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Background Aorto-ostial (AO) coronary interventions may be associated with multiple problems, including the potential embolization of atherothrombotic debris into the aorta and systemic circulation. Such embolization could theoretically lead to stroke or silent brain injury (SBI). In this study, we aimed to investigate whether there is an increased risk of SBI in patients undergoing AO stent implantation.Methods Fifty-five consecutive patients undergoing AO stenting and 55 consecutive patients undergoing non-AO stenting were included. Venous blood samples were obtained before and 12 h after the procedure to measure neuron-specific enolase (NSE), which is a sensitive marker of brain injury. Newly developed NSE elevation after the procedure in an asymptomatic patient was defined as SBI.Results SBI was detected in 24 (43.6%) patients in the AO stenting group and 17 (30.9%) patients in the non-AO stenting group (p = .167). Although the SBI rates were statistically comparable between the groups, the presence of significant (≥50%) AO stenosis was found to be an independent predictor of SBI in multivariate logistic regression analysis [odds ratio (OR) 2.856; 95% confidence interval (CI) 1.057-7.716; p = .038]. A longer procedure time was another independent predictor for the development of SBI (OR 1.037; 95% CI 1.005-1.069; p = .023).Conclusion This study suggests that AO stenting may be associated with an increased risk of SBI if the lesion in the ostium is significant.

Background and Objectives: Silent cerebral ischemia (SCI) is defined as a condition that can be detected by biochemical markers or cranial imaging methods but does not produce clinical symptom. This study aims both to compare the frequency of SCI in PCIs performed with right transradial access and left transradial access and to evaluate the influencing factors. Materials and Methods: A prospective, single-center study included 197 patients undergoing PCI via transradial access between November 2020 and July 2022. The patients were categorized into right radial and left radial groups. Neuron-specific enolase (NSE) values were measured and recorded before and 18 h after the procedure. A post-procedure NSE level higher than 20 ng/dL was defined as SCI. Results: SCI occurred in 60 of the 197 patients. NSE elevation was observed in 37.4% (n = 37) of the right radial group and in 23.5% (n = 23) of the left radial group (p = 0.032). Patients with SCI had higher rates of smoking (p = 0.043), presence of subclavian tortuosity (p = 0.027), and HbA1c (p = 0.031). In the multivariate logistic regression analysis, the level of EF (ejection fraction) (OR: 0.958 95% CI 0.920–0.998, p = 0.039), right radial preference (OR: 2.104 95% CI 1.102–3.995 p = 0.023), and smoking (OR: 2.088 95% CI 1.105–3.944, p = 0.023) were observed as independent variables of NSE elevation. Conclusions: Our findings suggest that PCI via right radial access poses a greater risk of SCI compared to left radial access. Anatomical considerations and technical challenges associated with right radial procedures and factors such as smoking and low ejection fraction contribute to this elevated risk.

Evaluation is an essential component of the learning process when discerning learning situations. Assessing natural language responses, like short answers, takes time and effort. Artificial intelligence and natural language processing advancements have led to more studies on automatically grading short answers. In this review, we systematically analyze short-answer evaluation studies. We present the development of the field in terms of scientific production features, datasets, and automatic evaluation features. The field has developed with pioneering studies in the US. Researchers generally conduct applications with English datasets. There has been a significant increase in research in recent years with large language models that support many different languages. These models have applications that achieve accuracy close to that of human evaluators. In addition, deep learning models do not require traditional approaches' detailed preprocessing and feature engineering processes. The dataset size trend is 1000 and above regarding the number of responses. It was observed that metrics such as accuracy, precision, and F1 score were used in performance determination. It is seen that the majority of the studies focus on scoring or rating. In this context, there needs to be more literature on the context of evaluation system applications that can provide descriptive and formative feedback. In addition, the developed assessment systems must be actively used in learning environments.

Vibration waves caused by construction or mining operations may cause damage to nearby structures or sensitive machinery and equipment. Some measures are implemented to eliminate or reduce this negative environmental effect of vibration. The barrier trench, one of these methods, aims to reduce the vibration by creating a suitable barrier between the structure and the vibration source on the ground. In this study, the effect of trench depth and distance from the source on vibration waves was simulated with a designed laboratory-scale test set-up to determine the effective parameters in barrier trench use. In addition, the effects of the superimposition of the source vibration wave with the reflected and refracted vibration waves from the trench, which has not been previously discussed in the literature, were also investigated. A laboratory scale gypsum-plaster block with dimensions of 200 cm × 90 cm x 70 cm was prepared and a Schmidt hammer was used as the impact energy source to generate vibration throughout the gypsum block. A trench barrier was opened at different depths on the test block and 588 vibration recordings were taken by the vibration monitor in different locations of the designed set-up. Statistical analyses were performed using vibration measurement results, trench source distance, and trench depths. As a result, vibration estimation equations depending on trench depth and the distance between the vibration source point and the trench were developed and how the presence of trench affects vibration propagation is revealed. It was found that vibrations increase due to the superposition of the source and reflected waves in front of the barrier trench. As the barrier depth increases, it is understood that the vibrations emanating from the near-surface vibration energy source are better blocked by the barrier. Thus, this study provides fundamental information on designing barrier trenches to avoid adverse effects of vibrations.

Allah, Kur’an’da, ibret alınması gereken pek çok olaydan bahsetmekte ve bunların kendi güç ve kudretine şahitlik ettiğini haber vermektedir. Bu sebeple öteden beri tefsirlerde, sağmal hayvanlardan ibret alınması gerektiğinden hareketle, sindirilmek için işkembede bulunan, gıdalarla kan arasından süzülüp gelen muhte-şem içecek olan sütten bahseden âyetler ele alınmış ve bu âyetlerden alınması gereken ibretin daha iyi orta-ya çıkması için sütün nasıl oluştuğuyla ilgili yorumlar yapılmıştır. Bu makalede, sütün oluşumundan bahse-den âyetten hareketle ilk dönemlerden başlamak üzere günümüze kadar sütün nasıl oluştuğuna dair yapılan yorumlar ele alınmıştır. Bu esnada, kaleme alınan ilk tefsirlerden itibaren, konuya yer veren eserlerde hem bilimsel bilginin ele alınış biçimi ve gelişimi hem de bu tür bilginin tefsirde kullanılış biçimi ortaya konul-maya çalışılmıştır. Bu açıklamalar, dini bilginin, Allah’ın peygamberleri vasıtasıyla gönderdiği âyetleri, bi-limsel bilginin ise Allah’ın evrene ve tüm varlığa nakşettiği âyetleri anlamaya yönelik bir faaliyet olduğu tezinden yola çıkılarak yapılmıştır. Böylece bilime taalluk eden hususların her devre göre farklılık arz ede-ceği gözler önüne serilmiş; bugünden geçmişe bakarak geçmişi yargılamanın doğru olmadığı gibi geçmişte söylenenleri vahiyle aynı kategoride değerlendirmenin de doğru olmayacağı üzerinde durulmuştur.

Glaucoma is a common eye disease that damages the optic nerve and leads to loss of vision. The disease shows few symptoms in the early stages, making its identification a complex task. To overcome the challenges associated with this task, this study aimed to tackle the localization and segmentation of the optic disc, as well as the classification of glaucoma. For the optic disc segmentation, we propose a novel metaheuristic approach called Grey Wolf Optimization (GWO). Two different approaches are used for glaucoma classification: a one-stage approach, in which the whole image without cropping is used for classification, and a two-stage approach. In the two-stage approach, the optic disc region is detected using the You Only Look Once (YOLO) detection algorithm. Once the optic disc region of interest (ROI) is identified, glaucoma classification is performed using pre-trained convolutional neural networks (CNNs) and vision transformation techniques. In addition, both the one-stage and the two-stage approaches are applied in combination with the pre-trained CNN using the Random Forest algorithm. In segmentation, GWO achieved an average sensitivity of 96.04%, a specificity of 99.58%, an accuracy of 99.39%, a DICE coefficient of 94.15%, and a Jaccard index of 90.4% on the Drishti-GS dataset. For classification, the proposed method achieved remarkable results with a high-test accuracy of 100% and 88.18% for hold-out validation and three-fold cross-validation for the Drishti-GS dataset, and 96.15% and 93.84% for ORIGA with hold-out and five-fold cross-validation, respectively. Comparing the results with previous studies, the proposed CNN model outperforms them. In addition, the use of the Swin transformer shows its effectiveness in classifying glaucoma in different subsets of the data.

Ruh sağlığı, kişinin yaşadığı süre içerisinde karşılaştığı acı, keder, kaygı ve bunalım gibi olumsuzlukları, tıpkı sevinç anındaki mutluluğa dönüştürebilme duygusudur. Bu duygunun oluşmasında Kur'anî telkinlerin çok önemli katkıları vardır. Zira din, insanoğlunun, yaşadığı olumsuzlukları hayatın bir parçası olarak kabullenip, bunlara karşı üstün bir moralle mücadele etmeyi öğretirken aynı zamanda ihmal olmaksızın başa gelen hadiselerin, ilâhî bir imtihanı da barındırdığı inancını ilham eder. Hayatı mutlulukla sürdürmenin yolu, hiç problemlerle karşılaşmamak değil başa gelen sıkıntıları büyük bir tevekkül duygusuyla karşılayabilmektir. Bir diğer deyişle bu tür olayları planlayanın Allah olduğu bilinciyle hareket edip asla yılgınlığa ve ümitsizliğe kapılmadan hayata dört elle sarılıp olumsuzlukların açtığı yaraları bir an önce sarmak ve tedavi etmek duygusuna sahip olmaktır. Bu konuda ihtiyaç duyulan donanım için gerekli rehberlik Kur'an tarafından çok açık ifadelerle yapılmaktadır. Bu çalışmada, hayatın, ruhen sağlıklı bir şekilde yaşanmasına vesile olacak âyetlerden bazıları ele alınarak, ruh sağlığına dair Kur'an’daki tavsiyeler üzerinde durulacaktır.

Kur’an’da, insanlara din ve inanç hürriyeti açısından çok geniş bir özgürlük alanı açıldığı, dinin tebliğcisi olan peygambere verilen talimatlarla ilan edilmiş ve herkesin istediği gibi inanabileceği teminat altına alınmış ve inanma kadar inanmamanın da bir insan hakkı olduğu vurgulanmıştır. Fakat ilerleyen safhalarda, gayrimüslimlerin saldırgan tutumları karşısında savunma amaçlı olarak indirilen savaşla ilgili ayetler, zaman içerisinde Müslümanlarda oluşan kanaatlerin de tesiriyle, Kur’an’ın din ve inanç hürriyetiyle ilgili ilkelerini gölgelediği gibi bir algı oluşmuştur. Dinden dönenlerin öldürülmesi gibi durumlar da buna eklenince İslâm’ın din ve inanç hürriyetini hiçe sayan bir din olduğu kanaatine varanların sayısı günden güne artmıştır. Bu makalede Kur’an’ın barışı ve uzlaşmayı önceleyen ayetleriyle savaşmayı emreden ayetleri arasındaki bağlantı tespit edilmeye çalışılacak ve bu bağlamda din değiştirmeyle ilgili hususların din hürriyetiyle ilişkisi belirlenmeye gayret edilecektir.

In this study, we discuss the idea of difference operators $ \Delta _{p}^{\alpha }, \Delta _{p}^{\left(\alpha \right) } $ $ \left(\alpha \in \mathbb{R}\right) $ and examine some properties of these operators. We also describe the concepts of ordered statistical convergence and lacunary statistical by using the $ \Delta _{p}^{\alpha } $-difference operator. We examine some features of these sequence spaces and present some inclusion theorems. We obtain the Caputo fractional derivative in this work.

Şeker hastalığı, kan şekerinde anormalliklere neden olan zararlı hastalıklardan biridir. Bu hastalığın erken teşhisi insan vücudunda oluşabilecek organ bozulmalarını engeller. Yapay zekâ tabanlı çalışmalar medikal alanda etkin bir şekilde gerçekleştirilmektedir. Makine öğrenmesine dayalı bilgisayar destekli uzman sistemler bu hastalığın erken teşhisi için oldukça faydalıdır. Bu çalışmadaki şeker hastalığı problemi, klasik bir denetimli ikili sınıflandırma problemidir. Bu verisetinde 16 öznitelik bulunmakta olup, 200'ü negatif örnek ve 320'si pozitif örnek olmak üzere toplam 520 örnek içermektedir. Önişlemden geçirilen veriseti üzerinde Rastgele Orman, Gradyan Arttırma, K-En Yakın Komşu, Derin Sinir Ağları ve son olarak da Oylama topluluk sınıflandırıcısı kullanılarak inşa edilen modellerin performansları dışarıda tutma ve 5-kat çapraz doğrulama senaryoları çerçevesinde analiz edilmiştir. Her iki senaryoda da, Oylama topluluğu sınıflandırıcısı, deneylerde en iyi performansı sundu. Buna göre, Oylama topluluğu sınıflandırıcısı, tutma tekniğiyle yapılan deneylerde %100'lük bir sınıflandırma doğruluğu ve 5 kat çapraz doğrulamalı deneylerde ortalama %97,31'lik bir sınıflandırma doğruluğu sundu. Sonuç olarak, Oylama topluluğu sınıflandırıcısı kullanılarak diyabeti gerçek zamanlı olarak erken teşhis eden bir uzman sistem tasarlanabilir.

Bu çalışmadaki amaç patlama sonucunda meydana gelen yüksek basınç dalgasını modelleyen bir simülasyon yazılımı geliştirmek ve bu simülasyon yazılımından elde edilen veri setini kullanarak derin sinir ağı ile basınç dalgası parametrelerini tahmin etmektir. Geliştirilen simülasyon yazılımı ile askeri alanda gerçekleştirilecek ana unsuru patlayıcı olan faaliyetlerin insan ve yapılar üzerindeki çevresel etkileri ortaya konulmaktadır. Kullanıcı tarafından belirlenen patlayıcı tipi, patlayıcı ağırlığı ve mesafe parametreleri girilerek basınç dalgası parametreleri hesaplanmaktadır. Basınç dalgası parametreleri hesaplanırken yazılım üzerinde matematiksel model veya derin sinir ağı modeli seçimi yapılabilmektedir. Üç boyutlu gösterim alanı veya harita üzerinde seçilen konum üzerinde basınç etkileri, basınç etki alanları, insan ve yapılar üzerindeki etkileri gösterilmektedir. Ayrıca geliştirilen yazılım birçok amaç için kullanılabilecek niteliktedir. Bunlardan bazıları; (i) askeri alanda stratejik bilginin hızlı ve kolay bir şekilde sağlanması, (ii) ideal patlayıcı yükünün bulunması, (iii) terör faaliyetlerinde kullanılan patlayıcı yüklerinin çevresel etkilerinin analiz edilmesi ve önlemlerin alınması, (iv) askeri operasyonlarda kullanılan patlayıcıların insan ve yapılar üzerindeki etkilerin tahmin edilmesi, (v) askeri alanda gerçekleştirilecek operasyonlarda belirlenen hedefe atılacak patlayıcı yükünün optimum seviyede belirlenmesi. Geliştirilen 3 boyutlu simülasyon ortamının patlama sonrası meydana gelen aşırı basınç dalgası parametrelerini doğru bir şekilde tahmin ederek, insan ve yapılar üzerindeki etkilerini etkili bir şekilde simüle ettiği gözlenmiştir. Bunun yanı sıra, çalışmada basınç verisi Derin Sinir Ağı ile de tahmin edilmiştir. Yazılım tarafından oluşturulan sentetik veri setleri ile derin sinir ağı modelinin eğitim ve test işlemleri gerçekleştirilmiştir. Seçilen patlayıcı tipine göre oluşturulan derin sinir ağı modeli ile yarı küresel patlamalar sonucu ortaya çıkan blast dalgası (aşırı basınç dalgası) parametreleri başarılı bir şekilde tahmin edilmiştir.

This work discusses a nudging intervention mechanism combined with an artificial intelligence (AI) system for early detection of learners’ risk of failing or dropping out. Different types of personalized nudges were designed according to educational principles and the learners’ risk classification. The impact on learners’ performance, dropout reduction, and satisfaction was evaluated through a study with 252 learners in a first-year course at a fully online university. Different learners’ groups were designed, with each receiving a different set of nudges. Results showed that nudges positively impacted the learners’ performance and satisfaction, and reduced dropout rates. The impact significantly increased when different types of nudges were provided. Our research reinforced the role of AI as useful in online, distance, and open learning for providing timely learner support, improved learning experiences, and enhanced learner-teacher communication.

INTRODUCTION: Bipolar disorder (BD) and unipolar depression (UD) are complex and multifactorial mental disorders characterized by mood swings, disability, and impaired quality of life. In the present study, we researched the roles of inflammatory cells and their value as inflammation markers in BD and UD. OBJECTIVE: Sixty-nine manic, 60 euthymic, and 70 UD patients and 60 sex-matched healthy volunteers (control group) were retrospectively analysed. Platelet (PLT), platelet distribution width (PDW), and red cell distribution width (RDW) levels were measured in four groups. The aim of this study was to evaluate PLT, PDW, and RDW levels patient with UD and two different phases of BD: euthymic and manic. RESULTS: In our study, 199 patients and 60 controls were included. There were no differences between the patients and the healthy control group participants in terms of age and sex. The bipolar episodes and the UD patient group were statistically significantly different from the healthy controls in terms of PLT, PDW, and RDW. CONCLUSION: Our study is the first in the literature to compare blood PLT, PDW, and RDW levels in bipolar episodes, UD patients, and healthy control groups. We believe that the levels of PLT, PDW, and RDW can be used as novel markers of bipolar episodes and UD. More detailed and larger prospective clinical studies are required to confirm these findings.

The excessive use of social media has become a social habit in today’s world, and social media addiction affects people worldwide. The purpose of this study is to explore social media use and addiction among secondary-school students, according to several personal variables as reported in a personal information form and a survey form asking respondents to disclose their reasons for using social media and to rate their level of social media addiction. Our research sample consisted of 1005 students studying at public schools in Kastamonu city centre, Turkey. The findings from this study indicated that students have an overall tendency to become social media addicts. Students sometimes use social media to prepare for their courses and in interpersonal interactions. The level of social media addiction is higher among males than females. Males use social media more than females for interpersonal communication. Social media addiction increases as the age of the students increases, and older students use social media more than their younger counterparts to communicate and interact with other people. As internet use increases among students, their use of social media for course preparation and interpersonal interactions increases as do their addictions to social media. The degree of addiction increases as the grade level increases, and the use of social media for course preparation decreases with this addiction. The use of social media at home and in transportation systems has more influence on the formation of social media addiction. Students usually use Facebook, Facebook Messenger and YouTube. They mostly use Facebook to communicate with their friends rather than to prepare for their courses. Thus, Facebook contributes little to their academic improvement. Social media addiction among students using Facebook, Facebook Messenger, YouTube, Twitter and Skype is higher. Most students start to use social media in primary school in the third and fourth grades. Thus, their addiction to social media and the use of social media in interpersonal interactions increase.&nbsp

The Brugada syndrome is one of the common causes of sudden cardiac arrest in healthy-appearing adults. The use of drugs in the treatment of this disease may give variable and unwanted results. Attention-deficit/hyperactivity disorder (ADHD) is a chronic neurobehavioural disorder which has begun to be noticed in adults as much as children. In our case, we present a 39-year-old male patient with an ADHD who was diagnosed with the Brugada syndrome during a routine examination and we discuss the treatment of this case. The association of ADHD and Brugada syndrome has not been previously reported in any clinical study. As far as we know, the present case is the first article in the literature to discuss the follow-up and treatment of ADHD in a patient with the Brugada syndrome. We observed all medical and non-medical treatment methods for ADHD treatment and discussed these methods such as psychostimulants, atomoxetine, bupropion, and psychotherapy.

The aim of this study was to identify students’ perceptions on cheating and plagiarism and trust in e-assessment according to their assessment experience and mode of learning as well as exploring their concerns in e-assessment. Participants were 952 students from two public universities in Turkey and Bulgaria. The study was designed as a cross-sectional survey. A questionnaire consisting of closed and open-ended questions was applied to collect data. Descriptive statistics, t-test, ANOVA and thematic analyses were performed. According to the results, no significant difference was found on students’ perceptions towards cheating and plagiarism and their feelings of trust in e-assessment regarding students’ prior e-assessment experience. However, there was a significant difference on students’ perceptions towards cheating and plagiarism and their feelings of trust in e-assessment regarding the mode of learning they are involved in. In addition, students’ concerns about e-assessment were explored in details in the paper.

Abstract Student authentication and authorship checking systems are intended to help teachers address cheating and plagiarism. This study set out to investigate higher education teachers’ perceptions of the prevalence and types of cheating in their courses with a focus on the possible changes that might come about as a result of an increased use of e-assessment, ways of addressing cheating, and how the use of student authentication and authorship checking systems might impact on assessment practice. This study was carried out within the context of the project TeSLA (an Adaptive Trust-based e-assessment System for Learning) which is developing a system intended for integration within an institution’s Virtual Learning Environment (VLE) offering a variety of instruments to assure student authentication and authorship checking. Data was collected at two universities that were trialling the TeSLA system, one in Turkey, where the main modes of teaching are face-to-face teaching and distance education, and one in Bulgaria, where the main modes of teaching are face-to-face teaching and blended learning. The study used questionnaires and interviews, building on existing TeSLA project evaluation activities and extending these to explore the specific areas we wished to examine in more depth. In three of the four contexts cheating was seen by teachers as a serious and growing problem, the exception was the distance education context where the teachers believed that the existing procedures were effective in controlling cheating. Most teachers in all four contexts expected cheating to become a greater problem with increased use of e-assessment. Student authentication was not seen as a major problem in any of the contexts, as this was felt to be well controlled through face-to-face proctored assessments, though the problem of assuring effective authentication was seen by many teachers as a barrier to increased use of e-assessment. Authorship checking was seen as a major issue in all contexts, as copying and pasting from the web, ghost writing and plagiarism were all reported as widely prevalent, and authorship checking was seen as becoming even more important with increased use of e-assessment. Teachers identified a third category of cheating behaviours, which was the accessing of information from other students, from written materials, and from the internet during assessments. Teachers identified a number of approaches to addressing the problem of cheating: education, technology, assessment design, sanctions, policy, and surveillance. Whilst technology was not seen as the most important approach to prevention, student authentication and authorship checking systems were seen as relevant in terms of reducing reliance on face-to-face proctored examinations, and in improving the quality of assessment through supporting the employment of a wider range of assessment methods. The development of authorship checking based on computational linguistic approaches was an area of particular interest. Student authentication and authorship checking systems were not seen as being able to address the third category of cheating behaviours that the study identified.

With the emergence of the Internet of Things (IoT), Industry 4.0, and cyber-physical system concepts, there is a tremendous change ongoing in industrial applications, which is imposing increasingly diverse and demanding network dynamics and requirements with a wider and more fine-grained scale. The purpose of this paper is to investigate how a hybrid schedule management in 6TiSCH architecture can be used to achieve the coexistence of applications with heavily diverse networking requirements. We study the fundamental functionalities and also describe network scenarios, where such a hybrid scheduling approach can be used. In addition, we present the details about the design and implementation of the first 6TiSCH centralized scheduling framework based on CoAP management interface (CoMI). We also provide theoretical and experimental analysis, where we study the cost of schedule management operations and illustrate the operation of the CoMI-based 6TiSCH schedule management.

Bu çalışmanın temel amacı açık ve uzaktan öğrenme süreçlerinde kullanılan basılı kitaplarda yer alan karekodları incelemektir. Bu amaç doğrultusunda on maddelik bir anket geliştirilmiş ve tarama çalışması yapılmıştır. Araştırma sonuçlarına göre erken benimseyenler olarak tanımlanabilecek bir öğrenci kitlesi karekod teknolojini kullanmaktadır. Araştırma bulgularına göre açık ve uzaktan öğrenme sisteminde yer alan öğrenenlerin karekod teknolojisini öğrenme hedeflerini hızlı bir şekilde gerçekleştirmek, etkileşimi artırmak, öğrenme performansını artırmak, öğrenme sürecinde verimliliği artırmak ve öğrenmeyi kolaylaştırmak bağlamında olumlu düşüncelere sahip oldukları karekod teknolojini kullanmanın kolay olduğu ve öğrenenlerin bu teknolojiyi başkalarına tavsiye edebilecekleri ortaya çıkmıştır. Çalışmanın devamında karekod teknolojini basılı kitaplarda kullanmanın üstünlükleri ve sınırlıkları açıklanmış ve ileri çalışmalar için önerilerde bulunulmuştur.

Learning analytics is quickly evolving. Old fashioned dashboards with descriptive information and trends about what happened in the past are slightly substituted by new dashboards with forecasting information and predicting relevant outcomes about learning. Artificial intelligence is aiding this revolution. The accessibility to computational resources has increased, and specific tools and packages for integrating artificial intelligence techniques leverage such new analytical tools. However, it is crucial to develop trustworthy systems, especially in education where skepticism about their application is due to the risk of teachers’ replacement. However, artificial intelligence systems should be seen as companions to empower teachers during the teaching and learning process. During the past years, the Universitat Oberta de Catalunya has advanced developing a data mart where all data about learners and campus utilization are stored for research purposes. The extensive collection of these educational data has been used to build a trustworthy early warning system whose infrastructure is introduced in this paper. The infrastructure supports such a trustworthy system built with artificial intelligence procedures to detect at-risk learners early on in order to help them to pass the course. To assess the system’s trustworthiness, we carried out an evaluation on the basis of the seven requirements of the European Assessment List for trustworthy artificial intelligence (ALTAI) guidelines that recognize an artificial intelligence system as a trustworthy one. Results show that it is feasible to build a trustworthy system wherein all seven ALTAI requirements are considered at once from the very beginning during the design phase.

Pregabalin is a novel isomer of gamma-aminobutyric acid that functions as a major inhibitory neurotransmitter in the brain. It is used daily in medical practice for treating neuropathic pain, fibromyalgia, generalized anxiety disorder, and partial seizures. Due to its anti-glutamatergic effects, it poses a potential addiction risk. For example, an abrupt discontinuation of this substance may cause patients to exhibit physical withdrawal symptoms, such as insomnia, nausea, headache, and diarrhoea. However, there is no information in the literature that addresses whether the rapid discontinuation of pregabalin can cause psychosis to occur. Here we presented a 20-year-old patient with his first episode of psychosis that was likely attributable to his withdrawal from a high dosage pregabalin. He lacked physical signs of withdrawal; however, a psychiatric examination was conducted. It was determined that the patient was experiencing paranoid ideation, auditory hallucinations, and mutism. Furthermore, he had engaged in self-mutilative actions and had attempted suicide. Due to the short time frame between the rapid discontinuation of a relatively large dose of pregabalin and the onset of the patient’s first episode of psychosis, it is likely that the psychotic episode was triggered by the cessation of the medication. This is the first known case of psychosis that was caused by the rapid withdrawal of pregabalin to be discussed in the literature. The results of this clinical case may guide clinicians to recognize the symptoms of acute pregabalin withdrawal.

Drug-induced alopecia, characterized by non-scarring hair loss of scalp and body, is a rare side effect of psychotropic drugs. It has previously been reported with the different antidepressant medications, but has not been described with agomelatine. Agomelatine is an antidepressant with a novel mechanism of action and fewer side effects. Here, we report a 31-year-old male patient with diffuse hair loss induced by agomelatine use and improved by discontinuation the drug. Because antidepressant-induced hair loss is relatively rare, many clinicians may not pay attention for this side effect. As far as we know, this is the first published case report of alopecia associated with agomelatine.

Ülkemizde kentsel dönüşüm kapsamında yıkılacak birçok eski veya hasar görmüş yapı olması, yeni yıkım tekniklerinin arayışına girilmesine sebep olmuştur. Yurt dışında yıllardır başarılı bir şekilde uygulanan patlayıcı ile kontrollü yapı yıkımı, avantajları düşünüldüğünde dikkate değer bir tekniktir.Bu çalışmada, Edirne Kapıkule Gümrük Lojman Binası’nın patlayıcı kullanılarak kontrollü yıkımı gerçekleştirilmiştir. Bu amaç doğrultusunda, hali hazırda bulunmayan bina planı şerit metre kullanılarak çıkarılmış ve bilgisayar ortamında 3 boyutlu modeli oluşturulmuştur. Binaya ait betonarme malzeme özellikleri laboratuvar çalışmaları sonucunda belirlenmiş ve binanın statik durumu hakkında bilgi edinilmiştir. Bina kolonlarında deneme atımları gerçekleştirilerek kolon başına düşen şarj miktarı hesaplanmıştır. Bu bilgiler ışığında yıkım tasarımı önerilmiştir. Önerilen yıkım tasarımı, bir sonlu elemanlar programı kullanılarak oluşturulan bina modeli üzerinde test edilmiştir. Oluşturulan simulasyon modelinde binanın davranışı ve kolonlara etkiyen moment ve basınç yükleri tespit edilmiştir. Kolonlara etkiyen yükler, kolonların taşıma kapasitesi ile karşılaştırılarak, kolonların deformasyon derecesi öngörülmüştür. Yıkım sonrası binanın durumu incelenerek öngörülen deformasyonun meydana gelip gelmediği incelenmiştir. Patlayıcı madde kullanılarak yıkım gerçekleştirildikten sonra, yıkımın amacına hizmet ettiği görülmüştür. Ancak patlayıcı konulmayan yapı elemanlarında öngörülen deformasyonun olmadığı gözlemlenmiş, bunun sebepleri irdelenmiştir. Yıkım sonucu, komşu yapılarda herhangi bir hasar oluşmamış, yıkımdan kaynaklanan yer sarsıntılarının betonarme yapılara hasar verici boyutta olmadığı ölçülmüştür.Çalışma sonunda, makineli yıkım ile patlayıcı madde kullanılarak gerçekleştirilen yıkım maliyet açısından karşılaştırılmıştır. Kat sayısının azlığı ve sıralı patlatma ateşleme süresinin kısa olmasından dolayı makineli yıkımın daha avantajlı olduğu sonucuna ulaşılmıştır.

Artificial intelligence has impacted education in recent years. Datafication of education has allowed developing automated methods to detect patterns in extensive collections of educational data to estimate unknown information and behavior about the students. This research has focused on finding accurate predictive models to identify at-risk students. This challenge may reduce the students’ risk of failure or disengage by decreasing the time lag between identification and the real at-risk state. The contribution of this paper is threefold. First, an in-depth analysis of a predictive model to detect at-risk students is performed. This model has been tested using data available in an institutional data mart where curated data from six semesters are available, and a method to obtain the best classifier and training set is proposed. Second, a method to determine a threshold for evaluating the quality of the predictive model is established. Third, an early warning system has been developed and tested in a real educational setting being accurate and useful for its purpose to detect at-risk students in online higher education. The stakeholders (i.e., students and teachers) can analyze the information through different dashboards, and teachers can also send early feedback as an intervention mechanism to mitigate at-risk situations. The system has been evaluated on two undergraduate courses where results shown a high accuracy to correctly detect at-risk students.

The wireless Internet of Things (IoT) landscape is quite diverse. For instance, Low-Power Wide-Area Network (LPWAN) technologies offer low data rate communication over long distance, whereas Wireless Personal Area Network (WPAN) technologies can reach higher data rates, but with a reduced range. For simple IoT applications, communication requirements can be fulfilled by a single technology. However, the requirements of more demanding IoT use cases can vary over time and with the type of data being exchanged. This is pushing the design towards multimodal approaches, where different wireless IoT technologies are combined and the most appropriate one is used as per the need. This paper considers the combination of Narrow Band IoT (NB-IoT) and Bluetooth Low Energy (BLE) as communication options for an IoT device that is running a Lightweight Machine to Machine/Constrained Application Protocol (LwM2M/CoAP) protocol stack. It analyses the challenges incurred by different protocol stack options, such as different transfer modes (IP versus non-IP), the use of Static Context Header Compression (SCHC) techniques, and Datagram Transport Layer Security (DTLS) security modes, and discusses the impact of handover between both communication technologies. A suitable end-to-end architecture for the targeted multimodal communication is presented. Using a prototype implementation of this architecture, an in-depth assessment of handover and its resulting latency is performed.

Previous studies have described many scales for measuring self-regulation; however, no scale has been developed specifically for self-paced open and distance learning environments. Therefore, the aim of this study is to develop a scale for determining the self-regulated learning skills of distance learners in self-paced open and distance learning courses. Participants of this study were 1279 distance learners who were part of self-paced distance learning courses in a public open and distance teaching university in Turkey. The items of the scale were prepared based on the literature review, expert opinions, and learner questionnaires. The items of the scale were reduced from 62 to 30 after expert opinions and validity and reliability analyses. For the validity of the scale, the exploratory and confirmatory factor analyses were conducted. The total variance was found to be 58.204%. The Cronbach’s alpha coefficient calculated for the reliability of the scale was found to be .937. Five factors composed of goal setting, help seeking, self-study strategies, managing physical environment, and effort regulation emerged in the 30-item scale. Thus, it was concluded that the scale has a high validity and reliability. This scale is intended to help teachers and instructional designers in developing strategies that will enable learners to either enhance their existing self-regulated learning skills or help them to acquire new skills in self-paced open and distance learning environments.

The advent of Web 2.0 technologies transformed online networks into interactive spaces in which user-generated content has become the core material. With the possibilities that emerged from Web 2.0, social networking sites became very popular. The capability of social networking sites promises opportunities for communication and interaction, especially for distance education students who are separated from their teachers, learning resources and other students in terms of time and/or space. Within this perspective, the aim of the study is to investigate distance education students’ perceptions and preferences regarding use of social networking sites for communication and interaction purposes. In this context, the study employed a quantitative cross-sectional methodology. Research findings were derived from a sample of 2065 distance education students and the data were gathered through an online questionnaire. The research findings indicate that social networking sites (SNSs) can be used to support social learning processes.

The potentiality determination of renewable energy resources is very important. The biomass is one of the alternative energy and material resources. There is great effort in their conversion to precious material but yet there is no generalized rule. Therefore, the prediction of the energy and material potentials of these resources has gained great importance. Also, the solution to environmental problems in real time can be found easily by predicting models. Here, the basic products of pyrolysis process, char, tar and gas were also predicted by artificial neural network modelling. The half of data obtained from real experimental process along with some content and proximate analysis were fed into artificial neural network modelling. After the training of the model with this data, the remaining half of the data were introduced into this artificial neural network model. And the model predicted the pyrolysis process products (char, tar and gaseous material). The predicted data and the real experimental data were compared. In addition, another aim of this study is to reduce the labour in identification and characterization of the pyrolysis products. For this purpose, a theoretical framework has also been sketched. The necessity of a generalized rule for generation of energy and matter production from biomass pyrolysis has been punctuated. As a result, the ANN modelling is found to be applicable in the prediction of pyrolysis process. Also, the extensive reduction in labour and saving in economy is possible.

Venlafaxine, which is often used for a number of psychiatric-related conditions such as the treatment of major depression, generalized anxiety disorder, social anxiety disorder and panic disorder, is generally a drug that is well tolerated and safe. The side effects of drugs can cause the treatment to prematurely terminate. Clinicians should prefer appropriate and low side-effects drugs to prevent this. This situation is also especially important for psychiatric patients. Prostatism, which impairs quality of life, is an important medical condition, with clinical and social implications. In the previous studies, prostatism was declared as a side effect of some antidepressant such as milnacipran, duloxetine and reboxetine. In our case, we discussed that venlafaxine-related prostatism developed in a male patient. As far as we know this is the first report of venlafaxine-induced prostatism.

As the ideas and technologies behind the Internet of Things (IoT) take root, a vast array of new possibilities and applications is emerging with the significantly increased number of devices connected to the Internet. Moreover, we are also witnessing the fast emergence of location-based services with an abundant number of localization technologies and solutions with varying capabilities and limitations. We believe that, at this moment in time, the successful integration of these two diverse technologies is mutually beneficial and even essential for both fields. IoT is one of the major fields that can benefit from localization services, and so, the integration of localization systems in the IoT ecosystem would enable numerous new IoT applications. Further, the use of standardized IoT architectures, interaction and information models will permit multiple localization systems to communicate and interoperate with each other in order to obtain better context information and resolve positioning errors or conflicts. Therefore, in this work, we investigate the semantic interoperation and integration of positioning systems in order to obtain the full potential of the localization ecosystem in the context of IoT. Additionally, we also validate the proposed design by means of an industrial case study, which targets fully-automated warehouses utilizing location-aware and interconnected IoT products and systems.

This study intends to explore the current trends in the field of distance education research during the period of 2009-2013. The trends were identified by an extensive review of seven peer reviewed scholarly journals: The American Journal of Distance Education (AJDE), Distance Education (DE), The European Journal of Open, Distance and e-Learning (EURODL), The Journal of Distance Education (JDE), The Journal of Online Learning and Technology (JOLT), Open Learning: The Journal of Open, Distance and e-Learning (OL) and The International Review of Research in Open and Distributed Learning (IRRODL). A total of 861 research articles was reviewed. Mainly content analysis was employed to be able to analyze the current research. Also, a social network analysis (SNA) was used to interpret the interrelationship between keywords indicated in these articles. Themes were developed and the content of the articles in the selected journals were coded according to categories derived from earlier studies. The results were interpreted using descriptive analysis (frequencies) and social network analysis. The reporting of the results were organized into the following categories: research areas, theoretical and conceptual frameworks, variables, methods, models, strategies, data collection and analysis methods, and the participants. The study also identified the most commonly used keywords, and the most frequently cited authors and studies in distance education. The findings obtained in this study may be useful in the exploration of potential research areas and identification of neglected areas in the field of distance education.