Search Results (55)

The purpose of this paper is to derive and propose site-specific joint environmental contours for two eligible Offshore Wind Farm Organized Development Areas (OWFODAs) in the Aegean Sea, Greece. The contours are tailored primarily for the design, structural reliability assessment and definition of site-specific environmental load combinations of offshore wind turbines (OWTs); they are quantified based on publicly available 28-year data sets related to offshore wind and wave conditions, namely, wave height, $H_s$, wave peak period, $T_p$ and mean wind speed at the hub height of the wind turbine, ${\overline{u}}_{hub}$. A new methodology, using the modified Inverse First Order Reliability Method (IFORM), is proposed to accurately reflect the regional climate peculiarities, combined with fifth-order polynomials and a sigmoid function to fit the data of the Weibull parameters and correctly capture the low- and mid-range values of $H_s$, which are statistically far more frequent. Several results, in terms of 2D and 3D contour surfaces for two locations in each OWFODA, for 50-year and 100-year return periods are presented. Finally, two tables are cited: one gathering $H_s$ and $T_p$ values corresponding to the maximum ${\overline{u}}_{\mathrm{h}\mathrm{u}\mathrm{b}}$ conditions, and another gathering ${\overline{u}}_{\mathrm{h}\mathrm{u}\mathrm{b}}$ and $T_p$ values corresponding to the maximum $H_s$ conditions. The presented joint probability distributions and the environmental contour surfaces bridge metocean statistical modelling with renewable energy systems design. By providing site-specific joint metocean conditions, the proposed methodology supports offshore wind farm design and structural assessment, thereby contributing to sustainable wind energy development in the Aegean Sea. Full article

Background: Psychosocial assessment is a core component of lung transplant candidate evaluation, but total scores and broad candidate categories do not necessarily show how individual psychosocial concerns co-occur or which modifiable domains require further clinical attention. This study describes the development and internal evaluation of a clinical decision-support application that reorganizes Stanford Integrated Psychosocial Assessment for Transplantation (SIPAT) data into structured multidomain profiles. Methods: The application was developed using a retrospective single-center dataset of 496 adult lung transplant candidates. It integrates the SIPAT total score and candidate category with seven SIPAT-derived domain indicators, domain burden scores, cohort-referenced z-scores, graphical displays, and a ranked summary of domains for clinical review. All seven indicator targets were prespecified deterministic functions of SIPAT items or domain scores obtained during the same assessment. Random forest algorithms with sigmoid calibration were used to transform these targets into percentage-scaled display values; they were not trained using independently assessed clinical outcomes. Analyses included descriptive statistics, Spearman correlations, exploratory clustering, resampling-based cluster stability assessment, threshold sensitivity analyses, and subgroup analyses by age, sex, and primary pulmonary diagnosis. Results: Upper display-band classifications were identified for depression-related concerns in 32 candidates (6.5%), anxiety-related concerns in 11 (2.2%), nicotine-related concerns in 56 (11.3%), alcohol-related concerns in 22 (4.4%), illicit drug-use concerns in 11 (2.2%), social-support deficits in 40 (8.1%), and non-adherence-related concerns in 7 (1.4%). Exploratory clustering yielded a low-burden majority group (n = 432), a nicotine-dominant group (n = 53), and a small multidomain-elevation group (n = 11). The generated percentage-scaled indicators were positively associated with their conceptually corresponding SIPAT domains (Spearman’s ρ = 0.321–0.774) and with the total SIPAT score (ρ = 0.406–0.802; all p < 0.001). Sensitivity analyses showed that the smaller clusters were less stable under bootstrap resampling. These findings demonstrate internal alignment with the source instrument but do not constitute validation against independent clinical outcomes. Conclusions: The application provides an early-stage framework for organizing and visualizing SIPAT information and identifying domains that may warrant additional clinical assessment. Its outputs should be interpreted as SIPAT-derived decision-support indicators, not as independently validated probabilities of future clinical events. Prospective studies are required to evaluate usability, clinical impact, and associations with longitudinal outcomes. Full article

The circular valorization of biomass for sustainable energy recovery is a strategic priority in the transition toward low-carbon systems. In the last decade, anaerobic digestion (AD) has emerged as an efficient technology to produce an energetic vector to replace natural gas with biomethane and reduce waste; however, the hydrolysis of refractory fractions remains the main rate-limiting step. This study investigates an innovative electro-assisted pretreatment of biomass to promote the first rate-limiting hydrolysis step of refractory compounds in biomethane production. Lignocellulosic residues are employed not only as feedstock for the AD process but also as substrates in electrohydrolysis (EH) pretreatment using an Ir-Ta mixed metal oxide (MMO) anode coupled with advanced biomass-derived carbon felt cathodes. Two cathodes were functionalized with Phragmites Australis (PhA) hydrochars, untreated (PA) and KOH-activated (PA-KOH), to enhance the in situ generation of reactive oxygen species (ROS). Brassica napus (Bn) was chosen as the other biomass selected as a feedstock of AD, and was subjected to EH at varying energy inputs (500–5000 kJ kg⁻¹), evaluating structural and biochemical shifts. The results demonstrate that EH effectively modifies the biomass matrix; the PA-KOH-CF cathode exhibited good selectivity to degrade lignocellulosic structures, but higher biomethane production was achieved at 2500 kJ·kg⁻¹ TS using PA-CF, reaching an increase of 52% compared with untreated samples. Kinetic analysis of the biomethane potential was performed using the modified Gompertz model. The model accurately captured the asymmetric sigmoidal transitions of methane production with different electrode configurations, and finally, energy balance assessment identified 2500 kJ·kg⁻¹ TS as the optimal operational threshold. These findings suggest that an excess of applied energy is critical to the availability of soluble organic matter and the presence of refractory compounds that reduce efficiency. This electro-assisted approach offers a robust strategy for intensifying AD, aligning with circular bioenergy objectives. Full article

Chain topology offers a chemistry-preserving route to tune block copolymer (BCP) self-assembly by modifying intrachain correlations and relaxation pathways without changing monomer interactions. Here, we perform a unit-matched comparison of four lamella-forming AB architectures reconstructed from an identical constitutive diblock unit ($N_0$): a linear diblock (DB), a linear multiblock (MB), a comb-like architecture (CB), and a star-like architecture (SB). Using dynamical density functional theory (DDFT), we quantify topology-dependent bulk ordering thresholds and show that architectural reconfiguration systematically stabilizes the ordered phase, reducing the order–disorder transition relative to DB (MB/CB/SB $\approx 0.793/0.762/0.752$ of the diblock value), in semi-quantitative agreement with random phase approximation (RPA) spinodal trends. We also compare topology-dependent directed self-assembly in a common trench geometry under matched reduced quench depth $\Delta \left(\chi N_0\right)=\chi N_0-{\left(\chi N_0\right)}_{\mathrm{ODT}}$, thereby isolating kinetic differences at comparable thermodynamic distance from bulk ordering. A Fourier-based alignment order parameter $\alpha \left(t\right)$ reveals sigmoidal alignment kinetics over decades in time and is well captured by a logistic form in $lnt$, enabling compact descriptors ($t_{50}$, $t_{90}$, and a steepness parameter k) that separate alignment onset from late-stage defect annihilation, while selective sidewalls robustly template sidewall-parallel lamellae across all topologies, the late-stage kinetics remain strongly connectivity dependent and can exhibit long-tailed completion associated with slow late-stage defect annihilation. These results demonstrate a dual role of topology in DSA: lowering the segregation strength required for bulk ordering while reshaping defect-mediated alignment pathways under confinement. Full article

Memristors, as novel one-port electronic elements, have very good memory and commutating properties, insignificant power consumption, and a good compatibility to present CMOS integrated chips. They are applicable in neural networks, memory arrays, and various electronic devices. This paper proposes a simple LTSPICE model of an adapted activation function and a neuron built on memristors. In the neuron, synaptic bonds are implemented by single memristors, allowing a decreased circuit complexity. The summing and scaling schemes are based on op-amps and memristors. The applied modified tangent-sigmoidal activation function is implemented with MOS transistors and memristors. Analyses and simulations are conducted using a simple and high-rate operating memristor model with parasitic parameters—resistance, inductance, capacitance, and small-signal DC components. Their influence on the normal operation of the memristors in the neuron is analyzed, paying attention to their usage and adjustment. The proposed memristor-based artificial neuron is analyzed in MATLAB–Simulink and LTSPICE simulators. A comparison between the derived results confirms the correct operation of the proposed memristor neuron. The generation and analyses of the suggested memristor-based neuron is a significant and promising step for the design and engineering of high-complexity neural networks and their realization in ultra-high-density integrated neural circuits and chips. Full article

The accurate determination of the equilibrium moisture content (EMC) of gel-related powdery samples requires strictly controlled conditions and a long time period. In this study, the adsorption and desorption isotherms of two fructooligosaccharide (FOS) powders and three inulin powders were determined using a dynamic moisture sorption analyzer at 0.1–0.9 water activity (a_w) and 20–35 °C, respectively. The adsorption and desorption isotherms all exhibited type IIa sigmoidal curves; the desorptive isotherm was smooth, the FOS adsorption curves had three inflection points, and the inulin adsorption curves had five inflection points. Large hysteresis between the adsorption and desorption isotherms occurred at 0.1–0.7 a_w for FOS and 0.1–0.6 a_w for inulin. Seven equations, Boquet, Ferro–Fontan, Guggenheim–Anderson–de Boer (GAB), Generalized D’Arcy and Watt (GDW), modified GAB (MGAB), Peleg, and our developed Polynomial, were found to fit the isotherms of the FOS and inulin samples; for adsorption, the best equations were Ferro–Fontan and GDW, and for desorption, the best equations were Polynomial and MGAB. The GDW and MGAB equations could not distinguish the effect of temperature on the isotherms, while the Polynomial equation could. The mean adsorptive monolayer moisture content (M₀) values in FOS and inulin samples were predicted as 7.29% and 7.94% wet basis, respectively. The heat of moisture sorption of FOS and inulin approached that of pure water at about 32.5% and 22.5% wet basis (w.b.) moisture content (MC), respectively. Fourier Transform Infrared Spectroscopy (FTIR) showed that the peaks in inulin with absorbance values above 0.52 and in FOS with absorbance values above 0.35 were at 1020, 1084, and 337 cm⁻¹; these could represent the amorphous structure (primary alcohol C-OH), C-O group, and hydroxyl functional group, respectively. Microscopic structure analysis showed that inulin powder particles were more round-shaped and adhered together, resulting in hygroscopic and sticky characteristics, with a maximum equilibrium moisture content (EMC) of 34% w.b. In contrast, the FOS powders exhibited irregular amorphous particles and a maximum EMC of 60% w.b. As hydrogels, 3–10% FOS or inulin addition reduced the peak, trough, final, breakdown, and setback viscosities of rice starch pasting, but increased the peak time and pasting temperature. FOS addition gave stronger reduction in the setback viscosity and in amylose retrogradation of rice starch pasting than inulin addition. The differential scanning calorimeter (DSC) showed 3–10% FOS addition reduced the amylopectin aging of retrograded paste of rice starch, but 5–7% inulin addition tended to reduce. These results suggest that FOS and inulin have strong hygroscopic properties and can be used to maintain the freshness of starch-based foods. These data can be used for drying, storage, and functional food design of FOS and inulin products. Full article

This study systematically investigates continuous and discrete spectra methodologies for determining time-domain viscoelastic response functions (creep compliance and relaxation modulus) in asphalt mixtures. Through complex modulus testing of three asphalt mixtures (base asphalt mixture, SBS-modified asphalt mixture, and crumb rubber-modified asphalt mixture), we established unified master curves using a Generalized Sigmoidal model with approximated Kramers–Kronig (K-K) relations. Discrete spectra can be obtained by Prony series of Maxwell/Kelvin modeling, while continuous spectra derived through integral transformation produced complementary response functions by numerical integration. Comparative analysis demonstrated that discrete and continuous spectra methods yield highly consistent predictions of the relaxation modulus and creep compliance within conventional time scales (10⁻⁷–10⁵ s), with significant deviations emerging only at extreme temporal extremities. Compared to discrete spectra results, material parameters (relaxation modulus and creep compliance) derived from continuous spectra methods invariably asymptotically approach upper and lower plateaus. Notably, the maximum equilibrium values derived from continuous spectra methods consistently surpassed those obtained through discrete approaches, whereas the corresponding minimum values were consistently lower. This comparative analysis highlights the inherent limitations in the extrapolation reliability of computational methodologies, particularly regarding spectra method implementation. Furthermore, within the linear viscoelastic range, the crumb rubber-modified asphalt mixtures exhibited superior low-temperature cracking resistance, whereas the SBS-modified asphalt mixtures demonstrated enhanced high-temperature deformation resistance. This systematic comparative study not only establishes a critical theoretical foundation for the precise characterization of asphalt mixture viscoelasticity across practical engineering time scales through optimal spectral method selection, but also provides actionable guidance for region-specific material selection strategies. Full article

The study of the Hankel determinant generated by the Maclaurin series of holomorphic functions belonging to particular classes of normalized univalent functions is one of the most significant problems in geometric function theory. Our goal in this study is first to define a family of alpha-convex functions associated with modified sigmoid functions and then to investigate sharp bounds of initial coefficients, Fekete-Szegö inequality, and second-order Hankel determinants. Moreover, we also examine the logarithmic and inverse coefficients of functions within a defined family regarding recent issues. All of the estimations that were found are sharp. Full article

Traditional methods for detecting high-impedance faults (HIFs) in distribution networks primarily rely on constructing fault diagnosis models using one-dimensional zero-sequence current sequences. A single diagnostic model often limits the deep exploration of fault characteristics. To improve the accuracy of HIF detection, a new method for detecting HIFs in active distribution networks is proposed. First, by applying continuous wavelet transform (CWT) to the collected zero-sequence currents under various operating conditions, the time–frequency spectrum (TFS) is obtained. An optimized algorithm, modified empirical wavelet transform (MEWT), is then used to denoise the zero-sequence current signals, resulting in a series of intrinsic mode functions (IMFs). Secondly, the intrinsic mode functions (IMFs) are transformed into a two-dimensional spatial domain fused image using the symmetric dot pattern (SDP). Finally, the TFS and SDP images are synchronized as inputs to a hybrid convolutional neural network (Hybrid-CNN) to fully explore the system’s fault features. The Sigmoid function is utilized to achieve HIF detection, followed by simulation and experimental validation. The results indicate that the proposed method can effectively overcome the issues of traditional methods, achieving a detection accuracy of up to 98.85% across different scenarios, representing a 2–7% improvement over single models. Full article

This paper is mainly devoted to studying the deployment problem of a multi-static radar system (MSRS) within a non-connected deployment region using multi-objective particle swarm optimization (MOPSO). By modeling and reformulating the problem, it can be represented as a multi-objective mixed integer programming (MOMIP), which eliminates the need for additional constraints. To enhance the algorithm performance, integer variables and continuous ones are treated separately employing multiple velocity formulas. The velocity formulas for integer variables are modified using the sigmoid function and genetic operation, leading to the proposal of two MSRS deployment algorithms, namely MOPSO-Sigmoid and MOPSO-Gene. To evaluate the performance of the proposed algorithms, they are compared with two existing MOPSO-based algorithms. The first algorithm is the MSRS deployment algorithm for the non-connected deployment region that addresses the additional constraint problem model. The second algorithm is based on an existing conventional MOPSO algorithm and addresses the equivalent MOMIP problem model. A numerical study demonstrates that MOPSO-Sigmoid and MOPSO-Gene exhibit promising efficiency and effectiveness. Full article

To address the shortcomings of the Dung Beetle Optimization (DBO) algorithm in ship power-system fault reconfiguration, such as low population diversity and an imbalance between global exploration and local exploitation, the authors of this paper propose an improved Dung Beetle Optimization (LESSDBO) algorithm. The improvements include optimizing the initial population using Latin hypercube sampling and an elite population strategy, optimizing parameters with an improved sigmoid activation function, introducing the sine–cosine algorithm (SCA) for position update optimization, and performing multi-population mutation operations based on individual quality. The LESSDBO algorithm was applied to simulate the fault reconfiguration of a ship power system, and it was compared with the traditional DBO, Genetic Algorithm (GA), and Modified Particle Swarm Optimization (MSCPSO) methods. The simulation results showed that LESSDBO outperformed the other algorithms in terms of convergence accuracy, convergence speed, and global search capability. Specifically, in the reconfiguration under Fault 1, LESSDBO achieved optimal convergence in seven iterations, reducing convergence iterations by more than 30% compared with the other algorithms. In the reconfiguration under Fault 2, LESSDBO achieved optimal convergence in eight iterations, reducing convergence iterations by more than 23% compared with the other algorithms. Additionally, in the reconfiguration under Fault Condition 1, LESSDBO achieved a minimum of four switch actions, which is 33% fewer than the other algorithms, on average. In the reconfiguration under Fault Condition 2, LESSDBO achieved a minimum of eight switch actions, which is a 5.9% reduction compared with the other algorithms. Furthermore, LESSDBO obtained the optimal reconfiguration solution in all 50 trials for both Faults 1 and 2, demonstrating a 100% optimal convergence probability and significantly enhancing the reliability and stability of the algorithm. The proposed method effectively overcomes the limitations of the traditional DBO in fault reconfiguration, providing an efficient and stable solution for the intelligent topology reconfiguration of ship power systems. Full article

This study uses a sigmoidal function to describe the plastic strain hardening of metallic materials, considering temperature and strain rate effects. The effectiveness of this approach is evaluated and systematically compared with other hardening laws. Incorporating temperature and strain rate effects into the parameters of this sigmoidal-type hardening law enables a more precise description and prediction of the plastic deformation of materials under different combinations of temperature and strain rate. The temperature effect is coupled using a simplified Arrhenius model, and the strain rate effect is coupled with a modified Johnson–Cook model. The sigmoidal-type hardening law is integrated with an asymmetric yield criterion to address complex behavior, such as anisotropy and strength differential effects. The calibration and validation of the constitutive model involve examining uniaxial tensile/compressive flow curves in various directions and biaxial tensile/compressive flow curves for diverse metallic alloys, proving the proposed model’s broad applicability. Full article

Kombucha is a traditional, fermented beverage made with an essential biomaterial known as SCOBY (symbiotic culture of bacteria and yeast). Three different tea types, namely black, green, and oolong, were compared in kombucha fermentation in terms of pH dynamics, the formation of SCOBY biomass, and the production of acetic acid. The rational, exponential, and polynomial models described pH dynamics with good fit, R² > 0.98. The formation of SCOBY biomass and the production of acetic acid were modelled using sigmoidal functions, with three-parameter logistic and Gompertz models and four-parameter Boltzmann and Richards models. The F-test indicated that the three-parameter models were statistically adequate; thus, the Gompertz model was modified to present the biological meaning of the parameters. The SCOBY biomass formation rates ranged from 7.323 to 9.980 g/L-day, and the acetic acid production rates ranged from 0.047 to 0.049% acid (wt/vol)/day, with the highest values from the non-conventional substrate, oolong tea. The correlations between pH and SCOBY biomass or acetic acid using polynomial models enable the prediction of product formation in kombucha processing. Full article

In order to provide a basis for the structural analysis, design and maintenance of permeable asphalt pavements, and to promote their engineering promotion and application, this study investigated the dynamic viscoelastic properties of permeable asphalt mixtures (PAC-13) under complex stress states. A Simple Performance Tester (SPT) system was used to measure the dynamic modulus of the mix under complex stress states. The displacement factor and principal dynamic modulus curves were formed by fitting Sigmoidal functions and using 1stOpt (first optimization) software, the phase angle principal curves were further determined, and the dynamic modulus was predicted for the ambient phase (15–25 °C) using the Hirsch model. The results showed that the dynamic modulus of the mixtures decreases with an increasing temperature, and the maximum decrease in the dynamic modulus is 93% when the confining pressure is 100 kPa and the loading frequency is 10 Hz. The dynamic modulus increases with an increasing confining pressure and loading frequency, the maximum increase with an increasing confining pressure is 26.1% when the temperature is 25 °C and the loading frequency is 10 Hz, and the maximum increase with an increasing loading frequency is 411% when the temperature is 25 °C and the confining pressure is 100 Hz. The dynamic modulus has a strong frequency dependence at low temperatures, while it is stress-dependent at high temperatures. Meanwhile, based on the Hirsch model, a new modified prediction model was developed, which can well predict the dynamic modulus of permeable asphalt mixtures at room temperature. Full article

Vibration monitoring and analysis are important methods in wind turbine gearbox fault diagnosis, and determining how to extract fault characteristics from the vibration signal is of primary importance. This paper presents a fault diagnosis approach based on modified hierarchical fluctuation dispersion entropy of tan-sigmoid mapping (MHFDE_TANSIG) and northern goshawk optimization–support vector machine (NGO–SVM) for wind turbine gearboxes. The tan-sigmoid (TANSIG) mapping function replaces the normal cumulative distribution function (NCDF) of the hierarchical fluctuation dispersion entropy (HFDE) method. Additionally, the hierarchical decomposition of the HFDE method is improved, resulting in the proposed MHFDE_TANSIG method. The vibration signals of wind turbine gearboxes are analyzed using the MHFDE_TANSIG method to extract fault features. The constructed fault feature set is used to intelligently recognize and classify the fault type of the gearboxes with the NGO–SVM classifier. The fault diagnosis methods based on MHFDE_TANSIG and NGO–SVM are applied to the experimental data analysis of gearboxes with different operating conditions. The results show that the fault diagnosis model proposed in this paper has the best performance with an average accuracy rate of 97.25%. Full article