Search Results (1,923)

The present paper examines a novel exact solution to nonlinear fractional partial differential equations (FDEs) through the Sardar sub-equation method (SSEM) coupled with Jumarie’s Modified Riemann–Liouville derivative (JMRLD). We take the (3+1)-dimensional space–time fractional modified Korteweg-de Vries (KdV) -Zakharov-Kuznetsov (ZK) equation as a case study, which describes some intricate phenomena of wave behavior in plasma physics and fluid dynamics. With the implementation of SSEM, we yield new solitary wave solutions and explicitly examine the role of the fractional-order parameter in the dynamics of the solutions. In addition, the sensitivity analysis of the results is conducted in the Galilean transformation in order to ensure that the obtained results are valid and have physical significance. Besides expanding the toolbox of analytical methods to address high-dimensional nonlinear FDEs, the proposed method helps to better understand how fractional-order dynamics affect the nonlinear wave phenomenon. The results are compared to known methods and a discussion about their possible applications and limitations is given. The results show the effectiveness and flexibility of SSEM along with JMRLD in forming new categories of exact solutions to nonlinear fractional models. Full article

Climate change, resource scarcity, and ecological degradation have become critical bottlenecks constraining socio-economic development. Basin cities serve as key nodes in China’s ecological security pattern, playing indispensable roles in ecological civilization construction. This study established an evaluation index system spanning five dimensions to assess the effectiveness of ecological civilization construction. This study employs the entropy-weighted Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and Back-Propagation (BP) neural network methods to evaluate the level of ecological civilization construction in the Yellow River Basin from 2010 to 2022, to analyze its indicator weights, and to explore the spatio-temporal evolution characteristics of each city. The results demonstrate the following: (1) Although the ecological civilization construction level of cities in the Yellow River Basin shows a steady improvement, significant regional development disparities persist. (2) The upper reaches are primarily constrained by ecological fragility and economic underdevelopment. The middle reaches exhibit significant internal divergence, with provincial capitals leading yet demonstrating limited spillover effects on neighboring areas. The lower reaches face intense anthropogenic pressures, necessitating greater economic–ecological coordination. (3) Among the dimensions considered, Territorial Space and Eco-environmental Protection emerged as the two most influential dimensions contributing to performance differences. According to the ecological civilization construction performance and changing characteristics of the 48 cities, this study proposes differentiated optimization measures and coordinated development pathways to advance the implementation of the national strategy for ecological protection and high-quality development in the Yellow River Basin. Full article

Accurate plant species identification in desert grasslands using hyperspectral data is a critical prerequisite for large-scale, high-precision grassland monitoring and management. However, due to prolonged overgrazing and the inherent ecological vulnerability of the environment, sericite–Artemisia desert grassland has experienced significant ecological degradation. Therefore, in this study, we obtained spectral images of the grassland in April 2022 using a Soc710 VP imaging spectrometer (Surface Optics Corporation, San Diego, CA, USA), which were classified into three levels (low, medium, and high) based on the level of participation of Seriphidium transiliense (Poljakov) Poljakov and Ceratocarpus arenarius L. in the community. The optimal index factor (OIF) was employed to synthesize feature band images, which were subsequently used as input for the DeepLabv3p, PSPNet, and UNet deep learning models in order to assess the influence of species participation on classification accuracy. The results indicated that species participation significantly impacted spectral information extraction and model classification performance. Higher participation enhanced the scattering of reflectivity in the canopy structure of S. transiliense, while the light saturation effect of C. arenarius was induced by its short stature. Band combinations—such as Blue, Red Edge, and NIR (BREN) and Red, Red Edge, and NIR (RREN)—exhibited strong capabilities in capturing structural vegetation information. The identification model performances were optimal, with a high level of S. transiliense participation and with DeepLabv3p, PSPNet, and UNet achieving an overall accuracy (OA) of 97.86%, 96.51%, and 98.20%. Among the tested models, UNet exhibited the highest classification accuracy and robustness with small sample datasets, effectively differentiating between S. transiliense, C. arenarius, and bare ground. However, when C. arenarius was the primary target species, the model’s performance declined as its participation levels increased, exhibiting significant omission errors for S. transiliense, whose producer’s accuracy (PA) decreased by 45.91%. The findings of this study provide effective technical means and theoretical support for the identification of plant species and ecological monitoring in sericite–Artemisia desert grasslands. Full article

Modern fly-by-wire (FBW) aircraft demand high-fidelity simulation systems for research and training, yet existing force-sensing solutions are often prohibitively expensive. This study presents the design, development, and validation of a low-cost, reconfigurable force-sensing sidestick. The system utilizes four strain-gauge load cells to capture pure pilot force inputs, integrated with a 6-DoF non-linear flight model. To evaluate its performance, a pitch-angle tracking task was conducted with 16 participants (pilots and non-pilots). Objective metrics revealed that the control strategy was a primary determinant of performance. Participants employing a proactive feedforward control strategy exhibited roughly an order of magnitude lower tracking-error variance than those relying on reactive corrections. Subjective assessments using the Cooper-Harper scale and NASA-TLX corroborated the objective data, confirming the sidestick’s ability to differentiate control techniques. This work demonstrates an open-source platform that makes high-fidelity FBW simulation accessible for academic research, pilot training, and human factors analysis at a fraction of the cost of commercial systems. Full article

Hyperspectral image (HSI) classification faces challenges such as high dimensionality, spectral redundancy, and difficulty in modeling the coupling between spectral and spatial features. Existing methods fail to fully exploit first-order derivatives and frequency domain information, which limits classification performance. To address these issues, this paper proposes a Differential-Frequency Attention-based Band Selection Transformer (DFAST) for HSI classification. Specifically, a Differential-Frequency Attention-based Band Selection Embedding Module (DFASEmbeddings) is designed to extract original spectral, first-order derivative, and frequency domain features via a multi-branch structure. Learnable band selection attention weights are introduced to adaptively select important bands, capture critical spectral information, and significantly reduce redundancy. A 3D convolution and a spectral–spatial attention mechanism are applied to perform fine-grained modeling of spectral and spatial features, further enhancing the global dependency capture of spectral–spatial features. The embedded features are then input into a cascaded Transformer encoder (SCEncoder) for deep modeling of spectral–spatial coupling characteristics to achieve classification. Additionally, learnable attention weights for band selection are outputted for dimensionality reduction. Experiments on several public hyperspectral datasets demonstrate that the proposed method outperforms existing CNN and Transformer-based approaches in classification performance. Full article

In this paper, we provide a novel extended mixed differential model that is appealing to users because of its numerous free parameters. The motivation of this research arises from the opportunity for a general investigation of some outstanding classical and novel dynamical models. The higher energy levels known in the literature can be governed by appropriately added correction factors. Furthermore, the different applications of the considered model can be achieved only after a proper parameter calibration. All these necessitate the use of diverse optimization and approximation techniques. The proposed extended model is especially useful in the important field of decision making, namely the antenna array theory. This is due to the possibility of generating high-order Melnikov polynomials. The work is a natural continuation of the authors’ previous research on the topic of chaos generation via the term ${x\left|x\right|}^{a-1}$. Some specialized modules for investigating the dynamics of the proposed oscillators are provided. Last but not least, the so-defined dynamical model can be of interest for scientists and practitioners in the area of antenna array theory, which is an important part of the decision-making field. The stochastic control of oscillations is also the subject of our consideration. The underlying distributions we use may be symmetric, asymmetric or strongly asymmetric. The same is true for the mass in the tails, too. As a result, the stochastic control of the oscillations we purpose may exhibit a variety of possible behaviors. In the final section, we raise some important issues related to the methodology of teaching Master’s and PhD students. Full article

Bupleurum scorzonerifolium Willd. is a perennial herbaceous plant of the genus Bupleurum in the Apiaceae family. Also known as red Bupleurum, it is mainly distributed in Northeast China, North China and other regions and is a commonly used medicinal plant. It is difficult for the wild plant resources of Bupleurum scorzonerifolium Willd. to meet the market demand. In artificial cultivation, there are problems such as a low yield per plant, low quality, weakened stress resistance and variety degradation. The contents of bioactive components and metabolites in traditional Chinese medicinal materials vary significantly across different growth years. The growth duration directly impacts their quality and clinical efficacy. Therefore, determining the optimal growth period is one of the crucial factors in ensuring the quality of traditional Chinese medicinal materials. In this study, Gas Chromatography–Mass Spectrometry (GC-MS) and High-performance liquid chromatography (HPLC) were comprehensively applied to analyze the metabolically differential substances in different parts of Bupleurum scorzonerifolium Willd. By comparing the compositions and content differences of chemical components in different growth years and different parts, the chemical components with significant differences were accurately screened out. In order to further explore the dynamic change characteristics and internal laws of metabolites, a metabolic network was constructed for a visual analysis and, finally, to see the optimal growth years of Bupleurum scorzonerifolium Willd. This result showed that with the accumulation of the growth cycle, the height, root width, fresh mass and saikosaponins content of Bupleurum scorzonerifolium Willd. increased year by year. Except for sodium and calcium elements in the main shoot, the other elements were significantly reduced. In addition, 59 primary metabolites were identified by GC-MS, with the accumulation of the growth cycle, the contents of organic acids, sugars, alcohols and amino acids gradually decreased, while the contents of alkyl, glycosides and other substances gradually increased. There were 53 positive correlations and 18 negative correlations in the triennial Bupleurum scorzonerifolium Willd. grid, all of which were positively correlated with saikosaponins. Therefore, the triennial Bupleurum scorzonerifolium Willd. was considered to be the suitable growth year. It not only provided a new idea and method for the quality evaluation of Bupleurum scorzonerifolium Willd., but also provided a scientific basis for the quality control of Chinese herbs. Full article

Urban parks are an important component of public urban spaces, which directly impact the living experiences of residents and the urban image. High-quality urban parks are crucial for enhancing the well-being of residents. This study selected Fukuoka, Japan, as the study site. Five urban parks were chosen to evaluate landscape visual quality by using the Scenic Beauty Estimation (SBE) method. The Semantic Differential (SD) method was used to get sample subjective landscape features. Meanwhile, sample objective landscape features were obtained by using semantic segmentation techniques in deep learning and combined with spatial analysis to understand their distribution. A regression model was established, which used the SBE values as the dependent variable and subjective landscape features as the independent variables to analyze the relationship between urban park landscape visual quality and subjective landscape features. The regression analysis revealed that sense of layering, harmony, interestingness, sense of order, and vitality were the core factors influencing visual quality. All five features had a significant positive impact on landscape visual quality. The sense of order was the most influential factor, which would be the key to enhancing the landscape perception experience. Moreover, the XGBoost model and SHAP value from machine learning were used to reveal the nonlinear relationships and significant threshold effects between urban park visual quality and five objective landscape features: openness, greenness, enclosure, vegetation diversity, and Shannon–Wiener diversity index. This study showed that when openness exceeded 0.27, the positive effect was significant. The optimal threshold for the greenness was 0.38. Vegetation diversity and enclosure had to be below 0.82 and 0.58, respectively, to have a positive impact. Meanwhile, the positive influence of the Shannon–Wiener diversity index reached its maximum at a value of 1.37. This study not only establishes a systematic method for diagnosing landscape problems and evaluating landscape visual quality but also provides both theoretical support and practical guidance for urban park landscape optimization. Full article

Radioactive iodine (RAI) therapy plays a fundamental role in the management of differentiated thyroid cancer (DTC) following appropriate surgical intervention. High levels of TSH are required in order to achieve maximum RAI uptake in residual thyroid tissue or metastatic cells. The two techniques that are most commonly used are thyroid hormone withdrawal (THW), which induces endogenous TSH elevation by creating a hypothyroid state, and exogenous stimulation with recombinant human TSH (rhTSH). This review compares both approaches over a range of DTC risk categories. Extensive evidence demonstrates that rhTSH and THW yield equivalent oncological outcomes, including remnant ablation success, recurrence-free survival, and overall survival, in low-, intermediate-, and high-risk disease. Additionally, rhTSH maintains quality of life by avoiding hypothyroid symptoms. While THW continues to be an excellent option when there is a lack of availability of rhTSH, its disadvantages, particularly the transient hypothyroid state, must be carefully weighed against the demonstrated equivalence in efficacy. In current clinical practice, rhTSH is frequently the preferred option for its convenience, safety, and patient-centered benefits; however, the selection of the optimal approach should be based on individual clinical circumstances and patients’ preferences, as well as resource considerations. Full article

In order to recycle plastic waste back to food contact materials (FCMs), it is necessary to identify hazardous substances in plastic packaging that pose a toxicological risk. Printing inks on plastics are not yet designed to withstand the high heat stress of mechanical recycling processes and therefore require hazard identification. In this study, virgin polypropylene (PP) foils were printed with different types of inks (UV-cured, water-based) and colour shades. Thermal analysis of printed foils and pigments was performed using differential scanning calorimetry (DSC). Samples were then thermally treated below and above measured thermal events at 120 °C, 160 °C, 200 °C or 240 °C for 30 min. Subsequently, migration tests and miniaturised Ames tests were performed. Four out of thirteen printed foils and all three pigments showed positive results for mutagenicity in miniaturised Ames tests after thermal treatment at 240 °C. Additionally, pre-incubation Plate Ames tests (according to OECD 471) were performed on three pigments and one printed foil, yielding two positive results after thermal treatment at 240 °C. These results indicate that certain ink components form hazardous decomposition products when heated up to a temperature of 240 °C. However, further research is needed to gain a better understanding of the chemical processes that occur during high thermal treatment. Full article

During carcinogenesis, cells must acquire a telomere maintenance mechanism in order to avoid telomere shortening-induced replicative senescence. While most tumors activate telomerase, a minority of them employ a recombinational mechanism called Alternative Lengthening of Telomeres (ALT). One of the most investigated features is the association between ALT and ATRX mutations, since this has been shown to be the gene with the highest rate of mutations among ALT tumors. However, most of these studies, and in particular, mechanistic studies in vitro, have been carried out on mesenchymal tumors (sarcomas). In the present study, using genomic and expression data from the DepMap portal, we identified several non-mesenchymal ALT cell lines, and we compared the incidence of ATRX and other gene mutations between ALT cell lines of different origins (mesenchymal, neural, epithelial, hematopoietic). We confirmed that ATRX is frequently mutated in mesenchymal and neural ALT cell lines but not in epithelial ones. Our results showed that mutations of ATRX or other proteins involved in the maintenance of telomere integrity are needed for ALT activation in all cell types, and ATRX is preferentially mutated in mesenchymal ALT cells. Besides a more precise interpretation of the role of ATRX loss in ALT establishment, we proposed a model in which mutation of this gene impairs differentiation in mesenchymal and neural cells (but not in epithelial ones). Therefore, we explained the high incidence of ATRX mutations in mesenchymal and neural tumors with the fact that they both trigger ALT and impair differentiation, thus promoting two steps at once in the process of carcinogenesis. Full article

Credit supervision of practitioners in the water conservancy construction market, a vital pillar of national infrastructure development, significantly impacts project safety and the maintenance of order in the industry. From the perspective of indirect supervision, this study constructs a tripartite evolutionary game model involving government departments, enterprises, and practitioners to analyze the dynamic evolution mechanism of credit supervision. By examining the strategic interactions among the three parties under different regulatory scenarios, we identify key factors influencing the stable equilibrium of evolution and verify the theoretical conclusions through numerical simulations. The study yields several key insights. First, while government regulation and social supervision can substantially increase the likelihood of practitioners’ integrity, relying solely on administrative regulation has an efficiency limit. Second, the effectiveness of the reward and punishment mechanism of the direct manager plays a crucial leveraging role in credit evolution. Lastly, under differentiated regulatory strategies, high-credit practitioners respond more strongly to long-term cost optimization, while low-credit practitioners are more effectively deterred by short-term, high-intensity disciplinary actions. Based on these findings, this study proposes a systematic governance framework of “regulatory model innovation–corporate responsibility enhancement–social supervision deepening.” Unlike previous studies, this framework adopts a comprehensive approach from three dimensions: regulatory model innovation, corporate responsibility enhancement, and social supervision deepening. It offers a more holistic and systematic solution for refining the credit system in the water conservancy construction market, providing both theoretical support and practical approaches. Full article

Land desertification represents a significant and sensitive global ecological issue. In the Inner Mongolia region of China, soil desertification and salinization are widespread, resulting from the combined effects of extreme drought conditions and human activities. Using Gaofen 5B AHSI imagery as our data source, we collected spectral data for seven distinct land cover types: lush vegetation, yellow sand, white sand, saline soil, saline shell, saline soil with saline vegetation, and sandy soil. We applied Particle Swarm Optimization (PSO) to fine-tune the Wavelet Packet (WP) decomposition levels, thresholds, and wavelet basis function, ensuring optimal spectral decomposition and reconstruction. Subsequently, PSO was deployed to optimize key hyperparameters of the Random Forest algorithm and compare its performance with the ResNet-Transformer model. Our results indicate that PSO effectively automates the search for optimal WP decomposition parameters, preserving essential spectral information while efficiently reducing high-frequency spectral noise. The Genetic Algorithm (GA) was also found to be effective in extracting feature bands relevant to land desertification, which enhances the classification accuracy of the model. Among all the models, integrating wavelet packet denoising, genetic algorithm feature selection, the first-order differential (FD), and the hybrid architecture of the ResNet-Transformer, the WP-GA-FD-ResNet-Transformer model achieved the highest accuracy in extracting soil sandification and salinization, with Kappa coefficients and validation set accuracies of 0.9746 and 97.82%, respectively. This study contributes to the field by advancing hyperspectral desertification monitoring techniques and suggests that the approach could be valuable for broader ecological conservation and land management efforts. Full article

Affecting millions of individuals each year, chronic wounds place a substantial strain on both the healthcare system and healthcare providers, becoming a global health issue that requires a rapid and efficient solution. Unlike acute wounds that heal naturally without any external intervention, chronic wounds necessitate proper medical treatment in order to promote the wound-healing process and avoid any arising complications. However, the traditional therapeutic strategies are often limited when it comes to treating chronic wounds, which is why new approaches that facilitate the timely and effective healing of skin have been explored. Due to their unique properties, collagen-based hydrogels have been widely investigated as potential candidates for the management of chronic skin wounds, owing to their good biocompatibility, high water retention capacity, which provides a moist microenvironment, and capacity to promote cell adhesion, proliferation, migration, and differentiation for optimal tissue repair. In this context, the current paper discusses the recent advancements in collagen-based hydrogels as wound dressings, thus highlighting their potential as a future therapeutic approach for skin chronic wound care. Full article

Polypropylene (PP), with its good physical, thermal, and mechanical properties and excellent processing capabilities, has become one of the most used synthetic polymers. It is known that the overall properties of semicrystalline polymers, including PP, are governed by morphology, which is influenced by the crystallization behavior of the polymer under specific conditions. The most important industrial PP remains the isotactic one, and it has been studied extensively for its polymorphic characteristics and crystallization behavior for over half a century. Due to its regular chain structure, isotactic polypropylene (iPP) belongs to the group of polymers with a high tendency for crystallization. The rapid quenching of molten iPP fails to produce a completely amorphous polymer but leads to an intermediate crystalline order. On the other hand, slow cooling yields a material with high crystalline content. The processing conditions that occur in practice and industry are between these two extremes and, in some cases, are even very close. Therefore, the study of limits in processability and the impact of extreme preparation conditions on morphology, structure, thermal, and mechanical properties fills a gap in the current understanding of how the processing conditions of iPP can be used to design the desired properties for specific applications and is in the focus of this research. The first set of samples (Q samples) was obtained by rapid quenching, while the second was prepared by very slow cooling from the melt to room temperature (SC samples). Testing of samples was performed by optical microscopy (OM), scanning electron microscopy (SEM), wide-angle X-ray diffraction (WAXD), Fourier transform infrared spectroscopy (FTIR), differential scanning calorimetry (DSC), dynamic dielectric spectroscopy (DDS), and mechanical measurements. Characterization revealed that slowly cooled samples exhibited a significantly higher degree of crystallinity and larger crystallites (χ ≥ 55% and L₍₁₁₀₎ ≈ 20 nm), compared to quenched samples (χ < 30%, L₍₁₁₀₎ ≤ 3 nm). Mechanical testing showed a drastic contrast: quenched samples exhibited elongation at break > 500%, while slowly cooled samples broke below 15%, reflecting their brittle behavior. For the first time, DDS is applied to investigate molecular mobility differences between processing-dependent structural forms, specifically the mesomorphic (smectic) and α-monoclinic forms. In slowly cooled samples, α relaxation exhibited both enhanced intensity and an upward temperature shift, indicating stronger structural constraints due to a much higher crystalline phase content and significantly larger crystallite size, respectively. These findings provide novel insights into the structure–property–processing relationship, which is crucial for industrial applications. Full article