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Smoke-wire visualization of the flow dynamics through a fluidic thrust vectoring system based on Coanda effect
No full textFluid dynamics, a foundational area of fluid mechanics, is a vital field with applications across numerous industries. Its principles are utilized in the design and structural integrity of aerodynamic vehicles and in the prediction of natural phenomena such as airflow patterns. An understanding of fluid behavior under varying conditions is essential for the optimization of processes and systems. This study examines a distinctive approach to visualizing fluid flow, namely Smoke Wire Visualization. While the final experiment setup in conventional cases is relatively simple, integrating novel systems requires meticulous attention to detail. This paper outlines the iterative process of conceptualizing, configuring, and refining the Smoke Wire Visualization technique of the flow dynamics through a fluidic thrust vectoring system based on Coanda effect. In the realm of engineering, compromise is inevitable, and this study exemplifies the pursuit of extracting optimal insights from fluid dynamics through innovative visualization methods
Diffeomorphism invariance breaking in gravity and cosmological evolution
No full textDiffeomorphism invariance breaking has been investigated in the literature in several contexts, including emergent General Relativity (GR). If GR emerges from an underlying theory without diffeomorphism invariance, there may be small violations of this symmetry at low energies. Since such small violations should not cause instabilities in cosmological evolution, it is a suitable framework for examining such symmetry-breaking effects. In this paper, the cosmological evolution with broken diffeomorphism invariance is investigated in the (modified) FLRW spacetime in the effective theory framework. The GR Lagrangian is augmented with all diffeomorphism-breaking but Lorentz-invariant terms in the leading order, namely, those involving two derivatives. The magnitudes of (minor) violations are kept general modulo the conditions arising in the linearized theory. The analytic solutions of the scale factor in the full non-linear theory for the single-component universes are attempted; the radiation and vacuum solutions are found analytically, whereas the matter solution is worked out numerically since an analytic solution does not exist in the required form. It is observed that the solutions smoothly connect to those of GR in the limit of vanishing symmetry-breaking. The more realistic, two-component, and three-component universes are numerically studied, and no signs of singular behavior are observed: minor diffeomorphism-violating modifications to GR at the level of two derivatives do not cause instabilities in the basic cosmological evolution
Generalized Θ-Φ<sub>8</sub>-Contractions and Θ-<i>f</i><sub>8</sub>-Expansion of Darbo-Type and Their Applications
No full textIn this work, we present the concept of 6-Px-contraction, 0-Px-Suzuki contraction, 0-x-Kannan type contraction, and 60-x-expansion, and establish some novel fixed point theorems in the light of Banach space. In order to verify our results, we construct some examples. Furthermore, we use our results to check the existence of a solution to differential equations
Constructing culturally appropriate childhood aggression theory in early childhood through situational analysis in Turkish context: A grounded theory
No full textExploring K-12 teachers' general attitudes towards ai and curriculum needs for AI literacy course
No full textArtificial Intelligence (AI) is increasinglytransforming education by providing innovative tools that enhance teaching andlearning. However, many educators remain uncertain about how to utilize AIeffectively while ensuring ethical practices, highlighting the need for AIliteracy in K-12 education. Before implementing AI literacy curricula, understandingteachers’ attitudes toward AI and their needs for successful adoption isessential.This study explored K-12 teachers’ attitudes toward AIand their curriculum needs for implementing AI literacy. A mixed-methodapproach was adopted, employing the General Attitudes towards ArtificialIntelligence Scale (GAAIS) to measure attitudes and open-ended survey questionsto capture teachers’ perspectives. The study involved 40 teachers from publicand private K-12 schools who voluntarily shared their views. Findings revealedthat teachers hold moderately positive attitudes toward the beneficial aspectsof AI (M = 3.33/5) and a somewhat forgiving attitude toward its negativeaspects (M = 3.07/5), suggesting a general openness to AI integration ineducation.Thematic analysis of teachers’ responses identifiedkey needs for successful AI literacy implementation, including professionaldevelopment training, technical support, comprehensive curriculum resources,and clear ethical and policy guidelines. Teachers also emphasized theimportance of promoting responsible AI use and aligning curriculum content withreal-world applications.Overall, the study contributes to the growing field ofAI in education by offering insights that can guide policymakers, curriculum developers,and educational leaders in designing effective AI literacy curricula for K-12schools.</p
The EU AI Act and Its Implications For Human Resource Management : Legal Frameworks, Challenges and Opportunities
No full textVALORIZATION OF AGRICULTURAL RESIDUES INTO BIOACTIVE COMPOUNDS: A SUPERCRITICAL EXTRACTION-BASED ECONOMIC PERSPECTIVE FOR TÜRKİYE
No full textEditorial: Studying rare diseases using induced pluripotent stem cell (iPSC)-based model systems
No full textNew data on text reading in English as a second language
No full textThis paper reports an expansion of the English as a second language (L2) component of the Multilingual Eye Movement Corpus (MECO L2), an international database of eye movements during text reading. While the previous Wave 1 of the MECO project (Kuperman et al., 2023) contained English as a L2 reading data from readers with 12 different first language (L1) backgrounds, the newly collected dataset adds eye-tracking data on English text reading from 13 distinct L1 backgrounds (N = 660) as well as participants' scores on component skills of English proficiency and information about their demographics and language background and use. The paper reports reliability estimates, descriptive statistics, and correlational analyses as means to validate the expansion dataset. Consistent with prior literature and the MECO Wave 1, trends in the MECO Wave 2 data include a weak correlation between reading comprehension and oculomotor measures of reading fluency and a greater L1-L2 contrast in reading fluency than reading comprehension. Jointly with Wave 1, the MECO project includes English reading data from more than 1,200 readers representing a diversity of native writing systems (logographic, abjad, abugida, and alphabetic) and 19 distinct L1 backgrounds. We provide multiple pointers to new venues of how L2 reading researchers can mine this rich publicly available dataset