P Wave Dispersion is Increased in Pulmonary Stenosis

Aim: The right atrium pressure load is increased in pulmonary stenosis (PS) that is a congenital anomaly and this changes the electrophysiological characteristics of the atria. However, there is not enough data on the issue of P wave dispersion (PWD) in PS. Methods: Forty- two patients diagnosed as having valvular PS with echocardiography and 33 completely healthy individuals as the control group were included in the study. P wave duration, p wave maximum (p max) and p minimum (p min) were calculated from resting electrocariography (ECG) obtained at the rate of 50 mm/sec. P wave dispersion was derived by subtracting p min from p max. The mean pressure gradient (MPG) at the pulmonary valve, structure of the valve and diameters of the right and left atria were measured with echocardiography. The data from two groups were compared with the Mann-Whitney U test and correlation analysis was performed with the Pearson correlation technique. Results: There wasn’t any statistically significance in the comparison of age, left atrial diameter and p min between two groups. While the MPG at the pulmonary valve was 43.11 ± 18.8 mmHg in PS patients, it was 8.4 ± 4.5 mmHg in the control group. While p max was 107.1 ± 11.5 in PS group, it was 98.2 ± 5.1 in control group (p=0.01), PWD was 40.4 ± 1.2 in PS group, and 27.2 ± 9.3 in the control group (p=0.01)Moreover, while the diameter of the right atrium in PS group was greater than that of the control group, (38.7 ± 3.9 vs 30.2 ± 2.5, p=0.02). We detected a correlation between PWD and pressure gradient in regression analysis. Conclusion: P wave dispersion and p max are increased in PS. While PWD was correlated with the pressure gradient that is the degree of narrowing, it was not correlated with the diameters of the right and left atria

Multivariate interpolation applications of different high dimensional model representations

Bu çalışmada adet bağımsız değişkene bağlı olan birçok değişkenli fonksiyonun değerlerinin bağımsız değişkenlerin sonlu sayıda değer takımı için verildiği ve fonksiyonun analitik yapısının istendiği çok değişkenli interpolasyon problemlerinin daha az değişkenli interpolasyon problemlerine indirgenmesi amaçlanmıştır. Böylelikle, hesaplama karmaşıklığı düşürülecek ve problemin bilgisayar ortamında programlanması da kolaylaşacaktır. Bu amaçla, değişkenli bir interpolasyon problemi  adet tek bağımsız değişkenli interpolasyon problemi haline getirilmektedir. Belirtilen indirgeme için ilk olarak I.M. Sobol tarafından tasarlanan Yüksek Boyutlu Model Gösterilim (YBMG) yöntemi geliştirilmiştir. Bu yöntem çok değişkenli verinin hiperprizmatik örgünün tüm düğümlerinde verildiği problemlerde veri bölümlemesinde kullanılmaktadır. Bölümleme sonucunda elde edilen tek değişkenli veri kümesinden çok değişkenli fonksiyon için aranılan analitik yapı yaklaşık olarak elde edilebilmektedir. Yöntemin temel felsefesini oluşturan sonlu terimden oluşan açılımın yapısı baskın olarak toplamsal özellikler taşıyan çokdeğişkenli veri kümelerine ait interpolasyon problemlerinde gerçek sonuca yakın gösterilimler elde etmeyi sağlamaktadır. Aranılan analitik yapı, yani verilen çok değişkenli veri kümesinin yapısı, toplamsal özelliklerden uzaklaşıp çarpımsal veya melez özelliklere sahip olmaya başladığında YBMG yönteminin verimi düşmektedir. Bu bağlamda alternatif yöntemlere ihtiyaç duyulmaktadır. Bu amaçla, problemde verilen veri takımının yapısına göre Çarpımsallaştırılmış Yüksek Boyutlu Model Gösterilim (ÇYBMG) ve Melez Yüksek Boyutlu Model Gösterilim (MYBMG) yöntemleri de oluşturulmuştur. Belirtilen bu yöntemler YBMG yöntemi aracılığıyla bölümlenmiş veriyi kullanarak çarpımsal veya melez yapıya sahip fonksiyonlar için daha iyi yaklaşıklık elde eden gösterilimler oluşturmayı hedeflemektedir. Anahtar Kelimeler: Yüksek boyutlu model gösterilim, çokdeğişkenli fonksiyonlar, interpolasyon, yaklaştırım.In this work, the main purpose is to reduce the multivariate interpolation problems to the less-variate interpolation problems in which the values of a multivariate function having  number of independent variables are given for a finite number of data and it is asked to determine an analytical structure for this function. As a result, the computational complexity of the problem will decrease and it will become easier to write programs for the computer-based applications. For this purpose, a package of  number of univariate interpolation problems is constructed from a  dimensional interpolation problem. High Dimensional Model Representation (HDMR) method is developed for the mentioned reduction process of the interpolation problem to determine approximate representation for the analytical structure of the sought function. HDMR is a divide conquer method and was first proposed by I.M. Sobol, then generalized by H. Rabitz. HDMR has an expansion for a given multivariate function such that its components are ordered starting from a constant component (zeroth order multivariance) and continuing in ascending multivariance, that is, univariate, bivariate, trivariate components and so on. Components of this representation are determined by using an imposition of vanishing integrals.  Since the main purpose of this work is to partition the given multivariate data into lower variate data, HDMR algorithm is reconstructed for data partitioning. This new method can be used for partitioning the data of multivariate interpolation problems in which the values of the sought function are given at all nodes of the hyperprismatic grid. Using these partitioned data the analytical structure for the sought function is obtained through Lagrange interpolation formula. When the nature of the HDMR expansion given below and the numerical implementations are examined it is seen that new methods are needed to obtain better approximate representations when the sought function does not have purely or dominantly additive nature. Hence, it can be said that the nature of the sought multivariate function and the features of the given data set have characteristic roles on the development of these methods. The sought function may have a multiplicative or an intermediate nature. Certain other methods are developed for interpolation problems having these types of structures. Factorized form of the HDMR method is called Factorized High Dimensional Model Representation (FHDMR). This method has a multiplicative expansion and the components of FHDMR expansion are evaluated by making comparisons between the HDMR and the FHDMR expansions of the multivariate function. To construct a unique comparison procedure certain idempotent operators are inserted into the HDMR expansion. After inserting these mentioned operators and expanding the FHDMR expansion into an additive expression, relations for FHDMR components of the multivariate function can be obtained in terms of the components of the data partitioning technique. In most cases the nature of the given multivariate data and the sought multivariate function have neither a purely additive nor a purely multiplicative nature. They have a hybrid nature. So, a new method is developed to obtain better results and it is called Hybrid High Dimensional Model Representation (HHDMR). This new method has an expansion including both the HDMR and the FHDMR expansions of the multivariate function through a hybridity parameter. The main problem in this method is to determine the best value for this parameter to obtain the best representation in the given interpolation problem. A cost functional is defined to obtain this mentioned value for the hybridity parameter. Another cost functional is defined to find the best representation obtained through three methods that were mentioned; HDMR, FHDMR and HHDMR for the sought multivariate function. Several numerical implementations are also given in this paper to test the efficiency of all these three methods. Various test functions are selected to examine the performance of the given methods. When the norm values, defined for finding the best representation, obtained for each representation method in the implementations are examined the best representation for the purely or dominantly additive functions are obtained through HDMR method. If the sought function has a purely or dominantly multiplicative nature, FHDMR method gives the best representation. On the other hand when the sought function has an intermediate nature then HHDMR method is needed to determine a better representation.       Keywords: High dimensional model representation, multivariate functions, interpolation, approximation

Cognitive Evaluation of Bupropion Sustained Release in Heavy Tobacco Smokers Using Event-Related Potentials

Objective. The aim of this study was to investigate the effects of bupropion sustained release (SR) on cognitive function, evaluated by event-related potentials (ERPs), in heavy tobacco smokers

Paraesthesia Caused by the Separated Endodontic Instrument: Case Report

Abstract In endodontics, separated endodontic instruments located in the mandibular canal may cause an injury of the inferior alveolar nerve (IAN) resulting in disabling sensory disturbances such as pain, paraesthesia, and dysaesthesia of the lower lip and chin area. In clinically paraesthesia usually manifests as numbness, tingling or any deviation from normal sensation. The suggested therapeutic sequence for endodontic related paraesthesia is the control of pain and inflammation and, whenever possible, the surgical elimination of the cause. A healthy 33-yearold woman was referred to the Department of Endodontics, Oral and Dental Healthy Hospital, Eskişehir suffering from pain and paraesthesia in the left lower lip and chin. Radiographic examination revealed the presence of a separated endodontic instrument beyond the apex of the mandibular left second molar and this instrument was inside the left mandibular canal. Damage to the IAN secondary to extrusion of a separated endodontic instrument was diagnosed. Extraction of the tooth was decided and after prednisone and pregabalin treatments both pain and paraesthesia on the left side of the lower lip and chin were gone

Maternal killer-cell immunoglobulin-like receptors and paternal human leukocyte antigen ligands in recurrent pregnancy loss cases in Turkey

Objective. The survival of a semi-allogeneic fetus depends on several immunological mechanisms, and it has been suggested that recurrent pregnancy loss (RPL) could develop as a result of one or more immunological abnormalities. Methods. Compatibility between partners for human leukocyte antigen (HLA) genotypes and the relationships between maternal killer-cell immunoglobulin-like receptor (KIR) and paternal HLA-Bw4/Bw6 and HLA-C1/C2 supra-groups were investigated in 25 couples with RPL in comparison to healthy couples with children. HLA and KIR genotyping was performed using polymerase chain reaction with sequence-specific primers and/or sequence-specific oligonucleotides. Results. HLA class I incompatibility between partners, especially in HLA-B alleles, was more common in the RPL group (p= 0.01). HLA-C2 homozygosity was more frequent in the male partners of RPL couples than in other groups (p= 0.03). The KIR2DL5 gene frequency was significantly higher in both the female and male partners of RPL couples, whereas the KIR2DS3 gene frequency in male partners of RPL couples was significantly reduced (p= 0.03). The presence of KIR2DL3 in women with RPL was correlated with the presence of HLA-C2 alleles in their spouses (p= 0.03). Conclusion. Our data from a Turkish population suggest that male HLA-C2 homozygosity may play an important role in RPL. Additionally, an incidental match between male HLA-C2 and female HLA-C1 ligand KIR receptors might perturb the balance between activatory and inhibitory KIR-ligand interactions during pregnancy in couples affected by RPL. The roles of orphan KIR2DL5 and orphan KIR2DS3 in RPL remain obscure

Ulusaldan Küresele: Popülizm, Demokrasi, Güvenlik Konferansı

Öngörülmesi giderek güçleşen, sarsıntılı ve savrulmalı zamanlardan geçiyoruz. İkinci Dünya Savaşı ve Soğuk Savaş ortak deneyimleri sonrasında 1950’lerden ve 1990’lardan itibaren demokratik sistemlerin peş peşe dalgalarla meşrulaşacağı, yaygınlaşacağı ve güçleneceği öngörüsü hakimdi. Ancak son yıllarda yaşanan bazı gelişmelerle demokrasilerin geleceği tekrar sorgulanmaya başladı. Gerek 11 Eylül ile başlayan ve IŞİD ile devam eden ve şiddet içeren İslamcı radikalizm, gerek Batı demokrasilerinde popülist radikal sağ hareketlerin ve beyaz ırkçı grupların yükselişi ve iktidara gelişi, bir yandan güvenlik-özgürlük ikileminin demokrasi dengesini bozdu, bir yandan da hem demokratik sistemlerin hem dünya barışının geleceğini bizi tekrar sorgular, sorgulatır hale getirdi. Demokrasileri bildiğimizi zannediyoruz, ama demokrasiler ile ilgili daha öğrenmemiz gereken çok şey var. Demokrasi kaderimiz de geleceğimiz de olmak zorunda değil belki de. Ya da belki yanlış yerden soru sormaya başlıyoruz, belki demokrasi yerine yeni bir referansa ihtiyacımız var. Aslında demokrasileri çantada keklik görmeyip, sabırla büyütüp yeşertmek, geliştirmek, korumak, ileri safhalara taşımak ve bizden sonraki nesillere aktarmak bir sorumluluk, ve bu sorumluluk bizlere ait. Popülizm, demokrasi, güvenlik kavramlarının her biri bugün sıkça ve yaygın olarak kullandığımız kavramlar olarak gündelik sohbetlerimizin içine kadar girmiş durumda. Bu yaygın kullanımlarına rağmen her bir kavram, üzerine düşünmeye, tartışmaya ve değerlendirmeye tekrar tekrar olanak verecek derinlikte. Her bir tartışma bir diğerini açarken, farklı gibi görünen bu kavramların birbirleriyle kesiştikleri zeminler bulmak mümkün. Popülist liderlerin politikaları bütün siyaset yapma biçimlerini kendine çeken ya da kendinden uzaklaştıran eksenler yaratarak her ikisini de aynı anda besleyebiliyor. Popülist politikaya angaje olan liderler ve grupların yanında bu politikaya karşı mücadele eden kişiler ve kitleler de yok değil, ancak kimi zaman bu kitleler eleştirdiği bu siyaset biçiminin kurucu öznesi haline de gelebiliyor. Bunun karşısında tabandan gelen demokratikleşme talepleri ve popülist siyasetle beraber kurumsallaşan diğer politika yapma biçimleri, demokrasi anlayışımızı farklı yönlere çekebiliyor. Bu demokratikleşme talepleri kimi zaman olumlu karşılıklar alsa da, kimi zaman devletlerin güvenlik politikaları ile etkisizleştirilmeye ve bastırılmaya çalışılıyor. Güvenlik politikalarının alanı günümüz teknolojisi sebebiyle o kadar genişledi ki, bu politikanın nesnesi haline gelmemiş varlık ve alan bulmak neredeyse mümkün değil. Ulusaldan Küresele: Popülizm, Demokrasi, Güvenlik konferansımız bu alanların kendine özgülüklerini göz önünde bulundururken, aralarındaki kesişimleri de ortaya koyan pek çok değerli sunuma ev sahipliği yaptı. Konferansın düzenlenmesinde emeği geçen herkese, ve bu bildiri kitabında tam metinleri ve özetleri bulunan bütün katılımcılarımıza çok teşekkür ederiz.Publisher's Versio

Yeni Ortadoğu: Toplum, Siyaset ve Ekonomi Konferansı

Ortadoğu asırlar boyu uluslararası siyasetin merkezinde yer almış, araştırmacı ve siyaset yapıcıların ilgi odağı olmuştur. Bu ilgiye rağmen, 2010 yılında başlayan ve ‘Arap Baharı’ olarak adlandırılan halk ayaklanmaları ve bu çerçevede yaşanan siyasal, ekonomik ve sosyal dönüşümler siyasetçiler ve sosyal bilimciler tarafından öngörülememiş ve mevcut varsayımları derinden sarsmıştır. Bir yandan demokratikleşme hareketleri ve ekonomik bir dönüşüm yaşayan bölge, diğer yandan iç çatışmaların, darbelerin ve vekalet savaşlarının merkezi haline gelmiş, ve tüm bu gelişmeler yeni yaklaşımları ve analizleri gerekli kılmıştır. Bu çerçevede Işık Üniversitesi Uluslararası İlişkiler Bölümü, Arap Baharı’yla başlayan süreçte bölgede gözlemlenen yeni toplumsal, ekonomik, iç ve dış siyasal dinamikleri akademik alanda tartışmaya açmak amacıyla ‘Yeni Ortadoğu’ başlıklı bir konferans düzenledi. Bu konferans çerçevesinde 24-25 Mart 2016 tarihlerinde Maslak Kampüsü’nde bizzat sunulan ve tam metin olarak bize iletilen bildirilerden bu kitabı oluşturduk.Publisher's Versio

Hybrid high dimensional model representation (HHDMR) on the partitioned data

A multivariate interpolation problem is generally constructed for appropriate determination of a multivariate function whose values are given at a finite number of nodes of a multivariate grid. One way to construct the solution of this problem is to partition the given multivariate data into low-variate data. High dimensional model representation (HDMR) and generalized high dimensional model representation (GHDMR) methods are used to make this partitioning. Using the components of the HDMR or the GHDMR expansions the multivariate data can be partitioned. When a cartesian product set in the space of the independent variables is given, the HDMR expansion is used. On the other band, if the nodes are the elements of a random discrete data the GHDMR expansion is used instead of HDMR. These two expansions work well for the multivariate data that have the additive nature. If the data have multiplicative nature then factorized high dimensional model representation (FHDMR) is used. But in most cases the nature of the given multivariate data and the sought multivariate function have neither additive nor multiplicative nature. They have a hybrid nature. So, a new method is developed to obtain better results and it is called hybrid high dimensional model representation (HHDMR). This new expansion includes both the HDMR (or GHDMR) and the FHDMR expansions through a hybridity parameter. In this work, the general structure of this hybrid expansion is given. It has tried to obtain the best value for the hybridity parameter. According to this value the analytical structure of the sought multivariate function can be determined via HHDMR.Publiher's Versio

Error propagation through generalized high dimensional model representation for data partitioning

In many circumstances the explicit form of a multivariate function is not known; rather a finite number of data is listed from some physical experiments. In such cases a function can be constructed only by imposing some analytical structures containing a finite number of adjustable parameters to fit the function with the given values at some specified points. This means interpolation. The given data is collected or produced by some devices or means which may cause unavoidable errors. This results in an uncertainty band for each datum. The propagation of these errors through the interpolation is the focus of this work. It uses a new form of a partitioning technique called Generalized High Dimensional Model Representation (GHDMR). GHDMR is a divide-and-conquer approach starting from a constant component and proceeding upto high variate terms, univariate, bivariate and so on in the representation. The representation is truncated by keeping only constant and univariate terms for approximation. In other words just a single N variate problem is approximated by N univariate problem.Publisher's Versio