Search Results (225)

The chlorophyll molecule is considered a low-cost material, easy to synthesize, and easily extracted from plant leaves. It exhibits high chemical stability, structural flexibility, and high absorbance ability at the visible range of electromagnetic radiation. In this work, the geometrical, electronic, and optical properties of pure, dissolved, and doped chlorophyll (C1) natural organic dye were computed by density functional theory (DFT) and time-dependent density functional theory (TD-DFT). The solvents considered include water (H₂O), acetone (C₂H₆O), dichloromethane (CH₂Cl₂), chloroform (CH₃Cl), and dimethyl-sulfoxide (DMSO) (C₂H₆OS). The solar photovoltaic parameters, such as light-harvesting efficiency (LHE), oscillation strength (f), free energy of electron injection (${\Delta \mathrm{G}}_{\mathrm{I}\mathrm{n}\mathrm{j}.}$) and regeneration (${\Delta \mathrm{G}}_{\mathrm{R}\mathrm{e}\mathrm{g}.}$), open-circuit voltaic (V_OC), and efficiency ($\eta$), were also investigated. The evaluated energy gap slightly shifted from 1.920 eV to 1.980 eV based on the solvent polarity, while the UV-Visible absorption spectrum red-shifted from 422.3 nm to 439.8 nm, improving the overall efficiency up to 21.5% in DMSO solvent. The (LHE) and (${\Delta \mathrm{G}}_{\mathrm{I}\mathrm{n}\mathrm{j}.}$) properties regarding Cl molecules improved up to 69.1% and −1.384 eV when dissolved in chloroform and DMSO solvents, respectively. Doping C1 molecule via metal transition atoms such as zinc (Zn), nickel (Ni) and copper (Cu) further modified the optical and photovoltaic performance. Doped C1 molecule via Cu atom shows the best photonic results, including the highest open-circuit voltage (V_oc) and conversion efficiency ($\mathrm{Ƞ}$), while the Ni-doped C1 dye displays the longest lifetime, 1.699 µs, and the highest electronic coupling constant, 1.975 eV; thus, it has the superior photovoltaic performance. These results demonstrate that both solvents and transition metal atom modification significantly improve C1 performance, making metal-doped C1 a promising low-cost and eco-friendly sensitizer for dye-sensitized solar cells (DSSCs). Full article

Precise and smooth actuation is a central requirement in surgical robotics, where small tracking errors or oscillations can directly affect task quality and safety. This paper studies the control of an induction-motor-driven surgical joint using a sliding-mode strategy enhanced by fractional-order operators and implemented within a DTC–SVM structure. The motivation is to improve motion smoothness and disturbance rejection without sacrificing the fast dynamic response offered by direct torque control. A dynamic model of the actuator is developed by combining the electrical equations of the induction motor with the mechanical dynamics of a robotic joint, including inertia, viscous friction, gravity-induced torque, and Coulomb friction. Fractional-order sliding surfaces are introduced for both position and flux regulation, and the closed-loop stability is examined through Lyapunov-based arguments. Simulation results show accurate trajectory tracking with limited overshoot and smooth transient responses. The motor speed remains well regulated, while stator flux and currents stay within admissible bounds. The electromagnetic torque adapts to load variations with reduced ripple, and the rotor pulsation remains bounded. Within the limits of numerical evaluation, these results indicate that the proposed fractional-order sliding-mode DTC–SVM scheme is suitable for precision-oriented surgical robotic actuation. Full article

This study develops and validates the Saharan Dust Flux and Transport Index (SDFTI) using a 22-year dataset (2003–2024) of dust-related and dynamical variables across the Mediterranean. The index integrates six components (surface-particulate matter, satellite-derived desert-dust optical depth, free-tropospheric dust mass, transport score, North-Atlantic Oscillation and Oceanic Niño Indices) combined through a physically calibrated weighting scheme. To assess the stability of the formulation, three alternative variants are constructed (dust-enhanced, dynamics-enhanced, and equal-weight) and evaluated across four Mediterranean sub-regions using seasonal means, inter-annual anomalies, component correlations, and extreme-event detection. The results show that the SDFTI is highly robust over the full 2003–2024 period. Across all regions, the calibrated variants reproduce nearly identical seasonal cycles (e.g., spring–summer peaks of +0.53 to +0.58 in Western Mediterranean), identify the same dusty and non-dusty years (2008–2012 minima, 2021–2022 maxima), and capture the same major dust outbreaks (e.g., March 2022, June 2021). SDFTI consistently provides the most balanced representation of dust-mass loading and transport dynamics, while the equal-weight variant diverges as expected due to its lack of physical calibration. Overall, the SDFTI offers a stable and regionally coherent measure of Saharan dust transport. The methodological framework (variable selection, normalisation, weighting, and sensitivity testing) is general and can be adapted to other dust-affected regions worldwide. Full article

Regional flood frequency analysis (RFFA) is a cornerstone for estimating design floods at ungauged or data-scarce sites by pooling information within hydrologically homogeneous regions. This study proposes and evaluates a hybrid RFFA framework that integrates the Index-Flood (IF) technique with a bivariate logistic extreme-value model whose marginal distributions are formulated under both stationary and non-stationary assumptions. Non-stationarity is incorporated through a covariate-dependent location parameter, using time and large-scale climate indices—the Pacific Decadal Oscillation (PDO) and the Southern Oscillation Index (SOI)—as explanatory variables. The proposed approach is applied to two contrasting hydrological regions in Mexico—RH10 (Sinaloa) and RH23 (Chiapas Coast)—to assess its performance under differing climatic and hydrological regimes. Model adequacy and stability are evaluated using likelihood-based goodness-of-fit criteria (log-likelihood and Akaike Information Criterion) and a leave-one-out (jackknife) cross-validation scheme embedded within the IF regionalization workflow. Results indicate that non-stationary bivariate formulations dominate model selection at most stations and yield stable regional growth curves, providing robust and engineering-relevant performance under cross-validation. Overall, the proposed framework offers a conservative and operational pathway for regional flood quantile estimation that bridges local data scarcity and regional hydrological characterization in environments influenced by climate variability and long-term change. Full article

This paper investigates the dynamics of a permanent magnet synchronous motor (PMSM) and controls its chaotic speed behavior using the synergetic control technique (SCT). The model includes electrical dynamics in the dq frame and mechanical speed dynamics, with a scalar parameter $\gamma$ capturing cross-coupling effects. The equilibrium structure and local stability properties of the PMSM are analyzed. For zero input voltages and zero load torque, the system exhibits a pitchfork-type bifurcation in the electrical–mechanical equilibrium as $\gamma$ crosses a critical value. Explicit expressions are derived for all equilibria, and their stability is characterized using eigenvalue analysis and the Routh–Hurwitz criterion, and a secondary loss of stability via a Hopf-type mechanism is identified. The case of nonzero input voltages with zero load torque is also discussed. Numerical simulations confirm the analytical results and highlight the parameter regions that admit stable operation. Bifurcation diagrams show the different PMSM behaviors as the parameter $\gamma$ varies. For a certain interval of $\gamma$, the PMSM speed undergoes chaotic oscillations. The SCT is introduced to control the chaos. Macro variables are chosen to design the SCT. The derived SCT is implemented to eliminate the chaotic speed. The controller provides good performance in suppressing the chaos. The controller is tested under sudden reference speed change where the controller gets the new reference speed accurately. It is also evaluated under sudden and sinusoidal load torque variations. Full article

Scene text recognition (STR) and automatic speech recognition (ASR) translate visual or acoustic signals into linguistic sequences and underpin many modern perception systems. Although their front-ends and decoders differ (e.g., CTC-based, attention-based, or variants), both tasks ultimately rely on aligning input frames to output tokens by deep learning techniques, which exposes a shared vulnerability to adversarial perturbations. Existing attacks commonly optimize global sequence-level objectives. As a result, decisive frames are treated implicitly, and optimization can become unnecessarily diffuse over long input sequences, hindering convergence and perceptual quality. To address the above issues, we propose FLAMA, a unified Frame-Level Alignment Margin Attack, which could be used for both STR and ASR models. FLAMA explicitly targets alignment by maximizing per frame (or per step) recognition margins. The design is decoder-agnostic and applies to both CTC-based and attention-based pipelines. It employs a recognition-score-aware Step/Halt gate that concentrates updates on the most critical frames, and a stabilization stage that suppresses late-iteration oscillations to improve optimization stability and perceptual control. Ablation analyses show that stabilization consistently enhances attack success and reduces distortion. We evaluate FLAMA on STR benchmarks (SVT, CUTE80, and IC13) with CRNN, STAR, and TRBA, and on the ASR benchmark (LibriSpeech) with a Wav2Vec 2.0 model. Across modalities and architectures, FLAMA achieves near-100% attack success while substantially reducing ${\mathcal{l}}_2$ distortion and improving perceptual metrics compared with FGSM/PGD baselines. These results highlight frame-level alignment as a shared weak point across visual and audio sequence recognizers and suggest localized margin objectives as a principled route to effective sequence attacks. Full article

Weakly nonlinear oscillators display complex behavior that perturbation methods struggle to analyze, particularly near critical thresholds. The non-perturbation approach (NPA) offers a unified, parameter-agnostic approach that is effective in strongly resonant situations, accurately capturing global phase space structures, and directly addressing chaotic transitions, providing predictive insights where traditional methods fail. The NPA as a novel technique successfully converts the nonlinear weakly oscillator of the ordinary differential equation (ODE) into a linear issue. Theoretical findings are confirmed through a numerical comparison using Mathematica Software (MS). The results of the numerical solution (NS) show excellent agreement. It is commonly acknowledged that all conventional perturbation methods utilize Taylor expansion to augment restoring forces, hence optimizing the usual conditions. A comprehensive analysis of the issue’s stability is easily achievable via NPA. Accordingly, when evaluating NS estimates of weakly nonlinear oscillators, NPA occupations serve as a more useful form of responsibility. Additionally, the stability analysis is easily accomplished via NPA. The system’s dynamics are examined by chaotic analyses, incorporating bifurcation diagrams (BDs), Poincaré maps (PMs), and Lyapunov exponents (LEs). This analysis identifies transitions between regular and complicated behavior and thoroughly examines the system’s stability features. The results provide a comprehensive understanding of the fundamental nonlinear dynamics and offer significant insights for future research on analogous systems. Full article

Differential equations are usually employed to accurately represent the ongoing relationships between tumor cells and immune effector populations, enabling scientists to discover how variation in growth and response rates affects tumor development or elimination. The essential objective of this work is to analyze the dynamical development of a discrete tumor-immune interaction model, with a particular focus on finding out how the combined effects of tumor growth and immune response influence tumor progression. The forward Euler approach is effectively used to discretize the governed system. The bifurcation theory is used to establish the fixed points of the considered system, the stability about the fixed points, and Neimark–Sacker and period-doubling bifurcations. We identify parameter domains that result in tumor existence, restricted oscillations, or full-tumor elimination utilizing stability evaluation, bifurcation examination, and computational simulations. In addition, the 0–1 test is presented. Chaos control is also developed. This article successfully discusses some numerical simulations to verify the results obtained. In general, the research gives an overall insight into this interaction and highlights the circumstances under which the immune system is capable of suppressing or removing tumor cells. Full article

Sweeping jet actuators (SJAs) are promising for active flow control in aerospace systems, but integrating actuator-resolved unsteady CFD into full-configuration simulations is often impractical due to small geometric scales and $\mathcal{O}({10}^2)$ Hz oscillations that demand fine grids and small time steps. This work develops a reduced-order modeling (ROM) framework to generate time-resolved boundary conditions at the actuator exit from SJA flow data. Dynamic mode decomposition (DMD) is particularly attractive for this purpose because it provides a linear, data-driven input–output representation of the actuator effect, even though it does not explicitly model the underlying nonlinear switching mechanism. We introduce an eigenvalue-sorted dynamic mode decomposition (ES-DMD) method that performs stability-aware mode ranking based on the discrete-time DMD eigenvalues, prioritizing modes with $\Re (\lambda )$ closest to unity to retain near-neutrally stable oscillatory dynamics, improving robustness relative to conventional amplitude-based selections for high-frequency oscillatory flows. The method is evaluated across multiple operating conditions, with detailed analysis performed for the highest mass-flow case ($\dot{m}=0.01$ lb/s), representing the most dynamically demanding condition considered. Across multiple operating conditions, ES-DMD yields consistent reconstructions of the dominant switching dynamics. For one-dimensional exit-plane profiles, combining ES-DMD with time-delay embedding enables accurate reconstruction and multi-period prediction using only 20 modes (7.6% of the full system rank). The proposed approach provides a practical pathway to incorporate unsteady SJA effects into large-scale aerospace CFD through compact, predictive boundary-condition models. Full article

Detecting precipitation patterns remains a central challenge in hydrological sciences due to the non-linear nature of atmospheric dynamics and the growing influence of climatic variability. This study investigates the evolution of a 64-year daily precipitation series (1961–2024) at the Tulcea meteorological station (Dobrogea, Romania) and introduces a novel adaptation of the Most Probable Precipitation Method (AMPPM), shifting its application from a regional spatial framework to a temporal one. Shannon Entropy is used as a measure of “climatic disorder.” Model evaluation incorporates Mean Error (ME), Mean Absolute Error (MAE), and Root Mean Squared Error (RMSE), which here measure structural divergence rather than predictive accuracy. Results demonstrate that the Synthetic Representative Series (SRS) isolates the stable climatic signal, reducing the global coefficient of variation (cv (%)) to 70.96% and mitigating extreme skewness typical of coastal convective activity. Seasonal entropy analysis reveals divergence: winter entropy decreases through signal stabilization (minimum 2.00 bits in March), whereas July–October entropy increases, highlighting previously hidden high-frequency daily oscillations. The aggregated Tot_64 series achieves a final entropy of 2.75 bits, confirming a complex, multi-state daily precipitation process. MAE and RMSE values for the SRS (e.g., October: MAE = 1.20, RMSE = 4.53; Tot_64: MAE = 1.40, RMSE = 4.58) indicate that the SRS captures dominant precipitation patterns with minimal deviation, comparable to or better than the moving average approaches. Full article

Background/Objectives: Phospholipase C zeta (PLCZ1; PLCζ) is a sperm-specific enzyme responsible for the Ca²⁺ oscillations required for oocyte activation, and altered PLCζ expression has been associated with fertilization failure in assisted reproductive technologies, particularly intracytoplasmic sperm injection (ICSI). This study aimed to develop and analytically validate a flow cytometry–based protocol for PLCζ quantification in human spermatozoa. Methods: The assay was established using normozoospermic samples and included validated positive and negative technical controls. Antibody specificity was confirmed by Western blot analysis. A defined gating strategy was used to assess linearity between fluorescence intensity and PLCζ expression. Analytical performance was evaluated for precision, reproducibility, stability, and sensitivity, including applicability to low sperm concentrations. Results: A linear relationship between fluorescence intensity and PLCζ expression was demonstrated. The assay showed high precision, reproducibility, and stability, with consistent results in samples stored up to 24 h at room temperature or up to one week post-fixation at 4 °C. Sensitivity testing confirmed suitability for low sperm concentrations. Conclusions: This work provides a standardized and analytically validated framework for PLCζ quantification using flow cytometry. Although the assay measures protein expression rather than functional competence or subcellular localization, it establishes a solid analytical basis for future studies to define clinically relevant PLCζ thresholds and assess its value as a biomarker of fertilization capacity. Full article

As renewable energy integration accelerates, the displacement of synchronous generators by inverter-based resources (IBRs) necessitates advanced grid-forming (GFM) control strategies to maintain system stability. While techniques such as Droop control, Virtual Synchronous Generator (VSG), and Dispatchable Virtual Oscillator Control (dVOC) are well-established, their comparative performance under coordinated cyber-physical stress remains underexplored. This paper presents a comprehensive Controller Hardware-in-the-Loop (CHIL) assessment of these three GFM strategies within a networked microgrid environment. Utilizing a co-simulation framework that integrates an OPAL-RT real-time simulator with the EXata CPS network emulator, we evaluate the dynamic resilience of each controller under islanded, parallel, and fault-induced reconfiguration scenarios. Experimental results demonstrate that the VSG strategy offers superior transient performance, characterized by faster settling times and enhanced fault-ride-through capabilities compared to the Droop and dVOC strategies. Furthermore, recognizing the vulnerability of connected microgrids to cyber threats, this study investigates the impact of False Data Injection (FDI) attacks on the control layer. To address this, a model-reference resilience layer is proposed and validated on a TI C2000 DSP. The results confirm that this protection mechanism effectively detects and mitigates attacks on control references and feedback measurements, ensuring stable operation despite cyber-physical disturbances. Full article

Kaolin is an abundant, low-cost filler for elastomeric compounds. The kaolin used here is primarily kaolinite, chemically clean, and contains a fine particle population. Although agglomeration is evident, it can be mitigated by appropriate physical processing and, when desired, by chemical coupling. This study evaluates kaolin in natural rubber (NR) and examines how adding bis(triethoxysilylpropyl) tetrasulfide (TESPT) during mixing affects filler–matrix compatibility, viscoelastic response, cure stability, and mechanical performance. Kaolin was structurally and morphologically characterized, and the compounds were prepared in a closed mixer coupled to a torque rheometer under controlled dispersion conditions. Part 1 assessed NR with kaolin without a coupling agent, and Part 2 assessed the NR–kaolin with TESPT added during mixing (0.5 and 5 phr). Small-amplitude oscillatory shear (SAOS) was used to probe viscoelastic behavior, while oscillating disk rheometry (ODR) and tensile tests quantified cure and mechanical properties. In Part 1, kaolin increased NR stiffness in SAOS and raised the 100% and 300% moduli by about 40% and 50%, respectively, relative to the unfilled NR compound, while reducing cure reversion from 30% to 10% at 150 °C. In Part 2, TESPT produced a threshold-like response: 0.5 phr caused only minor changes, whereas 5 phr led to pronounced stiffening and cure stabilization. At 5 phr, a low-frequency plateau in G′ below 0.1 Hz with no G′–G″ crossover was observed, accompanied by higher M_H and ΔM in ODR and reversion suppressed to 1% after 30 min. These trends indicate the formation of a more connected filler-rubber network, promoted by TESPT-assisted interfacial coupling/adhesion, while also reflecting the ability of TESPT (tetrasulfide) to contribute sulfur and modify the curing chemistry. Mechanically, kaolin produced marked stiffness increases, with the 100% and 300% moduli increasing by an additional 9% and 36%, respectively, at 5 phr TESPT. At the same time, ultimate tensile strength remained lower than that of neat NR, and elongation at break decreased slightly. Overall, adding TESPT during mixing enhances interfacial coupling and network connectivity and, at higher loading, also influences cure chemistry, yielding higher modulus and strongly improved reversion resistance without increasing ultimate tensile strength relative to neat NR. Full article

Solar drying is an energy-efficient and environmentally friendly method for dehydrating agricultural and medicinal products; however, its performance is strongly affected by fluctuating climatic conditions and nonlinear heat and mass transfer processes. In cabinet-type solar dryers, maintaining the drying air temperature and relative humidity within optimal ranges is particularly critical for medicinal plants such as Plantago major leaves, which are sensitive to overheating and non-uniform drying. In this study, a Mamdani-type fuzzy logic-based intelligent control system is developed and experimentally validated for a cabinet solar dryer operating under real summer climatic conditions in Tashkent, Uzbekistan. The proposed controller regulates fan speed using drying air temperature and relative humidity as inputs. To evaluate its effectiveness, the fuzzy logic controller is benchmarked against a conventionally tuned Proportional–Integral–Derivative (PID) controller under identical operating and climatic conditions. A coupled thermodynamic–hygrometric dynamic model of the drying process is implemented in MATLAB/Simulink (R2024a) to support controller design and analysis. Experimental results demonstrate that the fuzzy logic controller maintains the drying air temperature within the optimal range of 45–50 °C despite significant fluctuations in solar irradiance (650–900 W/m²), whereas the PID-controlled system exhibits noticeable overshoot and oscillations. Compared with PID control, the fuzzy-controlled dryer achieves a smoother reduction in relative humidity, a reduction of approximately 22% in total drying time for the same final moisture content (8–10% wet basis), and an 18% decrease in auxiliary electrical energy consumption. In addition, tray-wise moisture measurements indicate improved drying uniformity under fuzzy control, with moisture variation remaining within ±4%. Overall, the results confirm that fuzzy-logic-based intelligent control provides a robust and energy-efficient solution for cabinet solar dryers operating under hot continental climatic conditions, offering clear advantages over conventional PID control in terms of stability, drying performance, and uniformity. Full article

Circadian disruption (CD) has emerged as a critical factor compromising human health in contemporary society. Increasing evidence suggests that disturbances in circadian rhythms are involved in the pathogenesis of neurodegenerative diseases, such as Alzheimer’s disease (AD). The hyperphosphorylation of tau and the deposition of amyloid-β (Aβ) are recognized as major pathological hallmarks of AD. In this study, we aimed to explore the impact of long-term CD on AD-like pathological changes and to explore the underlying molecular mechanisms using a mouse model. To mimic the CD experienced by shift workers, mice were subjected to lighting conditions involving repeated reversals of the light–dark cycle. In this study, qPCR was to employed detect the expression profile of clock genes in the hippocampus. Subsequently, Western blotting and immunohistochemical analyses were used to evaluate AD-like pathological changes in the hippocampus following CD. For elucidating the underlying mechanisms, we assessed circadian expression patterns of major neurotransmitters, activation of microglia and astrocytes, and alterations of tight junction proteins within the hippocampus. Our findings demonstrated that light–dark cycle disruption triggered CD in mice, and then CD led to increased expression of Aβ protein and tau hyperphosphorylation. CD significantly disrupted the circadian expression profiles of hippocampal clock genes and major neurotransmitters, induced microglial and astrocytic activation, and decreased the expression of the tight junction proteins zonula occludens-1 and occludin in the hippocampus. These results suggest that changes in the light–dark cycles induced abnormal expression of hippocampal clock genes involved in circadian rhythm regulation, suggesting that the body is in a state of endogenous CD. CD induces AD-like pathological changes in mice, potentially mediated by dysregulated circadian oscillations of clock genes, neuroinflammation, loss of key blood–brain barrier proteins, and disturbed neurotransmitter expression in the hippocampus. Collectively, this study underscores the importance of circadian stability for brain health, and highlights the necessity for deeper exploration into the connection between AD and CD. Full article