Flow diverter as a rescue therapy for a complicated basilar angioplasty

Intracranial atherosclerotic disease is a major cause of ischemic stroke. Stenting and aggressive medical management for preventing recurrent stroke in intracranial stenosis was terminated prematurely due to a high stroke and death rate in patients randomized for intracranial stent placement. However, for some patients, angioplasty and/or stent placement remains the best approach. Flow diverters (FDs) are designed to produce a hemodynamic flow diversion by constituting a laminar flow pattern in the parent artery and are mainly used in non-ruptured complex wide-neck aneurysms as well as in ruptured aneurysms. Herein, we present a case where an FD was used in a complicated angioplasty for basilar artery atherosclerosis. A 72-year-old female patient was admitted to our hospital with left side weakness and vertigo. Her diffusion magnetic resonance imaging and magnetic resonance angiography showed right-sided pontine and left-sided occipital acute infarcts with left-sided pontine and right-sided occipital chronic infarcted areas and preocclusive mid-basilar stenosis. The patient was under supervised medical treatment. Despite chronic brain stem and occipital infarcts her modified Rankin Scale was 2. Diagnostic angiography showed no posterior communicating arteries and no pial-pial collaterals and a critical mid-basilar artery stenosis. We decided to perform intracranial angioplasty to increase the perfusion of posterior circulation and reduce the risk of additional embolic infarcts. Angioplasty was complicated with dissection and vessel perforation. We used an FD for rescue therapy to avoid rebleeding. The patient was discharged with good clinical and angiographic results

Association between myocardial hypertrophy and apical diverticulum: more than a coincidence?

PURPOSEWe aimed to investigate the possible association between the myocardial hypertrophy and the development of an apical diverticulum.MATERIALS AND METHODSWe retrospectively reviewed 786 multidetector computed tomography (MDCT) coronary angiography examinations (520 males, 266 females; mean age, 57±15 years; age range, 18–78 years). The end-diastolic left ventricle wall thickness was measured in all patients, and a wall thickness of 11 mm was determined to be the cut-off value for myocardial hypertrophy. The ventricular apex and subvalvular area were evaluated for ventricular diverticula. The difference between the apical diverticula in patients with and without myocardial hypertrophy was determined.RESULTSThere were 12 myocardial hypertrophy and nine apical diverticulum cases. Myocardial hypertrophy was observed in four (44%) of nine patients who had apical diverticula, and an apical diverticulum was observed in four (33%) of 12 patients who had myocardial hypertrophy. There was statistically significant difference for myocardial wall thickness between the apical diverticula in patients with myocardial hypertrophy and those without myocardial hypertrophy (P = 0.011).CONCLUSIONDiagnosis of apical diverticula has become easier by using imaging modalities such as MDCT. There may be an association between myocardial hypertrophy and apical diverticulum

Determining the physical properties of grain in bread and durum wheat populations developed by rapid breeding by image processing algorithm and classification with ai techniques

Tez No : 772023 15.06.2023 tarihine kadar kullanımı yazar tarafından kısıtlanmıştır.Buğday, besleyici özelliği, biyoçeşitliliği, verimliliği, çevresel streslere karşı direnci, fiyatı, kolay depolanması ve yıllarca tazeliğini koruyabilmesi gibi özelliklerinden dolayı binlerce yıldır gıda ihtiyacının giderilmesinde kullanılan tahılların ilk sıralarında yer almaktadır. Artan dünya nüfus, değişen iklim koşulları, pandemi ve savaşlar buğday üretiminde yetersizliğe sebep olmakta bu sebeplerden dolayı üretimi artırmak ve piyasanın taleplerini karşılamak için modern teknikler geliştiren çalışmalar yapılmaktadır. Bu çalışmamızda geliştirdiğimiz görüntüleme sistemi ve tane rengi analiz tekniği ile tanelere ait fiziksel özellikler çıkarılmış, veri tabanı oluşturulmuş ve sınıflandırma modellerine ait bazı parametreleri derlediğimiz algoritma tarafından belirlenerek genotip sınıflandırma işlemi gerçekleştirilmiştir. Ekmeklik buğday olan Nevzatbey, Triticum aestivum sphaerococcum ve bu iki genotipten elde edilen F5:6 melezinin fiziksel özellikleri karşılaştırılmıştır. Makarnalık buğday olan Ahmetbuğdayı, Cesare ve bu iki genotipten elde edilen GM1F5:6 ve GM2F4:5 popülasyonlarının fiziksel özelliklerinin yanı sıra protein analizleri yapılmış ve melezlerden anaç genotiplerine gözle anlaşılması zor olan iki melez veri tabanından seçilerek ANN, SVM, kNN, DT, RF ve NB makine öğrenme algoritmaları ve ResNet50, InceptionV2, DenseNet, VGG16 derin öğrenme modelleri kullanılarak sınıflandırma başarıları karşılaştırılmıştır. Elde edilen sonuçlara göre ANN algoritması ile renk özelliklerine göre %99,3, ResNet50 ve DenseNet derin öğrenme ağları ile %96 doğrulukta tür sınıflandırma başarıları elde edilmiştir. Geliştirdiğimiz görüntüleme kabini ve analiz teknikleri ile ıslah çalışmaları, buğday sınıflandırma işlemlerinde kullanılabilmekte ve farklı hassas tarım uygulamaları içinde kullanılması tavsiye edilmektedir.Wheat has been one of the first cereals used for thousands of years to meet food needs due to its nutritional properties, biyodiversity, productivity, resistance to environmental stresses, price, easy storage, and keeping its freshness for years. Increasing world population, climate changes, pandemics and wars cause inadequacy in wheat production and studies are carried out to develop modern techniques to increase production and meet the demands of the market. With the imaging system and grain color analysis technique we developed in this study, the physical properties of the grains were extracted, the database was created, and the genotype classification process was carried out by determining some parameters of the classification models by the algorithm we compiled. The physical properties of the bread wheat Nevzatbey, Triticum aestivum sphaerococcum and the F5:6 hybrid obtained from these two genotypes were compared. ANN, SVM, kNN, DT, RF and NB machine learning algorithms were selected from two hybrid databases where protein analyzes were made and the genotypes from hybrids to rootstock were difficult to understand, as well as the physical properties of Ahmet wheat, Cesare, and BC1F5:6 and BC2F4:5 populations obtained from these two genotypes. and ResNet50, InceptionV2, DenseNet, VGG16 deep learning models were used to compare the classification successes. According to the results obtained, species classification success was obtained with the ANN algorithm with an accuracy of 99.3% according to the color characteristics, and 96% with the ResNet and DenseNet deep learning networks. With the imaging booth and analysis techniques we have developed, it can be used in breeding studies, wheat classification processes and is recommended for use in different precision agriculture applications

Ekmeklik buğdayda geliştirilen rekombinant kendilenmiş hat populasyonunda çavdar translokasyonu, Glu-A3b, Glu-B3b ve Waxy protein allellerinin belirlenmesi

TEZ 633.11/SÖNeKaynakça: 39-52 ss.[Özet Yok

Optimal placement of elastic steel diagonal braces using artificial bee colony algorithm

Sönmez, Mustafa (Aksaray, Yazar) Karabork, Turan (Aksaray, Yazar)This paper presents a new algorithm to find the optimal distribution of steel diagonal braces (SDB) using artificial bee colony optimization technique. The four different objective functions are employed based on the transfer function amplitude of; the top displacement, the top absolute acceleration, the base shear and the base moment. The stiffness parameter of SDB at each floor level is taken into account as design variables and the sum of the stiffness parameter of the SDB is accepted as an active constraint. An optimization algorithm based on the Artificial Bee Colony (ABC) algorithm is proposed to minimize the objective functions. The proposed ABC algorithm is applied to determine the optimal SDB distribution for planar buildings in order to rehabilitate existing planar steel buildings or to design new steel buildings. Three planar building models are chosen as numerical examples to demonstrate the validity of the proposed method. The optimal SDB designs are compared with a uniform SDB design that uniformly distributes the total stiffness across the structure. The results of the analysis clearly show that each optimal SDB placement, which is determined based on different performance objectives, performs well for its own design aim

Using an artificial bee colony algorithm for the optimal placement of viscous dampers in planar building frames

WOS: 000322342300012In this study, an Artificial Bee Colony Algorithm (ABCA) is used to obtain the optimal size and location of viscous dampers in planar buildings to reduce the damage to the frame systems during an earthquake. The transfer function amplitude of the top displacement and the elastic base shear force evaluated at the first natural circular frequency of structures are chosen as objective functions. The damper coefficients of the added viscous dampers are taken into consideration as design variables in a planar building frame. Transfer function amplitude of the top displacement and the amplitude of the elastic base shear force at the fundamental natural frequency are minimized under an active constraint on sum of the damper coefficients of the added dampers. According to two specified objective functions, an optimization algorithm based on the ABCA is proposed. The proposed method is verified by a gradient-based algorithm; steepest direction search algorithm (SDSA). The proposed ABCA and the SDSA are applied to find the optimal damper distribution for a nine-storey planar building then the optimal damper allocation obtained from the ABCA is investigated to rehabilitate models of irregular planar buildings. The validity of the proposed method was demonstrated through a time history analysis of the optimal damper designs, which were determined based on the frequency domain using the ABCA. The numerical results of the proposed optimal damper design method show that the use of the ABCA can be a practical and powerful tool to determine the optimal damper allocation in planar building structures

Sound absorption depending on landscape pattern changes in a highway

Noise is one of the inevitable environmental problems caused by the increasing population all over the world. There are various sources of noise that have physiological and psychological effects on people. One of these is traffic noise, which is especially effective in residential areas. This study aims to investigate the effect of different vegetation types on noise reduction in a highway model with heavy traffic. Six locations with dense planting along the highway in terms of plant groups and species density were selected, and the correlation of species density with noise analysis values was examined. For each location point, 2 points were assigned on the line, in front of and behind the vegetation, and measurements were made at 12 stations in total. Measurements were taken by performing fieldwork 5 times in different seasons and months and expressed as Leq differences. Since the vegetation types at the measurement points were not ordered, the species density analysis was determined in percentage (%) within the square areas of 100x100 meters in the existing field conditions. Mapping was completed using GIS to visualize the spatial spread of the noise measurement results, and zoning was done with interpolation to determine the noise contours and noise effect. According to all the findings obtained in this study, the leafy shrub or the tree group were found more effective in noise absorption than the coniferous species. Numerical calculations on maps suggest that plant community size and diversity can have a positive impact on noise reduction