Dynamic Analysis Research Articles

PCSK9 inhibitors as safer therapeutics for atherosclerotic cardiovascular disease (ASCVD): Pharmacophore design and molecular dynamics analysis.

Cardiovascular disorders are still challenging and are among the deadly diseases. As a major risk factor for atherosclerotic cardiovascular disease, dyslipidemia, and high low-density lipoprotein cholesterol in particular, can be prevented primary and secondary by lipid-lowering medications. Therefore, insights are still needed into designing new drugs with minimal side effects. Proprotein convertase subtilisin/kexin 9 (PCSK9) enzyme catalyses protein-protein interactions with low-density lipoprotein, making it a critical target for designing promising inhibitors compared to statins. Therefore, we screened for potential compounds using a redesigned PCSK9 conformational behaviour to search for a significantly extensive chemical library and investigated the inhibitory mechanisms of the final compounds using integrated computational methods, from ligand essential functional group screening to all-atoms MD simulations and MMGBSA-based binding free energy. The inhibitory mechanisms of the screened compounds compared with the standard inhibitor. K31 and K34 molecules showed stronger interactions for PCSK9, having binding energy (kcal/mol) of -33.39 and -63.51, respectively, against -27.97 of control. The final molecules showed suitable drug-likeness, non-mutagenesis, permeability, and high solubility values. The C-α atoms root mean square deviation and root mean square fluctuation of the bound-PCSK9 complexes showed stable and lower fluctuations compared to apo PCSK9. The findings present a model that unravels the mechanism by which the final molecules proposedly inhibit the PCSK9 function and could further improve the design of novel drugs against cardiovascular diseases.

Comparative analysis of folding and unfolding dynamics and free-energy landscapes in homologous cold shock proteins with variable thermal stabilities

Comparative analysis of folding and unfolding dynamics and free-energy landscapes in homologous cold shock proteins with variable thermal stabilities

Mineral resource rents, fintech technological innovation, digital transformation, and environmental quality in BRI countries: An insight using panel NL-ARDL

The prime objective of the current study is to investigate the impact of mineral resource rents, fintech technological innovation, and digital transformation on the environmental quality of 50 BRI countries. The panel data from the twenty years from 2000 to 2019 of the sample countries are used in the analysis of this study. The study has employed the Panel NL-ARDL to achieve the research objectives. Meanwhile, the current study has employed conventional unit root tests based on Augmented Dickey-Fuller (ADF) unit root tests, such as the LLC and IPS tests. This study employs the method of heterogeneous dynamic panel analysis. The results obtained from the FMOLS regression analysis provide a detailed comprehension of the complex connections between Mineral Resource Rent, Fintech, Digital Transformation, and CO₂ emissions; these findings indicate that countries with advanced financial technology or heavy reliance on Mineral resources are more likely to observe the favorable impacts of digital transformation on the environment. The study results imply that policymakers should investigate all-encompassing policies that exploit these interactions, recognizing that a complete approach can produce substantial and enduring environmental advantages. The interaction variables (NRRDTT and FNTINDTT) demonstrate the negative coefficients that emphasize the combined impact of Mineral resource rent, Finetch, and digital transformation. Policymakers in resource-dependent economies should consider strategies incorporating digitalization and financial technology to optimize their potential impact on environmental sustainability.

Uncertain pedestrian load modeling for structural vibration assessment in footbridge design

The request of material savings in bridge constructions leads to the development towards slender and lightweight structures, which are more sensitive to human-induced vibrations caused by walking pedestrians. The resulting accelerations do not endanger the structural safety, but can be perceived as unpleasant for the user and must therefore be restricted within the limit state of serviceability. For this purpose, the guidelines define acceleration intervals, called as “comfort levels” (CL), which evaluate the comfort of the pedestrians, given the maximum acceleration of the bridge. The model for human-induced loads in the design guideline is based on conservative and deterministic simplifications. In particular, the uncertainties in the human gait parameters are neglected. The main objective of this paper is to develop an uncertain load model for walking pedestrians based on Fourier series. The aleatory and epistemic uncertainties in the human gait parameters are quantified with appropriate uncertainty models relying on available data. In a dynamical finite element analysis, the model is used to simulate groups of pedestrians randomly walking over a bridge to calculate the resulting acceleration amplitudes. The approach is applied to a single span beam and to a real world footbridge using a 3D finite element model. The results are then evaluated within the CLs, enabling new assessment methods.

Experimental and numerical investigation on the hydroelastic response of barge and KVLCC2 ship

In this paper, the hydroelasticity of two segmented ship models (Barge and KVLCC2) is investigated by experimental and numerical methods. A two-way Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA) coupled method is adopted and further validated its accuracy against experimental results. The current approach emphasizes the overall convergence between two solvers, maintaining a strongly coupled manner to comprehensively address the fluid-structure interaction phenomenon, including the added mass effect. A series of experiments of a segmented Barge and KVLCC2 under various wave conditions were firstly conducted. The motions of the models are measured and the displacement Response Amplitude Operators (RAOs) are calculated. The CFD-FEA coupled method is demonstrated in agreement with experimental results by comparing the numerical prediction with the tank test results in terms of motion, affirming the validity and robustness. Finally, the hydroelastic response is discussed and investigated.

Rigid-flexible-soft coupling dynamic modeling and analysis of clustered tensegrity

Rigid-flexible-soft coupling dynamic modeling and analysis of clustered tensegrity

International container intermodal competitiveness: An empirical study from Chinese hub ports

The global energy crisis and environmental degradation have prompted ports to strive for green transformation. Intermodal transport, as a green and efficient form of organization in the transport sector, currently has a lot of room for development. How can the competitiveness of intermodal transport be enhanced while realizing the green sustainability of ports? This study objectively evaluates the competitiveness of international container intermodal competitiveness of hub ports and analyzes the characteristics of 16 Chinese ports from 2011 to 2020. The obstacle degree model (ODM) and the panel Tobit model considering random effects are utilized to explore the complex multidimensional elements affecting the competitiveness of intermodal transport in ports. In addressing the imbalanced characteristics of intermodal transport in ports, a variety of augmentation pathways are devised using the dynamic multi-time period fuzzy-sets qualitative comparative analysis (fsQCA) method. The results found that: (1) The competitiveness of intermodal transport in ports shows a “three echelons” structure, requiring the implementation of appropriate augmentation strategies. (2) Elements affecting the competitiveness of intermodal transport in ports are multidimensional, underscoring the significance of holistically considering internal and external elements. (3) The key to enhancing the competitiveness of intermodal transport in ports lies in striking a balance between economic development and prudent attention to multiple dimensions to ensure sustainability. This study enriches the empirical research on intermodal transport in ports. It provides valuable references for ports seeking new avenues of growth and for governments with effective management practices.

Revolutionizing tire engineering: Finite element analysis and design of an X-shaped spoke structure for non-pneumatic military tires

In this study, we developed a non-pneumatic tire (NPT) specifically designed for military vehicles, such as the Humvee. Our aim was to enhance performance on challenging terrains crucial for mission success. We selected a novel X-shaped polygonal structure for the spoke design owing its exceptional load-carrying capacity and durability. The equivalent modulus, which is the key factor in spoke design, was analytically derived and formulated. This calculated modulus served as a benchmark for achieving the desired vertical stiffness of the NPT. We manufactured a prototype NPT and evaluated its mechanical properties by using a polyurethane (PU) spoke structure. Multiple finite element models of the novel NPT, considering different parameters such as the number of spoke sections, thickness, and modulus of elasticity, were developed while maintaining a consistent equivalent modulus value. Dynamic finite element analysis was then performed to assess the rolling performance of the NPT. We found that the maximum dynamic stress at the spoke was 2.387 MPa, which is 0.398 times the allowable yield strength of the PU spoke. This finding confirms the durability of the novel NPT under dynamic usage in military vehicles, with promising implications for overcoming challenging terrains.

Correlation Analysis of Tunnel Deformation and Internal Force in the Earthquake Based on Tunnel Inclination

An increasing number of studies have shown that the seismic response of shield tunnels differs from that of aboveground structures. While the seismic response of aboveground structures is mainly influenced by the peak acceleration and frequency of the earthquake, the seismic response of shield tunnels is more influenced by the ground displacement due to the surrounding soil layers. In this study, it is not appropriate to follow the seismic concept of aboveground structures. Dynamic time-history analysis is a powerful and effective method to study the seismic response of tunnels in the typical subway in this paper. The analysis results show that the overall levelling of the tunnel will not affect the tunnel too much, and the seismic response of the tunnel is mainly related to the relative displacement of the ground around the tunnel. The analysis results show that the internal force of the tunnel and the tunnel inclination have a good linear relationship, and the tunnel inclination can be used to measure the magnitude of the seismic response of the tunnel. In the seismic design of shield tunnels, the inclination of the tunnel can be taken into account to evaluate the change in the internal forces of the tunnel during earthquakes, which avoids the need for complex dynamic time-history analysis and greatly improves the efficiency of the seismic design of shield tunnels.

Feature-based deformation for flow visualization

AbstractWe present an approach that supports the analysis of flow dynamics in the neighborhood of curved line-type features, such as vortex core lines, attachment lines, and trajectories. We achieve this with continuous deformation to the flow field to straighten such features. This provides “deformed frames of reference”, within which qualitative flow dynamics are better observable with respect to the feature. Our approach operates at interactive rates on graphics hardware, and supports exploration of large and complex datasets by continuously navigating the additional degree of freedom of deformation. We demonstrate the properties and the utility of our approach using synthetic and simulated flow fields, with a focus on the application to vortex core lines. Graphical abstract

Comparative Analysis of Transposable Elements Dynamics in Fish with Different Sex Chromosome Systems.

Transposable elements (TEs) are widespread genomic components with substantial roles in genome evolution and sex chromosome differentiation. In this study, we compared the TE composition of three closely related fish with different sex chromosome systems: Megaleporinus elongatus (Z1Z1Z2Z2/Z1W1Z2W2), Megaleporinus macrocephalus (ZZ/ZW) (both with highly differentiated W sex chromosomes), and Leporinus friderici (without heteromorphic sex chromosomes). We created custom TE libraries for each species using clustering methods and manual annotation and prediction, and we predicted TE temporal dynamics through divergence-based analysis. The TE abundance ranged from 16 to 21% in the three mobilomes, with L. friderici having the lowest overall. Despite the recent amplification of TEs in all three species, we observed differing expansion activities, particularly between the two genera. Both Megaleporinus recently experienced high retrotransposon activity, with a reduction in DNA TEs, which could have implications in sex chromosome composition. In contrast, L. friderici showed the opposite pattern. Therefore, despite having similar TE compositions, Megaleporinus and Leporinus exhibit distinct TE histories that likely evolved after their separation, highlighting a rapid TE expansion over short evolutionary periods.

Corrosion effects of Na2CO3/NaCl molten salt eutectic on 316L stainless steel under isothermal and cycling conditions

Using phase-change materials in thermal energy storage systems for concentrating solar thermal plants can significantly reduce the volume of storage media and, therefore, the cost of the system. However, this approach introduces new material compatibility issues between the thermal energy storage material and the containment vessel in the form of corrosion and thermal transients, which are inherent in these systems. Rods and sheet coupons of stainless steel 316L were corroded for up to 768 h in 59.4/40.6 wt% Na2CO3/NaCl eutectic salt under isothermal (650 °C) and cycled conditions (between 600 and 650 °C). The testing methodologies correspond to actual service conditions, as isothermal degradation may not represent material loss under typical solar thermal cycling conditions. Mass losses were calculated via the Dynamic Gravimetric Analysis technique while Scanning Electron Microscopy utilizing Energy Dispersive Spectroscopy was used to analyze the corrosion layers. Isothermal mass loss plateaued at 75 mg/cm2 at 96 h with no further measurable loss after this time, while cycled samples had a fast initial mass loss rate of 60 mg/cm2 in the first 96 h and lost 0.0331 mg/cm2 every hour thereafter. The results indicate that isothermal samples corrode more slowly than the predominant industry cases of thermal cycling. Spalling is responsible for the degradation in both sets; the continual temperature changes in the cycled samples lead to additional stresses, exacerbating the effect.

An evolutionary game and system dynamics approach for the production and consumption of carbon-labeled products-based on a media monitoring perspective

Carbon label is acknowledged as an effective way to combat the problem of global warming. As a powerful way to encourage individuals to adjust their consumption patterns and to promote the development of green consumption, carbon-labeled products are widely developed in China. To reveal the production and consumption process of carbon-labeled products, the present study constructs a tripartite game model consisting of the government, carbon-labeled products manufacturers and consumers based on a media monitoring perspective. The evolutionary stability strategy (ESS) is firstly determined by solving the replication dynamic equations and stability analysis of the equilibrium point, followed by the strategy analysis and sensitivity analysis through numerical simulation. The results show that media supervision can effectively complement and constrain government supervision. In addition, it can promote enterprises to standardize production and enhance consumers' trust and willingness to buy carbon-labeled products. The introduction of media supervision can well realize the ideal equilibrium of "effective government supervision, enterprise compliance and consumer support for purchase".

Numerical investigation of blunt body's resistance and heat reduction with combination of airway spike and root jet

Aerodynamic heating and impact resistance present significant challenges for hypersonic aircraft. This study introduces a novel multi-jet strategy to enhance both resistance reduction and thermal protection performance of hypersonic aircraft. Computational Fluid Dynamics (CFD) analysis is employed for the aerodynamic evaluation. The results demonstrate that this novel strategy effectively mitigates the shock waves, the peak pressure coefficient and Stanton number have been reduced by 64.3 % and 73.2 %, respectively. Through a comprehensive analysis of the influencing factors, it has been found that increasing the pressure ratio of the root jet significantly lowers the heat flux and pressure on the blunt body, albeit at the cost of an increased total flight resistance. When the nozzle on the side of the airway is oriented perpendicularly to the incoming flow direction, a notable reduction in resistance and aerodynamic heating on the blunt body is noted. By increasing the length-diameter ratio of the spike, a significant decrease in the pressure coefficient of the blunt body is achieved, the Stanton number remains largely unaffected. This study offers insights into the engineering application of strategies for reducing resistance and heat in hypersonic aircraft.

Evaluation of Viscoelastic Performance and Molecular Structures of Natural Rubber/NBR Blends Reinforced by Carbon Black and Nano-Silica

This study focuses on the evaluation of the dynamic mechanical properties, molecular structure, density, hardness, swelling behavior of natural rubber blends (NR) and nitrile rubber (NBR) reinforced with carbon black and/or nano-silica. An experimental work has been conducted to study of the effects of increasing NR content and incorporating nano-silica on the mechanical properties and molecular structure were studied using dynamic mechanical analysis (DMA) and Fourier transform infrared (FTIR) spectroscopy. The results show that increasing the NR content and/or incorporating nano-silica into the elastomer leads to a higher storage modulus with no significant change in the glass transition temperature. FTIR analysis indicates the compatibility of the polyblends and the presence of oxidation of the main polymer chain generated during the grinding of the rubber. Additionally, the results of the swelling study demonstrate that stronger molecular interactions occur on the surface of the nano-silica between the nitrile radicals in the NBR and the silanol (Si-OH) radicals. These findings suggest that blending NR and NBR with carbon black and/or nano-silica can improve the mechanical properties and compatibility of the resulting polyblends, with potential applications in the development of advanced elastomeric materials.

(Thermo)mechanical and chemical characteristics of photochemically crosslinked acrylates from bio‐ and fossil‐based origin

AbstractThe acrylates with oligomers and monomers from (partially) bio‐based feedstock become available at (semi‐)industrial scale, which can be processed through photochemical crosslinking for applications in coatings, additive manufacturing, electronics, or inks. Although fossil‐ and bio‐based acrylates may have a similar chemical composition, it requires good understanding of processing and structure–property relationships as minor changes in microstructure may strongly alter the performance. A comparative study on mechanical properties and chemical structure of bio‐ and fossil‐based acrylates with different functionalities and backbone structures reveals higher ductility of bio‐based acrylates, in relation with a more complex organization of the intrinsic molecular structure. The latter is confirmed by mechanical testing and visco‐elastic characteristics (dynamic mechanical analysis) yielding lower stiffness and higher dampening of bio‐based acrylates, in parallel with a lower glass transition temperature (differential scanning calorimetry). The complex molecular arrangements include a nanoscale morphology with ordered structure (X‐ray diffraction), conformational changes (infrared spectroscopy), and a residual high‐molecular weight fraction (size exclusion chromatography). The visco‐elastic calculations indicate only 4% to 5% lower crosslinking density and around 10% higher mean molar mass of the polymer chains segments between chemical crosslinks and trapped chain entanglements, which explain the unique structure and performance of bio‐based acrylates.

Meta-Learning for Multi-Family Android Malware Classification

With the emergence of smartphones, Android has become a widely used mobile operating system. However, it is vulnerable when encountering various types of attacks. Every day, new malware threatens the security of users’ devices and private data. Many methods have been proposed to classify malicious applications, utilizing static or dynamic analysis for classification. However, previous methods still suffer from unsatisfactory performance due to two challenges. First, they are unable to address the imbalanced data distribution problem, leading to poor performance for malware families with few members. Second, they are unable to address the zero-day malware (zero-day malware refers to malicious applications that exploit unknown vulnerabilities) classification problem. In this paper, we introduce an innovative meta -learning approach for m ulti-family A ndroid m alware c lassification named Meta-MAMC , which uses meta-learning technology to learn meta-knowledge (i.e. the similarities and differences among different malware families) of few-family samples and combines new sampling algorithms to solve the above challenges. Meta-MAMC integrates (i) the meta-knowledge contained within the dataset to guide models in learning to identify unknown malware, and (ii) more accurate and diverse tasks based on novel sampling strategies, as well as directly adapting meta-learning to a new few-sample and zero-sample task to classify families. We have evaluated Meta-MAMC on two popular datasets and a corpus of real-world Android applications. The results demonstrate its efficacy in accurately classifying malicious applications belonging to certain malware families, even achieving 100% classification in some families.

Dynamic analysis of tethered defunct satellites with solar panels

Dynamic analysis of tethered defunct satellites with solar panels

An inversion-based clustering approach for complex clusters

BackgroundThe choice of an appropriate similarity measure plays a pivotal role in the effectiveness of clustering algorithms. However, many conventional measures rely solely on feature values to evaluate the similarity between objects to be clustered. Furthermore, the assumption of feature independence, while valid in certain scenarios, does not hold true for all real-world problems. Hence, considering alternative similarity measures that account for inter-dependencies among features can enhance the effectiveness of clustering in various applications.MethodsIn this paper, we present the Inv measure, a novel similarity measure founded on the concept of inversion. The Inv measure considers the significance of features, the values of all object features, and the feature values of other objects, leading to a comprehensive and precise evaluation of similarity. To assess the performance of our proposed clustering approach that incorporates the Inv measure, we evaluate it on simulated data using the adjusted Rand index.ResultsThe simulation results strongly indicate that inversion-based clustering outperforms other methods in scenarios where clusters are complex, i.e., apparently highly overlapped. This showcases the practicality and effectiveness of the proposed approach, making it a valuable choice for applications that involve complex clusters across various domains.ConclusionsThe inversion-based clustering approach may hold significant value in the healthcare industry, offering possible benefits in tasks like hospital ranking, treatment improvement, and high-risk patient identification. In social media analysis, it may prove valuable for trend detection, sentiment analysis, and user profiling. E-commerce may be able to utilize the approach for product recommendation and customer segmentation. The manufacturing sector may benefit from improved quality control, process optimization, and predictive maintenance. Additionally, the approach may be applied to traffic management and fleet optimization in the transportation domain. Its versatility and effectiveness make it a promising solution for diverse fields, providing valuable insights and optimization opportunities for complex and dynamic data analysis tasks.

Gear Train Optimization of High Speed Machinery by using CATIA and ANSYS

This project aims to optimize gear trains for high-speed machinery using CATIA and ANSYS. Gear trains are crucial in various mechanical systems, especially in high-speed applications where efficiency and reliability are essential. The objective is to combine CATIA for designing and modelling gear trains with ANSYS for analysing their performance under high rotational speeds. Helical gear train use for Reverses Motion design as per requiment of power and motor speed. Same design check for maximium load by load on pinion taken as step of 13K, 15K, 20K, 25K and 30K Newtons are applied on helical gear and check the stress and other parameters material High speed steel. Dynamic analysis model also be carried for mode frequency Keywords: Gear trains, Finite element analysis, CATIA, ANSYS.