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Yayın Covid 19 döneminde algılanan tehdit, algılanan ciddiyet ve kendini izole etme niyetinin dürtüsel satın alma üzerindeki etkisi: bir seri aracılık modeli incelemesi(Melih Topaloğlu, 2021) Sağlam, Mehmet; Tavman, Emine BaşakAmaç – Bu çalışmanın amacı, COVID-19 salgını sırasında ortaya çıkan algılanan tehdit, algılanan ciddiyet ve kendini izole etme niyetinin dürtüsel satın alma üzerindeki etkilerini belirlemektir. Ek olarak, algılanan ciddiyet ve kendini izole etme niyetinin bu ilişkiler üzerindeki aracılık etkilerini seri aracılık modeli üzerinden tespit etmeyi amaçlamaktadır. Tasarım/Yöntem/Yaklaşım – Veri toplama aracı olarak online anket, örnekleme yöntemi olarak kolayda ve kartopu örnekleme kullanılmıştır. 4 Ocak-15 Ocak 2021 tarihleri arasındaki veri toplama sürecinde 403 katılımcı verisi elde edilmiştir. Veri analizinde SPSS 24, AMOS 24 ve PROCESS 3.1 makro uzantısı kullanılmıştır. Araştırma modeli, koruma motivasyonu teorisine dayandırılmıştır. Analiz yöntemlerinde tanımlayıcı istatistikler, doğrulayıcı faktör analizi, güvenilirlik analizi, geçerlilik analizleri ve seri aracılık analizi kullanılmıştır. Bulgular – Araştırma bulgularında, algılanan tehdidin (?=0,283*), algılanan ciddiyetin (?=0,365*) ve kendini izole etme niyetinin (?=0,434*) dürtüsel satın alma üzerinde doğrudan etkiye sahip olduğu tespit edilmiştir. Aracılık etkileri (dolaylı etki) değerlendirildiğinde ise algılanan tehdidin dürtüsel satın alma üzerindeki etkisinde algılanan ciddiyetin aracı etkisi olduğu (?=0,246**), kendini izole etme niyetinin aracı etkiye sahip olduğu (?=0,099*), kendini izole etme niyetinin algılanan ciddiyet aracılığıyla birlikte aracı etkiye sahip olduğu (?=0,139**), belirlenmiştir. Tartışma – Araştırma bulguları doğrultusunda dürtüsel satın alma üzerinde en etkili boyut kendini izole etme niyeti olarak ortaya çıkmıştır. Algılanan tehdidin dürtüsel satın alma üzerindeki etkisinde algılanan ciddiyetin aracı etkisi daha büyüktür. Kendini izole etme niyetinin aracı etkisi, algılanan ciddiyetin etkisiyle birlikte gerçekleşmesi durumunda artmaktadır. Elde edilen sonuçlar literatürdeki çalışmalarla paralellik göstermektedir.Yayın Developing an efficient deep neural network for automatic detection of COVID-19 using chest X-ray images(Elsevier B.V., 2021-06) Sheykhivand, Sobhan; Mousavi, Zohreh; Mojtahedi, Sina; Yousefi Rezaii, Tohid; Farzamnia, Ali; Meshgini, Saeed; Saad, IsmailThe novel coronavirus (COVID-19) could be described as the greatest human challenge of the 21st century. The development and transmission of the disease have increased mortality in all countries. Therefore, a rapid diagnosis of COVID-19 is necessary to treat and control the disease. In this paper, a new method for the automatic identification of pneumonia (including COVID-19) is presented using a proposed deep neural network. In the proposed method, the chest X-ray images are used to separate 2–4 classes in 7 different and functional scenarios according to healthy, viral, bacterial, and COVID-19 classes. In the proposed architecture, Generative Adversarial Networks (GANs) are used together with a fusion of the deep transfer learning and LSTM networks, without involving feature extraction/selection for classification of pneumonia. We have achieved more than 90% accuracy for all scenarios except one and also achieved 99% accuracy for separating COVID-19 from healthy group. We also compared our deep proposed network with other deep transfer learning networks (including Inception-ResNet V2, Inception V4, VGG16 and MobileNet) that have been recently widely used in pneumonia detection studies. The results based on the proposed network were very promising in terms of accuracy, precision, sensitivity, and specificity compared to the other deep transfer learning approaches. Depending on the high performance of the proposed method, it can be used during the treatment of patients.Yayın The effect of SARS-CoV-2 virus on resting-state functional connectivity during adolescence: Investigating brain correlates of psychotic-like experiences and SARS-CoV-2 related inflammation response(Elsevier Ireland Ltd, 2023-12) Yılmaz Kafalı, Helin; Daşgın, Hacer; Şahin Çevik, Didenur; Sozan, Sara Sinem; Oğuz, Kader K.; Mutlu, Müge; Özkaya Parlakay, Aslınur; Toulopoulou, TimotheaWe first aimed to investigate resting-state functional connectivity (rs-FC) differences between adolescents exposed to SARS-CoV-2 and healthy controls. Secondly, the moderator effect of PLEs on group differences in rs-FC was examined. Thirdly, brain correlates of inflammation response during acute SARS-CoV-2 infection were investigated. Eighty-two participants aged between 14 and 24 years (SARS-CoV-2 (n = 35), controls (n = 47)) were examined using rs-fMRI. Seed-based rs-FC analysis was performed. The positive subscale of Community Assessment of Psychotic Experiences-42 (CAPE-Pos) was used to measure PLEs. The SARS-CoV-2 group had a lesser rs-FC within sensorimotor network (SMN), central executive network (CEN) and language network (LN), but an increased rs-FC within visual network (VN) compared to controls. No significant differences were detected between the groups regarding CAPE-Pos-score. However, including CAPE-Pos as a covariate, we found increased rs-FC within CEN and SN in SARS-CoV-2 compared to controls. Among the SARS-CoV-2 group, neutrophil/lymphocyte and thrombocyte*neutrophil/lymphocyte ratio was correlated with decreased/increased FC within DMN and SN, and increased FC within CEN. Our results showed rs-FC alterations within the SMN, CEN, LN, and VN among adolescents exposed to SARS-CoV-2. Moreover, changes in rs-FC associated with PLEs existed in these adolescents despite the absence of clinical changes. Furthermore, inflammation response was correlated with alterations in FC within the triple network system.Yayın ComStreamClust: a communicative multi-agent approach to text clustering in streaming data(Springer Science and Business Media Deutschland GmbH, 2023-12) Najafi, Ali; Gholipour-Shilabin, Araz; Dehkharghani, Rahim; Mohammadpur-Fard, Ali; Asgari-Chenaghlu, MeysamTopic detection is the task of determining and tracking hot topics in social media. Twitter is arguably the most popular platform for people to share their ideas with others about different issues. One such prevalent issue is the COVID-19 pandemic. Detecting and tracking topics on these kinds of issues would help governments and healthcare companies deal with this phenomenon. In this paper, we propose a novel, multi-agent, communicative clustering approach, so-called ComStreamClust for clustering sub-topics inside a broader topic, e.g., the COVID-19 and the FA CUP. The proposed approach is parallelizable, and can simultaneously handle several data-point. The LaBSE sentence embedding is used to measure the semantic similarity between two tweets. ComStreamClust has been evaluated by several metrics such as keyword precision, keyword recall, and topic recall. Based on topic recall on different number of keywords, ComStreamClust obtains superior results when compared to the existing methods.Yayın Reliability of direct-to-home teleneuropsychological assessment: a within-subject design study(Routledge, 2025-07-04) Yıldırım, Elif; Soncu Büyükişcan, Ezgi; Akça Kalem, Şükriye; Gürvit, HakanObjective: During the COVID-19 pandemic, the need to continue diagnosis and treatment processes, in addition to scientific research, led to a rapid shift towards direct-to-home tele-neuropsychology administrations, the reliability and validity of which had not been clearly established then. This study, therefore, aimed to examine the reliability of direct-to-home tele-neuropsychological assessment (TNP). Method: The sample included 105 cognitively healthy individuals aged between 50–83 years, and 47 patients diagnosed with neurocognitive disorders (mild cognitive impairment and early-stage Alzheimer’s type dementia). All participants underwent both face-to-face and teleneuropsychological assessments in a counterbalanced order. Results: The results revealed that performances across measures of attention, working memory, verbal fluency, verbal and visual memory, and visual perception were comparable across assessment modalities. Intraclass correlation coefficients of the tests ranged from.54 to.92. Conclusions: The findings of the study provide support for direct-to-home teleneuropsychological assessment among patients with neurocognitive disorders. Neuropsychological tests relying on verbal administration and independent of motor performance may represent a reliable alternative for this patient group when administered in settings where external distractions or technological limitations are controlled. For cognitively healthy individuals, on the other hand, the reliability of the TNP application is more questionable for memory and some executive function tests and therefore needs further exploration.
