İzmir Institute of Technology (Turkish: İzmir Yüksek Teknoloji Enstitüsü, commonly referred to as İYTE) is a public research university in İzmir, Turkey. İYTE maintains a strong emphasis on the natural sciences and engineering and is the only institute of its kind in Turkey with a special focus on scientific research. İzmir Institute of Technology is often cited among Turkey's top universities. The medium of instruction in all the departments of İYTE is English.
Recent advances in Kolmogorov–Arnold Networks (KANs) have shown strong potential for functional representation learning; however, existing formulations remain limited in their ability to provide explicit geometric interpretability, curvature control, and deformation-aware adaptation for biomedical image analysis. This paper introduces q-FunKAN, a geometry-aware Functional Kolmogorov–Arnold Network that integrates learnable Lupaş q-Bézier inner functions and q-Hermite spectral parameterizations within a unified geometric–spectral framework for biomedical image enhancement and segmentation. The central novelty of the proposed model lies in embedding a learnable deformation parameter q into the KAN functional space, enabling curvature-adaptive modulation of local anatomical structures while preserving global smoothness through spectral regularization.The proposed framework combines three complementary mechanisms: Bézier-based control-point parameterization for interpretable local deformation, q-Hermite spectral expansion for stable global representation, and topology-preserving deformation regularization for anatomically plausible enhancement and segmentation. This design allows q-FunKAN to explicitly balance local boundary precision and global structural consistency, providing a transparent alternative to highly parameterized convolutional and transformer-based models.Extensive experiments on five benchmark MRI datasets, including BRATS 2021, CHAOS, fastMRI, IXI, and a controlled synthetic phantom dataset, demonstrate the effectiveness of the proposed framework. Compared with strong convolutional, transformer-based, restoration-oriented, and KAN-based baselines, q-FunKAN achieves consistent improvements in image fidelity, perceptual quality, and segmentation accuracy, including gains of up to (+1.3) dB PSNR, (+1.0%) Dice, and (-0.004) LPIPS over leading competing models. Ablation studies further confirm that learnable q-adaptivity, Bézier geometric modeling, Hermite spectral regularization, and Jacobian-based topology preservation make complementary contributions to performance and stability. Qualitative analyses show sharper anatomical boundaries, reduced artifacts, and interpretable q-heatmaps aligned with curvature-sensitive regions.By bridging q-calculus, geometric approximation theory, and functional neural representation learning, q-FunKAN establishes a mathematically grounded, interpretable, and geometry-aware framework for biomedical image enhancement and segmentation.
In this paper, we study the well-posedness and boundary stabilization of the initial-boundary value problem for the complex Ginzburg-Landau (CGL) equation on a finite interval. First, we establish a local well-posedness theory for the open loop model in L^2-based fractional Sobolev spaces in the case of Dirichlet-Neumann type inhomogeneous mixed boundary conditions. This local well-posedness result is based on linear estimates derived by using the weak solution formula obtained via the unified transform (also known as the Fokas method). Next, we study the global well-posedness properties of the open loop model in presence of inhomogeneous boundary conditions. Then, we turn our attention to the rapid boundary feedback stabilization problem and design a nonlocal controller which uses a finite number of Fourier modes of the state of solution. This design relies on the fact that solutions of the CGL equation can be separated into a slow, finite-dimensional component and a rapidly decaying tail, with the former primarily governing long-term behavior. We determine the necessary number of modes required to stabilize the system at a specified rate. Additionally, we identify the minimum number of modes that ensure stabilization at an unspecified decay rate. These theoretical results are validated by numerical simulations. The spatiotemporal estimates established in the first part of the paper are also employed to obtain local solutions of the controlled system. The existence of global energy solutions follows from stabilization estimates, while uniqueness follows from the uniqueness of an associated initial-boundary value problem with homogeneous boundary conditions whose solutions are in correspondence with the solutions of the original system through a bounded invertible Volterra-type integral transform on Sobolev spaces.
BACKGROUND:Cell migration is a fundamental biological process essential for embryonic development and hematopoiesis. In a shRNA screen, we identified the TRAM-LAG1-CLN8 domain-containing transmembrane protein TMEM56 as a previously uncharacterized regulator of stromal cell-derived factor 1 (SDF-1)-mediated cell migration. This study investigates the molecular mechanisms underlying TMEM56 function. RESULTS:TMEM56 is expressed in both murine embryonic and adult tissues, with enrichment in hematopoietic stem and erythroid progenitor cells. Lipidomic analysis reveals that TMEM56 modulates ceramide metabolism, particularly affecting levels of hexosylated ceramides. Co-immunoprecipitation assays indicate that TMEM56 physically interacts with ceramide synthase 2 (CerS2), suggesting a role in lipid signaling pathways. CONCLUSION:Our findings identify TMEM56 as a key regulator of cell migration, linking lipid metabolism with hematopoietic and developmental processes. These results provide novel insights into the molecular mechanisms governing migration.
Groundwater serves as the primary source of freshwater in rapidly growing semi-arid urban settlements. Climate change and intensive exploitation pose serious threats to the sustainability of groundwater resources in the future. The purpose of this paper is to analyze the temporal-spatial dynamics of groundwater levels and drought characteristics in the area of Peshawar (Pakistan). A monthly time series from 2006 to 2023 was used to assess long-term trends in groundwater levels and their relationship to drought events using the Mann-Kendall test, Sen’s slope estimation, and the Innovative Trend Analysis method. Climatic factors influencing water dynamics were identified using the Standardized Precipitation Index (SPI) and the Standardized Precipitation-Evapotranspiration Index (SPEI) at three time scales (6, 12, and 24 months). Findings: The results indicate strong negative trends in groundwater levels (statistically significant, p < 0.05), with a total decline of 20.11–56.49 m. Sen’s slope estimates range between 1.19 and 2.81 m per year. The strongest declines in groundwater levels are observed in the central and western zones of the region. On the other hand, weak trends for both indices (SPI/SPEI) characterize the studied period. Both SPI and SPEI indicate occasional droughts, which could not entirely explain the observed decline in groundwater levels. Lag-correlation analysis showed moderate sensitivity of groundwater to precipitation deficits, with a 4-month lag for SPI-12 and up to 11 months for SPEI-12. While 24-month periods were considered, the strongest correlation with groundwater anomalies occurred at the 12-month accumulation period. SPEI-24 showed higher dry condition occurrences than SPI-24, but the explanatory power of both remained insufficient to fully account for the magnitude of groundwater depletion. Finally, land-use analysis demonstrates a high prevalence of urban areas (covering over 69 Groundwater depletion is a big problem in many urban regions. Statistically significant groundwater depletion (1.19–2.81 m yr⁻¹) was observed across all urban management zones from 2006 to 2023. Weak long-term SPI and SPEI trends indicate limited climatic control over persistent aquifer decline. Rapid urban expansion and sustained groundwater abstraction were identified as the primary drivers of long-term depletion.
This study investigates the incorporation of recycled GG25 gray cast iron machining waste as a sustainable and cost-efficient partial substitute for conventional steel fibers in composite friction materials engineered for aircraft clutch systems. Five composite formulations were manufactured using powder metallurgy by systematically varying the ratios of steel fibers and GG25 particulates (<500 µm) from 0 to 20 wt.
