Search Results (966)

This paper investigates the error rate performance of simultaneous wireless information and power transfer (SWIPT) systems employing opportunistic amplify-and-forward (OAF) relaying under Rayleigh fading conditions. To support both data forwarding and energy harvesting at relays, a power splitting (PS) mechanism is applied. We derive exact and asymptotic symbol error rate (SER) expressions using moment-generating function (MGF) methods, providing analytical insights into how the power splitting ratio $\rho$ and the quality of source–relay (SR) and relay–destination (RD) links jointly affect system behavior. Additionally, we propose a novel approximation that interprets the SWIPT-OAF configuration as an equivalent non-SWIPT OAF model. This enables tractable performance analysis while preserving key diversity characteristics. The framework is extended to include scenarios with partial channel state information (CSI) and $N_{\mathrm{th}}$ best relay selection, addressing practical concerns such as limited relay availability and imperfect decision-making. Extensive simulations validate the theoretical analysis and demonstrate the robustness of the proposed approach under a wide range of signal-to-noise ratio (SNR) and channel conditions. These findings contribute to a flexible and scalable design strategy for SWIPT-OAF relay systems, making them suitable for deployment in emerging wireless sensor and internet of things (IoT) networks. Full article

In digital pathology, accurate diagnosis and prognosis critically depend on robust feature representation of Whole Slide Images (WSIs). While deep learning offers powerful solutions, its “black box” nature presents significant challenges to clinical interpretability and widespread adoption. Handcrafted features offer interpretability, yet orthogonal moments, particularly Tchebichef moments (TMs), remain underexplored for WSI analysis. This study introduces TMs as interpretable, efficient, and scalable handcrafted descriptors for WSIs, alongside a novel two-dimensional digital filter architecture designed to enhance numerical stability and hardware compatibility during TM computation. We conducted a comprehensive reconstruction analysis using H&E-stained WSIs from the MIDOG++ dataset to evaluate TM effectiveness. Our results demonstrate that lower-order TMs accurately reconstruct both square and rectangular WSI patches, with performance stabilising beyond a threshold moment order, confirmed by SNIRE, SSIM, and BRISQUE metrics, highlighting their capacity to retain structural fidelity. Furthermore, our analysis reveals significant computational efficiency gains through the use of pre-computed polynomials. These findings establish TMs as highly promising, interpretable, and scalable feature descriptors, offering a robust alternative for computational pathology applications that prioritise both accuracy and transparency. Full article

This paper presents a combined theoretical, numerical, and experimental analysis to investigate the lateral plastic crushing behavior and energy absorption of circular and non-circular thin-walled rings between two rigid plates. Theoretical solutions incorporating both linear material hardening and power-law material hardening models are solved via numerical shooting methods. The theoretically predicted force-denting displacement relations agree excellently with both FEA and experimental results. The FEA simulation clearly reveals the coexistence of an upper moving plastic region and a fixed bottom plastic region. A robust automatic extraction method of the fully plastic region at the bottom from FEA is proposed. A modified criterion considering the unloading effect based on the resultant moment of cross-section is proposed to allow accurate theoretical estimation of the fully plastic region length. The detailed study implies an abrupt and almost linear drop of the fully plastic region length after the maximum value by the proposed modified criterion, while the conventional fully plastic criterion leads to significant over-estimation of the length. Evolution patterns of the upper and lower plastic regions in FEA are clearly illustrated. Furthermore, the distribution of plastic energy dissipation is compared in the bottom and upper regions through FEA and theoretical results. Purely analytical solutions are formulated for linear hardening material case by elliptical integrals. A simple algebraic function solution is derived without necessity of solving differential equations for general power-law hardening material case by adopting a constant curvature assumption. Parametric analyses indicate the significant effect of ovality and hardening on plastic region evolution and crushing force. This paper should enhance the understanding of the crushing behavior of circular and non-circular rings applicable to the structural engineering and impact of the absorption domain. Full article

Background/Objectives: Senior nurses in Taiwan shoulder layered responsibilities shaped by professional roles, gendered expectations, and family duty. Although Taiwan faces a persistent shortage of experienced clinical nurses, limited research has explored how long-serving nurses sustain identity and commitment across decades of caregiving. This study examines how senior staff nurses understand their journeys of becoming—and remaining—nurses within a culturally and emotionally complex landscape. Methods: Interviews were conducted between May 2019 and September 2023 in locations chosen by participants, with most sessions face-to-face and others undertaken via video conferencing during COVID-19. This narrative inquiry involved in-depth, multi-session interviews with five female senior staff nurses born in the 1970s to early 1980s. Each participant reflected on her life and career, supported by co-constructed “nursing life lines.” Thematic narrative analysis was conducted using McCormack’s five-lens framework and Riessman’s model, with ethical rigor ensured through reflexive journaling and participant validation. Results: Three overarching themes emerged: (1) inner strength and endurance, highlighting silent resilience and the ethical weight of caregiving; (2) support and responsibility in relationships, revealing the influence of family, faith, and relational duty; and (3) role navigation and professional identity, showing how nurses revisit meaning, self-understanding, and tensions across time. Participants described emotionally powerful moments, identity re-connection, and cultural values that shaped their paths. Conclusions: These narratives offer a relational and culturally embedded understanding of what it means to sustain a career in nursing. Narrative inquiry created space for reflection, meaning-making, and voice in a system where such voices are often unheard. Identity was not static—it was lived, reshaped, and held in story. Full article

This article presents a comparative study of the storage of energy produced by photovoltaic panels by means of two types of batteries: Lead–Acid and Lithium-Ion batteries. The work involved the construction of a model in MATLAB-Simulink for controlling the loading/unloading of storage batteries with energy produced by photovoltaic panels through a buck-type DC-DC convertor, controlled by means of the MPPT algorithm implemented through the method of incremental conductance based on a MATLAB function. The program for the MATLAB function was developed by the author in the C++ programming environment. The MPPT algorithm provides maximum energy transfer from the photovoltaic panels to the battery. The electric power taken over at a certain moment by Lithium-Ion batteries in photovoltaic panels is higher than the electric power taken over by Lead–Acid batteries. Two types of batteries were successively used in this model: Lead–Acid and Lithium-Ion batteries. Based on the results being obtained and presented in this work it may be affirmed that the storage battery Lithium-Ion is more performant than the Lead-Acid storage battery. At the Laboratory of Electrical Machinery and Drives of the Engineering Faculty of Bacau, an experimental stand was built for a storing system for electric energy produced by photovoltaic panels. For controlling DC-DC buck-type convertors, a program was developed in the programming environment Arduino IDE for implementing the MPPT algorithm for incremental conductance. The simulation part of this program is similar to that of the program developed in C++. Through conducting experiments, it was observed that, during battery charging, along with an increase in the charging voltage, an increase in the filling factor of the PWM signal controlling the buck DC-DC convertor also occurred. The findings of this study may be applicable to the storage of battery-generated electrical energy used for supplying electrical motors in electric cars. Full article

Based on ethnographic data collected in Germany, this article compares ultra-conservative Salafi and progressive, LGBTQI-plus Muslim movements and examines their negotiation of religious identity and practice within and in contrast to ‘mainstream Islam’ (e.g., DİTİB). While on the surface these movements appear to be on the fringes of Islam and clearly opposed to each other, a closer look reveals interesting moments of convergence and publicly gained prominence. In doing so, this article explores the actor biography issues that drive affiliation, including negative experiences with mainstream mosques and the search for authentic expression and roots. It analyses the politics of labelling (e.g., ‘Salafi’, ‘liberal’), and how these groups define their target audiences in relation to the perceived mainstream. It examines the negotiation of cultural diversity and Islamic ‘purity’, contrasting Salafi reform with progressive interpretations. Finally, it examines strategies for challenging mainstream institutions. By comparing these groups, the article offers a nuanced insight into Islamic practices at the margins. It sheds light on the various strategies employed to discredit mainstream Islamic institutions, ranging from theological differences to power struggles within the contested religious field. Full article

This study explores virtual sensing techniques for the Eolink floating offshore wind turbine (FOWT), which features a pyramidal platform and a single-point mooring system that enables weathervaning to maximize power production and reduce structural loads. To address the challenges and costs associated with monitoring submerged components, virtual sensors are investigated as an alternative to physical instrumentation. The main objective is to design a virtual sensor of mooring hawser loads using a reduced set of input features from GPS, anemometer, and inertial measurement unit (IMU) data. A virtual sensor is also proposed to estimate the bending moment at the joint of the pyramid masts. The FOWT is modeled in OrcaFlex, and a range of load cases is simulated for training and testing. Under defined sensor sampling conditions, both supervised and physics-informed machine learning algorithms are evaluated. The models are tested under aligned and misaligned environmental conditions, as well as across operating regimes below- and above-rated conditions. Results show that mooring tensions can be estimated with high accuracy, while bending moment predictions also perform well, though with lower precision. These findings support the use of virtual sensing to reduce instrumentation requirements in critical areas of the floating wind platform. Full article

Stylolites, common dissolution surfaces in carbonate rocks, form due to localized stress-induced pressure-solution during burial compaction or tectonic contraction. Their morphology and growth are influenced by dissolution kinetics, rock heterogeneity, clay content, burial depth, stress evolution, diagenesis, and pore fluid availability. This study applies the stylolite roughness inversion technique (SRIT), a proven paleopizometer that quantifies the principal vertical stress (σ_v = σ₁) prevailing in strata in the last moments of bedding-parallel stylolites (BPS) formation, to the Late Cretaceous Bagh Group carbonates in the Narmada Basin, India, to estimate their burial paleo-depth. Using the Fourier Power Spectrum (FPS), we obtained 18 σ₁ values from a collection of 30 samples, enabling us to estimate paleo-burial depths for the Bagh Group ranging from 660 to 1320 m. As the Bagh Group burial history is unknown, but as there is no subsequent sedimentary deposition above it, we relate this ca. 1.3 km burial depth to the now eroded thickness of the deposits related to Deccan volcanism at the end of the Cretaceous time, implying a quasi-instantaneous development of the BPS population in the strata. This research highlights the robustness of SRIT for reconstructing burial histories in carbonate sequences and that it can be a reliable way to reconstruct the thickness of eroded deposits in well-constrained geological history. Full article

Compared to spiral bevel gear drives with localized conjugation, line contact spiral bevel gears possess a significantly larger meshing area, theoretically achieving full tooth surface contact and substantially enhancing load capacity. To accurately support the root strength calculation and parameter design of line contact spiral bevel gear drives, this paper presents a theoretical analysis and experimental study of the root bending stress of gear pairs. First, based on the analysis of the meshing characteristics of line contact spiral bevel gear pairs, the load distribution along the contact lines is investigated. Using the slicing method, the load distribution characteristics along the contact line are obtained, and the load sharing among multiple tooth pairs during meshing is further studied. Then, by applying a cantilever beam bending stress model, the root bending stress on such a gear drive is calculated. A root bending moment distribution model is proposed based on the characteristics of the line load distribution previously obtained, from which a formula for calculating root bending stress is derived. Finally, static-condition experiments are conducted to test the root bending stress. The accuracy of the proposed calculation method is verified through experimental testing and finite element analysis. The results of this study provide a foundation for designing lightweight and high-power-density spiral bevel gear drives. Full article

This article discusses the transformation of a continuous-time model of the fractional system into a discrete-time model of the fractional system. For the continuous-time model, the exact solution of the nonlinear equation with fractional derivatives (FDs) that has the form of the damped rotator type with power non-locality in time is obtained.This equation with two FDs and periodic kicks is solved in the general case for the arbitrary orders of FDs without any approximations. A three-stage method for solving a nonlinear equation with two FDs and deriving discrete maps with memory (DMMs) is proposed. The exact solutions of the nonlinear equation with two FDs are obtained for arbitrary values of the orders of these derivatives. In this article, the orders of two FDs are not related to each other, unlike in previous works. The exact solution of nonlinear equation with two FDs of different orders and periodic kicks are proposed. Using this exact solution, we derive DMMs that describe a kicked damped rotator with power-law non-localities in time. For the discrete-time model, these damped DMMs are described by the exact solution of nonlinear equations with FDs at discrete time points as the functions of all past discrete moments of time. An example of the application, the exact solution and DMMs are proposed for the economic growth model with two-parameter power-law memory and price kicks. It should be emphasized that the manuscript proposes exact analytical solutions to nonlinear equations with FDs, which are derived without any approximations. Therefore, it does not require any numerical proofs, justifications, or numerical validation. The proposed method gives exact analytical solutions, where approximations are not used at all. Full article

This paper presents the exponentiated power shanker (EPS) distribution, a fresh three-parameter extension of the standard Shanker distribution with the ability to extend a wider class of data behaviors, from right-skewed and heavy-tailed phenomena. The structural properties of the distribution, namely complete and incomplete moments, entropy, and the moment generating function, are derived and examined in a formal manner. Maximum likelihood estimation (MLE) techniques are used for estimation of parameters, as well as a Monte Carlo simulation study to account for estimator performance across varying sample sizes and parameter values. The EPS model is also generalized to a regression paradigm to include covariate data, whose estimation is also conducted via MLE. Practical utility and flexibility of the EPS distribution are demonstrated through two real examples: one for the duration of repairs and another for HIV/AIDS mortality in Germany. Comparisons with some of the existing distributions, i.e., power Zeghdoudi, power Ishita, power Prakaamy, and logistic-Weibull, are made through some of the goodness-of-fit statistics such as log-likelihood, AIC, BIC, and the Kolmogorov–Smirnov statistic. Graphical plots, including PP plots, QQ plots, TTT plots, and empirical CDFs, further confirm the high modeling capacity of the EPS distribution. Results confirm the high goodness-of-fit and flexibility of the EPS model, making it a very good tool for reliability and biomedical modeling. Full article

The development of wave energy is of great ecological and commercial value. This paper studies the linear vertical array arrangement of the slope–pendulum wave energy conversion device (S-PWEC). Based on the WEC-Sim open-source program, we build four wave energy-generating devices with linear vertical array distributions to study the power generation performance of the array platform and establish the factors influencing the array. S-PWEC is affected by radiation and a shading effect from neighboring devices in a linear vertical array configuration. The overall and individual power generation efficiencies are similar. An increase in the number of devices in the linear vertical array exacerbates the fluctuation of wave excitation moment and output power, indicating that there exists an optimal array configuration for maximizing the power generation efficiency. The performance of the array devices is significantly affected by the direction of incoming waves, and the spacing of the arrays should therefore be adjusted according to the periods of the sea state: increasing the spacing in small periods and decreasing the spacing in large periods can effectively improve the overall power generation. In the future, we will continue to study other array forms of S-PWEC to improve the conversion efficiency of array wave power generation devices. Full article

Growing concern over anthropogenic underwater noise, highlighted by initiatives like the Marine Strategy Framework Directive (MSFD) and its Technical Group on Underwater Noise (TG Noise), emphasizes regions like the Western Black Sea, where increasing activities threaten marine habitats. This region is experiencing rapid growth in maritime traffic and resource exploitation, which is intensifying concerns over the noise impacts on its unique marine habitats. While machine learning offers promising solutions, a research gap persists in comprehensively evaluating diverse ML models within an integrated framework for complex underwater acoustic data, particularly concerning real-world data limitations like class imbalance. This paper addresses this by presenting a multi-faceted framework using passive acoustic monitoring (PAM) data from fixed locations (50–100 m depth). Acoustic data are processed using advanced signal processing (broadband Sound Pressure Level (SPL), Power Spectral Density (PSD)) for feature extraction (Mel-spectrograms for deep learning; PSD statistical moments for classical/unsupervised ML). The framework evaluates Convolutional Neural Networks (CNNs), Random Forest, and Support Vector Machines (SVMs) for noise event classification, alongside Gaussian Mixture Models (GMMs) for anomaly detection. Our results demonstrate that the CNN achieved the highest classification accuracy of 0.9359, significantly outperforming Random Forest (0.8494) and SVM (0.8397) on the test dataset. These findings emphasize the capability of deep learning in automatically extracting discriminative features, highlighting its potential for enhanced automated underwater acoustic monitoring. Full article

The intentional yaw offset of wind turbines has shown potential to redirect wakes, enhancing overall plant power production, but it may increase fatigue loading on turbine components. This study analyzed fatigue loads on the NREL 5 MW reference wind turbine under varying yaw offsets using blade element momentum theory, dynamic blade element momentum, and the converging Lagrange filaments vortex method, all implemented in OpenFAST. Simulations employed yaw angles from −40° to 40°, with turbulent inflow generated by TurbSim, an OpenFAST tool for realistic wind conditions. Fatigue loads were calculated according to IEC 61400-1 design load case 1.2 standards, using thirty simulations per yaw angle across five wind speed bins. Damage equivalent load was evaluated via rainflow counting, Miner’s rule, and Goodman correction. Results showed that the free vortex method, by modeling unsteady aerodynamic forces, yielded distinct differences in damage equivalent load compared to the blade element method in yawed conditions. The free vortex method predicted lower damage equivalent load for the low-speed shaft bending moment at negative yaw offsets, attributed to its improved handling of unsteady effects that reduce load variations. Conversely, for yaw offsets above 20°, the free vortex method indicated higher damage equivalent for low-speed shaft torque, reflecting its accurate capture of dynamic inflow and unsteady loading. These findings highlight the critical role of unsteady aerodynamics in fatigue load predictions and demonstrate the free vortex method’s value within OpenFAST for realistic damage equivalent load estimates in yawed turbines. The results emphasize the need to incorporate unsteady aerodynamic models like the free vortex method to accurately assess yaw offset impacts on wind turbine component fatigue. Full article

This paper introduces a novel and flexible class of continuous probability distributions, termed the Alpha Power Survival Ratio-X (APSR-X) family. Unlike many existing transformation-based families, the APSR-X class integrates an alpha power transformation with a survival ratio structure, offering a new mechanism for enhancing shape flexibility while maintaining mathematical tractability. This construction enables fine control over both the tail behavior and the symmetry properties, distinguishing it from traditional alpha power or survival-based extensions. We focus on a key member of this family, the two-parameter Alpha Power Survival Ratio Exponential (APSR-Exp) distribution, deriving essential mathematical properties including moments, quantile functions and hazard rate structures. We estimate the model parameters using eight frequentist methods: the maximum likelihood (MLE), maximum product of spacings (MPSE), least squares (LSE), weighted least squares (WLSE), Anderson–Darling (ADE), right-tailed Anderson–Darling (RADE), Cramér–von Mises (CVME) and percentile (PCE) estimation. Through comprehensive Monte Carlo simulations, we evaluate the estimator performance using bias, mean squared error and mean relative error metrics. The proposed APSR-X framework uniquely enables preservation or controlled modification of the symmetry in probability density and hazard rate functions via its shape parameter. This capability is particularly valuable in reliability and survival analyses, where symmetric patterns represent balanced risk profiles while asymmetric shapes capture skewed failure behaviors. We demonstrate the practical utility of the APSR-Exp model through three real-world applications: economic (tax revenue durations), engineering (mechanical repair times) and medical (infection durations) datasets. In all cases, the proposed model achieves a superior fit over that of the conventional alternatives, supported by goodness-of-fit statistics and visual diagnostics. These findings establish the APSR-X family as a unique, symmetry-aware modeling framework for complex lifetime data. Full article