Search Results (627)

This study employed an integrated computational approach to discover novel nucleoprotein (NP) inhibitors for influenza A virus (IAV). Beginning with virtual screening of over 10 million compounds using Schrödinger’s Glide module (HTVS, SP, XP docking), the workflow identified promising candidates with favorable binding energies. Subsequent molecular mechanics/generalized born surface area (MM-GBSA) calculations and 100 ns molecular dynamics (MD) simulations prioritized 16 compounds for experimental validation. Surface plasmon resonance (SPR) assays revealed that compounds 8, 13, and 14 demonstrated superior target engagement, showing equilibrium dissociation constants (K_D) of 7.85 × 10⁻⁵ M, 3.82 × 10⁻⁵ M, and 6.97 × 10⁻⁵ M, respectively. Molecular dynamics, alanine scanning mutagenesis, and quantum mechanics/molecular mechanics (QM/MM) analysis were conducted to analyze the binding modes, providing a reference for the design of subsequent compounds. These findings validate the efficacy of structure-based virtual screening in identifying high-affinity NP inhibitors and provide insights for the development of broad-spectrum anti-influenza therapeutics. Full article

Forests are critical ecosystems that play a fundamental role in supporting biodiversity and maintaining climate stability. However, forest monitoring and exploration present huge challenges due to the vast scale and complex terrain. This paper proposes a novel bionic robot, PteroBot, designed to support a new paradigm for forest exploration inspired by the locomotion of Pteromyini. PteroBot is capable of regulating its gliding posture via a flexible membrane, enabling low-energy and low-disturbance mobility within forest environments. An adaptive gliding control system tailored to the robot’s structure is developed and its effectiveness is validated through aerodynamic analysis, simulation, and experimental testing. Results show that under a cascaded closed-loop attitude controller, PteroBot achieves an average glide ratio of 2.02 and demonstrates controllable turning via attitude modulation. Additionally, comparative tests with UAVs demonstrate that PteroBot offers significant advantages in energy efficiency and acoustic disturbance. Experimental outcomes confirm that PteroBot offers a biologically inspired and ecologically compatible solution for forest exploration, with strong potential in applications such as environmental monitoring, habitat assessment, and covert reconnaissance. Full article

Anti-apoptotic Bcl-2 family proteins (Bcl-2, Bcl-xL, and Mcl-1), are often overexpressed in cancer, which aids tumor growth and treatment resistance. As a result, these proteins are excellent candidates for novel anticancer drugs. Within this study a virtual library of betuline derivatives was built and screened for possible Bcl-2, Bcl-XL, and Mcl-1 inhibitors. For every target, molecular docking simulations were performed using two different engines (AutoDock Vina and Glide). The ligands that most frequently appeared among the top candidates were shortlisted after comparing the top-20 hits from both docking scoring functions. To assess binding stability, five of these promising compounds were chosen and run through 100 ns molecular dynamics (MD) simulations in complex with every target protein. Key persistent intermolecular contacts were identified from MD contact frequency histograms, and stability was evaluated using root-mean-square deviation (RMSD) profiles of protein–ligand complexes following equilibration. Additionally, Prime MM-GBSA binding energies (ΔG_bind) for the 15 docked complexes were computed, and ligand efficiency was reported. Two substances, BOxNaf1 and BT3, stood out among the screened derivatives as the most stable binders to all three Bcl-2 family targets according to the dual docking and MD analysis approach. When the MM-GBSA and RMSF/rGyr data are considered alongside docking and MD stability, BOxNaf1 and BOxPhCl1 emerge as the most compelling dual/multi-target candidates, whereas BT3, though MD stable, shows weaker MM-GBSA energetics and is retained as a lower-priority backup chemotype. Full article

Under stringent flight constraint conditions, trajectory optimization of Hypersonic Vehicles (HV) is crucial for guidance. Therefore, this paper proposes an hp-adaptive dynamic trust region SCP method to address the problems of initial value sensitivity and low computational efficiency that arise in traditional Sequential Convex Programming (SCP) methods during HV trajectory optimization. First, the discrete symmetry principle is utilized to simplify the boundary conditions and constraint handling of the trajectory model while combining scale transformation invariance to achieve nondimensionalization of the model’s physical quantities, thereby constructing the trajectory optimization model. On this basis, the hp-adaptive method is adopted to dynamically adjust the discretization step size and polynomial approximation order, and combined with an adaptive adjustment strategy for the trust region radius, to improve computational efficiency while ensuring optimization accuracy. Finally, the effectiveness of the algorithm is validated through optimizing the gliding phase of HV, and compared with GPOPS-II and fixed trust region SCP methods. The experimental results show that the algorithm has superiority in improving convergence speed, computational efficiency and solution accuracy, with its performance significantly outperforming traditional trajectory optimization schemes. Full article

Low-level wind shear (LLWS) is a critical issue in aviation meteorology, posing serious risks to flight safety—especially at plateau airports with high elevation and complex terrain. This study investigates a convective wind shear event at Xining Airport on 29 May 2021. Multi-source observations—including the Doppler Wind Lidar (DWL), the Doppler weather radar (DWR), reanalysis datasets, and automated weather observation systems (AWOS)—were integrated to examine the event’s fine-scale structure and temporal evolution. High-resolution simulations were conducted using the Large Eddy Simulation (LES) framework within the Weather Research and Forecasting (WRF) model. Results indicate that the formation of this wind shear was jointly triggered by convective downdrafts and the gust front. A northwesterly flow with peak wind speeds of 18 m/s intruded eastward across the runway, generating multiple radial velocity couplets on the eastern side, closely associated with mesoscale convergence and divergence. A vertical shear layer developed around 700 m above ground level, and the critical wind shear during aircraft go-around was linked to two convergence zones east of the runway. The event lasted about 30 min, producing abrupt changes in wind direction and vertical velocity, potentially causing flight path deviation and landing offset. Analysis of horizontal, vertical, and glide-path wind fields reveals the spatiotemporal evolution of the wind shear and its impact on aviation safety. The WRF-LES accurately captured key features such as wind shifts, speed surges, and vertical disturbances, with strong agreement to observations. The integration of multi-source observations with WRF-LES improves the accuracy and timeliness of wind shear detection and warning, providing valuable scientific support for enhancing safety at plateau airports. Full article

This study employs first-principles calculations combined with the Special Quasirandom Structure (SQS) technique to investigate the impact of three interstitial elements C, N, and O, on the mechanical properties and stacking fault energy (SFE) of NiCoCr medium-entropy alloys. The results indicate that non-metallic O, C, and N tend to occupy octahedral interstitial sites, which can effectively release stress concentration and enhance the strength and deformability of the material. Differential charge density analysis shows that the dissolution of C, N, and O significantly alters the surrounding electronic environment, strengthening the interaction between solute atoms and metal atoms, thereby hindering dislocation glide and increasing the strength and hardness of the material. Elastic property analysis indicates that NiCoCr alloys doped with C, N, and O exhibit good ductility and anisotropic characteristics. Furthermore, the study of stacking fault energy reveals that the doping with C, N, and O can significantly increase the stacking fault energy of NiCoCr alloys, thereby optimizing their mechanical properties. These findings provide theoretical evidence for the design of advanced high-entropy alloys that combine high strength with good ductility. Full article

This paper proposes a closed-loop nonlinear model predictive control for the first time for the trajectory tracking of a spaceplane descending and gliding on Mars. Previous studies presented the optimization of descending trajectory solving optimal control problems to reach a specific region (longitude, latitude, and altitude) by the end of the atmospheric flight. Following those approaches, in this work, an optimal trajectory was selected for a semi-optimal controller, specifically the nonlinear model predictive control. This controller and its robustness were validated through Monte Carlo simulations, demonstrating that it is robust enough to direct the spaceplane along the reference path, even when the atmospheric density changes by 15% of the standard deviation. Full article

Hybrid underwater gliders (HUGs) combine buoyancy-driven gliding with propeller-assisted propulsion, offering extended endurance and enhanced mobility for complex underwater missions. However, precise depth control remains challenging due to system uncertainties, environmental disturbances, and inadequate adaptability of conventional control methods. This study proposes a novel optimized line-of-sight active disturbance rejection control (OLOS-ADRC) strategy for HUG depth tracking in the vertical plane. First, an Optimized Line-of-Sight (OLOS) guidance dynamically adjusts the look-ahead distance based on real-time cross-track error and velocity, mitigating error accumulation during path following. Second, a Tangent Sigmoid-based Tracking Differentiator (TSTD) enhances the disturbance estimation capability of the Extended State Observer (ESO) within the Active Disturbance Rejection Control (ADRC) framework, improving robustness against unmodeled dynamics and ocean currents. As a critical step before costly sea trials, this study establishes a high-fidelity simulation environment to validate the proposed method. The comparative experiments under gliding and hybrid propulsion modes demonstrated that OLOS-ADRC has significant advantages: the root mean square error (RMSE) for depth tracking was reduced by 83% compared to traditional ADRC, the root mean square error for pitch angle was decreased by 32%, and the stabilization time was shortened by 14%. This method effectively handles ocean current interference through real-time disturbance compensation, providing a reliable solution for high-precision HUG motion control. The simulation results provide a convincing foundation for future field validation in oceanic environments. Despite these improvements, the study is limited to vertical plane control and simulations; future work will involve full ocean trials and 3D path tracking. Full article

This article examines the impact of an undetected Instrument Landing System (ILS) failure on crew situational awareness. A literature review of similar aviation accidents is presented, highlighting the recurring challenge of misleading instrument indications and their influence on approach safety. The research environment consisted of flight simulator replicating both ideal and accident-weather conditions at two airports, with the final scenario involving a simulated ILS receiver malfunction providing erroneous yet seemingly valid indications. Six pilots with varying flight hours participated, conducting four simulated approaches under different conditions. Flight path stability, deviation from glide slope and course, approach speed, and decision-making were recorded and analyzed. The results indicate that experienced pilots detected inconsistencies more quickly, maintained more stable control inputs, and initiated go-arounds earlier, while less experienced pilots required more time but were still able to correctly assess the risks. The primary goal of this research was to identify cognitive mechanisms and operational decision-making processes under simulated conditions, not to establish universally generalizable outcomes. The findings underline the importance of simulator-based training incorporating unexpected navigation system failures to reinforce cross-checking habits, enhance situational awareness, and improve decision-making during critical phases of flight. Full article

Research on morphing aircraft that can change geometry to achieve the desired performance and stability under different flight conditions has been ongoing for many years. This study provides a conceptual-level, preliminary analysis of the impact of symmetrically changing the wing sweep angle on aircraft performance and stability. The T-37B-like aircraft is selected as a base to compare the results with T-37B’s known data. The T-37B-like aircraft is modeled in both Digital DATCOM and Open VSP software. Changes in aircraft performance and stability are demonstrated for changes in the wing sweep angle between −10° and 40°. When 0° and 40° wing sweep configurations are compared, it is observed that the 40° wing sweep configuration performs better in terms of climb and range, but worse in terms of takeoff distance, glide, approach, and radius of turn. In terms of static stability, it has a positive effect on longitudinal stability. While it does not significantly affect lateral stability overall, it contributes positively to stability around the roll axis. Changing the symmetrical wing sweep angle is expected to improve certain performance and stability parameters while degrading others. A symmetrical variable-sweep wing offers advantages by adjusting to the optimal sweep angle for each flight phase. Thus, benefits can be fully utilized, and drawbacks minimized. However, it entails design, mechanical, weight, and financial costs. Therefore, whether the performance and stability benefits outweigh these costs must be evaluated on an aircraft-specific basis. Full article

Gliders are engineless aircraft capable of maintaining altitude for extended periods and achieving long ranges. This paper presents an optimal aerodynamic design method for flying wing gliders, leveraging a combination of artificial neural networks (ANNs) as a surrogate model and genetic algorithms (GAs) for optimization. Data for training the ANN is generated using the vortex-lattice method (VLM). The study identifies optimal aerodynamic shapes for two objectives: maximum flight endurance and maximum range. A key finding is the inherent conflict between aerodynamic performance and static stability in tailless designs. By introducing a stability constraint via a penalty function, we successfully generate stable and high-performance configurations. For instance, the stabilized RG15 airfoil design achieves a maximum glide ratio of 24.1 with a robust 5.1% static margin. This represents a calculated 11.5% performance reduction compared to its unstable theoretical optimum, quantitatively demonstrating the crucial trade-off between stability and performance. The methodology provides a computationally efficient path to designing practical, high-performance, and inherently stable flying wing gliders. Full article

As an essential technology for precision airdrop missions, parafoil systems have gained widespread adoption in military and civilian applications due to their superior glide performance and maneuverability compared to conventional parachutes. Addressing the trajectory-tracking control challenges of the parafoil system under significant wind disturbances, characterized by wind uncertainty and system underactuation, this paper proposes a stochastic model predictive control (SMPC) framework based on Markov-based multi-scenario optimization. Traditional deterministic model predictive control (MPC) methods often exhibit excessive conservatism due to reliance on worst-case assumptions and fail to capture the time-varying nature of real-world wind fields. To address these limitations, a high-fidelity dynamic model is developed to accurately characterize aerodynamic coupling effects, overcoming the oversimplifications of conventional three-degree-of-freedom point-mass models. Leveraging Markov state transitions, multiple wind-disturbance scenarios are dynamically generated, effectively overcoming the limitations of independent and identically distributed hypotheses in modeling realistic wind variations. A probabilistic constraint-reconstruction strategy combined with a rolling time-domain covariance update mechanism mitigates uncertainties and enables cooperative optimization of inner-loop attitude stabilization and outer-loop trajectory tracking. The simulation results demonstrate that the SMPC framework achieves superior comprehensive performance compared to deterministic MPC, evidenced by significant reductions in maximum position error, average position error, and control effort variation rate, along with a 94% tracking success rate. By balancing robustness, tracking precision, and computational efficiency, the method provides a theoretical foundation and a promising simulation-validated solution for airdrop missions. Full article

Eutectic FeNiMnAl multi-principal element alloys exhibit exceptional strength–ductility synergy, yet their dynamic deformation mechanisms remain poorly characterized. This study employs in situ transmission electron microscopy to investigate dislocation-mediated plasticity in Fe₃₆Ni₁₈Mn₃₃Al₁₃—a lamellar FCC/B2 alloy with balanced properties. Real-time observations under tensile loading (at a strain rate of 0.1 μm/s, with a resolution of ~2 nm) reveal coordinated dislocation planar glide, cross-slip at obstacles, and pile-up formation at phase boundaries. Planar slip bands dominate early deformation, while cross-slip facilitates barrier bypass and strain homogenization. The coarse microstructure of Fe₃₆Ni₁₈Mn₃₃Al₁₃ promotes extensive dislocation storage, reducing strength but enhancing ductility compared to finer FeNiMnAl variants. Full article

In this paper, a hierarchical optimization framework combining Bayesian and pseudospectral approaches is developed to solve the challenging problem of hybrid trajectory planning for energy-augmented hypersonic skip–glide vehicles that have plane symmetry. Traditional trajectory optimization methods usually deal with discrete energy injection timing and continuous flight control variables separately, yielding suboptimal solutions. To achieve global optimality, this proposed framework optimizes the discrete and continuous variables simultaneously, conducting Bayesian optimization for discrete global search and hp-adaptive pseudospectral algorithm for local continuous optimization. A rigorous dynamic model, considering Earth’s oblateness, rotation, aerodynamic interactions, and thrust dynamics, is established to ensure high-fidelity trajectory simulation. Numerical simulation through three representative tests indicates significant improvements: The hp-adaptive pseudospectral method achieves over 20% higher computational efficiency and accuracy compared to standard pseudospectral methods. Bayesian optimization demonstrates rapid global convergence within 22 iterations, achieving the optimal single augmentation timing that enhances flight range by up to 55.08%. Further, comprehensive joint optimization with double energy augmentation yields an additional 7.5% range extension compared to randomly selected augmentation timings. The results verify that the proposed hierarchical framework substantially improves the planned trajectory performance and adaptability to the skip–glide trajectories with hybrid maneuver. Full article

Swarm Intelligence (SI) algorithms were applied widely in solving complex optimization problems because they are simple, flexible, and efficient. The current paper proposes a new SI algorithm, which is based on the bird-like actions of swallows, which have highly synchronized behaviors of foraging and migration. The optimization algorithm (SWSO) makes use of these behaviors to boost the ability of exploration and exploitation in the optimization process. Unlike other birds, swallows are known to be so precise when performing fast directional alterations and making intricate aerial acrobatics during foraging. Moreover, the flight patterns of swallows are very efficient; they have extensive capabilities to transition between flapping and gliding with ease to save energy over long distances during migration. This allows instantaneous changes of wing shape variations to optimize performance in any number of flying conditions. The model used by the SWSO algorithm combines these biologically inspired flight dynamics into a new computational model that is aimed at enhancing search performance in rugged terrain. The design of the algorithm simulates the swallow’s social behavior and energy-saving behavior, converting it into exploration, exploitation, control mechanisms, and convergence control. In order to verify its effectiveness, (SWSO) is applied to many benchmark problems, such as unimodal, multimodal, fixed-dimension functions, and a benchmark CEC2019, which consists of some of the most widely used benchmark functions. Comparative tests are conducted against more than 30 metaheuristic algorithms that are regarded as state-of-the-art, developed so far, including PSO, MFO, WOA, GWO, and GA, among others. The measures of performance included best fitness, rate of convergence, robustness, and statistical significance. Moreover, the use of (SWSO) in solving real-life engineering design problems is used to prove (SWSO)’s practicality and generality. The results confirm that the proposed algorithm offers a competitive and reliable solution methodology, making it a valuable addition to the field of swarm-based optimization. Full article