Search Results (1,343)

The design of sustainable hydrogel materials with tunable mechanical and thermal properties is essential for emerging applications in flexible and wearable electronics. In this study, hydrogels based on natural gums such as Guar, Tara, and Xanthan and their composites with Cellulose Citrate were developed through a mild physical crosslinking process, ensuring environmental compatibility and structural integrity. The effect of cellulose citrate pretreatment under different alkaline conditions (0.04%, 5%, and 10% NaOH) was systematically investigated using Fourier Transform Infrared Spectroscopy (FT-IR), Thermogravimetric Analysis (TGA), and dynamic rheology. Overall, the results show that the composites exhibit different properties of the hydrogel networks compared to the pure hydrogel gums, strongly depending on the alkaline treatment. In all composite hydrogels, a significant increase in the number of interacting rheological units occurs, though the strength of the interactions decreases in Guar and Tara composites, which exhibit partial structural destabilization. In contrast, Xanthan–Cellulose Citrate hydrogels display enhanced strong gel character, and crosslinking density. These improvements reflect stronger intermolecular associations and a more compact polymer network, due to the favorable H-bonding and ionic interactions among Xanthan, Cellulose and Citrate mediated by water and sodium ions. Overall, the results demonstrate that Xanthan–Cellulose Citrate systems represent a new class of eco-friendly, mechanically robust hydrogels with controllable viscoelastic and thermal responses, features highly relevant for the next generation of flexible, self-supporting, and responsive soft materials suitable for wearable and stretchable electronic devices. Full article

This paper investigates the flow of a second-grade hybrid nanofluid through a Darcy–Forchheimer porous medium under Cattaneo–Christov heat and mass flux models. The hybrid nanofluid, composed of alumina and copper nanoparticles in water, enhances thermal and mass transport, while the second-grade model captures viscoelastic effects, and the Darcy–Forchheimer medium accounts for both linear and nonlinear drag. Using similarity transformations and the spectral quasilinearisation method, the nonlinear governing equations are solved numerically and validated against benchmark results. The results show that hybrid nanoparticles significantly boost heat and mass transfer, while Cattaneo–Christov fluxes delay thermal and concentration responses, reducing the near-wall temperature and concentration. The distributions of velocity, temperature, concentration, and microorganism density are markedly affected by porosity, the Forchheimer number, the bio-convection Peclet number, and relaxation times. The results illustrate that hybrid nanoparticles significantly increase heat and mass transfer, whereas thermal and concentration relaxation factors delay energy and species diffusion, thickening the associated boundary layers. Viscoelasticity, porous medium resistance, Forchheimer drag, and bio-convection all have an influence on flow velocity and transfer rates, highlighting the subtle link between these mechanisms. These breakthroughs may be beneficial in establishing and enhancing bioreactors, microbial fuel cells, geothermal systems, and other applications that need hybrid nanofluids and non-Fourier/non-Fickian transport. Full article

There are 880 studies focused on trivalent chrome baths, and several studies suggest the formation of ${\left[Cr\left(III\right)L(H_{2}O{)}_5\right]}^{2+}$, where $L$ is an additive such as oxalate. The literature suggests that this compound decreases the energy needed in the electrodeposition process. We call this approach the inner-sphere complex hypothesis because these complexes are suggested, such as principal intermediate compounds. There are several disadvantages of this postulate, which are numbered in our study. This hypothesis was tested via Fourier transform infrared spectroscopy performed in attenuated total reflectance (ATR) mode. In addition, the potassium bis(oxalato) diaqua chromate (III) dihydrate ($K\left[Cr{\left(C_2{O}_4\right)}_2{\left(O{H}_2\right)}_2\right]·2H_{2}O$) compound was selected as a probe molecule because it contains bridging $C-O-Cr$ bonds, which are supposedly the largest number of bonds in the inner-sphere complexes in bath solutions. There is strong evidence of numerous bridging $C-O-Cr$ bonds in the solid sample; conversely, in solution, $Cr\left(III\right)$ prefers to form terminal bonds ($Cr-O$). These results suggest that the concentration of the inner-sphere complex is lower in solution. In solutions containing chromium (III) sulfate and oxalate anions, the concentrations of these complexes are much lower. Although some inner-sphere complexes are formed, their concentration does not seem to be relevant to the electrodeposition process. Otherwise, at high ionic strengths, the formation of ion pairs and hydrogen bonds between $Cr\left(III\right)$ and additives is probable. Our research highlights the importance of vibrational spectroscopy in resolving the mechanics of the trivalent chrome electrodeposition process. This is the first study reporting a band of $Cr-O$ bonds in trivalent chrome baths. Full article

Furfural (FAL), an important biomass-derived platform molecule, plays a vital role in bridging biorefineries and the production of high-value chemicals through its selective hydrogenation to furfuryl alcohol (FOL). In this work, a series of Cu-based bimetallic catalysts (Cu₅Ni_x/SiO₂) were prepared by a simple impregnation method and exhibited outstanding catalytic performance for the hydrogenation of furfural under the mild conditions. When the loading of Ni was 2 wt%, the optimal catalytic activity was obtained at 150 °C and 1 MPa H₂, achieving a furfural conversion of 97.3%. This catalyst also showed excellent stability, maintaining high activity and selectivity toward FOL after five consecutive reaction cycles. Structural characterizations using X-ray diffraction (XRD), Hydrogen temperature-programmed reduction (H₂-TPR), Fourier transform infrared spectroscopy (FT-IR), and X-ray photoelectron spectroscopy (XPS) revealed strong electronic interactions between Cu and Ni species. The introduction of Ni promoted the reduction of Ni²⁺ and improved the dispersion of Cu, which in turn increased the number of accessible active sites and facilitated the hydrogenation process. This synergistic effect between Cu and Ni provides an efficient and low-cost strategy for the selective hydrogenation of biomass-derived furfural to high-valued chemicals. Full article

This study investigated the electrochemical deposition of a novel composite polymer, 3-methylpyrrole–sodium dioctyl sulfosuccinate/3-methylthiophene (P3MPY–AOT/P3MTP), as protective coatings on OL 37 steel for anticorrosion applications. The anionic surfactant sodium dioctyl sulfosuccinate used in the deposition process enhances the protective efficiency of the coating. The coating films were characterized by CV (cyclic voltammetry), FT-IR (Fourier-transform infrared spectroscopy), and SEM (scanning electron microscopy). The anticorrosive properties of OL 37 steel coated with P3MPY-AOT/P3MTP were investigated in 1 M HCl using potentiostatic and potentiodynamic polarization, as well as electrochemical impedance spectroscopy (EIS). The coated samples exhibited a corrosion rate nearly ninefold lower than the bare substrate, with protection efficiencies exceeding 90%. Optimal performance was obtained for electrochemical deposition of P3MPY-AOT/P3MTP at potentials of 1.0, 1.2, and 1.4 V, current densities of 3 and 5 mA/cm², and a molar ratio of 5:3 for 20 min. The influence of electrochemical polymerization parameters—including applied potential, current density, scan rate, cycle number, and monomer ratio—on the anticorrosion efficiency of the coatings was systematically evaluated, allowing the identification of optimal synthesis conditions. Overall, the results confirm that P3MPY-AOT/P3MTP coatings provide highly effective corrosion protection for OL 37 steel in acidic environments. Full article

The evolution of a coherent structure in a cylindrical wake was studied through observing its energy contribution to the flow field. Analysis using the proper orthogonal decomposition on the PIV data measured at two Reynolds numbers (Re) of 3840 and 9440 was performed. The coherent structure was identified by checking the Fourier power spectrum for each temporal mode coefficient and selecting those whose peak magnitudes were greater than the smallest magnitude of the identified harmonic frequency family as the large-scale organized motions. The energy contribution by the coherent structure is significantly dependent on Re. The evolution of the energy contribution by the coherent structure exhibits a monotonously decaying trend when moving downstream. The coherent structure primarily contains the Kármán vortices in the near wake. The contribution weight of the secondary vortices gradually increases, along with the streamwise distance, except in the very upstream subregions for the case of Re = 9440. The energy contribution by the secondary vortices immediately behind the cylinder (x/d = 0.5–5.5) was 30% for Re = 9440, in comparison with <1% for Re = 3840, but decayed rapidly to the value of <10% in the downstream subranges. Full article

The interaction between the ship hull and the propeller’s rotational motion causes the propeller to operate under non-uniform inflow conditions. In reality, the ship’s effective wake constitutes a complex nonlinear superposition of multiple wave numbers. However, existing studies often neglect these multi-scale interactions. In this work, Unsteady Reynolds-Averaged Navier–Stokes (URANS) simulations with a two-scale inflow model are conducted to investigate the fluid–structure interaction of a propeller under multi-scale inflow. The model introduces large-scale and small-scale Fourier modes together with transverse perturbations, allowing systematic variation of inflow characteristics. The results reveal that large-scale modes amplify unsteady thrust fluctuations and enhance vortex fragmentation, while small-scale modes produce similar but weaker effects, mainly influencing the high-frequency components of unsteady thrust. In contrast, transverse perturbations reduce inflow non-uniformity, effectively suppress single blade thrust fluctuations, and preserve the coherent vortex structures of the wake. This study highlights the importance of multi-scale effects in the unsteady hydrodynamic characteristics of marine propellers and provides useful insights for the optimization of propeller design and energy-saving devices. Full article

Massive Multiple-Input Multiple-Output (MIMO) systems with hundreds or thousands of antenna elements are fundamental to next-generation wireless networks, promising unprecedented spectral efficiency through spatial multiplexing and beamforming. However, the computational burden of channel state information (CSI) acquisition and processing scales dramatically with array size, creating a critical bottleneck for practical deployments. While previous works demonstrated that Fast Fourier Transform (FFT)-based beamspace processing can exploit the inherent angular sparsity of wireless channels to compress CSI feedback, the digital implementation requires intensive computations that become prohibitive for ultra-large arrays. This paper presents an analog alternative using Butler matrices—passive beamforming networks that realize the Discrete Fourier Transform in hardware—combined with RF switching circuits to select only dominant angular components. We provide a comprehensive analysis of Butler matrix architectures for arrays up to 32 × 32 elements, characterizing insertion losses across different technologies (microstrip, substrate-integrated waveguide, and waveguide) and operating frequencies (10–30 GHz). The proposed system incorporates parallel power sensing with Winner-Take-All circuits for sub-microsecond beam selection, drastically reducing the number of active RF chains. Full-wave simulations and capacity evaluations at 12 and 30 GHz demonstrate that the Butler-based approach achieves comparable performance to FFT methods while offering significant advantages in power consumption and processing latency. For a 256 × 256 array, FFT computation requires 0.36 ms compared to near-instantaneous analog processing, making Butler matrices particularly attractive for real-time massive MIMO systems. These findings establish Butler matrix front-ends as a practical pathway toward scalable, energy-efficient beamspace processing in 6G networks. Full article

Background/Objectives: Fused deposition modeling (FDM) three-dimensional (3D) printing represents an emerging manufacturing platform for personalized oral dosage forms. Its success relies on developing robust drug-loaded filaments with consistent mechanical, thermal, and dissolution properties. This work aims to (i) develop and characterize ketoprofen-loaded filaments using hot-melt extrusion (HME) and (ii) utilize them to fabricate both immediate-release (IR) and sustained-release (SR) tablets via FDM 3D printing. Methods: Filaments were prepared using Kollicoat^® IR and hydroxypropyl methylcellulose (HPMC, 2600–5600 cP) as functional polymers. Sorbitol and sodium lauryl sulfate (SLS) were incorporated as plasticizer and surfactant, respectively. Filaments were evaluated for quality attributes, drug content, tensile strength, and physicochemical and surface characteristics using Scanning Electron Microscopy (SEM), Attenuated Total Reflection Fourier-transform infrared (ATR-FTIR), X-ray Diffraction (XRD), Differential Scanning Calorimetry (DSC) and Thermogravimetric Analysis (TGA). Optimized filaments were fed into an FDM 3D printer to fabricate ketoprofen tablets with varied geometries, shell numbers, and infill densities. Tablets were subjected to USP tests (weight variation, friability, hardness, disintegration, assay, content uniformity), dissolution profiling, and release kinetics modeling. Comparative dissolution studies with market Profenid^® and Bi-Profenid^® tablets were conducted. GastroPlus^® simulations were used for in vitro–in silico correlation. Results: Among the tested formulations, Kollicoat^® IR-based filaments with sorbitol and SLS (F6) demonstrated superior printability, characterized by consistent feeding, stable extrusion, and reliable formation of uniform structures for immediate-release applications. In contrast, HPMC-based filaments with sorbitol (F13) offered the most robust performance for SR formulations. Both exhibited uniform diameter, drug loading, and mechanical strength. IR tablets achieved >80% release within 30 min, while SR tablets prolonged release up to 12 h, following Higuchi and Korsmeyer–Peppas kinetics. All quality attributes complied with USP limits. Market products showed comparable dissolution, validating the approach. GastroPlus^® simulations predicted pharmacokinetic profiles consistent with reported data, supporting IVIVC. Conclusions: This integrated workflow establishes a robust strategy for producing IR and SR ketoprofen tablets from a single FDM platform. The results highlight the feasibility of point-of-care, personalized medicine using 3D printing technologies. Full article

Foot gesture recognition using a continuous-wave (CW) radar requires implementation on edge hardware with strict latency and memory budgets. Existing structured and unstructured pruning pipelines rely on iterative training–pruning–retraining cycles, increasing search costs and making them significantly time-consuming. We propose a NAS-guided bisection hybrid pruning framework on foot gesture recognition from a continuous-wave (CW) radar, which employs a weighted shared supernet encompassing both block and channel options. The method consists of three major steps. In the bisection-guided NAS structured pruning stage, the algorithm identifies the minimum number of retained blocks—or equivalently, the maximum achievable sparsity—that satisfies the target accuracy under specified FLOPs and latency constraints. Next, during the hybrid compression phase, a global L1 percentile-based unstructured pruning and channel repacking are applied to further reduce memory usage. Finally, in the low-cost decision protocol stage, each pruning decision is evaluated using short fine-tuning (1–3 epochs) and partial validation (10–30% of dataset) to avoid repeated full retraining. We further provide a unified theory for hybrid pruning—formulating a resource-aware objective, a logit-perturbation invariance bound for unstructured pruning/INT8/repacking, a Hoeffding-based bisection decision margin, and a compression (code-length) generalization bound—explaining when the compressed models match baseline accuracy while meeting edge budgets. Radar return signals are processed with a short-time Fourier transform (STFT) to generate unique time–frequency spectrograms for each gesture (kick, swing, slide, tap). The proposed pruning method achieves 20–57% reductions in floating-point operations (FLOPs) and approximately 86% reductions in parameters, while preserving equivalent recognition accuracy. Experimental results demonstrate that the pruned model maintains high gesture recognition performance with substantially lower computational cost, making it suitable for real-time deployment on edge devices. Full article

In this study, subject-independent (inter-subject), multiple-session electroencephalography (EEG) data classification was tested for loving-kindness meditation (LKM) and non-meditation. This is a novel study that extends our previous work on intra-subject, multiple-session classification. Here, two meditation techniques, LKM-Self and LKM-Other, were independently compared with non-meditation. For each mental task, five sessions of data collected from each of the twelve participants were placed in a common data pool, from which randomly selected session data were used for training and testing the machine learning algorithms. Three previously tested BCI pipelines were used. In each case, feature extraction was performed using common spatial patterns (CSPs), short-time Fourier transform (STFT), or a fusion of CSP and STFT, followed by classification using a neural network structure. This study was further divided into three cases, where two, three, or four session pairs were used to train the algorithms, and the remaining session pair was used for testing. For each individual instance, the test was repeated thirty times to generalize the results. Thus, a total of 9900 independent tests were conducted for the entire dataset. The mean classification accuracies obtained in this study were lower than those reported in our previous intra-subject classification study. For example, in LKM-Self/non-meditation classification using three session pairs with the CSP + STFT pipeline, the mean accuracy for all tests was 62.3%, with the bottom 50% at 46.0% and the top 50% at 78.3%, demonstrating variability across session selections. The corresponding intra-subject classification result for the same instance was 72.1%. For all other instances, a similar pattern was observed. Furthermore, when considering all mean accuracies obtained, in 83.3% of the instances, CSP + STFT produced better classification accuracies than CSP or STFT alone. At the same time, in 75.0% of the instances, increasing the number of training session pairs led to improved classification accuracies. This study demonstrates that the subject-independent, multiple-session EEG classification of meditation and non-meditation is feasible for specific session combinations. Further research is needed to confirm these findings across larger and more diverse participant groups. These findings provide a foundation for developing subject-independent algorithms that can guide long-term meditation practice. Full article

Achieving long-lived room-temperature phosphorescence (RTP) with high quantum efficiency is of significant interest for applications in anti-counterfeiting, flexible optoelectronic displays, and multi-level information encryption. Here, we presented a hydrogen-bond engineering strategy to enhance RTP performance by progressively increasing the number of hydrogen-bonding sites within a polyvinyl alcohol (PVA) matrix. A series of carbazole-based chromophores (Cz, ICz and 2ICz) were embedded into the PVA network, and their photophysical properties were systematically characterized using steady-state photoluminescence spectra, time-decay spectra, Fourier-transform infrared (FTIR), and Raman and X-ray photoelectron spectroscopy (XPS). Spectroscopic analysis revealed that the increased number of N-H groups significantly strengthened hydrogen-bonding interactions, effectively suppressing non-radiative decay pathways and stabilizing triplet excitons. As a result, the phosphorescence lifetime was prolonged up to 1.68 s with a quantum yield of 38.63%. Furthermore, leveraging the spectral overlap integral between the phosphorescent emission and dye absorption, efficient Förster resonance energy transfer (FRET) was realized, enabling tunable multi-color afterglow emissions. This study establishes a design strategy validated by spectroscopy for high-performance RTP materials and highlights their promising potential in advanced optical encryption and flexible photonic applications. Full article

The Laplace equation is an important partial differential equation, typically used to describe the properties of steady-state distributions or passive fields in physical phenomena. Its Cauchy problem is one of the classic, serious, ill-posed problems, characterized by the fact that minor disturbances in the data can lead to significant errors in the solution and lack stability. Secondly, the determination of the parameters of the classical Laplace equation is difficult to adapt to the requirements of complex applications. For this purpose, in this paper, the Laplace equation with uncertain parameters is defined, and the uncertainty is represented by fuzzy numbers. In the case of granular differentiability, it is transformed into a granular differential equation, proving its serious ill-posedness. To overcome the ill-posedness, the Fourier regularization method is used to stabilize the numerical solution, and the stability estimation and error analysis between the regularization solution and the exact solution are given. Finally, numerical examples are given to illustrate the effectiveness and practicability of this method. Full article

In this paper, we propose a novel low-power implementation of the radix-2² Fast Fourier Transform (FFT) processor that exploits optimized multiplications and low-voltage memory buffers. The FFT computation requires complex products between input samples and precomputed coefficients, known as twiddle factors, as well as a large number of memory elements to store intermediate signals. To reduce power consumption, we bypass multiplications when twiddle factors are equal to zero or one. Furthermore, we introduce a fixed-width technique that lowers multiplier complexity for non-trivial coefficients by pruning the least significant columns of the partial product matrix and discarding the most significant partial products with low activation probability. To further minimize power consumption, we lower the supply voltage of memory buffers, creating two power domains in the design. Post-synthesis analysis in 28 nm technology shows that the proposed FFT achieves superior SNR and MSE compared to existing implementations, with reductions of 33% in power consumption and 30% in the power-delay product. In an OFDM receiver, the design also achieves optimal bit error rate performance under various levels of channel noise. Full article

Cavalieri estimation is a widely used technique in stereology (applied geometric sampling) for approximating the volume of a solid by sampling cross-sectional areas along a fixed axis. Classical theory shows that, under systematic equidistant sampling (the well-known Cavalieri estimator), the variance decay depends on the smoothness of the area function, which is essentially measured by the number of continuous derivatives. This paper focuses on the natural assumptions under which the theory holds. We first obtain sharp and explicit variance rates: when the Fourier decay is of order $s>1/2$, the variance of the Cavalieri estimator decays as $t^{2s}$ with a constant independent of t. Building on this, we show that the smoothness condition expressed in terms of the algebraic Fourier decay subsumes both integer- and fractional-order frameworks used to date. Finally, we establish a matching converse showing that, under general assumptions, no broader smoothness framework extends the theory; that is, any algebraic variance decay implies the corresponding Fourier decay. Full article