Growth and Superconductivity of Pb and Pb-Bi Alloys in the Quantum Regime

Superconductivity is a collective quantum phenomenon that is inevitably suppressed in reduced dimensionality. Questions of how thin superconducting wires or films can be before they lose their superconducting properties have important technological ramifications and go to the heart of understanding formation, coherence, and robustness of the superconducting state in quantum confined geometries. Suppression of superconductivity in low dimensions is usually attributed to thermal or quantum fluctuations, or to pair-breaking Coulomb interactions in the presence of strong disorder. Control and quantification of a film’s disorder length scale remained a critical experimental obstacle, however. Here, we exploit quantum confinement of itinerant electrons in a soft metal (Pb), to stabilize atomically-flat superconductors with lateral dimensions of the order of a few millimeters and vertical dimensions of only a few atomic layers. These extremely thin superconductors show no indication of defect- or fluctuation-driven suppression of superconductivity and sustain macroscopic super- currents of up to ~10% of the theoretical depairing current density. The extreme hardness of the critical state can be attributed to the presence of intrinsic vortex traps that are stabilized by quantum confinement. We furthermore show that the quantum growth and superconductive properties of the films can be tailored by Fermi surface engineering via controlled alloying. The present study paints a conceptually appealing, elegant picture of a model nano-scale superconductor with calculable critical state properties. It furthermore indicates the intriguing possibility of achieving and exploiting superconductivity in the ultimate low-dimensional limit

Discovering the food travel preferences of university students

The main purposes of this study are to understand the perspectives of university students on food tourism and to discover their gastronomic travel preferences. 89 responses were gathered from a university in Izmir (on the west coast of Turkey) by using a structured interview technique. The data were analyzed through the descriptive methods including frequency analysis. Results indicate that the students\u27 food travel preferences significantly vary due to their gastronomic motivations. The vast majority of these potential consumers consider going on a food-related travel in the future. Kebab, doner and baklava have an advantage over other dishes in terms of representing the region and becoming a brand. Participants believe that Turkey, Italy, Mexico, France and Spain are the top five countries that offer the best food experience. This study makes a considerable contribution to the literature on gastronomic preferences of young people through in-depth interviews. This exploratory research sheds light on this field of study for researchers, practitioners and food tourism professionals

Discovering the food travel preferences of university students

The main purposes of this study are to understand the perspectives of university students on food tourism and to discover their gastronomic travel preferences. 89 responses were gathered from a university in Izmir (on the west coast of Turkey) by using a structured interview technique. The data were analyzed through the descriptive methods including frequency analysis. Results indicate that the students\u27 food travel preferences significantly vary due to their gastronomic motivations. The vast majority of these potential consumers consider going on a food-related travel in the future. Kebab, doner and baklava have an advantage over other dishes in terms of representing the region and becoming a brand. Participants believe that Turkey, Italy, Mexico, France and Spain are the top five countries that offer the best food experience. This study makes a considerable contribution to the literature on gastronomic preferences of young people through in-depth interviews. This exploratory research sheds light on this field of study for researchers, practitioners and food tourism professionals

Machine Learning Based IoT Adaptive Architecture for Epilepsy Seizure Detection: Anatomy and Analysis

A seizure tracking system is crucial for monitoring and evaluating epilepsy treatments. Caretaker seizure diaries are used in epilepsy care today, but clinical seizure monitoring may miss seizures. Monitoring devices that can be worn may be better tolerated and more suitable for long-term ambulatory use. Many techniques and methods are proposed for seizure detection; However, simplicity and affordability are key concepts for daily use while preserving the accuracy of the detection. In this study, we propose a versal, affordable noninvasive based on a simple real-time k-Nearest-Neighbors (kNN) machine learning that can be customized and adapted to individual users in less than four seconds of training time; the system was verified and validated using 500 subjects, with seizure detection data sampled at 178 Hz, the operated with a mean accuracy of (94.5%).Comment: Under review, 5 pages, 7 figures, 3 table

The formations and constructions of the American identity: a case for classical antiquity

The present work studies the role of classical tradition in the formations and constructions of the American Identity. The first part of this thesis aims to outline the processes of formation and the consequences of the conditions prevalent in the American Continent. In the second part, it is observed that during the period of American Revolution, the allusions and references to the classical antiquity are numerous. This observation necessitated a methodical study, in which the role of these allusions and references were studied in order to understand their influences, if any, on the processes of construction of the American Identity. The methods used for the analysis of construction and formation are based on the methodology of the study of nationalism. In this methodology the works of the ideologues are studied, and their key propositions are analyzed for their relevance to the criteria established by the studies of nationalism. Through this study it has been found that some of the features of the allusions and references to the classical antiquty have indeed conformed to the characteristics of a nationalistic movement. The political discourses, personalities and myths of the ancient Greek and Roman states have been presented in the revolutionary period as viable models with which the ideal American identity could be formed. The significance of the classical texts had been maintained in the American revolutionary period as a linkage to the source of 'European civilization'. The construction of American identity on the idea of a civilization, therefore has been made the basis of nationalism in America

Serum Levels of TNF-α, IFN-γ, IL-6, IL-8, IL-12, IL-17, and IL-18 in Patients With Active Psoriasis and Correlation With Disease Severity

Recent progress in the understanding of psoriasis has shown that the regulation of local and systemic cytokines plays an important role in its pathogenesis. The most often used psoriasis score is the psoriasis area and severity index (PASI). A simple laboratory test from a blood sample would be an attractive, patient-independent, and observer-independent marker of disease severity. To this end, we evaluated the association of serum levels of some proinflammatory cytokines in vivo and their correlation with severity of psoriasis. The serum levels of cytokines levels were determined with the use of the ELISA method. All mean values except IL-17 levels of patients were significantly higher than those of controls. There was a significant correlation between serum levels of IFN-γ, IL-12, IL-17, and IL-18, and severity of the disease. Psoriasis can be described as a T-cell-mediated disease, with a complex role for a variety of cytokines, which has led to the development of new immunomodulatory therapies. In this study, serum TNF-α, IFN-γ, IL-6, IL-8, IL-12, and IL-18 levels were significantly higher in active psoriatic patients than in controls. Furthermore, high levels of IFN-γ, IL-12, and IL-18 correlated with the clinical severity and activity of psoriasis, and those measurements of serum levels of these cytokines may be objective parameters for the disease severity

A Convolutional-based Model for Early Prediction of Alzheimer's based on the Dementia Stage in the MRI Brain Images

Alzheimer's disease is a degenerative brain disease. Being the primary cause of Dementia in adults and progressively destroys brain memory. Though Alzheimer's disease does not have a cure currently, diagnosing it at an earlier stage will help reduce the severity of the disease. Thus, early diagnosis of Alzheimer's could help to reduce or stop the disease from progressing. In this paper, we proposed a deep convolutional neural network-based model for learning model using to determine the stage of Dementia in adults based on the Magnetic Resonance Imaging (MRI) images to detect the early onset of Alzheimer's.Comment: Short paper, Under Review in FLAIRS-3

Deep Learning Approach for Early Stage Lung Cancer Detection

Lung cancer is the leading cause of death among different types of cancers. Every year, the lives lost due to lung cancer exceed those lost to pancreatic, breast, and prostate cancer combined. The survival rate for lung cancer patients is very low compared to other cancer patients due to late diagnostics. Thus, early lung cancer diagnostics is crucial for patients to receive early treatments, increasing the survival rate or even becoming cancer-free. This paper proposed a deep-learning model for early lung cancer prediction and diagnosis from Computed Tomography (CT) scans. The proposed mode achieves high accuracy. In addition, it can be a beneficial tool to support radiologists' decisions in predicting and detecting lung cancer and its stage.Comment: Under review in FLAIRS 202