Leptospirosis accompanying COVID-19: A case report

The SARS CoV-2 virus, which broke out in Wuhan, China in december 2019 and took over the whole world, was declared as pandemic by the World Health Organization on march 11, 2020. COVID-19 disease caused by this virus, another zoonotic factor in the Coronavirus family, can affect various systems, particularly the respiratory system. Leptospirosis is a zoonotic disease caused by Leptospira. It presents symptoms of fatigue, febrile, and icterus. We aimed to present a case in which the association of SARS CoV-2 with leptospirosis was detected

An Investigation on “Property Right” of the Trabzon Ayasofya Mosque

Mülkiyeti mazbut Fatih Sultan Mehmet Vakfı’na yönetim ve temsili 5737 sayılı Vakıflar Kanunu ile Vakıflar Genel Müdürlüğü’ne (VGM) ait Trabzon Merkez Fatih Mahallesi’nde “çeşmesi olan bahçeli kargir cami” vasıflı, 6.951,75 m2 miktarlı vakıf taşınmaz, vakıf taşınmaz mallar kütüklerinde mazbut hayrat olarak tescillidir. Bu vakıf taşınmaz aynı zamanda 2863 sayılı Kültür ve Tabiat Varlıklarını Koruma Kanunu uyarınca “korunması gerekli kültür ve tabiat varlığı” olarak tescilli olup 1.derece arkeolojik sit alanında bulunmaktadır. Taşınmazı VII. Osmanlı Padişahı Fatih Sultan Mehmet’in Trabzon’u 1461 yılında fethetmesi ile kendi kurduğu vakfına alarak camiye dönüştürüp vakfettiği bilinmektedir. Uzun süre VGM rızası dışında müze olarak kullanılan bu taşınmazın vakıf hukukuna uygun olarak tekrar cami vasfında kullanımı tartışılmıştır. Bu çalışma kapsamında Cumhuriyet’ten sonra taşınmazın mülkiyet hakkı kavramı çerçevesindeki hukukî durumu ülkemizin de tanıdığı uluslararası beyanname, sözleşme ve protokoller ile Anayasa, Medeni Kanun, Vakıflar Kanunu, Kadastro Kanunu, Kültür ve Tabiat Varlıklarını Koruma Kanunu ve Gayrimenkul Kiraları Hakkında Kanun çerçevesinde irdelenerek, taşınmazın konu olduğu idarî kararlar ve yargı kararları da özetlenerek taşınmaz özelinde değerlendirmeler yapılacaktır.Ayasofya Mosque as the property of The Foundation of Fatih Sultan Mehmet is administered and represented by General Directorate of Foundations (VGM) in Turkey, according to the Foundations Law numbered 5737. It is 6.951,75 m2 at Fatih District in Trabzon and registered as mazbut waqf on title deed “masonry mosque garden with fountain”. In addition, it is registered on title deed “cultural and natural property to be protected” and is in first-degree archaeological protected area according to Protection of Cultural and Natural Heritages Law numbered 2863. It is known that VIIth Ottoman Sultan, Fatih Sultan Mehmet conquered Trabzon in 1461. After the conquest, Fatih Sultan Mehmet converted Ayasofya into a mosque by including its own foundation. In a long time Ayasofya was used as a museum without permission of General Directorate of Foundations and usage of Ayasofya as a mosque has been discussed instead of a museum because of its status in accordance with the law of foundations. In this study, after establishment of Turkish Republic legal status of Ayasofya Mosque in terms of the concept of property rights will be investigated by examining the Universal Declaration of Human Rights, European Convention on Human Rights, The Constitution, Civil Law, Foundations Law, Cadastre Law, Protection of Cultural and Natural Heritages Law, Letting Law. Administrative decisions and adjudications will be summarized

Modelling and simulation with neural and fuzzy-neural networks of switched circuits

Recently, the modelling and simulation of switched systems containing new nonlinear components in electronics and power electronics industry have gained importance. In this paper, both feed‐forward artificial neural networks (ANN) and adaptive network‐based fuzzy inference systems (ANFIS) have been applied to switched circuits and systems. Then their performances have been compared in this contribution by developed simulation programs. It has been shown that ANFIS require less training time and offer better performance than those of ANN. In addition, ANFIS using “clustering algorithm” to generate the rules and the numbers of membership functions gives a smaller number of parameters, better performance and less training time than those of ANFIS using “grid partition” to generate the rules. The work not only demonstrates the advantage of the ANFIS architecture using clustering algorithm but also highlights the advantages of the architecture for hardware realizations

A comparative anatomical study on leaf and scape of Androsace taxa (Primulaceae): contribution to Androsace taxonomy

In the present study, the leaf and scape anatomical features of ten Androsace taxa distributed in Turkiye were defined to contribute to plant identification. Hand sections from both the scape and leaf examined 43 anatomical characters. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) were performed for the first time for Androsace. The results show that there are differences as well as similarities between Androsace species. It is noteworthy that Androsace artvinensis forms a separate main group with HCA. In addition, the fact that two of the five basic components are represented by a single variable according to the PCA results suggests that the anatomical characters examined are determinative for Androsace taxa.). In PCA, eigenvalues of PC1 (2.435), PC2 (1.749), PC3 (1.369), PC4 (1.223), and PC5 (1.006) were greater than 1.0. Cortex width, aerenchyma, arrangement of vascular bundles, and four-branched non-glandular hairs are among the important anatomical characteristics of the scape. Leaf cross-sectional shape, epidermis dimensions, glandular hair types, presence of five branched non-glandular hairs, stoma sizes, presence of crystals in the mesophyll, and types are among the qualitative and quantitative anatomical characteristics that attract attention in the leaf. This study examined almost all taxa of the genus Androsace distributed in Turkiye. The results will be important in finding new species among the examined taxa and revealing the anatomical features of the taxa for the first time. They will contribute to other studies on the genus

Long-lasting cognitive effects of COVID-19: is there a role of BDNF?

Coronavirus disease 2019 (COVID-19) affects numerous systems of the body during the illness, and there have been long-lasting effects. BDNF plays an important role in synaptic plasticity and synaptic communication. According to the inclusion and exclusion criteria, 54 patients who had COVID-19 infection participated in this study. Thirty-six age-, sex-, body mass index (BMI)-, education level- and smoking status-matched healthy controls were included in the present study. All participants were individually administered the Stroop test and Visual Aural Digit Span Test Form B (VADS-B). Serum BDNF levels were measured by ELISA. Stroop test word reading spontaneous correction number and reading time, word color saying wrong number, spontaneous correction number and reading time, box color speaking spontaneous correction number and reading time, Stroop interference and speed factor duration were significantly higher in the COVID-19 group than in the control group. All scores of the VADS-B test were found to be significantly lower in the COVID-19 group. The mean serum BDNF levels were found to be 10.9 +/- 6.9 ng/ml in the COVID-19 group and 12.8 +/- 6.4 ng/ml in the healthy control group. Two-way ANOVA showed that the serum mean BDNF level was significantly lower in the COVID-19 group than in the control group. Gender had a significant effect on BDNF levels (F = 12.21; p = 0.008). The present study is the first to demonstrate the association between the role of serum BDNF and cognitive decline in patients with COVID-19 infection. Additionally, there is a significant role of male gender in terms of lower BDNF level and cognitive decline

Moving towards in object recognition with deep learning for autonomous driving applications

Object recognition and pedestrian detection are of crucial importance to autonomous driving applications. Deep learning based methods have exhibited very large improvements in accuracy and fast decision in real time applications thanks to CUDA support. In this paper, we propose two Convolutions Neural Networks (CNNs) architectures with different layers. We extract the features obtained from the proposed CNN, CNN in AlexNet architecture, and Bag of visual Words (BOW) approach by using SURF, HOG and k-means. We use linear SVM classifiers for training the features. In the experiments, we carried out object recognition and pedestrian detection tasks using the benchmark the Caltech 101 and the Caltech Pedestrian Detection datasets

Unocculuded object grasping by using visual data

Automatic grasping objects can become important in the areas such as industrial processes, processes which are dangerous for human, or the operations which should be executed in the places, small for people work. In this study, it is aimed to design a robotic system for grasping unocculuded certain objects by using visual data. For this aim an experimental process was implemented. Visual data process can be divided in two main parts: identification and three dimensional positioning. Identification issue suffers from several conditions as rotation, camera position, and location of the subject in the frame. Also obtaining the features invariant from these conditions is important. Therefore Zernike moment method can be used to overcome these negativities. In order to identify the objects an artificial neural network was used to classify the objects by using Zernike moment coefficients. In the experimental system a parallel axis stereovision subsystem, a DSPFPGA embedded media processor, and five-axis robot arm were used. The success rate of artificial neural network was 98%. After identifying the objects, a sequential algebra were performed in the DSP part of the media processor and the position of the object according to robot arm reference point was extracted. After all, desired object in the instant frame was grasped and placed in different location by the robot arm

THE EFFECTS OF FACE MASK USE DURING COVID-19 ON SPEECH COMPREHENSION IN GERIATRIC PATIENTS WITH HEARING LOSS WHO USE LIP-READING FOR COMMUNICATION: A PROSPECTIVE CROSS-SECTIONAL STUDY

Objective: Communication difficulties are considered the most significant consequence of hearing loss. This study aimed to determine whether surgical face masks, which have been mandatory throughout the COVID-19 pandemic, have an effect on speech comprehension scores in geriatric lip-reading patients with hearing loss and to raise awareness of the need for solutions to this problem. Materials and Method: Patients with moderate and higher sensorineural or mixed bilateral symmetrical hearing loss who stated that they lip-read to better understand during communication were included in the study. The patients’ speech comprehension scores were gathered while the audiologist wore a surgical mask and then a transparent mask, respectively. Results: Twelve (33,3%) of the patients were female, and 24 (66.7%) were male. The mean age of the patients was 66.64±1.53 years. The mean speech comprehension scores of the patients when the audiologist was wearing a surgical mask (38.25±14.33) and a transparent mask (67.81 ± 14.30), respectively, were compared. The surgical mask significantly affected speech comprehension scores, and the Cohen d value of the effect size was 2.06. As such, the surgical face mask had a great effect on these patients’ speech comprehension scores. Conclusions: In elderly lip-reading patients who suffer from hearing loss, seeing the lip movements of the speaker, especially in hospital applications, promotes more effective communication. Transparent face masks can be considered a solution. © 2022, Geriatrics Society. All rights reserved