype, a histological meningioma variant, architectonically resembling the non-neoplastic meningeal cells, gave us the impression that CD133 may play a role in the formation and progression of fibroblastic meningioma variants. The persistency and the validity of this finding need to be verified by further histopathological and molecular research in order to clarify the possible role of CD133 in meningiogenesis.Wstęp i cel pracy Nie określono dotąd unikalnego znacznika molekularnego lub komórkowego dla oponiaków, najczęstszych guzów wewnątrzczaszkowych. Wcześniej wykazano, że CD133 – znacznik błony komórkowej komórek macierzystych – jest związany z zapoczątkowaniem, a także wzrostem wewnątrzczaszkowych glejaków i rdzeniaków płodowych. Materiał i metody Zbadano odsetek współlokalizacji CD133/Ki-67 w zestawach macierzy tkankowych oponiaków, złożonych z próbek 80 rozmaitych odmian histologicznych oponiaków. Wyniki Immunohistochemiczna współlokalizacja CD133 i Ki-67 była stwierdzana istotnie częściej w podtypie włóknistym oponiaka niż w podtypach meningotelialnym lub przejściowym. Ze względu na małą liczbę preparatów opo-niaków atypowych (3) oraz złośliwych (1) w badanej macierzy tkankowej trudno wyciągnąć jednoznaczne wnioski dotyczące rzeczywistego odsetka współlokalizacji i utrzymywania się CD133/Ki-67 w oponiakach atypowych i złośliwych. Wnioski Znacząco większy odsetek wspólnie występującej reaktywności CD133/Ki-67 w preparatach oponiaka włóknistego w porównaniu z podtypem meningotelialnym, którego architektonika przypomina nienowotworowe komórki opon, sprawia wrażenie, że CD133 może odgrywać rolę w powstawaniu i rozwoju oponiaków włóknistych. Trafność tego spostrzeżenia wymaga weryfikacji w dalszych badaniach histopatologicznych i molekularnych w celu wyjaśnienia możliwej roli CD133 w powstawaniu oponiaków

Dendritic spine shape classification from two-photon microscopy images (Dendritik diken şekillerinin iki foton mikroskopi görüntüleri kullanılarak sınıflandırılması)

Functional properties of a neuron are coupled with its morphology, particularly the morphology of dendritic spines. Spine volume has been used as the primary morphological parameter in order the characterize the structure and function coupling. However, this reductionist approach neglects the rich shape repertoire of dendritic spines. First step to incorporate spine shape information into functional coupling is classifying main spine shapes that were proposed in the literature. Due to the lack of reliable and fully automatic tools to analyze the morphology of the spines, such analysis is often performed manually, which is a laborious and time intensive task and prone to subjectivity. In this paper we present an automated approach to extract features using basic image processing techniques, and classify spines into mushroom or stubby by applying machine learning algorithms. Out of 50 manually segmented mushroom and stubby spines, Support Vector Machine was able to classify 98% of the spines correctly

Assessment of ventricular septal defects by real-time three-dimensional echocardiography and comparison with surgical measurements

Peer reviewe

Dendritic spine shape analysis using disjunctive normal shape models

Analysis of dendritic spines is an essential task to understand the functional behavior of neurons. Their shape variations are known to be closely linked with neuronal activities. Spine shape analysis in particular, can assist neuroscientists to identify this relationship. A novel shape representation has been proposed recently, called Disjunctive Normal Shape Models (DNSM). DNSM is a parametric shape representation and has proven to be successful in several segmentation problems. In this paper, we apply this parametric shape representation as a feature extraction algorithm. Further, we propose a kernel density estimation (KDE) based classification approach for dendritic spine classification. We evaluate our proposed approach on a data set of 242 spines, and observe that it outperforms the classical morphological feature based approach for spine classification. Our probabilistic framework also provides a way to examine the separability of spine shape classes in the likelihood ratio space, which leads to further insights about the nature of the shape analysis problem in this context

Volume CXIV, Number 4, November 7, 1996

Objective: Turner syndrome (TS) is a chromosomal disorder caused by complete or partial X chromosome monosomy that manifests various clinical features depending on the karyotype and on the genetic background of affected girls. This study aimed to systematically investigate the key clinical features of TS in relationship to karyotype in a large pediatric Turkish patient population.Methods: Our retrospective study included 842 karyotype-proven TS patients aged 0-18 years who were evaluated in 35 different centers in Turkey in the years 2013-2014.Results: The most common karyotype was 45,X (50.7%), followed by 45,X/46,XX (10.8%), 46,X,i(Xq) (10.1%) and 45,X/46,X,i(Xq) (9.5%). Mean age at diagnosis was 10.2±4.4 years. The most common presenting complaints were short stature and delayed puberty. Among patients diagnosed before age one year, the ratio of karyotype 45,X was significantly higher than that of other karyotype groups. Cardiac defects (bicuspid aortic valve, coarctation of the aorta and aortic stenosis) were the most common congenital anomalies, occurring in 25% of the TS cases. This was followed by urinary system anomalies (horseshoe kidney, double collector duct system and renal rotation) detected in 16.3%. Hashimoto's thyroiditis was found in 11.1% of patients, gastrointestinal abnormalities in 8.9%, ear nose and throat problems in 22.6%, dermatologic problems in 21.8% and osteoporosis in 15.3%. Learning difficulties and/or psychosocial problems were encountered in 39.1%. Insulin resistance and impaired fasting glucose were detected in 3.4% and 2.2%, respectively. Dyslipidemia prevalence was 11.4%.Conclusion: This comprehensive study systematically evaluated the largest group of karyotype-proven TS girls to date. The karyotype distribution, congenital anomaly and comorbidity profile closely parallel that from other countries and support the need for close medical surveillance of these complex patients throughout their lifespa

Teaching the Academic Word List in Foreign Language Speaking Classes

WOS: 00043485270039