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Riccati equations and LQ-optimal control for a class of hyperbolic PDEs
No full textWe derive an explicit solution to the operator Riccati equation solving the Linear–Quadratic (LQ) optimal control problem for a class of boundary controlled hyperbolic partial differential equations (PDEs) defined on a one-dimensional spatial domain. Different descriptions of the system are used to obtain different representations of the operator Riccati equation. By means of an example, we illustrate the importance of considering an extended operator Riccati equation to solve the LQ-optimal control problem for our class of systems.</p
Dialogic Learning in Child-Robot Interaction:A Hybrid Approach to Personalized Educational Content Generation
Get PDFDialogic learning fosters motivation and deeper understanding in education through purposeful and structured dialogues. Foundational models offer a transformative potential for child-robot interactions, enabling the design of personalized, engaging, and scalable interactions. However, their integration into educational contexts presents challenges in terms of ensuring age-appropriate and safe content and alignment with pedagogical goals. We introduce a hybrid approach to designing personalized educational dialogues in child-robot interactions. By combining rule-based systems with LLMs for selective offline content generation and human validation, the framework ensures educational quality and developmental appropriateness. We illustrate this approach through a project aimed at enhancing reading motivation, in which a robot facilitated book-related dialogues.</p
Efficient Ranking, Order Statistics, and Sorting under CKKS
Get PDFFully Homomorphic Encryption (FHE) enables operations on encrypted data, making it extremely useful for privacy-preserving applications, especially in cloud computing environments. In such contexts, operations like ranking, order statistics, and sorting are fundamental functionalities often required for database queries or as building blocks of larger protocols. However, the high computational overhead and limited native operations of FHE pose significant challenges for an efficient implementation of these tasks. These challenges are exacerbated by the fact that all these functionalities are based on comparing elements, which is a severely expensive operation under encryption. Previous solutions have typically based their designs on swap-based techniques, where two elements are conditionally swapped based on the results of their comparison. These methods aim to reduce the primary computational bottleneck: the comparison depth, which is the number of non-parallelizable homomorphic comparisons in the algorithm. The current state of the art solutions for sorting by Lu et al. (IEEE S&P’21) and Hong et al. (IEEE TIFS 2021), for instance, achieve a comparison depth of log 2 N and klog 2 k N, respectively. In this paper, we address the challenge of reducing the comparison depth by shifting away from the swap-based paradigm. We present solutions for ranking, order statistics, and sorting, that achieve a comparison depth of up to 2 (constant), making our approach highly parallelizable and suitable for hardware acceleration. Leveraging the SIMD capabilities of the CKKS FHE scheme, our approach re-encodes the input vector under encryption to allow for simultaneous comparisons of all elements with each other. The homomorphic re-encoding incurs a minimal computational overhead of O(log N) rotations. Experimental results show that our approach ranks a 128-element vector in approximately 5.76s, computes its argmin/argmax in 12.83s, and sorts it in 78.64s.</p
Radiative local density of states in three-dimensional photonic band-gap crystals to interpret time-resolved emission
Get PDFWe investigate the spontaneous emission of light in three-dimensional (3D) photonic crystals through theoretical calculations and simulations. It is well known that spontaneous emission depends on the radiative local density of states (RLDOS). Photonic band-gap crystals radically modulate the RLDOS, thereby controlling spontaneous emission. We compare two different methods to calculate the RLDOS: the plane-wave expansion (PWE) method and the finite-difference time-domain (FDTD) method. The PWE method directly calculates the RLDOS of an infinite photonic crystal, whereas the FDTD method simulates the RLDOS through the power emitted by a dipole in a finite photonic crystal. We demonstrate that the methods yield similar frequency-dependent trends in the RLDOS, with relative differences of less than 12% that originate from the different boundary conditions. We employ the plane-wave expansion method to compute distributions of emission rates that are relevant to many optical experiments where quantum emitters are distributed within a crystal. Such distributions of emission rates enable us to compute and directly interpret the time-resolved decay as observed in experiments. We expect that our results promote the RLDOS to the realm of optical design and products
Reproducibility and replication of research results:A special issue for RRRR 2022
Get PDFWhile a reproducible research result can be independently confirmed by third parties using artifacts provided by the original authors, replicating a research result means to independently obtain it using new measurements, data, or implementations. Various initiatives like artifact evaluations and tool competitions support reproducibility, and replication studies are slowly gaining recognition. The RRRR workshop on reproducibility and replication of research results seeks to improve the knowledge transfer between the many reproducibility initiatives, and to provide a venue to formally publish replication studies, recognising their immense benefit to the scientific community and the hard work involved. This special issue of the International Journal on Software Tools for Technology Transfer gathers four articles originating from the 2022 edition of RRRR, on topics ranging from the concept of replicable theory to tools for scalable software benchmarking.</p
A personalized approach to classify the degree of liver insulin resistance in children with obesity
Get PDFAims: This study aimed to develop a novel approach for quantifying liver insulin resistance (LIR) in children with obesity using personalized glucose and insulin responses from oral glucose tolerance tests (OGTTs).Materials and Methods: A total of 242 OGTTs were performed on paediatric patients with obesity. Blood glucose and insulin levels were determined at six timepoints. Measurements of liver enzymes, plasma lipids, blood pressure and height and weight were obtained concurrently. Associations of LIR with other clinical parameters of obesity and type 2 diabetes were compared between the conventional and novel LIR quantification.Results: The study revealed heterogeneous OGTT response dynamics among the population, with substantial variability in peak levels of glucose and insulin. The novel approach to quantify LIR showed stronger associations between glucose and insulin responses and clinical markers of obesity and type 2 diabetes, compared to the conventional method.Conclusions: The novel LIR quantification method provides a more precise assessment of insulin resistance in paediatric obesity management compared to traditional methods. By considering individual glucose and insulin dynamics, this approach enhances risk stratification and treatment planning tailored to each patient's OGTT response curve.</p
Modeling and characterization of thermo-viscoelastic behavior of rubber compounds
Get PDFViscoelasticity as a unique property of rubber materials, has a significant influence on the product performance, for example, on the wet grip and the rolling resistance of tires. The viscoelasticity of rubber materials has been described by mathematical models and characterized by experimental approaches. In many existing models, the viscous behavior is usually assumed to be independent or linearly dependent on temperature. This simplification leads to inaccurate predictions under real operating conditions, especially when temperature-sensitive ingredients like resins are added to rubber compounds. Moreover, such models are rarely validated against experimental results. This work addresses these limitations by developing a modelling and testing framework for filled rubber compounds that consistently integrates mathematical modeling, parameter identification, and experimental validation. Firstly, a thermo-viscoelastic model that explicitly captures the nonlinear temperature dependence of viscosity was developed Then, the parameters of the developed model were identified by fitting the model to the experimental data obtained from the Dynamic Mechanical Analysis (DMA) measurements, where the constrained optimization problem was solved. To apply the material model in structure analysis, the developed model was implemented in the Finite Element Method (FEM) scheme. Finally, the developed material model was successfully validated by comparing the model prediction results with the experiments including the Temperature Scanning Stress Relaxation (TSSR) measurements. With the thermo-viscoelasticity model, the dynamic properties of the rubber compound at higher frequencies can be predicted without master curve creation, which offers a faster and more physically accurate route to assess dynamic properties such as tire wet grip.</p
Approximate deconvolution and velocity estimation modeling of decaying Burgers turbulence
Get PDFThe paper presents Burgers turbulence simulated using Large Eddy Simulations (LES). Two types of subfilter models are applied: Approximate Deconvolution Model (ADM) and Velocity Estimation Concept (VEC). In the ADM approach, two different filter types were applied indicating the influence of the filter on the deconvolution convergence via comparison with a direct inversion method. In both approaches the ADM and VEC the deconvolved and estimated fields are shown. It is stressed that ADM introduces flow structures characterized by subfilter scales down to the mesh cut-off length scale. In the case of the VEC only the kinematic step was applied for the subgrid velocity field estimation. We observe that both ADM and VEC provide predictions that are closely related to direct numerical simulations (DNS) provided the spatial resolution is adequate. Moreover, results based on the top-hat filter as the basis for LES are in general agreement with results obtained on the basis of a sixth-order Padé filter. The VEC model provides further opportunities to include much finer scales that evolve under simplified approximate dynamics, thereby enabling additional fine-tuning of the predictions of higher-order statistical quantities.</p
Which ASDAS cut-off corresponds best to treatment intensification in patients with axial spondyloarthritis in daily practice? A prospective study from a clinical registry
No full textTo investigate which Axial Spondyloarthritis Disease Activity Score (ASDAS) cut-off corresponds best with treatment intensification (TI) in daily practice in patients with axial spondyloarthritis (axSpA). Patients from the prospective SpA-Net registry with axSpA and ≥ 1 ASDAS measurement in 2016–2022 were included. TI was defined as (1) increasing dose/frequency of current drug, (2) switching drug(s) or (3) adding drug(s); all due to inefficacy of current treatment and only considering anti-inflammatory drugs. Patients could contribute multiple observations. Receiver operating characteristic analyses assessed the ability of ASDAS to discriminate between TI/non-TI (Area Under the Curve [AUC]), and identify the ASDAS cut-off that discriminated best. In a random subsample, the rationale for treatment decisions was retrospectively analyzed using patient records. In total, 350 patients with 2,191 ASDAS measurements (243 TI events, 11.1%) were included. Median follow-up was 2.8 years. At inclusion, mean age was 48.2 (SD 14.3) years, 152 (43.4%) were female, and mean ASDAS was 2.4 (SD 1.0). The mean ASDAS was 3.0 (SD 1.0) at TI versus 2.3 (SD 1.0) at non-TI timepoints. TI occurred infrequently at ASDAS ≥ 2.1 observations (203/1,266 [16.0%]). Using all observations, the AUC was 0.71 (95%CI 0.68–0.74) with an optimal ASDAS cut-off of 2.7 (sensitivity 69%, specificity 66%). When stratifying by drug exposure or extra-musculoskeletal manifestations, results were similar (ASDAS cut-off 2.6–3.2). The patient record analysis supported the findings. In daily practice, TI is associated with a higher ASDAS cut-off than the recommended one (≥ 2.1). Rheumatologists consider factors beyond disease activity when making treatment decisions.</p
Wavefront Shaping with varying degrees of freedom
No full textOptical WaveFront Shaping (WFS) uses the physical feature that whereas light scattering is complex, it is a linear process, thus deterministic. The incident wavefront is controlled to focus light through a scattering sample, by spatially dividing an incoming wavefront and modulating the resulting segments with Spatial Light Modulators (SLMs) or Digital Micromirror Devices (DMDs) paired with a holography system.The main criterion for such a process is the enhancement of the intensity at the target, defined as the ratio of the optimized intensity at the target, and the average intensity at the target for many realizations of the scattering sample. We focus on the effect of restricting the degrees of freedom of the phase modulating devices on the optimization performance. By turning off certain segments, which contribute very little to the optimization, it is possible to greatly shorten optimizations without a significant loss in enhancement. By shrinking the active area of segments, issues with holography systems occur, as small segments and phase transitions negatively affect performance.Our results lead to better choices regarding the areas of interest and limits of such optimizations to improve speed and efficiency, which are relevant for WFS applications