Search Results (270)

Background/Objectives: Silodosin (SLD) is a selective α1A-adrenoceptor antagonist used in the treatment of benign prostatic hyperplasia. Bioequivalence failures have been reported for hard capsule formulations, largely due to the effect of disintegrant excipients, making soft capsules a promising alternative dosage form. This study investigated the stability of SLD soft capsules stored in two different packaging materials, PVC/PVDC and AquaBa^®. Methods: Storage temperatures at 25 °C/60%, 30 °C/65% RH, 30 °C/75% RH, and 40 °C/75% RH, and sampling were performed according to the International Council for Harmonisation (ICH) stability conditions. Assays were performed by HPLC and UV, and mass detection. Results: Degradation analysis revealed that temperature played a critical role in SLD degradation and the formation of its primary degradation products, dehydrosilodosin and impurity 1. Conclusions: AquaBa^® demonstrated superior protective properties compared to PVC/PVDC, preserving SLD content above 95% for over 12 months under 25 °C and 30 °C conditions while limiting the formation of degradation products. Nevertheless, impurity 1 exceeded its ICH Q3B (R2) specification limit (0.3%) after six months under all conditions tested, suggesting a critical interaction between SLD and excipients such as Capryol^® 90. Kinetic modeling confirmed first-order degradation kinetics for both dehydrosilodosin and impurity 1, with a faster degradation rate observed in PVC/PVDC blisters. These findings highlight the critical role of packaging in pharmaceutical stability. While AquaBa^® emerges as the preferred option for SLD soft capsules, formulation optimization remains necessary to limit impurity formation, extend shelf life, and ensure regulatory compliance. Full article

In this paper, we study the optimal boundary control of solidification governed by the classical two-phase Stefan problem with a sharp moving interface. The main objective is to formulate an optimal control problem for interface motion using boundary heat-flux control. The control acts as a Neumann heat flux on a designated boundary segment and steers the interface through the Stefan condition. Using an enthalpy formulation, we prove well-posedness under boundary control and establish Lipschitz continuity of the control-to-state map and continuous dependence on the initial data. We then derive first-order necessary optimality conditions using a Lagrangian approach and propose a practical algorithm that couples a semismooth Newton method with Sequential Quadratic Programming (SQP) to compute the optimal boundary flux. Full article

This paper presents the development and analysis of novel explicit special two-derivative Runge–Kutta (STDRK) pairs for the numerical integration of ordinary differential equations (ODEs), with a focus on achieving seventh-order accuracy and embedded fifth-order error estimation. The proposed schemes utilize both the first and second derivatives of the solution, leveraging the identity $y^{\prime \prime }=f^{\prime }\left(y\right)f\left(y\right)$, to attain high-order accuracy while minimizing the number of evaluations of the primary function f. A notable feature of the constructed methods is that they require only a single evaluation of f per step, along with five evaluations of $g=f^{\prime }f$, resulting in a significant reduction in computational cost compared to classical Runge–Kutta methods. The necessary order conditions are derived via an algebraic framework based on compositions with parts not exceeding 2. A supporting Mathematica package facilitates the construction of methods of arbitrary order. A new STDRK pair of orders seven and five is derived. Numerical experiments on standard benchmark problems, including the Prothero–Robinson, Kaps, and Kepler systems, highlight the efficiency and competitive performance of the proposed schemes relative to established Runge–Kutta pairs. Full article

Fractional calculus of variations for a broad class of fractional operators with a general analytic kernel function is considered. Using techniques from variational analysis, we derive first- and second-order necessary optimality conditions, namely the Euler–Lagrange equation, the Weierstrass necessary condition, the Legendre condition, and finally the Legendre–Clebsch condition. Our results are new in the sense that the Euler–Lagrange equation is based on duality theory, and thus build up only with left fractional operators. The Weierstrass necessary condition is a variant of strong necessary optimality condition, and it is derived from maximum condition of Pontryagin for this general analytic kernels. The Legendre–Clebsch condition is obtained under normality assumptions on data because of equality constraints. Full article

Water reservoirs play a crucial role in the environment in many aspects: hydrology, geochemistry, sediment lithology, geo- and biodiversity, landscape, etc. First of all, it is necessary to have accurate information about the spatial distribution of these objects in a given area to assess their size and functioning. Maps and contemporary spatial databases are often incomplete or outdated, especially in regard to small objects, of variable surface area and condition. This article uses the following approach: high-resolution terrain models derived from airborne laser scanning (ALS) were used for visual interpretation of extensive, flat depressions representing water body basins, thus determining the total number of objects, and classifying them as kettle holes, lakes, ponds, and other types of reservoirs (e.g., overbank basins, oxbow lakes). Using an aerial orthophotomap, the objects were subsequently verified as to how many basins are currently occupied by water bodies. The next step was to determine a number of topographic and morphometric parameters for each object in order to assess their functioning conditions. For selected objects, the assessment was expanded to include a geochemical and lithological analysis of the sediments. The study was conducted in the catchment of the Słubia River (136 km²), located in Central Europe, in northwestern Poland. In the Słubia catchment, a total of 931 water body basins were mapped. The dominant forms are kettle holes (<1 ha), representing nearly 80% of all objects. At present, kettle holes are largely devoid of water bodies and subject to a strong human impact. In addition to those, 118 lake basins were identified (>1 ha, the largest being Lake Morzycko, 360 ha), half of which are occupied by water reservoirs. Ponds and other reservoirs were represented by 37 and 47 objects, respectively. From the perspective of contemporary sediment-forming processes in the documented sedimentary basins, the most favorable conditions for biogenous sediment accumulation exist in the catchments of the upper and medium courses of the Słubia River valley. Although the lithological diversity and thickness of individual sediment types in the Słubia catchment represent local features, they corroborate the results of previous telmatologic research conducted in Myślibórz Lakeland. Full article

Large synchronous motors are typically used to drive various load equipment, such as reciprocating compressors. Due to the continuous oscillation of the load, the pulsating torque acting on the main shaft of the synchronous motor will continuously vary with the load changes. This leads to forced oscillations during the dynamic stable operation of the unit, subsequently causing severe problems such as overheating, noise, and failures. Moreover, the rotor length of large synchronous motors is generally greater than the rotor diameter, giving the rotor certain flexible characteristics. During a motor’s operation, it is necessary to cross the first-order critical speed, making resonance highly likely to occur. Therefore, the analysis of dynamic characteristics of large synchronous motors is particularly important. This study investigates the dynamic characteristics of a 7800 kW-18P large synchronous motor rotor system through comprehensive theoretical and experimental analyses. The research encompasses three key aspects: (1) modal analysis comparing fan-equipped and fan-free configurations, (2) harmonic response evaluation, and (3) critical speed determination under concentrated mass conditions. Experimental validation was performed via impact hammer testing, with measured natural frequencies showing a strong correlation with simulated results for the magnetic pole core assembly. The findings not only confirm the operational speed validity but also establish a reliable foundation for the subsequent structural optimization of high-power synchronous machines. Full article

Rock grade is a key indicator guiding tunnel construction. In order to ensure the efficiency and safety of construction, it is necessary to accurately predict the rock grade of the unexcavated part of a tunnel. Currently, geological sketches and geophysical exploration methods can be employed to obtain multi-source and heterogeneous detection data. However, the key challenge lies in how to integrate various types of exploration data to predict the rock grade, which is the focus of the current research. In this paper, we propose a multi-source information fusion-based rock-grade hybrid model for the tunnel construction process. The proposed approach consists of several steps. In the first step, homogenization processing of the acquired multi-source and heterogeneous data, such as geological and TSP (Tunnel Seismic Prediction) detection data, is performed. This primarily includes feature extraction, spatial registration, and the filtering of anomalous data, aimed at enhancing the quality of the data. In the second step, considering the variations in the geological conditions of the construction face, this paper first stratifies the rock grades at the construction face. Subsequently, utilizing TSP detection data, a rock-grade prediction model is established by combining knowledge-driven and data-driven approaches. In the third step, based on the rock grade predictions obtained from the rock grade forecasting model established in the second step, an intelligent decision-making process is conducted by comparing these predictions with the rock grades anticipated during the design stage. This results in the determination of the final rock grade. Finally, the effectiveness of the proposed method is validated through comparison with experimental results. Full article

Since the monotonicity of the best approximant is crucial to establish partial ordering methods, in this paper, we, respectively, characterize the best approximants in Banach function spaces and Lorentz spaces ${\mathrm{\Gamma }}_{p,w}$, in which we especially focus on the monotonicity characterizations. We first study monotonicity characterizations of the metric projection operator onto sublattices in general Banach function spaces by the property $H_g$. The sufficient and necessary conditions for monotonicity of the metric projection onto cones and sublattices are then, respectively, established in ${\mathrm{\Gamma }}_{p,w}$. The Lorentz spaces ${\mathrm{\Gamma }}_{p,w}$ are also shown to be reflexive under the condition $R{B}_p$, which is the basis for the existence of the best approximant. As applications, by establishing the partial ordering methods based on the obtained monotonicity characterizations, the solvability and approximation theorems for best proximity points are deduced without imposing any contractive and compact conditions in ${\mathrm{\Gamma }}_{p,w}$. Our results extend and improve many previous results in the field of the approximation and partial ordering theory. Full article

It is well-known that the necessary and sufficient condition for a connected graph to be unicyclic is that its omega invariant, a recently introduced graph invariant useful in combinatorial and topological calculations, is zero. This condition could be stated as the condition that the order and the size of the graph are equal. Using a recent result saying that the length of the unique cycle could be any integer between 1 and n − a₁ where a₁ is the number of pendant vertices in the graph, two explicit labeling algorithms are provided that attain these extremal values of the first and second Zagreb indices by means of an application of the well-known rearrangement inequality. When the cycle has the maximum length, we obtain the situation where all the pendant vertices are adjacent to the support vertices, the neighbors of the pendant vertices, which are placed only on the unique cycle. This makes it easy to calculate the second Zagreb index, as the contribution of the pendant edges to such indices is fixed, implying that we can only calculate these indices for the edges on the cycle. Full article

Asphalt pavement cracking is an important factor affecting its service life. Under certain conditions, the self-healing behavior of asphalt itself can repair pavement cracks. However, the self-healing ability of asphalt itself is limited. In order to strengthen the self-healing ability of asphalt, the microcapsule wrapped with a repair agent is pre-mixed into the asphalt mixture. When the crack occurs and spreads to the surface of the microcapsule, the microcapsule ruptures and the healing agent flows out to realize the self-healing of the crack. Current microcapsules are mostly prepared with healing agents and bio-oil as core materials, and their high-temperature resistance to rutting is poor. While the epoxy resin contains a three-membered cyclic ether, it can undergo ring-opening polymerization to bond and repair the asphalt matrix. In addition, research on microcapsules mainly focuses on the self-healing properties of microcapsule-modified asphalt. In fact, before adding microcapsules to asphalt to improve its self-healing performance, it is necessary to ensure that the asphalt has a good road performance. On this basis, the self-healing performance of asphalt is improved, thereby extending the service life of asphalt pavement. Therefore, two-component epoxy self-healing microcapsules (E-mic and G-mic) were first prepared in this paper. Then, a temperature scanning test, rheological test of bending beams, and linear amplitude scanning test were, respectively, conducted for the microcapsule/asphalt to evaluate its road performance, including the high-temperature performance, low-temperature crack resistance, and fatigue performance. Finally, the self-healing performance of microcapsules/asphalt was tested. The results showed that the self-developed epoxy self-healing microcapsules were well encapsulated and presented as spherical micron-sized particles. The average particle size of the E-mic was approximately 23.582 μm, while the average particle size of the G-mic was approximately 22.440 μm, exhibiting a good normal distribution. In addition, they can remain intact and unbroken under high-temperature conditions. The results of road performance tests indicated that the microcapsule/asphalt mixture exhibits an excellent high-temperature resistance to permanent deformation, low-temperature crack resistance, and fatigue resistance. The self-healing test demonstrated that the microcapsule/asphalt exhibited an excellent self-healing performance. When the microcapsule content was 4%, the self-healing rate reached its optimal level of 67.8%, which was 149.2% higher than that of the base asphalt. Full article

This article proposes a method to solve nonlinear optimal control problems with arbitrary performance indices and terminal constraints, which is based on the neighboring extremal method and Gauss pseudospectral collocation. Firstly, a quadratic performance index is formulated, which minimizes the second-order variation of the nonlinear performance index and fully considers the deviations in initial states and terminal constraints. Secondly, the first-order necessary conditions are applied to derive the perturbation differential equations involving deviations in state and costate variables. Therefore, a quadratic optimal control problem is formulated, which is subject to such perturbation differential equations. Thirdly, the Gauss pseudospectral collocation is used to transform the differential and integral operators into algebraic operations. Therefore, an analytical solution of the control correction can be successfully derived in the polynomial space, which comes close to the optimal solution. This method has a fast computation speed and low computational complexity due to the discretization at orthogonal points, making it suitable for online applications. Finally, some simulations and comparisons with the optimal solution and other typical methods have been carried out to evaluate the performance of the method. Results show that it not only performs well in computational efficiency and accuracy but also has great adaptability and optimality. Moreover, Monte Carlo simulations have been conducted. The results demonstrate that it has strong robustness and excellent performance even in highly dispersed environments. Full article

Strongly driven fluid and combustion systems typically contain a few, nonlinearly coupled, major flow constituents. It is necessary to identify the flow constituents in order to establish the underlying dynamics and to control these complex flows. Due to non-trivial boundary condition in realistic systems and long-range coupling, it is often difficult to construct accurate models of large-scale reacting systems. The question then arises if these flow constituents can be identified and controlled through analysis of experimental data. The difficulties in such analyses originate in the presence of high levels of noise and irregularities in the flow. A typical time series contains high-frequency noise as well as low-frequency features originating from the near translational invariance of the underlying fluid systems. We propose a pair of approaches to study such data. The first is the use of auto and cross correlation functions. Auto-correlation functions of the time series from a single transducer can be used effectively to demonstrate the low dimensionality of the flow. Second, we show that multi-point time series from appropriately placed transducers can be used to establish spatial characteristics of these flow constituents. The novelty of the approaches lies in the establishment of geometric and dynamic features of the primary flow constituents based on sensor data only, without the need of expensive imaging tools. These methods can potentially identify changes in flow behavior within complex propulsion systems, such as aircraft engines, by utilizing data collected from embedded transducers. Full article

In this paper, a prey–predator diffusion model with isolation and drug treatment control measures for prey infection is studied. The main objective is to find an optimal control that minimizes the population density of infected prey and the costs of isolation and drug treatment for infected prey. Through analysis, the existence and uniqueness of weak solution, as well as the existence and local uniqueness of optimal controls are proven. The first-order necessary condition is derived, and the feasibility of the theoretical proof is verified through numerical simulations. Full article

In this paper, we study the global dynamics, boundedness, existence of invariant intervals, and identification of codimension-two bifurcation sets with detailed bifurcation analysis at the epidemic fixed point of a discrete epidemic model. More precisely, under definite parametric conditions, it is proved that every positive solution of the discrete epidemic model is bounded, and furthermore, we have also constructed the invariant interval. By the linear stability theory, we have derived the sufficient condition, as well as the necessary and sufficient condition(s) under which fixed points obey certain local dynamical characteristics. We also gave the global analysis at fixed points and proved that both disease-free and epidemic fixed points become globally stable under certain conditions and parameters. Next, in order to study the two-parameter bifurcations of the discrete epidemic model at the epidemic fixed point, we first identified the two-parameter bifurcation sets, and then a detailed two-parameter bifurcation analysis is given by the bifurcation theory and affine transformations. Furthermore, we have given the biological interpretations of the theoretical findings. Finally, numerical simulation validated the theoretical results. Full article

Preparative protein crystallization is regarded as an economically sustainable protein purification alternative to chromatography in biotechnological downstream processing. However, protein crystallization is a not-well-understood process that is usually slow and poorly reproducible. A promising strategy for enhancing protein crystallization is exploiting the metastable liquid–liquid phase separation (LLPS) of protein solutions. Here, we report an enhancement of lysozyme-crystallization yield by using a combination of two additives under LLPS conditions. The first additive, NaCl (0.15 M), is necessary to introduce protein–protein attractive interactions and induce LLPS by lowering temperature. The second additive, 4-(2-hydroxyethyl)-1-piperazineethanesulfonate (HEPES, 0.10 M, pH 7.4), accumulates in the metastable protein-rich liquid phase and thermodynamically stabilizes lysozyme crystals. We found that this combination of additives leads to crystallization yields of higher than 90% under LLPS conditions at a lysozyme concentration of 5% by weight and a fairly low ionic strength (0.2 M) within an operational time of the order of one hour. This crystallization yield is more than three-fold larger than that obtained from samples containing NaCl without HEPES at the same pH and ionic strength. Moreover, we determined crystallization yield as a function of incubation time, and temperature below and above the LLPS boundary. As crystallization temperature intersects with LLPS temperature, a significant increase in crystallization yield is observed. This is consistent with LLPS boosting protein crystallization. Our work suggests a possible strategy for increasing the crystallization success of other proteins, with applications in protein purification. Full article