Synthesis of novel oxadiazole derivatives and their cytotoxic activity against various cancer cell lines

Caffeic acid (CA), ferulic acid (FA) and caffeic acid phenethyl ester (CAPE) have a broad anticancer effect on various cell lines. In this study, nine ferulic and caffeic acid-based 1,2,4 and 1,3,4 oxadiazole molecular hybrids were synthesized and their cytotoxic activity was evaluated mainly against Glioblastoma (GBM) cell lines. Compounds 1 and 5 exhibited the highest inhibitory activity against three different GBM cell lines (LN229, T98G, and U87), without toxicity to healthy human mesenchymal stem cells (hMSC). In addition, their cytotoxicity was also evaluated against three additional cancer cell lines and more inhibitory results were found than GBM cell lines. The IC50 values of compound 5 in U87, T98G, LN229, SKOV3, MCF7, and A549 cells were determined as 35.1, 34.4, 37.9, 14.2, 30.9, and 18.3 µM. In the light of biological activity studies, the developed compounds have a high potential to lead studies for the development of new drug candidates for the treatment of cancer

Simulations in Pre-emptive and Preventive Intervention

Simulations are digital environments created by imitating real environments and creating similar ones with mathematical models. In this respect, it is possible to calculate all the possibilities that can be experienced by uploading the data of the real world to these imitated digital environments. The fact that the resulting knowledge can affect real-world policies is a subject that needs to be discussed. Thanks to simulations, probability calculations for important security issues of states have now become frequently used methods. However, it should be discussed whether this security method tried to be provided through the digital space will be a directing factor as a basis for defence or whether taking an action based on simulation data can be interpreted as an attack. This study undertakes to seek answers to these questions. The conceptual framework of the study is the concepts of pre-emptive and preventive intervention. In this context, the study examines whether the use of simulation data as a basis for defence in interventions can be a pre-emptive and preventive approach. The legitimacy of using simulation data and artificial intelligence analyses for identifying enemies and calculating aggression indicators depends on the specific forms of international cooperation and the processes through which international actors establish acceptable options

Adaptive Regularization for Class-Incremental Learning

Class-Incremental Learning updates a deep classifier with new categories while maintaining the previously observed class accuracy. Regularizing the neural network weights is a common method to prevent forgetting previously learned classes while learning novel ones. However, existing regularizers use a constant magnitude throughout the learning sessions, which may not reflect the varying levels of difficulty of the tasks encountered during incremental learning. This study investigates the necessity of adaptive regularization in Class-Incremental Learning, which dynamically adjusts the regularization strength according to the complexity of the task at hand. We propose a Bayesian Optimization-based approach to automatically determine the optimal regularization magnitude for each learning task. Our experiments on two datasets via two regularizers demonstrate the importance of adaptive regularization for achieving accurate and less forgetful visual incremental learning

The Revised Emotional Intelligence Scale: Cross Cultural Validation in a Turkish Psychiatric Outpatient Cohort

The original Emotional Intelligence Scale of Fukunishi utilized 65 items, measuring three basic dimensions: Intrapersonal, Interpersonal and Situational. Subsequently, using a sample of 170 U.S.psychiatric outpatients, it was factor reduced from 65 to 34 items that showed excellent internal consistency both overall and for two of its three hypothesized factors. This study examined the internal consistency of the 34-item solution in a cohort of 123 Turkish psychiatric outpatients. The mean age of the sample was 34.5 years (SD=11.2). The internal consistency of the total scale was 0.91. Scores also were high for the Interpersonal dimension (0.90) and the Intrapersonal dimension (.0.84), but not for the Situational dimension (0.67). A similar lower scoring pattern for the Si- tuational dimension has been seen both in US and Japanese outpatient populations. These data suggest that, in a Turkish psychiatric outpatient population, this scale also appears to maintain excellent internal consistency both overall and for two of its three hypothesized factors. This inventory may be suitable to investigate suitability for psychological treatment

Deconstruction, legibility and space: four experimental typographic practices

In this article we wish to present the typographic experimentations of four designers, each of whom looks at typography and its implementations from different viewpoints; however with similar goals – namely to investigate how typographic systems can be implemented, their attributes as carriers of semantic meaning be redefined, and/or their functions be improved upon within the digital medium that presents challenges as well as opportunities that enable graphic designers to reach well beyond the traditional medium of typographic work; i.e., printed paper. The article will examine these four projects under the umbrella concept of Deconstruction, also extending into a consideration of Legibility; setting them forth as examples of the impact that the digital medium has brought to bear upon typographic practice in recent decades

Investigation of water sorption and aluminum releases from high viscosity and resin modified glass ionomer

High viscosity glass ionomer cement (HVGIC) and resin-modified glass ionomer cement (RMGIC) have recently been clinically preferred thanks to their numerous advantages. However, initial moisture contamination has a negative effect on the mechanical and physical properties of these cements. The aim of this study was in vitro of HVGICs and RMGICs, with and without surface protection, on water sorption, solubility and release of aluminum. In this study, as HVGICs; Equia Forte, IonoStar Plus, Riva Self Cure; as RMCIS, Ionolux and Riva Light Cure; and as control, Z250 universal composite was used. Equia coat, Voco varnish and Riva coat were chosen as surface protective. Water sorption and solubility levels of the samples were measured according to ISO 4049:2009. Al levels released from samples were determined by graphite furnace atomic absorption spectroscopy (GFAAS) for 7, 14 and 21 days. Statistical evaluation of the results was made using one-way variance analysis (ANOVA) and Tukey post-hoc test (p<0.05). RMGICs from restorative materials showed more water absorption than HVGICs, but no differences in solubility. Among the materials tested, the water absorption values of the HVGIC and RMGIC materials without surface protection were higher than those with the surface protection (p<0.001). It was determined that the Al release of HVGIC and RMGIC groups with the surface protection were lower in all time periods than the groups without surface protection (p<0.001). The application of surface protection effectively reduced water sorption and Al release from HVGICs and RMGICs

Continual Learning with Dynamic Sparse Training: Exploring Algorithms for Effective Model Updates

Continual learning (CL) refers to the ability of an intelligent system to sequentially acquire and retain knowledge from a stream of data with as little computational overhead as possible. To this end; regularization, replay, architecture, and parameter isolation approaches were introduced to the literature. Parameter isolation using a sparse network which enables to allocate distinct parts of the neural network to different tasks and also allows to share of parameters between tasks if they are similar. Dynamic Sparse Training (DST) is a prominent way to find these sparse networks and isolate them for each task. This paper is the first empirical study investigating the effect of different DST components under the CL paradigm to fill a critical research gap and shed light on the optimal configuration of DST for CL if it exists. Therefore, we perform a comprehensive study in which we investigate various DST components to find the best topology per task on well-known CIFAR100 and miniImageNet benchmarks in a task-incremental CL setup since our primary focus is to evaluate the performance of various DST criteria, rather than the process of mask selection. We found that, at a low sparsity level, Erdos-Renyi Kernel (ERK) initialization utilizes the backbone more efficiently and allows to effectively learn increments of tasks. At a high sparsity level, however, uniform initialization demonstrates more reliable and robust performance. In terms of growth strategy; performance is dependent on the defined initialization strategy, and the extent of sparsity. Finally, adaptivity within DST components is a promising way for better continual learners

İşitme Engelli Öğrencilerin Okuma-Yazma Eğitiminde Mobil Uygulama Kullanımı

Literacy is a fundamental skill to function in society. However, hearing impaired are severely disadvantaged in literacy development by lack of access to language's phonemic system. Recent developments in information and communication technologies stimulated technology integration endeavors in special education field. Hearing impaired children’s literacy instruction stands a fruitful area of technology integration. Former studies generally reported development or examination of supportive tools like visual dictionaries, sign language support, vocabulary drills or storybooks. However, few studies developed an overall approach and reported whole technology integration procedures. This study reports findings from a research which investigated the affordances of mobile devices in hearing impaired children’s literacy instruction. Two mobile applications were built from scratch and optimized through design based research. Furthermore, affordances and integration guidelines of these applications were investigated in a case study. The research was conducted in Anadolu University’s Applied Research Center for Hearing Impaired Children (İÇEM). Participants of the study are hearing impaired children studying at İÇEM in 2013-2014 and 2014-2015 academic years. Data sources of the project were observations, video recordings, audio recordings of expert panels and semi-structured interviews. The data were analyzed inductively using NVivo 10 software. Results suggested significant increase in student motivation towards the technology enriched instructional environment. This paper summarizes design and optimization studies along with technology integration guidelines to hearing impaired children’s literacy classes.Okuryazarlık, toplumda işlev görebilmek için gereken temel becerilerden biridir. Ancak işitme engelli bireyler, dilin fonetik sistemine erişememeleri nedeniyle okuryazarlık gelişiminde dezavantajlı durumdadır. Bilgi ve iletişim teknolojilerindeki güncel gelişmeler, özel eğitim alanında teknoloji entegrasyonu çabalarını teşvik eder niteliktedir. Bu durum, işitme engelli çocuklara yönelik okuma-yazma eğitimi için verimli bir teknoloji entegrasyon alanı olarak öne çıkmaktadır. Alanyazındaki teknoloji entegrasyonu çalışmaları genellikle görsel sözlüklere, işaret diline, kelime egzersizlerine ya da hikâye kitaplarına yoğunlaşmaktadır. Bunun yanında, çalışmaların süreci değil, sonuçları raporladığı görülmektedir. Ancak, bütüncül bir yaklaşımla tüm teknoloji entegrasyonu sürecini betimleyen az sayıda çalışma bulunmaktadır. Bu çalışma, işitme engelli çocuklara okuma yazma öğretiminde mobil araçların uygulanabilirliğini inceleyen bir araştırma projesi kapsamında gerçekleştirilmiştir. Bu bağlamda, iki uygulama sıfırdan başlanarak geliştirilmiş, tasarım tabanlı araştırma yoluyla iyileştirilmiş ve durum çalışması yoluyla sınıf ortamında kullanımları incelenmiştir. Araştırma, işitme engelli bireylere işitsel ve sözel yöntemle eğitim veren, İşitme Engelli Çocuklar Eğitim Araştırma ve Uygulama Merkezi’nde (İÇEM) gerçekleştirilmiştir. Araştırmanın katılımcıları 2013-2014 ve 2014-2015 eğitim öğretim yıllarında İÇEM’de öğrenim gören ilkokul ve ortaokul kademesindeki işitme engelli öğrencilerdir. Araştırmanın her aşamasında farklı katılımcılar ile çalışılmıştır. Araştırmanın verileri gözlemler, video kayıtları, uzman panelleri, ses kayıtları ve yarı yapılandırılmış görüşmeler yoluyla toplanmıştır. Toplanan veriler tümevarım analizi yoluyla ve NVivo 10 programı kullanılarak analiz edilmiştir. Verilerin analizi sonucunda öğrenme ortamında teknolojiden faydalanılmasının öğrencilerin derse yönelik ilgilerini ve motivasyonlarını arttırdığı görülmüştür. Bu çalışma, geliştirilen mobil uygulamalara yönelik tasarım, iyileştirme ve entegrasyon aşamalarını özetlemekte; işitme engelli çocukların okuma yazma öğretimine ilişkin öneriler sunmaktadır

Towards real-time human behavior understanding: A suboptimal shape descriptor

Bu çalışmada insan davranışı anlama (İDA) probleminin çözümünde kullanılmak üzere özgün optimal ve optimal-altı şekil tanımlayıcıları önerilmiştir. Bu şekilde en az veri kullanımıyla en fazla davranış bilgisini sınıflandırabilmek amaçlanmıştır. Optimal şekil tanımlayıcısı başarısı yüksek olmakla beraber algoritmik karmaşıklığı yüksek olduğu için oldukça yavaş çalışmaktadır. Bu sorunu gidermek için daha hızlı çalışan bir optimal-altı tanımlayıcı önerilmiştir. Optimal-altı tanımlayıcının başarısı optimal tanımlayıcıya çok yakın olmakla beraber çok daha düşük algoritmik karmaşıklığa sahip olup çok daha hızlıdır. Sonuçlar Weizmann veri setinde denenmiş ve şekiller ve video bağlantıları ile gösterilmiştir. Veri setinden elde edilen siluet görüntü akışlarından 12 adet istatistiksel öznitelik çıkarılıp sınıflandırmada kullanılmıştır. Sınıflandırmada kullanılan Öklid uzaklığı yöntemi sayesinde oldukça hızlı sonuçlar üretilerek %92 doğruluk oranına ulaşılmıştır.In this study, two novel shape descriptors are proposed to be used in human behavior understanding problem. First is optimal shape descriptor, which has high performance but works very slow due to high algorithmic complexity. Second is suboptimal shape descriptor, performance of which is very close to optimal one, but works much more faster. Optimal means using minimum data to represent maximum knowledge. Algorithms are run on Weizmann dataset and results are shown both as figure and video link. Classification was performed using 12 statistical features extracted from the data sets' human silhouettes. An accuracy rating of 92 percent was obtained by using Euclidean distance in classification