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Constrained paths: legal status and mobility governance of Syrian refugees after the 2023 earthquakes
No full textThis article examines how legal status shapes the post-disaster mobility of Syrian refugees in Turkey following the February 2023 earthquakes. While it is well established that disasters often exacerbate the vulnerabilities of displaced populations, less attention has been paid to how legal and bureaucratic regimes structure not only who can move, but also where they are permitted to go. Drawing on a review of literature on immigrants and refugees in disaster contexts and post-disaster mobility, as well as fieldwork based on in-depth interviews, we argue that legal status operates as a form of governance that constrains both mobility and its directionality. Although Syrians under Temporary Protection in Turkey possess legal status, their rights to relocate or access services are highly conditional and spatially circumscribed. The earthquake momentarily disrupted—but did not dismantle—these restrictions. The state selectively managed refugee movement, granting temporary permissions while blocking durable relocation to cities like Istanbul. Often seen as a space of refuge, Istanbul has increasingly become a site of exclusion. As such, the paper contributes to debates on legal status and mobility governance in disaster contexts
Mapping allergy research: a comprehensive visual and bibliometric analysis of socioeconomic and quality-of-life dimensions
Get PDFBackground: The increasing prevalence of allergic diseases has increased attention to their socioeconomic impact and health-related quality of life. Yet, research in this domain remains dispersed and underrepresented across disciplines and regions. Objective: We sought to analyze allergy research related to socioeconomic impacts and quality of life from 1994 to 2025 and identifying key trends, collaborations, and emerging themes. Methods: A total of 913 documents from 412 sources were retrieved from the Web of Science and Scopus databases using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow diagram. Bibliometric tools, including VOSviewer and the Bibliometrix R package, were used to assess publication growth, authorship patterns, collaboration networks, and thematic trends. Results: The annual growth rate was 5.68%, with 6229 authors and an international coauthorship rate of 24.42%, reflecting robust global collaboration. Keyword trends revealed a shift from asthma to food allergies and patient-centered themes such as quality of life, treatment satisfaction, and digital health. Thematic evolution showed increasing interest in psychosocial care, chronic allergy conditions, and technological interventions. Although the United States and the United Kingdom remain leading contributors, research from Asia and non–English-speaking countries increased following the inclusion of non-English literature. Conclusions: Allergy research is evolving toward a more holistic, interdisciplinary, and globally engaged model. Future efforts should focus on bridging regional disparities, incorporating underrepresented disciplines, and promoting inclusive, patient-centered research
Read and imagine: visual imagery experience evoked by first versus second language
No full textThis research examined visual imagery evoked during reading in relation to language. Following the previous reports that bilinguals experience less vivid imagery in their second language (L2) than first language (L1), we studied how visual imagery is affected by the language in use, characteristics of text, and readers’ individual differences. In L1 and L2, 382 bilinguals read object texts describing pictorial properties of objects such as color and shape, spatial texts describing spatial properties such as spatial relations and locations, and excerpts from novels. They rated imagery vividness after each segment and the whole text, and rated the specific imagery characteristics (e.g., color, spatial relations). Regardless of the types of text or the timing of rating, the vividness of imagery was higher in L1 than in L2. However, English proficiency also predicted vividness in L2. Further, vividness in the object and spatial trials were predicted by the individual’s object and spatial imagery skills. The effect of language on imagery depends on the text nature and difficulty, when and how vividness is measured, and individual differences
Damage diagnosis of plates and shells through modal parameters reconstruction using inverse finite-element method
No full textIn this study, a new modal-based structural health monitoring (SHM) approach is proposed based on the inverse finite-element method (iFEM) to perform damage diagnosis of the plate and shell structures based on full-field modal parameters reconstructed from discrete sensor data. The iFEM formulation can effectively solve a shape sensing or deformation reconstruction problem, where changing displacements of the structure are predicted by minimizing a variational least squares error function of analytical and experimental discrete strains with respect to unknown displacements. Such a solution provides the time-domain response of the structures, which may be solely not enough to extract the dynamical properties of the structure for underlying the unhealthy conditions. To address this important gap, the iFEM is enhanced by processing the full-field displacement solution with fast Fourier transformation, enabling mechanical parameters to switch from time to frequency domain. This posterior step, named iFEM Modal Reconstruction (iFEM-MoRe), can recover full-field dynamical characteristics from the response discrete Fourier transformation of a structure for the investigation of unhealthy structural conditions and damage identification. In this regard, iFEM-MoRe allows the utilization of the entire time/frequency-domain response of structures for correlating modal/dynamical characteristics with structural anomalies. To verify the capability of the approach, intact and damaged cases of benchmark problems are solved. According to the results, it is demonstrated that iFEM-MoRe can predict highly precise natural frequencies just from discrete sensor data without loading/material information. Also, it is revealed that iFEM-MoRe can highly accurately reconstruct full-field mode shapes and diagnose damaged conditions by pinpointing alternated dynamical characteristics of structures as compared to intact parameters. Overall, the presented approach can serve as a complementary toolbox for vibration and/or statistical time series SHM methods to understand full-field modal characteristics of damaged cases just from a network of sensors
Shape memory PLA/TPU blend using high-speed thermo-kinetic mixing
No full textIn this study, a thorough examination of the chemical, thermal, and mechanical characteristics, as well as shape memory behavior at low temperatures, of blends consisting of polylactic acid (PLA) and polyurethane (TPU) is conducted. The research involves the preparation of PLA/TPU mixtures with varying concentrations of TPU using a high-speed thermo-kinetic mixing approach. Chemical, morphological, and thermal analyses were conducted on pure PLA, TPU, and PLA/TPU mixtures by using Fourier Transform Infrared (FTIR), X-ray diffraction pattern spectroscopy (XRD), scanning electron microscopy (SEM), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), and dynamic mechanical analysis (DMA). Mechanical properties were assessed through tensile and three-point bending tests. The achievement of a uniform mixture is confirmed through SEM images, reduction in the glass transition temperature according to DSC and DMA, and an improvement in mechanical properties compared to results documented in the literature, implying a more effective mixing method for the compounds. To assess the practical applicability of this blend, an investigation into the shape memory properties of the mixture when deformed at low temperatures, i.e., cold programming) is carried out. Gray relational analysis (GRA) is employed to identify the optimal TPU content for the mixture, considering both mechanical and shape memory properties. The results indicate that a mixture with a 20% volume fraction of TPU exhibits mechanical properties comparable to those of pure PLA, along with sufficient flexibility at room temperature and notable shape recovery properties
Chromatographic analysis and pKa evaluation of active pharmaceutical ingredients in anti-metastatic breast cancer: green vs. conventional RPLC
No full textThis study aimed to determine the chromatographic retention and dissociation/protonation constant (pKa) values of lapatinib and tamoxifen, key drugs used in metastatic breast cancer treatment, at 37°C using both conventional and green high-performance liquid chromatography (HPLC) methods. Qualitative analysis was conducted on an XTerra C18 column (250 ×4.6 mm I.D., 5 μm particle size) at a flow rate of 1 mL/min. Hydroorganic mixtures with 45 %, 50 %, 55 %, and 60 % (v/v) organic modifiers were used to evaluate the retention times of the compounds. The compatibility of pKa values pKass of the compounds in water-organic solvent mixtures obtained from these studies, which were carried out without any significant change in liquid chromatography performance, with the values obtained by the conventional method is remarkable. The pKass values determined in this study were correlated with the macroscopic parameters of acetonitrile, methanol, ethanol and the pKa (pKaww)values of lapatinib and tamoxifen in water were calculated. The pKaww values calculated from these studies are compatible with each other and with the literature values. The environmental impact of the study, which was carried out using the green method and the conventional RPLC method, was evaluated using the Green Solvent Selection Tool (GSST), Green Analytical Procedures Index (GAPI), and Analytical Greenness Metric Approach (AGREE)
Investigating wire electric-discharge machining (WEDM) parameters for improved machining of D2 steel: a multi-objective optimization study
No full textWire Electric-Discharge Machining (WEDM) represents a non-traditional approach to metal cutting, providing the advantage of precision manufacturing over conventional methods. In recent years, the metal machining industry has witnessed numerous benefits in terms of high speed and accuracy through the utilization of WEDM in both additive and subtractive manufacturing processes. This research focuses on studying the process parameters and their impact on surface roughness, energy consumption, kerf width, and material removal rates in Wire Electric-Discharge Machining of D2 steel. The Taguchi approach to experimental design (L16) was employed to conduct cutting experiments at varying levels of ON Time, OFF Time, Servo Voltage, and Wire Tension. Experimental results were optimized using ANOVA and Grey Relational Analysis to refine the process inputs and achieve performance measures that minimize surface roughness, power consumption, and kerf width while maximizing material removal rate. Statistical analysis revealed that ON Time is the most significant factor (73%) affecting both individual and multiple responses. The optimized model indicates that significant improvements can be simultaneously achieved in all response parameters by selecting the optimal combination of parameters. This not only enhances the part quality but contributes positively towards process sustainability and productivity
Analyzing stiffness variations in 3D woven composites: a multi-instrumental study on Glass/Kevlar hybridization effects under tensile and shear loads
No full textThis study focuses on exploring the influence of glass/Kevlar hybridization on the tensile and shear properties of 3D woven composites. The study delves into the behavior of two distinct hybridization scales, inter-ply and intra-tow hybridizations at the outer layers of the 3D woven composites, and compares them with a full-Kevlar configuration while maintaining consistent fabric architecture across all three configurations. The hybridization process for Kevlar 3D woven composites is conducted in the weft direction. Tensile properties are systematically examined along both the warp and weft directions to comprehensively assess the effect of hybridization. To gain a thorough understanding of stiffness changes during loading, all tensile tests are monitored using digital image correlation and acoustic emission analysis techniques. Furthermore, the study investigates the influence of various hybridization techniques on the shear properties and behavior of 3D woven composites. The analysis of shear stiffness variation in all composite configurations is conducted through the utilization of full-field strain distribution obtained from digital image correlation. The tensile test results indicate that hybridization with glass positively influences stiffness recovery along the hybridization direction, whereas the baseline configuration performs better in the perpendicular to the hybridization direction. On the other hand, the shear test results reveal that, although the baseline configuration exhibits a lower shear modulus compared to its hybrid counterparts, it experiences less loss in shear stiffness
The German economy in Trump's trade war
Get PDFAt the start of Trump’s second term as US President, Germany and the EU are facing a number of new challenges, from punitive tariffs to increased defense spending. These new challenges have precipitated several questions. Namely, what impact will Trump’s trade policy have on the German economy, and how will Berlin deal with trade policy challenges together with Brussels in the coming years? This article will try to find answers to these questions
DiFuseR: a distributed sketch-based influence maximization algorithm for GPUs
No full textInfluence maximization (IM) aims to find a given number of “seed" vertices that can effectively maximize the expected spread under a given diffusion model. Due to the NP-hardness of finding an optimal seed set, approximation algorithms are often used for IM. However, these algorithms require a large number of simulations to find good seed sets. In this work, we propose DiFuseR, a blazing-fast, high-quality IM algorithm that can run on multiple GPUs in a distributed setting. DiFuseR is designed to increase GPU utilization, reduce internode communication, and minimize overlapping data/computation among the nodes. Based on the experiments with various graphs, containing some of the largest networks available, and diffusion settings, the proposed approach is found to be 3.2× and 12× faster on average on a single GPU and 8 GPUs, respectively. It can achieve up to 8× and 233.7× speedup on the same hardware settings. Furthermore, thanks to its smart load-balancing mechanism, on 8 GPUs, it is on average 5.6× faster compared to its single-GPU performance