This study investigates the impact of historical and ideological continuities in Turkey’s migration policies on contemporary attitudes toward Syrian refugees. It examines how ethnic homogenization and discrimination, rooted in the foundation of the Turkish Republic, continue to shape public perceptions and policy frameworks. The research is based on qualitative methodologies, including 41 semi-structured in-depth interviews conducted between July and December 2021 with Syrian refugees and Turkish community members residing in Altındağ, Mamak, and Ümitköy districts of Ankara. Participants were purposively selected to provide diverse perspectives on social integration and identity formation. The findings reveal a shift from initial acceptance under religious solidarity to increasing exclusion, driven by nationalist rhetoric. Despite official claims of promoting multiculturalism, Turkish policies and societal attitudes often reinforce prejudices, fostering a socio-political environment where racial and ethnic biases persist.

Quantum learning models hold the potential to bring computational advantages over the classical realm. As powerful quantum servers become available on the cloud, ensuring the protection of clients’ private data becomes crucial. By incorporating quantum homomorphic encryption schemes, we present a general framework that enables quantum delegated and federated learning with a computation-theoretical data privacy guarantee. We show that learning and inference under this framework feature substantially lower communication complexity compared with schemes based on blind quantum computing. In addition, in the proposed quantum federated learning scenario, there is less computational burden on local quantum devices from the client side, since the server can operate on encrypted quantum data without extracting any information. We further prove that certain quantum speedups in supervised learning carry over to private delegated learning scenarios employing quantum kernel methods. Our results provide a valuable guide toward privacy-guaranteed quantum learning on the cloud, which may benefit future studies and security-related applications.

This study aimed to investigate the psychological impact of the Turkey 2023 earthquakes on preschool-aged children and to compare them with those with other life-threatening traumas. Thirty-four preschool children who experienced earthquakes on February 6, 2023, and applied to our outpatient clinic in the following 3 months, and 37 other trauma-experienced preschool children were included in this cross-sectional study. Preschool Age Psychiatric Assessment/Post-Traumatic Stress sections were conducted. Parents were asked to complete the Pediatric Emotional Distress Scale and the Child Behavior Checklist for Ages 1.5–5 to evaluate stress-related reactions alongside psychiatric problems of children. The results showed that acute stress disorder and post-traumatic stress disorder (PTSD) were more common in the earthquake-experienced group than in the other trauma-experienced group (Fisher’s exact test, 52.9% vs. 8.1%, p < 0.001 and 38.2% vs. 8.1%, p = 0.004, respectively). Migration after the earthquake had no additional impact on trauma-related psychiatric outcomes, either ASD or PTSD (p = .153, and p = 0.106, respectively); whereas sleep problems predicted PTSD (OR = 1.26, β = 0.42, p = 0.036) in the earthquake-experienced group. Our study provides implications for understanding the psychological impact of earthquakes and risk factors for PTSD among preschool children.

The magnetostrictive response of a Terfenol-D pellet was measured via a laboratory-based X-ray diffractometer. X-ray diffraction patterns were collected from the pellet sample with and without the presence of an applied magnetic field (~30 mT) generated by placing a large magnet under the pellet. A standard reference material, Silicon 640c, was employed as an internal standard. Magnetostriction values of 323 and 227 ppm Δl/l were determined for the (104) and (110) indexed peaks, respectively, assuming a rhombohedral structure for Terfenol-D. A threshold noise level value of ~20 to 30 ppm Δl/l was suggested based on before/after measurements in the absence of the applied field. No clear evidence of domain wall rotation was detected via changes in relative intensities of diffraction peaks in the presence of the applied magnetic field.

The generation of floor plan layouts has been extensively studied in recent years, driven by the need for efficient and functional architectural designs. Despite significant advancements, existing methods often face limitations when dealing with specific input adjacency graphs or room shapes and boundary layouts. When adjacency graphs contain separating triangles, the floor plan must include rectilinear rooms (non-rectangular rooms with concave corners). From a design perspective, minimizing corners or bends in rooms is crucial for functionality and aesthetics. In this article, we present a Python-based application called G-Drawer for automatically generating floor plans with a minimum number of bends. G-Drawer takes any plane triangulated graph as an input and outputs a floor plan layout with minimum bends. It prioritizes generating a rectangular floor plan (RFP); if an RFP is not feasible, it then generates an orthogonal floor plan or an irregular floor plan. G-Drawer modifies orthogonal drawing techniques based on flow networks and applies them on the dual graph of a given PTG to generate the required floor plans. The results of this article demonstrate the efficacy of G-Drawer in creating efficient floor plans. However, in future, we need to work on generating multiple dimensioned floor plans having non-rectangular rooms as well as non-rectangular boundary. These enhancements will address both mathematical and architectural challenges, advancing the automated generation of floor plans toward more practical and versatile applications.

The aim of this paper is to analyze gender differences in the determinants of the gap between actual and desired fertility in Spain. To this aim, we exploit the 2018 Fertility Survey (EF2018) from the Spanish Statistical Institute (INE). A binary probit model shows that gender differences in the risk (and its pattern) of not reaching the desired family size are generally more pronounced amongst parents than amongst childless adults. For women, a high level of education, a potentially unstable employment situation (as an employee in the private sector) and not living with a partner increases the risk of not having the desired number of children. For men, variables related to income instability or low monthly income cause a more pronounced differential between desired and actual parenthood than amongst women, while neither educational level nor partner status – amongst those who are already fathers – significantly influences their probability of not reaching the desired number of children.

This paper explores the intersection of physical health and recovery-oriented approaches in psychosis, offering a unique perspective through autoethnography. By combining personal experience with a broader analysis of existing mental health frameworks, the paper highlights the often overlooked importance of physical health in the recovery process for individuals with psychosis. The autoethnographic narrative reveals the complex challenges posed by antipsychotic medications, including weight gain and metabolic complications, and their impact on overall well-being. It emphasizes the dual stigma of mental health challenges and weight gain, highlighting the need for a more integrated, holistic approach to mental health care. Recommendations include enhanced education for healthcare providers, personalized care plans, and a multidisciplinary approach aimed at bridging the gap between physical and mental health in psychosis recovery.

Language is known to play a crucial role in influencing how humans perceive and categorize sensory stimuli, including odors. This study investigated the impact of linguistic labeling on odor categorization among bilingual participants proficient in Chinese (L1) and English (L2). We hypothesized that L1-like linguistic labels would more robustly propel the learning of new olfactory categories compared to a condition without language, and more familiar labels would better support odor category learning. The analysis focused on comparing learning trajectories and odor categorization performance of four groups, three in which odors were paired with different sets of verbal labels and a control group that categorized odors without any verbal labeling. Following four days of intensive training, the results showed that the groups with verbal labels numerically outperformed the control group, and that the less familiar the labels sounded the more successful categorization became. However, between-group differences did not reach statistical significance. These findings, while not conclusively supporting our hypotheses, provide insights into the complex relationship between linguistic familiarity and odor category formation. The results are nested within Ad Hoc Cognition, highlighting that variations in linguistic familiarity may not induce robust enough contextual changes to differentially affect how odor categories are formed.

The initial mass function (IMF) is a construct that describes the distribution of stellar masses for a newly formed population of stars. It is a fundamental element underlying all of star and galaxy formation, and has been the subject of extensive investigation for more than 60 years. In the past few decades there has been a growing, and now substantial, body of evidence supporting the need for a variable IMF. In this light, it is crucial to investigate the IMF’s characteristics across different spatial scales and to understand the factors driving its variability. We make use of spatially resolved spectroscopy to examine the high-mass IMF slope of star-forming galaxies within the SAMI survey. By applying the Kennicutt method and stellar population synthesis models, we estimated both the spaxel-resolved (αres) and galaxy-integrated (αint) high-mass IMF slopes of these galaxies. Our findings indicate that the resolved and integrated IMF slopes exhibit a near 1:1 relationship for αint ≳ –2.7. We observe a wide range of αres distributions within galaxies. To explore the sources of this variability, we analyse the relationships between the resolved and integrated IMF slopes and both the star formation rate (SFR) and SFR surface density (ΣSFR). Our results reveal a strong correlation where flatter/steeper slopes are associated with higher/lower SFR and ΣSFR. This trend is qualitatively similar for resolved and global scales. Additionally, we identify a mass dependency in the relationship with SFR, though none was found in the relation between the resolved slope and ΣSFR. These findings suggest an scenario where the formation of high-mass stars is favoured in regions with more concentrated star formation. This may be a consequence of the reduced fragmentation of molecular clouds, which nonetheless accrete more material.

We explored whether bilingual toddlers make use of semantic and phonological overlap between their languages to learn new words. We analysed cross-sectional and longitudinal CDI data on the words understood and produced by 1.0 to 3.0-year-old bilingual toddlers with English and one additional language. Cognates were more likely to be understood and produced compared to non-cognates. Cognate effects were modulated by whether the toddler knew the translation equivalent in the other language, highlighting that young learners are sensitive to the similarities across their languages. Additionally, exploratory analyses suggest that children with smaller vocabularies rely more on translation equivalents to support the acquisition of difficult words. Children with larger vocabulary sizes exhibited no preference for translation equivalents in comprehension, and a preference for new concepts in production. The rapid acceleration of vocabulary growth in the second year of life may explain this developmental change in translation equivalent preference.

This study examines biased media portrayals of refugees, focusing on the contrast between Ukrainian and MENA refugees. It proposes a “politics-media cycle of reinforcement” where political agendas influence media narratives, and vice versa. This cycle amplifies racial bias, impacting how refugees are perceived. The research employs a comparative content analysis of Western media and political rhetoric. Findings reveal a stark difference: Ukrainians are seen as deserving victims, while MENA refugees face negative stereotypes. Interviews with media professionals and analysts support these conclusions. The study exposes racialized “othering” that marginalizes specific refugee groups. It confirms a more sympathetic portrayal of Ukrainians, likely due to political and racial factors. This research highlights the need for a more balanced and empathetic approach to all refugees.

We consider the hard-core model on a finite square grid graph with stochastic Glauber dynamics parametrized by the inverse temperature $\beta$. We investigate how the transition between its two maximum-occupancy configurations takes place in the low-temperature regime $\beta \to \infty$ in the case of periodic boundary conditions. The hard-core constraints and the grid symmetry make the structure of the critical configurations for this transition, also known as essential saddles, very rich and complex. We provide a comprehensive geometrical characterization of these configurations that together constitute a bottleneck for the Glauber dynamics in the low-temperature limit. In particular, we develop a novel isoperimetric inequality for hard-core configurations with a fixed number of particles and show how the essential saddles are characterized not only by the number of particles but also their geometry.