Search Results (814)

Gait analysis plays a crucial role in assessing and monitoring the progress of individuals undergoing rehabilitation. This preliminary validation study aims to compare the performance of a new wearable system, NeuroSkin^®, equipped with embedded sensors (inertial measurement unit and pressure sensors), with the non-wearable gold standard, GAITRite^®, in assessing spatio-temporal parameters during gait. Data was collected from nine healthy participants wearing the NeuroSkin while walking on the GAITRite walkway. Temporal parameters were calculated using the pressure sensors of the NeuroSkin^® to detect heel strike (HS) and toe off (TO) on both sides. Distances were calculated using vertical hip acceleration with an inverted pendulum method. We found that the level of agreement between NeuroSkin^® and GAITRite^® measures was excellent for speed, cadence, as well as length and duration of stride and step (lower bound of intraclass correlation coefficients (ICCs) > 0.95), and moderate to excellent for stance and swing durations (ICC > 0.5). These levels of agreement are comparable to the known test–retest reliability of GAITRite^® measures. These results demonstrate the potential of NeuroSkin^® as an embedded gait assessment system for healthy subjects. As this study was conducted exclusively in healthy adults, the results are not directly generalizable to clinical populations. Thus, future studies are needed to investigate its use in patients. Full article

This paper investigates a new subclass of bi-univalent analytic functions defined on the open unit disk in the complex plane, associated with the subordination to $1+\mathrm{s}\mathrm{i}\mathrm{n}z$. Coefficient bounds are obtained for the initial Taylor–Maclaurin coefficients, with a particular focus on the second- and third-order Hankel determinants. To illustrate the non-emptiness of the proposed class, we consider the function $\sqrt{1+tanhz}$, which maps the unit disk onto a bean-shaped domain. This function satisfies the required subordination condition and hence serves as an explicit member of the class. A graphical depiction of the image domain is provided to highlight its geometric characteristics. The results obtained in this work confirm that the class under study is non-trivial and possesses rich geometric structure, making it suitable for further development in the theory of geometric function classes and coefficient estimation problems. Full article

The coefficient of variation α is a critical parameter in the Brownian Passage Time (BPT) model, used to quantify the variability of large earthquake recurrence intervals. In this paper, a new estimation method is proposed for α based on paleoseismic sequences across multiple faults within a given tectonic region. By integrating Monte Carlo simulations with a Bayesian framework, the method assesses the probability distribution of α without assuming that the sample average recurrence interval equals the true mean μ, thereby avoiding epistemic bias. To validate the method, 1,000,000 simulations were conducted in two study areas of differing spatial scales. In the Western Qilian Mountains-Hexi Corridor, the posterior mean of α is 0.36 (without dating uncertainty) and 0.34 (with uncertainty). Expanding the analysis to 29 faults across western China, the estimated α increases to 0.39 (without dating uncertainty) and 0.36 (with uncertainty), with substantially reduced uncertainty bounds. The results reveal that increasing the number of paleoseismic sequences significantly reduces the uncertainty in estimating α, while considering dating uncertainty has only a minor impact. The methodology provides a robust framework for deriving region-specific recurrence variability parameters and proves particularly valuable for tectonically active regions where individual fault records are sparse but collectively form comprehensive datasets across multiple fault systems. Full article

We propose a new strategy for constructing Runge–Kutta (RK) methods using evolutionary computation techniques, with the goal of directly minimising global error rather than relying on traditional local properties. This approach is general and applicable to a wide range of differential equations. To highlight its effectiveness, we apply it to two benchmark problems with oscillatory behaviour: the (2+1)-dimensional nonlinear Schrödinger equation and the N-Body problem (the latter over a long interval), which are central in quantum physics and astronomy, respectively. The method optimises four free coefficients of a sixth-order, eight-stage parametric RK scheme using a novel objective function that compares global error against a benchmark method over a range of step lengths. It overcomes challenges such as local minima in the free coefficient search space and the absence of derivative information of the objective function. Notably, the optimisation relaxes standard RK node bounds ($c_i\in [0,1]$), leading to improved local stability, lower truncation error, and superior global accuracy. The results also reveal structural patterns in coefficient values when targeting high eccentricity and non-sinusoidal problems, offering insight for future RK method design. Full article

Pipe exits into cryogenic systems, such as an exit of a venting or sensor tube inside a cryogenic storage tank, can affect spontaneously occurring acoustic oscillations, known as Taconis oscillations. The amplitude which such oscillations will reach is dependent on losses at the pipe exit that prevent resonant oscillations from growing without bound. Consequently, being able to accurately determine minor losses at a pipe exit is important in predicting the behavior of these oscillations. Current thermoacoustic modeling of such transitions typically relies on steady-flow minor loss coefficients, which are usually assumed to be constant for a pipe entrance or exit. In this study, numerical simulations are performed for acoustic flow at a pipe exit, with and without a wall adjacent to the exit. The operating fluid is cryogenic hydrogen gas, while the pipe radius (2 and 4 mm), temperature (40 and 80 K), and acoustic velocity amplitudes (varying in the range of 10 m/s to 70 m/s) are variable parameters. The simulation results are compared with one-dimensional acoustic models to determine the behavior of minor losses. Results are also analyzed to find harmonics behavior and a build-up of mean pressure differences. Minor losses decrease to an asymptotic value with increasing Reynolds number, while higher temperatures also reduce minor losses (10% reduction at 80 K versus 40 K). A baffle sharply increases minor losses as the distance to pipe exit decreases. These findings can be used to improve the accuracy of oscillation predictions by reduced-order thermoacoustic models. Full article

The issue of working face stability in shield tunnels crossing inclined layered soil is addressed by a modified version of the Mohr–Coulomb strength criterion. This model considers spatial nonhomogeneity and anisotropy of the soil layer, and enables a 3D tunnel stability analysis. It derives the energy equation using virtual work, finds the ultimate support stress at the working face, and solves for its optimal upper bound using an algorithm. This research examined the impact of soil nonhomogeneity, anisotropy, and reduced tensile strength parameters on the stability of tunnel working faces. The results demonstrate the validity of the model, as the findings are consistent with existing research when only tensile strength is considered. The ultimate support force decreases with the nonhomogeneous coefficient and increases with the nonhomogeneously directional angle. The ultimate support force decreases first, and then increases with the soil layer’s inclined angle. Soil layers between 10° and 30° have the lowest ultimate support force. This ultimate support force gets stronger with an increasing anisotropic coefficient. Case studies show that using a method that accounts for soil tensile strength to calculate tunnel working face support force results in a relative error of only 1.92%, improving tunnel stability assessment accuracy. Full article

The proper development of groundwater resources is very important in many parts of the world. Its planning requires mathematical simulation of groundwater flows. Simulation can be either analytical or numerical. Analytical tools, when available, require fewer computational resources, but they are usually based on more assumptions, at the conceptual level, which restrict their applicability. In this paper, we aim to check the applicability of one-dimensional analytical solutions for groundwater flows through non-homogeneous aquifers, which are bound by two constant head and two impermeable boundaries and bear many zones of different transmissivities. These solutions are based on the stepwise inclusion of neighboring zones to larger ones, with equivalent transmissivity coefficients. We compare analytical results with numerical ones, obtained from a two-dimensional numerical model. We have selected the boundary element method (BEM) for this task. BEM is very versatile in solving steady-state groundwater flow problems, since discretization is restricted to external and internal field boundaries only. This feature fits perfectly with our research, which requires flow velocities at the boundaries only. Our research shows that analytical results can serve as upper and lower limits of total inflow. If the differences between the transmissivities of adjacent zones are small, they can be used in preliminary calculations too. Full article

Developing advanced receiver autonomous integrity monitoring (ARAIM) for ground real-time precise positioning applications such as autonomous vehicles presents computational challenges, particularly in calculating real-time protection levels (PLs) that bound possible positioning errors under an acceptable integrity risk. This study proposes an enhanced method for fast PL estimation by introducing a segmentation approach to the Gershgorin circle theorem-based technique for computing standard deviation upper bounds (UBs). This method divides satellites into segments based on normalised geometry mapping coefficients, allowing multiple UBs instead of a single bound for all subsets within each fault-tolerant mode. The approach is implemented for PPP-RTK with an improved Classification Adaptive Kalman Filter (CAKF). Testing is conducted using a network of 10 continuously operating reference stations (CORSs) employing dual-frequency multi-constellation GNSS data. Results show that when monitoring single fault mode, the PL ranges from 0.05 to 0.1 m with a PL-to-PE ratio of 30:1, while dual fault modes monitoring yields PL from 1 to 10 m with a ratio of 3700:1. The segmentation method achieves 1–5% tighter PLs, i.e., better integrity monitoring (IM) availability, compared to the classical single UB approach while maintaining the same computational efficiency by reducing processed subsets from 325 to 1 for dual fault modes. While the method provides slight improvement in PL tightness, it can be more computationally efficient when having geometries with dominant off-diagonal correlation that fails the computation of a UB. Full article

Blood units are routinely collected from adult donors and stored as packed red blood cells (PRBC). The quality of PRBC, including their deformability, decreases during storage. Since PRBC transfusion has been reported to promote circulatory issues in premature neonates (PNs), they typically receive freshly stored units. To test the hypothesis that freshly stored PRBCs can provide red blood cells (RBCs) with appropriate deformability for PN recipients, we compared the deformability of PRBCs transfused to PNs with that of cord blood RBCs (CRBCs), which are known to have deformability equivalent to that of newborn RBCs (PN-RBC). We found that, on average, CRBC deformability was higher than that of PRBCs. However, both showed significant variability with overlapping ranges. A highly significant correlation was observed between cell deformability and the combined levels of specific membrane proteins (ezrin, stomatin, flotillins) and membrane-bound hemoglobin (Pearson coefficient > 0.70, p < 0.02). This study indicates that the storage duration is inadequate for selecting PRBCs for PN recipients. PRBCs with deformability similar to that of PN-RBCs could enable safer and more effective transfusions for PN patients. Measuring membrane proteins alongside membrane-bound hemoglobin can serve as a useful method for selecting appropriate PRBC units for transfusion to PNs. Full article

The classical Eneström–Kakeya theorem states that an n-degree polynomial ${\displaystyle p\left(z\right)={\displaystyle \sum _{k=0}^n}{a}_k{z}^k}$ with real coefficients satisfying $0\le a_0\le a_1\le \cdots \le a_n$ has all of its zeros in $|z|\le 1$ in the complex plane. Numerous generalizations of this result exist, many of them weakening the condition on the coefficients in order to be applicable to a larger class of polynomials. In this paper, a monotonicity condition on the real and imaginary parts of the even- and odd-indexed coefficients is imposed and bounds on the location of the zeros are established. Full article

This study analyzes the stability of embankment slopes with inclined interlayers and vertical tensile cracks at the crest under saturated conditions. This study first establishes a composite failure mechanism based on a finite element limit analysis; then, it derives an upper-bound solution formula for stability considering pore water pressure; and finally, it verifies the rationality of the method through case comparisons. This study finds that an increase in crack depth (H_c) causes the crack initiation position to approach the crest edge, while increases in the slope angle (β), pore water pressure coefficient (r_u), and interlayer embedment depth (d) lead to the opposite trend. Both the stability number (γH/c₁) and safety factor (F_s) decrease with the increase in the slope angle, pore water pressure coefficient, and crack depth, and they increase with the enhancement of relative soil strength and the increase in interlayer embedment depth. When cracks exist at the crest, the influence of pore water pressure on the sliding surface is diminished, while decreasing the cohesion ratio of interlayer to embankment slope soil (c₂/c₁) expands the range of the critical sliding surface. Full article

Spectrum map fusion has emerged as an effective technique to enhance the accuracy of spectrum map construction. However, many existing fusion methods fail to address the strong correlation between spectrum data, resulting in sub-optimal performance. In this paper, we propose a new multi-unmanned aerial vehicle (UAV) spectrum map fusion method based on differential ridge regression. We first construct spectrum maps of UAVs by using differential features of spectrum data. Next, we present a spectrum map fusion model by leveraging the spatial distribution characteristic of spectrum data. To reduce the sensitivity of the fusion model to the strongly correlated data, a new map fusion regularization term is designed, which introduces $l_2$-norm to constrain the fusion regularization parameters and compress the ridge regression coefficient sizes. As a result, accurate spectrum maps can be constructed for the environments with highly correlated spectrum data. We then formulate a model-driven solution to the spectrum map fusion problem and derive its lower bound. By combining the propagation characteristics of the spectrum signal with the developed Lagrange duality, we can guarantee the convergence of map fusion processing while enhancing the convergence rate. Finally, we propose an accelerated maximally split alternating directions method of multipliers (AMS-ADMM) to reduce the computational complexity of spectrum map construction. Simulation results demonstrate that our proposed method can effectively eliminate external noise interference and outliers, and achieve an accuracy improvement of more than 27% compared to state-of-the-art fusion methods in spectrum map construction with low complexity. Full article

The integration of artificial intelligence (AI) into environmental, social, and governance (ESG) disclosure represents a critical frontier for corporate transparency in emerging markets. This study investigates the relationship between AI adoption in ESG reporting, disclosure quality, and financial performance among 180 Saudi-listed companies (2021–2024) within Vision 2030’s transformative context. Using the System Generalized Method of Moments (GMM) estimation with panel unit root and cointegration testing to ensure stationarity assumptions and addressing endogeneity through bounding analysis, the study finds that AI adoption intensity significantly enhances ESG disclosure quality (β = 0.289, p < 0.001), with coefficient significance assessed through t-tests using firm-clustered robust standard errors. Enhanced disclosure quality translates into meaningful financial performance improvements: 0.094 percentage points in return on assets (ROA), 0.156 in return on equity (ROE), and 0.0073 units in Tobin’s Q. Mediation analysis reveals that 73% of AI’s total effect operates through improved ESG quality rather than direct operational benefits. The findings demonstrate parametric bounds robust to macroeconomic confounders, suggesting AI-enhanced transparency creates substantial shareholder value through strengthened stakeholder relationships and reduced information asymmetries. Full article

Accurate teeth segmentation and orientation are fundamental in modern oral healthcare, enabling precise diagnosis, treatment planning, and dental implant design. In this study, we present a comprehensive approach to teeth segmentation and orientation from panoramic X-ray images, leveraging deep-learning techniques. We built an end-to-end instance segmentation network that uses an encoder–decoder architecture reinforced with grid-aware attention gates along the skip connections. We introduce oriented bounding box (OBB) generation through principal component analysis (PCA) for precise tooth orientation estimation. Evaluating our approach on the publicly available DNS dataset, comprising 543 panoramic X-ray images, we achieve the highest Intersection-over-Union (IoU) score of 82.43% and a Dice Similarity Coefficient (DSC) score of 90.37% among compared models in teeth instance segmentation. In OBB analysis, we obtain the Rotated IoU (RIoU) score of 82.82%. We also conduct detailed analyses of individual tooth labels and categorical performance, shedding light on strengths and weaknesses. The proposed model’s accuracy and versatility offer promising prospects for improving dental diagnoses, treatment planning, and personalized healthcare in the oral domain. Full article

The reinforcement effect of single-reinforced soil support under external loading has limitations, and it is difficult for it to meet engineering stability requirements. Therefore, the stability analysis of slopes supported by a combination of anti-slip piles and reinforced soil under the seismic loading effect needs an in-depth study. Based on the upper-bound theorem of limit analysis and the strength-reduction technique, this study establishes an upper-bound stability model for high–steep slopes that simultaneously considers seismic action and the combined reinforcement of anti-slide piles and reinforced soil. A closed-form safety factor is derived. The theoretical results are validated against published data, demonstrating satisfactory agreement. Finally, the MATLAB R2022a sequential quadratic programming method is used to optimize the objective function, and the Optum G2 2023 software is employed to analyze the factors influencing slope stability due to the interaction between anti-slide piles and geogrids. The research indicates that the horizontal seismic acceleration coefficient k_h exhibits a significant negative correlation with the safety factor F_s. Increases in the tensile strength T of the reinforcing materials, the number of layers n, and the length l all significantly improve the safety factor F_s of the reinforced-soil slope. Additionally, as l increases, the potential slip plane of the slope shifts backward. For slope support systems combining anti-slide piles and reinforced soil, when the length of the geogrid is the same, adding anti-slide piles can significantly improve the slope’s safety factor. As anti-slide piles move from the toe to the crest of the slope, the safety factor first decreases and then increases, indicating that the optimal reinforcement position for anti-slide piles should be in the middle to lower part of the slope body. The length of the anti-slip piles should exceed the lowest layer of the geogrid to more effectively utilize the blocking effect of the pile ends on the slip surface. The research findings can provide a theoretical basis and practical guidance for parameter optimization in high–steep slope support engineering. Full article