Search Results (123)

The quality of medicinal plants is closely related to the ecological factors of their growing environment, as their efficacy is reflected in the content of key medicinal components, which in turn indicates the quality of the plants. This study measured the daily variations in major constituents, including lobetyolin, polysaccharides, and total flavonoids, in Codonopsis pilosula (Franch.) Nannf., which in the Changzhi and Jincheng regions of Shanxi Province, China is known as Lu Tangshen. Throughout its growth cycle. Additionally, the study explored the effects of 11 ecological factors (both climatic and soil variables) on the primary medicinal components of C. pilosula. Through block experiments and comparisons between future data predictions and actual measurements, the reliability of the model and the consistency of block experimental data were ultimately confirmed. Principal component analysis (PCA), stepwise multiple linear regression analysis, and nonlinear polynomial modeling were employed to investigate the relationships between ecological factors and quality-related constituents (polysaccharides, total flavonoids, and lobetyolin). The results showed that linear models effectively explained daily temperature (DT) with an adjusted R² exceeding 0.8, but due to the inherently nonlinear nature of the data, it is evident that linear models are fundamentally inadequate for accurately capturing the underlying relationships. Therefore, their fit for total flavonoids and lobetyolin was suboptimal. The introduction of nonlinear polynomial models (second-, fourth-, and fifth-order) significantly improved the model fit, indicating the existence of complex nonlinear relationships between ecological factors and medicinal components. For polysaccharides, the fourth-order model demonstrated the best performance, while fifth-order models were required to adequately describe the relationships for total flavonoids and lobetyolin. Based on the best models, the optimal ranges for key ecological factors were identified: polysaccharides were best influenced by atmospheric pressure (AP) between 9.1 and 9.3 kPa, air relative humidity (ARH) between 30% and 60%, 40 cm soil mean annual temperature (40cmMAT) between 27.5 °C and 28.5 °C, soil pH between 9.68 and 9.72, and soil nitrogen (N) content between 7 and 9 mg/kg. For total flavonoids, narrow optimal ranges were observed for temperature, humidity, and pH (MAT between 10 °C and 15 °C, 40cmMAT between 27.5 °C and 28.5 °C, and pH between 9.68 and 9.72). Lobetyolin showed optimal conditions at AP of 9.1 to 9.3 kPa, 40cmMAT of 28.0 °C to 28.5 °C, ARH of 65% to 75%, pH near 9.70, and days after planting (DAP) between 10 and 50. The adoption of higher-order polynomial models clarified critical nonlinear inflection points and optimal ecological ranges, providing a refined reference for enhancing the content of medicinal components. These findings offer valuable insights for precision cultivation strategies aimed at improving the quality of C. pilosula. Full article

The broken phase of the next-to-two-Higgs-doublet model (N2HDM) constitutes an archetype of extended Higgs sectors. In the presence of a softly broken ${\mathrm{Z}}_2$ symmetry throughout the scalar and Yukawa sectors, as the additional gauge singlet field does not interact with fermions, the model admits four variants of Yukawa interactions between the doublets and Standard Model fermions. We confront each type with experimental Higgs data, especially those from CMS and ATLAS detectors at the LHC. Interfacing the models with the state-of-the-art package $\mathtt{HiggsTools}$, we perform a statistical ${\chi }^2$ analysis to determine the best-fit points and exclusion limits at the $95\%$ and $68\%$ C.L.’s and identify SM-like Higgs measurements that affect each type the most. We further analyze the exclusion bounds on the additional Higgs bosons at the $95\%$ C.L., paying special attention to searches for hypothetical non-SM Higgs resonances decaying into a pair of bosons or fermions. We show regions where the additional Higgs bosons do not satisfy the narrow-width approximation utilized in most experimental searches. Full article

This paper presents datasets and analyses of 3D LiDAR scans capturing the rutting behavior of a rover wheel in a single-wheel terramechanics testbed. The data were acquired using a LiDAR sensor to record the terrain deformation caused by the wheel’s passage through a Toyoura sandbed, which mimics lunar regolith. Vertical loads of 25 N, 40 N, and 65 N were applied to study how rutting patterns change, focusing on rut amplitude, height, and inclination. This study emphasizes the extraction and processing of terrain profiles from noisy point cloud data, using methods like curve fitting and moving averages to capture the ruts’ geometric characteristics. A sine wave model, adjusted for translation, scaling, and inclination, was fitted to describe the wheel-induced wave-like patterns. It was found that the mean height of the terrain increases after the grouser wheel passes over it, forming ruts that slope downward, likely due to the transition from static to dynamic sinkage. Both the rut depth at the end of the wheel’s path and the incline increased with larger loads. These findings contribute to understanding wheel–terrain interactions and provide a reference for validating and calibrating models and simulations. The dataset from this study is made available to the scientific community. Full article

This study presents the optimization of the friction stir welding (FSW) process using polynomial regression to predict the maximum tensile load (MTL) of welded joints. The experimental design included varying spindle speeds from 600 to 2200 rpm and welding speeds from 100 to 350 mm/min over 28 experimental points. The resulting MTL values ranged from 1912 to 15,336 N. A fifth-degree polynomial regression model was developed to fit the experimental data. Diagnostic tests, including the Shapiro–Wilk test and kurtosis analysis, indicated a non-normal distribution of the MTL data. Model validation showed that fifth-degree polynomial regression provided a robust fit with high fitted and predicted R² values, indicating strong predictive power. Hill-climbing optimization was used to fine-tune the welding parameters, identifying an optimal spindle speed of 1100 rpm and a welding speed of 332 mm/min, which was predicted to achieve an MTL of 16,852 N. Response surface analysis confirmed the effectiveness of the identified parameters and demonstrated their significant influence on the MTL. These results suggest that the applied polynomial regression model and optimization approach are effective tools for improving the performance and reliability of the FSW process. Full article

The Density Gradient Theory (DGT) permits obtaining the surface tension by using an equation of state and the so-called influence parameter. Different correlations of the influence parameter versus temperature have been proposed, with the two-coefficient ones from Zuo and Stenby (full temperature range) and Miqueu et al. (valid for the lower temperature range) being widely used. Recently, Cachadiña et al. applied the DGT with the Peng-Robinson Equation of State to esters. They proposed a new two-coefficient correlation that uses a universal exponent related to the critical exponent associated with the dependence of coexistence densities on temperature near the critical point. When applied to n-alkanes, it is shown that the Cachadiña et al. correlation must be modified to improve the lower temperature range behavior. The proposed modification results in a three-coefficient correlation that includes the triple point temperature as an input parameter and incorporates the Zuo and Stenby and Miqueu et al. correlations as particular cases. Firstly, the correlation coefficients for each of the 32 n-alkanes considered are obtained by fitting the selected values for the surface tension obtained from different databases, books, and papers. The results obtained are comparable to other specific correlations reported in the literature. The overall mean absolute percentage deviation (OMAPD) between the selected and calculated data is just $0.79\%$. Secondly, a general correlation with three adjustable coefficients valid for all the n-alkanes is considered. Despite the OMAPD of 4.38% obtained, this correlation is discarded due to the high deviations found for methane. Finally, it is found that a new six-coefficient general correlation, including the radius of gyration as an input fluid parameter, leads to an OMAPD of $1.78\%$ for the fluid set considered. The use of other fluid properties as an alternative to the radius of gyration is briefly discussed. Full article

Global physical fitness (PF) levels have declined over the past 50 years, contributing to early health risks in children although it is still unclear how age, gender and socioeconomic status (SES) impact PF risk. This study aimed to identify unique health risks related to age, SES and gender that might influence muscular fitness (MF) and cardiorespiratory fitness (CRF) levels of primary school children in South Africa. Children (N = 349, boys = 165; girls = 184) of low (n = 201) and high SES (n = 148) underwent three time point measurements at 6, 9 and 12 years spanning seven primary school years. MF was assessed with the strength sub-test of the Bruininks–Oseretsky Test of Motor Proficiency (BOT-2) and CRF with a 20 m shuttle run. Relationships between biographical data, anthropometric data and PF were analysed using mixed linear regression models. After controlling for covariates, findings from unadjusted interaction models were used, revealing significant (p < 0.05) two-way age and SES interactions in standing long jump (SLJ), push-ups, wall-sit, sit-ups and VO₂max and age and gender interactions (p < 0.001) in sit-ups, push-ups and VO₂max. Universal cut-points are considered valid monitoring guidelines of PF risk in South African school children. For comparison, standardised global protocols for sit-ups and push-ups should be prioritised and intervention strategies should focus on improving PF in girls, older children from the age of 9 and children from low SES backgrounds. Full article

We introduce a new model for non-linear endmember extraction and spectral unmixing of hyperspectral imagery called Generative Simplex Mapping (GSM). The model represents endmember mixing using a latent space of points sampled within a $(n-1)$-simplex corresponding to n unique sources. Barycentric coordinates within this simplex are naturally interpreted as relative endmember abundances satisfying both the abundance sum-to-one and abundance non-negativity constraints. Points in this latent space are mapped to reflectance spectra via a flexible function combining linear and non-linear mixing. Due to the probabilistic formulation of the GSM, spectral variability is also estimated by a precision parameter describing the distribution of observed spectra. Model parameters are determined using a generalized expectation-maximization algorithm, which guarantees non-negativity for extracted endmembers. We first compare the GSM against three varieties of non-negative matrix factorization (NMF) on a synthetic data set of linearly mixed spectra from the USGS spectral database. Here, the GSM performed favorably for both endmember accuracy and abundance estimation with all non-linear contributions driven to zero by the fitting procedure. In a second experiment, we apply the GTM to model non-linear mixing in real hyperspectral imagery captured over a pond in North Texas. The model accurately identified spectral signatures corresponding to near-shore algae, water, and rhodamine tracer dye introduced into the pond to simulate water contamination by a localized source. Abundance maps generated using the GSM accurately track the evolution of the dye plume as it mixes into the surrounding water. Full article

This study aimed to evaluate the marginal and internal adaptation of CAD/CAM crowns milled using two different milling protocols (fine or extra-fine) within a 4-axis milling machine. The crowns were fabricated from lithium disilicate ceramic (IPS e.max CAD) and resin composite (Tetric CAD), assessing their fit in various regions. The crowns (N = 40, n = 10) were milled from lithium disilicate and resin composite using a CEREC Primemill unit. Four groups were formed based on the material and milling protocol: EFLD (extra-fine lithium disilicate), FLD (fine lithium disilicate), EFRC (extra-fine resin composite), and FRC (fine resin composite). The crowns were measured using the replica technique, evaluating internal and marginal adaptation in 18 measuring points per specimen. Data were statistically analyzed using ANOVA and Tukey’s test. Resin composite crowns demonstrated a significantly better internal fit compared to lithium disilicate (p < 0.001). Marginal and internal measurements for resin composites were consistently smaller across regions compared to lithium disilicate. No significant differences were found between milling protocols except for the axial wall region (p = 0.001), where extra-fine milling resulted in smaller values. Resin composite crowns exhibited superior internal fit compared to lithium disilicate, regardless of milling protocol. Both the fine and extra-fine milling protocols had minimal impact on adaptation, except at the axial wall region, with both protocols promoting adequate results overall. Full article

The GF-7 satellite, China’s inaugural sub-meter-level stereoscopic mapping satellite, has been deployed for a wide range of applications, including natural resource investigation, environmental monitoring, fundamental surveying, and the development of global geospatial information resources. The satellite’s stable platform and reliable imaging systems are crucial for achieving high-quality imaging and precise attitude measurements. However, the satellite’s operation is affected by both internal and external factors, which induce vibrations in the satellite platform, thereby affecting image quality and mapping accuracy. To address this challenge, this paper proposes a novel method for constructing a satellite platform vibration model based on geographic location information. The model is developed by integrating composite data from star sensors and gyroscopes (gyro) with subsatellite point location data. The experimental methodology involves the composite processing of gyro data and star sensor optical axis angles, integration of the processed data through time-matching and normalization, and denoising of the integrated data, followed by trigonometric fitting to capture the periodic characteristics of platform vibrations. The positions of the satellite substellar points are determined from the satellite orbit data. A rigorous geometric imaging model is then used to construct a vibration model with geographic location correlation in combination with the satellite subsatellite point positions. The experimental results demonstrate the following: (1) Over the same temporal range, there is a significant convergence in the waveform similarities between the gyro data and the star sensor optical axis angles, indicating a strong correlation in the jitter information; (2) The platform vibration exhibits a robust correlation with the satellite’s geographic location along its orbit. Specifically, the model reveals that the GF-7 satellite experiences the maximum vibration amplitude between 5° S and 20° S latitude during its ascending phase, and the minimum vibration amplitude between 5° N and 20° N latitude during the descending phase. The model established in this study offers theoretical support for optimizing satellite attitude and mitigating platform vibrations. Full article

(1) Background: Ultrashort high-energy laser pulses may cause interaction mechanisms, including photodisruption and plasma-induced ablation in the medium. It is not always easy to distinguish between these two processes, as both interaction mechanisms rely on plasma generation and overlap. The purpose of this paper is to discuss prominent cavitation bubble models describing photodisruption and plasma-induced ablation and to explore their nature for different threshold energies. This exploration will help to better distinguish the two interaction mechanisms. As a second aim, we present an alternative model for the low-energy regime close to the laser-induced optical breakdown (LIOB) threshold, representing the phenomenological effect of the plasma-induced ablation regime. (2) Methods: The cavitation bubble models for photodisruption and plasma-induced ablation were used to calculate the bubble radius for a series of threshold energies (E_Th = 30, 50, 70, and 300 nJ) that loosely represent commercial systems currently used in ultrashort-pulse tissue ablation. Taking a photodisruption model coefficient commonly used in the literature, the root mean square error between the two interaction models was minimized using the generalized reduced gradient fitting method to calculate the optimum scaling factors for the plasma model. The refined models with optimized coefficients were compared for a range of pulse and threshold energies. (3) Results: For low E_Th (30, 50, and 70 nJ), the plasma-induced ablation model dominates for low energies that are close to the threshold energy. The photodisruption model dominates for high energies that are well above the threshold energy. At very high pulse energies, for all the simulated cases, the photodisruption model transitions and crosses over to the plasma-induced ablation model. The cross-over points from which the photodisruption model dominates tend to be reduced for larger E_Th. A new universally applicable model for plasma-induced ablation has been hypothesized that considers the cavitation bubble volume and potentially better explains the bubble dynamics during intrastromal processes. (4) Conclusions: This theoretical exploration and the comparison of the outcomes to empirical data substantiate that inadvertently using the photodisruption model to explain the cavitation bubble dynamics for the entire spectrum of pulse energies and laser systems might provide erroneous estimates of cavitation bubble sizes. A reliable estimate of the true size (the maximum radius) of the cavitation bubble can be reasonably retrieved as the maximum predicted size from the fit of the photodisruption model and the newly proposed plasma-induced ablation model at any given pulse energy. Full article

Despite the benefits of inclusion at work, organizational inclusivity efforts—such as diversity, equity, and inclusion (DE&I) trainings—often fail. Thus, there is a need to investigate from an employee point of view which characteristics (including both organizational culture and inclusion training modalities themselves) may have the biggest impact when it comes to increasing inclusion in the workplace. Combining “planned behavior” and social constructionist theoretical approaches, this study uses logistic regression and data from an original survey with a diverse, international group of employees who have undergone inclusion training (n = 2043) to understand which factors matter for perceptions of inclusion success in the workplace. Findings indicate that coworker and leader support for inclusion predict employee optimism around the achievability of inclusion. In addition, leader and coworker support for inclusion predict employees’ attitudes, beliefs, and perceptions of how their own actions matter when it comes to inclusion. Despite the difficulty with identifying a “one-size-fits-all” approach, this research finds that globally, employees are more likely to believe in inclusion—and to believe that their own actions around inclusion matter—when they perceive that leaders and coworkers are also committed to the cause. Full article

The growth rate of in situ-induced hepatic lesions in an Oncopig large animal model is quantitatively assessed. Oncopigs (n = 9) received baseline triple-phase CT scans prior to lesion induction. Lesions were subsequently induced by delivering the Ad-Cre vector to four locations in the liver. Triple-phase CT scans were obtained weekly to track the growth of the lesions. Animals were sacrificed at 14, 21, or 28 days (n = 3 in each group). The overall success rate of lesion generation was ~78%. Histopathology sections consistently revealed lesions that were highly inflammatory and consisted of a large leukocyte population without clear evidence of carcinomas. Lesions presented within imaging as hypovascular, low attenuating masses with slight contrast enhancement around the margins but little to no enhancement within the lesions themselves. The observed lesions were manually segmented on the venous phase image. Segmentation volumes were fitted to a logistic growth and decay model. Several lesions observed at earlier time points in the 28-day group had fully regressed by the time of the necropsy. The overall trend of rapid growth for the first 21 days, with spontaneous regression of the lesions being observed from day 21 to 28, suggests that the optimal window for experimental studies may be from days 14 to 21. The data and mathematical models generated from this study may be used for future computational models; however, the current model presented has moderate clinical relevance because many induced tumors resolved spontaneously within a few weeks. Awareness and careful consideration of the modest relevance and limitations of the model are advisable for each specific use case. Full article

COVID-19 is an enveloped virus with a single-stranded $RNA$ genome. The surface of the virus contains spike proteins, which enable the virus to attach to host cells and enter the interior of the cells. After entering the cell, the virus exploits the host cell’s mechanisms for replication and dissemination. Since the end of 2019, COVID-19 has spread rapidly around the world, leading to a large-scale epidemic. In response to the COVID-19 pandemic, the global scientific community quickly launched vaccine research and development. Vaccination is regarded as a crucial strategy for controlling viral transmission and mitigating severe cases. In this paper, we propose a novel mathematical model for COVID-19 infection incorporating vaccine-induced immunization failure. As a cornerstone of infectious disease prevention measures, vaccination stands as the most effective and efficient strategy for curtailing disease transmission. Nevertheless, even with vaccination, the occurrence of vaccine immunization failure is not uncommon. This necessitates a comprehensive understanding and consideration of vaccine effectiveness in epidemiological models and public health strategies. In this paper, the basic regeneration number is calculated by the next generation matrix method, and the local and global asymptotic stability of disease-free equilibrium point and endemic equilibrium point are proven by methods such as the Routh–Hurwitz criterion and Lyapunov functions. Additionally, we conduct fractional-order numerical simulations to verify that order $0.86$ provides the best fit with COVID-19 data. This study sheds light on the roles of immunization failure and fractional-order control. Full article

In this paper, we address the problem of estimating the position of a mobile such as a drone from noisy position measurements using the framework of Lie groups. To model the motion of a rigid body, the relevant Lie group happens to be the Special Euclidean group $SE\left(n\right)$, with $n=2$ or 3. Our work was carried out using a previously used parametric framework which derived equations for geodesic regression and polynomial regression on Riemannian manifolds. Based on this approach, our goal was to implement this technique in the Lie group $SE\left(3\right)$ context. Given a set of noisy points in $SE\left(3\right)$ representing measurements on the trajectory of a mobile, one wants to find the geodesic that best fits those points in a Riemannian least squares sense. Finally, applications to simulated data are proposed to illustrate this work. The limitations of such a method and future perspectives are discussed. Full article

This study employs the two-dimensional Legendre polynomial fitting (2-D LPF) method to fit M2 tidal harmonic constants from satellite altimetry data within the region of 53°E–131°E, 34°S–6°N, extracting internal tide signals acting on the sea surface. The M2 tidal harmonic constants are derived from the sea surface height (SSH) data of the TOPEX/Poseidon (T/P), Jason-1, Jason-2, and Jason-3 satellites via t-tide analysis. We validate the 2-D LPF method against the 300 km moving average (300 km smooth) method and the one-dimensional Legendre polynomial fitting (1-D LPF) method. Through cross-validation across 42 orbits, the optimal polynomial orders are determined to be seven for 1-D LPF, and eight and seven for the longitudinal and latitudinal directions in 2-D LPF, respectively. The 2-D LPF method demonstrated superior spatial continuity and smoothness of internal tide signals. Further single-orbit correlation analysis confirmed generally higher correlation with topographic and density perturbations (correlation coefficients: 0.502, 0.620, 0.245; 0.420, 0.273, −0.101), underscoring its accuracy. Overall, the 2-D LPF method can use all regional data points, overcoming the limitations of single-orbit approaches and proving its effectiveness in extracting internal tide signals acting on the sea surface. Full article