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ABSTRACT: Health tourism, which is a sub-field of tourism, has an important place in the development of countries and regions. It is the people living in that region who are most affected by the development of health tourism activities in a region. Perceptions and support of local people have important effects on the development and sustainability of health tourism in a destination. It should be ensured that the local people have positive perceptions about the effects of health tourism and support tourism development. In this study, the effect of four factors affecting health tourism on the support of local people to the development of health tourism was investigated. Study data were collected through face-to-face survey application to 392 participants residing in Akyazı. The research model and hypotheses developed in line with the purpose of the study were tested with the structural equation model using AMOS 4 and SPSS 22 package programs. As a result of the test, it was determined that the model had a good fit. It has been determined that the effect of socio-cultural and health-related factors on the total impact of health tourism development is significant. The total impacts, economic and health impact variables were all found to have a significant impact on the local community's support for health tourism development. ÖZ: Turizmin alt alanı olan sağlık turizmi ülkelerin ve bölgelerin kalkınmasında önemli bir yere sahiptir. Sağlık turizmi faaliyetlerinin bir yöredeki gelişiminden en fazla etkilenen o bölgede yaşayan halktır. Sağlık turizminin bir destinasyonda gelişimi ve sürdürülebilirliği üzerinde yerel halkın algıları ve desteği önemli etkiler yaratmaktadır. Sağlık turizminin etkilerine yönelik yerel halkın olumlu algılara sahip olması ve turizm gelişimini desteklemesi sağlanmalıdır. Bu çalışmada sağlık turizmini etkileyen dört faktörün sağlık turizminin yerel halkın sağlık turizminin gelişimine verdiği desteğe etkisi araştırılmıştır. Çalışma verileri Akyazı’da ikamet eden 392 katılımcıya yüz yüze anket uygulamasıyla toplanmıştır. Çalışmanın amacı doğrultusunda geliştirilen araştırma modeli ve hipotezler AMOS 4 ve SPSS 22 paket programları kullanılarak yapısal eşitlik modeli ile test edilmiştir. Test sonucunda modelin iyi bir uyuma sahip olduğu belirlenmiştir. Sosyo-kültürel ve sağlıkla ilgili faktörlerin sağlık turizmi gelişiminin toplam etkisi üzerindeki etkisinin anlamlı olduğu tespit edilmiştir. Toplam etkiler, ekonomik ve sağlık etkileri değişkenlerinin hepsinin yerel halkın sağlık turizminin gelişimine verdiği destek üzerinde önemli bir etkisi olduğu bulunmuştur.

Abstract Introduction Radiomics methods are used to analyze various medical images, including computed tomography (CT), magnetic resonance, and positron emission tomography to provide information regarding the diagnosis, patient outcome, tumor phenotype, and the gene-protein signatures of various diseases. In low-risk group, complete surgical resection is typically sufficient, whereas in high-risk thymoma, adjuvant therapy is usually required. Therefore, it is important to distinguish between both. This study evaluated the CT radiomics features of thymomas to discriminate between low- and high-risk thymoma groups. Materials and methods In total, 83 patients with thymoma were included in this study between 2004 and 2019. We used the Radcloud platform (Huiying Medical Technology Co., Ltd.) to manage the imaging and clinical data and perform the radiomics statistical analysis. The training and validation datasets were separated by a random method with a ratio of 2:8 and 502 random seeds. The histopathological diagnosis was noted from the pathology report. Results Four machine-learning radiomics features were identified to differentiate a low-risk thymoma group from a high-risk thymoma group. The radiomics feature names were Energy, Zone Entropy, Long Run Low Gray Level Emphasis, and Large Dependence Low Gray Level Emphasis. Conclusions The results demonstrated that a machine-learning model and a multilayer perceptron classifier analysis can be used on CT images to predict low- and high-risk thymomas. This combination could be a useful preoperative method to determine the surgical approach for thymoma.

Academia is one of the main hubs for promoting gender equality and non-discrimination, yet very few programs in Romania actively tackle the topic. An assessment of students’ perceptions is thus necessary in order to identify the level of awareness around gender issues and potential barriers hindering an inclusive academic environment. The present exploratory study aims to fill this gap by providing information on four dimensions of gender equality: attitudes towards gender equality, prevalence of gender stereotypes, gender- based violence and sexual harassment, and gender-based discrimination. The questionnaire was applied online and offline between October 2018 and March 2019 to 275 students enrolled in Bachelor, Master and Doctoral studies at Babeș- Bolyai University, Cluj-Napoca.The study found that students had a rather high awareness about gender issues in general and held favorable views towards gender equality and its enforcement. However, female students were more prone to stereotype, claiming more traits for themselves, and were more likely than their male counterparts to experience sexual harassment and discrimination regarding professional promotion. A series of implications for practitioners and recommendations are also discussed.

Abstract The homozygous LAMC3 gene mutation is associated with severe bilateral smoothening and thickening of the lateral occipital cortex . Despite this and further significant changes in gray matter structure, a patient harboring this mutation exhibited a range of remarkably intact perceptual abilities . One possible explanation of this perceptual sparing could be that the white matter structural integrity and functional connectivity in relevant pathways remained intact. To test this idea, we used diffusion tensor and functional magnetic resonance imaging to investigate functional connectivity in resting‐state networks in major structural pathways involved in object perception and visual attention and corresponding microstructural integrity in a patient with homozygous LAMC3 mutation and sex, age, education, and socioeconomically matched healthy control group. White matter microstructural integrity results indicated widespread disruptions in both intra‐ and interhemispheric structural connections except inferior longitudinal fasciculus. With a few exceptions, the functional connectivity between the patient's adjacent gray matter regions of major white matter tracts of interest was conserved. In addition, functional localizers for face, object, and place areas showed similar results with a representative control, providing an explanation for the patient's intact face, place, and object recognition abilities. To generalize this finding, we also compared functional connectivity between early visual areas and face, place, and object category‐selective areas, and we found that the functional connectivity of the patient was not different from the control group. Overall, our results provided complementary information about the effects of LAMC3 gene mutation on the human brain including intact temporo‐occipital structural and functional connectivity that are compatible with preserved perceptual abilities.

Genelleştirilmiş Regresyon Yapay Sinir Ağı (GRYSA) radyal tabanlı çalışan ve genellikle tahminleyici olarak kullanılan denetimli-öğrenimli bir yapay sinir ağı (YSA) modelidir. Kolay modellenebilmesinin yanında hızlı ve tutarlı sonuçlar üretmesi bu algoritmanın güçlü yanlarını oluşturmaktadır. Ancak GRYSA tahmin mekanizmasında, eğitim veri setindeki her örnek veri için örüntü katmanında bir adet nöron tutulmaktadır. Bu nedenle, eğitim veri setinin çok büyük olduğu çalışmalarda örüntü katman yapısı örnek verilerinin sayısıyla aynı oranda büyümekte, yapılan işlem sayısı ve bellek gereksinimi artmaktadır. Bu çalışmada, GRYSA algoritmasının işlem sayısını azaltmaya yönelik olarak literatürde daha önce de denenmiş olan k-ortalama kümeleme algoritması ön-işlemci olarak kullanılmış, literatürdeki çalışmalardan farklı olarak, bu çalışmaların performansını negatif anlamda etkileyen kümeler arasına düşen test verileri bulunarak aykırı veri oluşmasının önüne geçilmiştir. Böylece, örüntü katmanındaki bellek ihtiyacı ve işlem sayısı azaltılırken, kümeleme algoritmasının eklenmesi ile performansta ortaya çıkan negatif etki büyük oranda giderilmiş ve yaklaşık %90 daha az eğitim verisi ile neredeyse aynı tahmin sonuçları elde edilmiştir.

Genelleştirilmiş Regresyon Yapay Sinir Ağı (GRYSA) radyal tabanlı çalışan ve genellikle tahminleyici olarak kullanılan denetimli-öğrenimli bir yapay sinir ağı (YSA) modelidir. Kolay modellenebilmesinin yanında hızlı ve tutarlı sonuçlar üretmesi bu algoritmanın güçlü yanlarını oluşturmaktadır. Ancak GRYSA tahmin mekanizmasında, eğitim veri setindeki her örnek veri için örüntü katmanında bir adet nöron tutulmaktadır. Bu nedenle, eğitim veri setinin çok büyük olduğu çalışmalarda örüntü katman yapısı örnek verilerinin sayısıyla aynı oranda büyümekte, yapılan işlem sayısı ve bellek gereksinimi artmaktadır. Bu çalışmada, GRYSA algoritmasının işlem sayısını azaltmaya yönelik olarak literatürde daha önce de denenmiş olan k-ortalama kümeleme algoritması ön-işlemci olarak kullanılmış, literatürdeki çalışmalardan farklı olarak, bu çalışmaların performansını negatif anlamda etkileyen kümeler arasına düşen test verileri bulunarak aykırı veri oluşmasının önüne geçilmiştir. Böylece, örüntü katmanındaki bellek ihtiyacı ve işlem sayısı azaltılırken, kümeleme algoritmasının eklenmesi ile performansta ortaya çıkan negatif etki büyük oranda giderilmiş ve yaklaşık %90 daha az eğitim verisi ile neredeyse aynı tahmin sonuçları elde edilmiştir.

Objective: Prior knowledge and expectations strongly shape perceptual decision-making mechanism. However, it is not clear whether and how they affect low-level sensory processes. In this study we investigated the effect of expectation on visual perception at the threshold level in a 2AFC paradigm. Methods: Task-irrelevant cues, face or house, provided prior information about the likelihood of the upcoming target stimulus category. Participants' (n=8) task was to report the spatial location of the target stimulus. We systematically manipulated the expectation's validity by setting the validity of the category-cue at 100%, 75%, 50%, and neutral in separate sessions. Duration thresholds (70.9% success) were computed in neutral, expected and unexpected trials. Next, we used a mechanistic cortical model with dynamic priors to unravel the computational mechanism underlying the effects we found in the experiment. We implemented the model on a trial by trial basis. At each trial the prior did not remain fixed, but it was updated at each iteration. Results: Our behavioral results showed that thresholds were higher in unexpected trials than in expected trials [t(7)=3.079, p=0.018]. However, thresholds of expected trials (100%) were not different from neutral trials [t(7)=0.676, p=0.521]. Our modeling findings revealed that the observed increase of the thresholds in the unexpected trials is due to greater number of iterations that are required for a successful detection when the expectation and actual input disagree [t(7)=3.220, p=0.015]. Conclusion: Our behavioral findings reveal that violation of expectations delay sensory processes. This happens because when expectations are violated further processing is required by the system to complete the sensory process. Our findings on mechanistic cortical model also demonstrate that a parsimonious cortical model can successfully explain human behavior. [ABSTRACT FROM AUTHOR]