Drug nanosuspensions offer a promising approach to improve bioavailability for poorly soluble drug candidates. Such formulations often necessitate the inclusion of an excipient to stabilize the drug nanoparticles. However, a rationale to choose the correct excipient for a given drug candidate remains unclear. To gain molecular insight into formulation design, this work first utilizes molecular dynamics simulation to computationally investigate drug-excipient interactions for a number of combinations that have been previously studied experimentally. We find that hydrophobic interactions drive excipient adsorption to drug nanoparticles, and that the fraction of polar surface area serves as a predictor for experimental measurements of nanosuspension stability. To test these ideas prospectively, we applied our model to an uncharacterized drug compound, GDC-0810. Our simulations predicted that salt forms of GDC-0810 would lead to more stable nanosuspensions than the neutral form; therefore, we tested the stability of salt GDC-0810 nanosuspensions and found that the salt form readily formed nanosuspensions even without excipient. To avoid computationally expensive simulations in the future, we extended our model by showing that simple, two-dimensional properties of the single drug molecule can be used to rationalize nanosuspension design without simulation. In all, our work demonstrates how computational tools can provide molecular insight into drug-excipient interactions, and aid in rational formulation design.

The article presents the stages of modeling and simulation of a new design of a wheelchair with the option of moving up and down stairs. These analyzes were aimed at the synthesis of the de-sign parameters and parameters of the sensor and control systems. The simulation results were verified by experimentally testing the prototype.

Zirconium nitride (Zr-N) is a candidate material for inert matric fuel elements in breeder reactors. They have shown exceptional resistance to radiative corrosive environments. They have shown excellent resistance to radiation stability at operational conditions in current generation reactors. But being a candidate nuclear fuel material in generation reactors, their radiation stability at higher temperature conditions observed has not been reported. We have employed molecular dynamics simulations to study the damage cascades and radiation stability of ZrN at 600K. The process of primary damage evolution by considering varying overlapping cascades with 10, 20 keV incident PKA’s reported here. The defects interface interaction and diffusion mechanism at the interface are reported.

We extend our high-resolution MRI-based Finite Element (FE) head model, previously presented and validated in [1–3], by considering the heterogeneities of the white matter structures captured through the use of Magnetic Resonance Elastography (MRE). This approach imparts more sophistication to our numerical model and yields results that more closely match experimental results. It is found that the peak pressure more closely matches the experiments as compared to the heterogeneous case. Qualitatively, we find differences in stress wave propagation near the corpus callosum and the corona radiata, which are stiffer on average than the global white matter. We are able to study the effects of these stiff structures on transient stress wave propagation within the cerebrum, something that cannot be done with a homogenized material model.

Tissues of the brain, especially white matter, are extremely heterogeneous - with constitutive response varying spatially. In this paper, we implement a high-resolution Finite Element (FE) head model where heterogeneities of white matter structures are introduced through Magnetic Resonance Elastography (MRE) experiments. Displacement of white matter under shear wave excitation is captured and the material properties determined though an inversion algorithm are directly used in the FE model. This approach is found to improve model predictions when compared to experimental results. In the first place, responses in the cerebrum near stiff structures such as the corpus callosum and corona radiata are markedly different compared with a homogenized material model. Additionally, the heterogeneities introduce additional attenuation of the shear wave due to wave scattering within the cerebrum.

Markov chain Monte Carlo sampling propagators, including numerical integrators for stochastic dynamics, are central to the calculation of thermodynamic quantities and determination of structure for molecular systems. Efficiency is paramount, and to a great extent, this is determined by the integrated autocorrelation time (IAcT). This quantity varies depending on the observable that is being estimated. It is suggested that it is the maximum of the IAcT over all observables that is the relevant metric. Reviewed here is a method for estimating this quantity. For reversible propagators (which are those that satisfy detailed balance), the maximum IAcT is determined by the spectral gap in the forward transfer operator, but for irreversible propagators, the maximum IAcT can be far less than or greater than what might be inferred from the spectral gap. This is consistent with recent theoretical results (not to mention past practical experience) suggesting that irreversible propagators generally perform better if not much better than reversible ones. Typical irreversible propagators involve a parameter controlling the mix of ballistic and diffusive movement. To gain insight into the effect of the damping parameter for Langevin dynamics, its optimal value is obtained here for a multidimensional quadratic potential energy function.

The optimization methods are increasingly used to solve challenging problems of aeronautical engineering. Typically, the optimization methods are utilized in design of aircraft airframe or its structure. The presented study is focused on an improvement of aircraft-flight-control procedures through the numerical optimization approach. The optimization problems concern selected phases of flight of light gyroplane - a rotorcraft using an unpowered rotor in autorotation to develop lift and an engine-powered propeller to provide thrust. An original methodology of computational simulation of rotorcraft flight was developed and implemented. In this approach the aircraft-motion equations are solved step-by-step, simultaneously with the solution of the Unsteady Reynolds-Averaged Navier-Stokes equations, which is conducted to assess aerodynamic forces acting on the aircraft. As a numerical optimization method, the BFGS algorithm was adapted. The developed methodology was applied to optimize the flight-control procedures in selected stages of gyroplane flight in direct proximity of the ground, where properly conducted control of the aircraft is critical to ensure flight safety and performance. The results of conducted computational optimizations proved qualitative correctness of the developed methodology. The research results can be helpful in design of easy-to-control gyroplanes and also in the training of pilots of this type of rotorcraft.

Distant Retrograde Orbits in the Earth-Moon system are gaining in popularity as stable `parking' orbits for various conceptual missions. To investigate the stability of potential Distant Retrograde Orbits, simulations were executed, with propagation running over a thirty-year period. Initial conditions for the vehicle state were limited such that the position and velocity vectors were in the Earth-Moon orbital plane, with the velocity oriented such that it would produce retrograde motion about Moon. The resulting trajectories were investigated for stability against the eccentric relative orbits of Earth and Moon in an environment that also included gravitational perturbations from Sun, Jupiter, and Venus, and the effects of radiation pressure. The results appear to indicate that stability is enhanced for certain resonant states within the Earth-Moon system.

Heat dissipation from Li-ion batteries is a potential safety issue for large-scale energy storage applications. Maintaining low and uniform temperature distribution, and low energy consumption of the battery storage is very important. We studied the fluid dynamics and heat transfer phenomena of a single cell, 16-cell modules, battery packs, and cabinet through computer simulations and experimental measurements. The results show that the temperature distribution of single cell is relatively uniform when the cell is facing the air flow. In a module, very high air flow rate and large gap between the cells can reduce the cell temperature. A pack with a good thermally conductive case is very important to ensure good heat dissipation of the battery module. Due to limited space in the cabinet, additional air inlets and outlets can be opened outside of the cabinet to slightly lower the pack temperature. Installing fins outside the cabinet can also slightly reduce the temperature inside the cabinet. Liquid cooling medium, such as water, is much better than the air-cooling medium.

A large amount of steel slag (SS) and CO2 are generated in the steelmaking process. The indirect CO2 capture using SS is a promising way for co-treatment of the wastes. Ammonium salt solution is widely used to extract Ca2+ from the SS since it is recyclable. Several works have focus on improving the carbonation rate by adjusting various parameters (e.g., temperature and pH). However, there is little detail information about the associating behaviors and interaction strength between the various ions in the ammonia solution during the carbonation process. In this work, the Ca2+–CO32-–NH4+–Cl-–H2O system was established by using Material studio software. The effects of temperature and concentration of CO32- on CaCO3 growth were explored at the atomic scale by calculating the binding energy, mean square displacement, and diffusion coefficient between particles. Furthermore, the microstructure, bonding characteristics, and occurrence behavior of each particle were studied though molecular dynamics simulation methods. The results showed that with the increase of temperature (20–80 ℃), the binding ability and diffusion coefficients of Ca2+ and CO32- increase in the system, which is beneficial to the formation of CaCO3 clusters. With the increase of the concentration of CO32- (15–25 vol.%), the binding ability and diffusion coefficient of Ca2+ and CO32- in the system are enhanced, which is beneficial to the formation of CaCO3 clusters.

Micro-pollutants such as 17β-Estradiol (E2) have been detected in different water resources and their negative effects on the environment and organisms have been observed. Aptamers are established as a possible detection tool, but the underlying ligand binding is largely unexplored. In this study, a previously described 35-mer E2-specific aptamer was used to analyse the binding characteristics between E2 and the aptamer with a MD simulation in an aqueous medium. Because there is no 3D structure information available for this aptamer, it was modeled using coarse-grained modeling method. The E2 ligand was positioned inside a potential binding area of the predicted aptamer structure, the complex was used for an 25 ns MD simulation, and the interactions were examined for each time step. We identified E2-specific bases within the interior loop of the aptamer and also demonstrated the influence of frequently underestimated water-mediated hydrogen bonds. The study contributes to the understanding of the behavior of ligands binding with aptamer structure in an aqueous solution. The developed workflow allows generating and examining further appealing ligand-aptamer complexes.

In this paper, the boiling flow inside a nanochannel with 700000 argon particle has been simulated by molecular dynamics (MD) simulation. This approach has been employed to analysis the superheated flow and its heat transfer pattern as well. For all simulations an external thrust force varying from 1 PN to 12 PN is exerted on inlet nanoparticles along the channel to have the forced annular boiling flow. Computations reveal that saturation condition and superheat degree have significant impacts on the liquid-vapor interface. Furthermore, because of the major influence of surface tension throughout a nanochannel, the x-velocity of liquid film and vapor core has not considerable fluctuations and stay smooth. All provided results show the behaviors completely similar to the available outcomes in the literature.

Magnetorheological fluids (MRFs) are smart materials consisting of micro-scale magnetizable particles suspended in a carrier fluid. The rheological properties of a MRF can be changed from a fluid-state to a solid-state upon the application of an external magnetic field. This study reports the development of a particle-level simulation code for magnetic solid spheres moving through an incompressible Newtonian carrier fluid. The numerical algorithm is implemented within an open-source finite-volume solver coupled with an immersed boundary method (FVM-IBM) to perform fully-resolved simulations. The particulate phase of the MRF is modeled using the discrete element method (DEM). The resultant force acting on the particles due to the external magnetic field (i.e., magnetostatic polarization force) is computed based on the Clausius-Mossotti relationship. The fixed and mutual dipole magnetic models are then used to account for the magnetic (MAG) interactions between particles. Several benchmark flows were simulated using the newly-developed FVM-IBM-DEM-MAG algorithm to assess the accuracy and robustness of the calculations. First, the sedimentation of two spheres in a rectangular duct containing a Newtonian fluid is computed without the presence of an external magnetic field, mimicking the so-called drafting-kissing-tumbling (DKT) phenomenon. The numerical results obtained for the DKT case study are verified against published data from the scientific literature. Second, we activate both the magnetostatic polarization and the dipole-dipole forces and resultant torques between the spheres for the DKT case study. Next, we study the robustness of the FVM-IBM-DEM-MAG solver by computing multi-particle chaining (i.e., particle assembly) in a two-dimensional (2D) domain for area volume fractions of 20% (260 particles) and 30% (390 particles) under vertical and horizontal magnetic fields. Finally, the fourth computational experiment describes the multi-particle chaining in a three-dimensional (3D) domain allowing to study fully-resolved MRF simulations of 580 magnetic particles under vertical and horizontal magnetic fields.

This project aims to simulate and analyze population dynamics in evolutionary systems, using stochastic differential equations and probabilistic rules for crossbreeding and benefits. The study employs advanced computational techniques to model the evolution of populations over an extended period. Specifically, we explore a scenario with ten distinct groups, each starting with an equal population and evolving under defined genetic and cooperative behaviors. The simulation spans 1000 years, incorporating individual lifespans, stochastic updates, and probabilistic interactions. To ensure robustness and reliability, the study includes detailed statistical analysis, encompassing descriptive statistics, confidence intervals, and ANOVA tests. We further visualize the temporal behavior of populations and subpopulations, providing insights into the evolutionary dynamics and stability of the system. The results demonstrate the effectiveness of balanced cooperation and genetic diversity in maintaining stable population distributions. The project showcases the integration of mathematical modeling, statistical analysis, and computational simulations, contributing valuable insights into evolutionary biology and complex systems. It highlights the importance of interdisciplinary approaches in understanding and predicting population behaviors, with implications for both theoretical research and practical applications in fields such as ecology, genetics, probability and social sciences.

In view of the inability to directly and accurately obtain the athlete's aerodynamic force during take-off phase through wind tunnel test, the athlete's aerodynamic force and surrounding flow field form under different take-off postures are obtained through numerical simulation research, and the effects of different take-off modes on the aerodynamic characteristics during take-off in ski jumping are discussed. The multi-body system composed of the athlete and skis was selected as the research objects. By using partially averaged Navier-Stokes (PANS) turbulence model and 3D numerical simulation of computational fluid dynamics (CFD), the aerodynamic characteristics of the athlete under different take-off postures were predicted. Take-off modes include knee-push-hip (KPH) mode and hip-drive-knee (HDK) mode, and the hip joint angle of HDK mode is significantly greater than KPH mode. First, the aerodynamic force ratio of the athlete’s torso and legs is obviously large. Although the aerodynamic force of arms themselves is not obvious, they have a great impact on the overall aerodynamic characteristics of the athlete, so the posture of arms cannot be ignored. Then, the total drag and moment of HDK mode are significantly higher than that of KPH mode, and the lift-to-drag ratio of HDK mode is significantly lower than that of KPH mode. At first the total lift of HDK mode is higher than that of KPH mode, but in the last attitude the total lift of HDK mode does not rise but fall, and finally the total lift of HDK mode is lower than KPH mode. The aerodynamic characteristics change dramatically during take-off phase, and the aerodynamic characteristics of the two take-off modes are quite different, and these changes and differences are difficult to be observed in real training and competition site. KPH mode has obvious aerodynamic advantage over HDK mode. During the take-off process, the athlete should increasethe force generated by the knee joint extension and appropriately reduce the speed of hip joint extension, and control the using force order of the lower limb joints, and push hip joint extension by knee joint extension, in order to avoid issues such as the hip joint angle is too large, the hip joint extension angle is too fast, the center of gravity is to back and other problems. Studying the aerodynamic characteristics during the take-off phase provides valuable insights for athletes to achieve favorable flight postures after take-off, offering scientific guidance to improve training strategies and enhance competitive performance.

Groundwater degradation is a global problem linked to irrigation agriculture and aggravated by climate change. In drylands, where aquifer recharge is low, irrigation has emerged as an engine of economic growth. This problem falls under the paradigm of desertification, as it fits the definition of this complex problem in that the degradation of drylands is due to climatic variations and inappropriate human activities. Land Degradation Neutrality (LDN), the response of the United Nations Convention to Combat Desertification to the lack of progress in tackling desertification, is integrated into Sustainable Development Goal 15.3 and provides the adequate framework for implementing effective solutions. LDN prioritizes prevention strategies, and early warning systems coupled to integrated simulation models is a sound approach. We analyze the dynamics of a coastal aquifer in southern Spain, a “desertification landscape” according to the Spanish National Action Plan to Combat Desertification. For this purpose, we have (i) adapted a generic desertification model that considers socio-ecological systems as a particular case of predator-prey systems; and (ii) coupled to this model a risk analysis to calculate the probabilities of groundwater salinization under the current scenario of water resources use, driven by the expansion of greenhouse agriculture supported by external water transfer. The risk of desertification is close to 100%: groundwater salinity is 40 dS m-1 (well above tomato tolerance, 3.5 dS m-1), and 2.4 Mm3 yr–1 water transfer is needed to support the 631 ha of greenhouses. This worrying result suggests that complimentary solutions should be promoted to deactivate the ongoing process of desertification. Among them, we propose reclaimed water, diversifying the economy, or promoting crops adapted to aridity. This simulation framework shows how to explore the future of a socio-ecosystem under current scenarios and others that consider climate change, the energy crisis, or the impact of alternative solutions.

We outline and test a new methodology for genuine simulation of stochastic processes with any dependence and any marginal distribution. We reproduce time dependence with a generalized, time symmetric or asymmetric, moving-average scheme. This implements linear filtering of non-Gaussian white noise, with the weights of the filter determined by analytical equations in terms of the autocovariance of the process. We approximate the marginal distribution of the process, irrespective of its type, using a number of its cumulants, which in turn determine the cumulants of white noise in a manner that can readily support the generation of random numbers from that approximation, so that it be applicable for stochastic simulation. The simulation method is genuine as it uses the process of interest directly without any transformation (e.g. normalization). We illustrate the method in a number of synthetic and real-world applications with either persistence or antipersistence, and with non-Gaussian marginal distributions that are bounded, thus making the problem more demanding. These include distributions bounded from both sides, such as uniform, and bounded form below, such as exponential and Pareto, possibly having a discontinuity at the origin (intermittence). All examples studied show the satisfactory performance of the method.

Road vehicles are a large contributor to Nitrogen Oxides (NOx) pollution. The routine road-side monitoring stations, however, may underrepresent the severity of personal exposure in urban areas, because long-term average readings cannot capture the effects of momentary, high peaks of air pollution. While numerical modelling tools historically have been used to propose an improved distribution of monitoring stations, ultra-high resolution Computational Fluid Dynamics models can further assist the relevant stakeholders in understanding the important details of pollutant dispersion and exposure at local level. This study deploys a 10 cm-resolution CFD model to evaluate actual high peaks of personal exposure to NOx from traffic, by tracking the gases emitted from the tailpipe of moving vehicles being dispersed towards the roadside. The investigation shows that a set of four Euro 5-rated diesel vehicles travelling at constant speed may generate momentary road-side concentrations of NOx as high as 1.25 mg/m3, with 25% expected increase for doubling the number of vehicles and approximately 50% reduction when considering Euro 6-rated vehicles. The paper demonstrates how the numerical tool can be used to identify the impact of measures to reduce personal exposure, such as protective urban furniture, as traffic patterns and environmental conditions change.

The stick-free flight stability is an old-fashioned and non-progressive issue; nevertheless, it is still existent, and of significant importance to the design of aircraft whose control system is reversible. The problem’s existence necessitates a deep assessment of stick-free flight stability throughout the aircraft design. Up to now, this problem has been addressed using either analytical approaches, which are only related to the static stability evaluation, or performing flight tests. In this study, the problem is handled in its entirety, from static and dynamic flight stability assessment to design criteria with a comprehensive perspective. Moreover, it is also exhibited that contrary to what has been generally proposed in the literature, limiting the problem of stick-free flight stability through static stability assessment is far from the main challenge. As a brief scope, the derivation of the control surface dynamics, a stick-free trim algorithm, and assessment rationale of the stick-free static and dynamic flight stability using a simulation approach are proposed. As a consequence, the aim is to set a broad understanding for designers related to this phenomenon and add adjunct design criteria in the design optimization process by approaching it in terms of modeling, simulation, and flight test perspective.

Shear dynamics simulation under extreme pressure was used to optimise the composition of ester-based lubricant base oil and extreme pressure additives. As a result, the ester-based lubricant in the weak-gel drilling fluid achieves reduction and increases the efficiency in drilling construction, and the field operation efficiency improves. The results of base oil lubrication simulation show that three base oils, namely, methyl oleate, ethyl oleate and butyl oleate, can be stably adsorbed on the surface layer of the shear surface. Methyl oleate has the lowest system temperature after shear stabilisation and has a high load-bearing capacity. The shear stress of methyl oleate decreases by changing the initial shear temperature and speed. It increases by 6.36 MPa when the speed increases from 10 m/s to 30 m/s. At this time, the shear stress of butyl oleate increases by 10.11 MPa. The results of the four-ball friction experiments show that the radius of the abrasion spot of methyl oleate is 179.83 μm, which is smaller than that of the other two base oils. Moreover, the friction coefficient of methyl oleate is 0.0018, which is approximately 1/3 of that of butyl oleate. Methyl oleate has better lubrication efficiency. The shear simulation results are consistent with the experimental results. The simulation can be used for the molecular design of lubricant materials. The oleic acid amide–containing amine group and the glyceride oleic–containing hydroxyl group were selected as the extreme pressure functional components for shear simulation. Results show that the shear stress of oleic acid amide is much lower than that of oleic acid glyceride when the initial shear temperature and speed change. The extreme pressure lubrication component–containing amine group is better than the extreme pressure lubrication material–containing hydroxyl group. The effects of different oleamide contents in the two-component mixtures on the lubricating properties were investigated through shear simulation, with methyl oleate as the base oil and oleamide as the extreme pressure functional component. The simulation results show that the lubricant has the optimal shear stress when 10% oleamide is added to the lubricant. The base properties of the lubricant were tested using a mixture of 90% methyl oleate and 10% oleamide, formulated as a lubricant. Results show that the friction coefficient can be reduced to 0.03 when 0.5% of the lubricant is added to the base mud. Moreover, the lubricant film formed shows high strength. Then, 1% lubricant was added to the weak-gel drilling fluid to evaluate the effect of the lubricant on the gel structure of the drilling fluid. Results show that adding lubricant does not affect the rheological properties of the drilling fluid. The gel structure of the system also remains stable even after 7 days of continuous ageing. The results of the field experiments in Hua3-01 well show that adding 1% ester-based lubricant to the field drilling fluid reduces the drilling friction by 33%. Thus, the efficiency of directional side drilling can be effectively improved, complicated accidents, such as poor starting and stopping of drilling and stuck jamming, can be avoided, and the goals of reducing quantity and increasing efficiency can be completed.

In this work, we incorporate a thixotropic-viscoelastic model into the widely used Computational Fluid Dynamics (CFD) software OpenFOAM, along with the rheoTool library. The model we implement is known as the Modified-Bautista-Manero (MBM), and effectively describes the rheological behavior of worm-like micellar solutions in extensional flows. We provide a detailed explanation of the numerical implementation of the model, specifically using the log-conformation tensor approach. Unlike previous works focused on this kind of fluids, we simulate inertial flows while considering convective terms in the governing equations, thus obtaining a more realistic behavior on the calculated results. The MBM model implementation is validated through numerical simulations on two different industrial-relevant geometries: the planar 4:1 contraction and the 4:1:4 contraction-expansion configurations. Furthermore, we investigate the influence of inertial, viscoelastic, and thixotropic effects on various flow field variables. These variables include velocity, viscosity, normal stresses, and corner vortex size. Our analysis encompasses both transient and steady solutions of corner vortexes across a range of Deborah and Reynolds numbers. Our results are also directly compared with simulations obtained using the non-thixotropic rubber network-based exponential Phan-Thien-Tanner (EPTT) model. From our planar 4:1 contraction results, we found that vortex-enhancement is seen when high elasticity is coupled with quick structural reformation and very low inertial effects. From our planar 4:1:4 contraction-expansion simulations, we show that an increase in inertia leads both to vortex-inhibition in the upstream channel and slight vortex-enhancement in the downstream channel. Lastly, we show the strong effect of the convection of fluidity into the fluidity profiles and into the upstream/downstream corner vortex sizes.

The chemical feedback between building blocks in templated polymerization of diblock copolymers and their consecutive micellization was studied for the first time by means of coarse-grained molecular dynamics simulations. Using a stochastic polymerization model, we were able to reproduce the experimental findings on the effect of chemical feedback on the polymerization rates at low and high solution concentrations. The size and shape of micelles were computed using a newly development software in python conjugated with graph theory. In full agreement with the experiments, our simulations revealed that micelles formed by the templated micellization are more spherical and have lower radius of gyration than those formed by the traditional two-step micellization method. Understanding the underlying mechanisms in templated reaction/assembly of polymers will help for rational design of new synthetic supramolecular materials.

Driven by the growing interest of the scientific community and the proliferation of research in this field, cranial implants have seen significant advancements in recent years regarding design techniques, structural optimisation, appropriate material selection and fixation system method. Custom implants not only enhance aesthetics and functionality but are also crucial for achieving proper biological integration and optimal blood irrigation, critical aspects in bone regeneration and tissue health. This research aims to optimize the properties of implants designed from triply periodic minimal surface structures. The gyroid architecture is employed for its balance between mechanical and biological properties. Experimental samples were designed varying three parameters of the surface model: cell size, isovalue and shape factor. Computational simulation tools were used for determining the relationship between those parameters and the response variables: the surface area, permeability, porosity and Young modulus. These tools include computer aided design, finite element method and computational fluid dynamics. With the simulated values, the corresponding regression models were fitted. Using the NSGA-II, a multi-objective optimisation was carried out, finding the Pareto set which includes surface area and permeability as targets, and fulfil the constraints related with the porosity and Young modulus. From these non-dominated solutions, the most convenient for a given application was chosen, and an optimal implant was designed, from a patient computed tomography scan. An implant prototype was additively manufactured for validating the proposed approach.

Solid asperity interactions are common and inevitable under severe loading conditions for any lubricated contact. Heavy-duty machine components (gear, bearings etc.) generally operate under Mixed Lubrication, where uneven surface features contact each other when generated fluid pressure is not enough to support the external load. The Reynolds equation is commonly used to simulate smooth lubricated contacts numerically. In rough lubricated interfaces where opposite surface asperities make contact, the Reynolds equation alone cannot accurately predict pressure using the traditional numerical simulation method. In this paper, Lubrication-Contact interface conditions (LCICs) have been implemented and extended to solve the multiple asperity contact problem using the full-multigrid approach. The developed novel algorithm has significantly accelerated the solution process and improved the accuracy and efficiency of pressure calculation for fluid-solid sub-interactions that can occur under ML regions. The Finite Difference Method (FDM) results have been compared with Computational Fluid Dynamics (CFD) simulation to validate the newly developed model. Hence, the proposed optimized solution method will provide valuable insight to researchers and industry engineers interested in simulating the ML problem where the effect of the fluid-solid interface can be captured effectively to improve reliability in the calculation of the life expectancy of the lubricated parts.

We performed for the first time to our knowledge fully ab initio molecular dynamics simulations of additive tribochemistry in boundary lubrication conditions. We consider an organophosphourus additive that has been experimentally shown to reduce friction in steel-on-steel sliding contacts thanks to the tribologically-induced formation of an iron phosphide tribofilm. The simulations allow us to observe in real time the molecular dissociation at the sliding iron interface under pressure and to understand the mechanism of iron phosphide formation. We discuss the role played by the mechanical stress by comparing the activation times for molecular dissociation observed in the tribological simulations at different applied loads with that expected on the basis of the dissociation barrier.

Existing methods for simulating missile dynamics and training often rely on three degrees of freedom (3DOF) motions, limiting their ability to represent the complex maneuvers and targeting strategies of modern missiles. This paper proposes integrating virtual reality (VR) technology with six degrees of freedom (6DOF) dynamics to enhance the accuracy and efficiency of missile simulation and training. By incorporating 6DOF dynamics, simulations can capture the full range of missile motion, providing a comprehensive understanding of their capabilities and limitations. Through VR, users can immerse themselves in realistic missile scenarios, interact with dynamic behaviors in real-time, and refine their targeting and interception skills. The integration of VR with 6DOF dynamics also facilitates real-time feedback and evaluation, enhancing training efficiency and proficiency in missile operations. This approach aims to revolutionize missile training by bridging the gap between traditional simulation methods and real-world dynamics.

The accelerated pace with which new diagnostic possibilities are produced and the budget re-strictions of the healthcare sector require that the decision-making process of acquiring new technologies becomes systematic in nature. There are some methodologies such as the Health Technology Assessment (HTA) that encompasses technological domains, clinical effectiveness, patient safety, organizational and financial aspects, among others. However, these methods do not contemplate the learning curve (LC) which is a differential factor in operator-dependent technologies. An assessment model was conceived based on the assessment domains of the AdHopHTA project with the addition of LC. The model was validated and calibrated through System Dynamics (SD) and using as case study the assessment of Point-of-care Ultrasound (POCUS) equipment in dengue screening. The model helped identify the influence of the LC and patient demand on the income and costs for the healthcare system regarding dengue screening as well as the cost-benefit indicator. The control charts LC-CUSUM and CUSUM are graphic tools to intuitively assess the learning curve which can be used for real-time monitoring once students reach a certain skill level.

The analysis of high-temperature physicochemical properties of theK₃AlF₆-Na₃AlF₆-AlF₃ molten salt system is crucial for practical production of electrolytic aluminum. In this paper, the physicochemical properties of the K₃AlF₆-Na₃AlF₆-AlF₃ molten salt electrolyte system at 1173 K and standard atmospheric pressure were simulated using molecular dynamics calculations. The effects of Zr、B、C、W、Ti、Hf、Nb、and Ta on the radial distribution function, coordination number, viscosity and conductivity of the electrolyte system are discussed in detail. The simulation results show that the coordination number between Al-F and the conductivity is decreasing as the content of B²- increases. And the coordination number between Al-F and the viscosity is decreasing as the content of Zr⁴⁺ increases. With the addition of impurity elements such as C, W, Ti, Hf, Nb, and Ta, the data show that C has no significant effect on this electrolyte system, while the presence of W will decrease the coordination number between Al-F in the system. The presence of Ti, Hf, Nb, and Ta may intensify the decomposition reaction between one of the Al-F ligands, which increases the coordination number between Al-F and the number of ions in the electrolyte. This work provides theoretical support for the subsequent study of inert anodes containing Zr, B, Ti, Hf, Nb, and Ta.

The human serotonin transporter (hSERT) terminates neurotransmission by removing serotonin from the synaptic cleft, which is an essential process plays an important role in depression. In addition to substrate serotonin, hSERT is also the target of drugs of abuse like cocaine and clinically used antidepressants such as escitalopram and paroxetine. To date, few studies attempt to investigate the unbinding mechanism underlying the orthosteric and allosteric modulation of hSERT. The high-resolution X-ray structure of hSERT resolved recently enables us to theoretically study the unbinding of the above four ligands against the S1 or S2 site of hSERT, by means of molecular docking, molecular dynamics (MD) and potential of mean force (PMF) simulations. We proved that for either the S1 or S2 site, the other three ligands (cocaine, escitalopram and paroxetine) are much more favorable than the original substrate serotonin, whether in kinetics along the unbinding pathways or in thermodynamics at the equilibrium states. Furthermore, the S1 site is much more favorable than the S2 site, for each ligand. Interestingly, inspection revealed that there are ~ 3Å lengths between the allosteric site of serotonin and cocaine, and an unseen un-binding pathway for escitalopram at the S1 site except for verification of the broadest trail.

Electrowetting – induced detachment of droplets from solid surfaces is important for numerous applications in the fields of heat transfer and fluid mechanics. The forced oscillations of droplets on solid surfaces and their ability to detach are studied. In this study the process is efficiently simulated by implementing a powerful methodology developed by our team. Our results agree with experiments, showing that optimal detachment, in terms of actuation energy, is achieved when the application of voltage is synchronized with the spreading time of the droplet. Under these conditions, the droplet oscillates with a period close to that of a mirrored Rayleigh droplet. The relation between the droplet’s oscillation period and its physical properties is examined. During voltage-droplet synchronization, the droplet’s ability to detach depends mostly on its contact angle, its viscosity, and the applied voltage. An energy analysis is also conducted, revealing how energy is supplied to the droplet by electrowetting-induced detachment.

The adsorption of proteins on polymer is widely used in biosensors. Here, molecular dynamics (MD) simulation was used to study the immobilization of angiotensin converting enzyme II (ACE2) with six initial orientations proposed on polystyrene (PS) at the ambient conditions of pH (4.5, 6, 7, 8, 9.5) and NaCl (0.01, 0.05, 0.1, 0.15, 0.2, 0.25 M). ACE2 immobilization under favorable ambient conditions was characterized by minimum distance (short), settlement time (fast), interaction energy (substantial) and protein configuration (stable). ACE2 orientations proposed in 0.15M NaCl were respectively preferable to (90, 0, 0), (0, 0, 0) and (0, 270, 0), (180, 0, 0) and (0, 90, 0), (90, 0, 0) at pH 4.5, 6, 7, 9.5. ACE2 immobilization was further evaluated at pH 7 by optimizing NaCl concentration. Its proposed orientations of (i) (0, 270, 0), (ii) (0, 0, 0) and (90, 0, 0), and (iii) (0, 90, 0) and (90, 0, 0) were preferable in 0.05, 0.1 and 0.2 M NaCl, respectively. The great significance of cubic-orientation settlement mode provides tangible improvement for the microfabrication of biochips for rapid diagnosis of severe acute respiratory syndrome coronavirus II (SARS-CoV-2).

Certain configurations of liquefied natural gas refueling stations exhibit a deficiency in managing boil-off gas. Furthermore, the ill-conceived linkage between the submersible pump and the gas storage tank pipeline leads to impeded natural gas transmission. This study employs Computational Fluid Dynamics (CFD) methodology to scrutinize the hydrodynamic attributes of T-type tee and dovetail tee configurations implemented in the pipeline design connecting the submersible pump and storage tank in an LNG filling station across diverse operational scenarios. The T-type tee induces detachment of the primary flow from the inner wall due to inertial forces, resulting in vortex formation and heightened resistance, accompanied by increased energy dissipation. Conversely, the dovetail tee, with its circular wall transition, mitigates vortex generation, reducing the separation zone and consequently minimizing resistance and energy loss. The maximum static differential pressure between the inlet and outlet of the dovetail tee is diminished by 52.52% when compared to that of the T-type tee. In the most noteworthy scenarios, the local resistance coefficient of the dovetail tee is even less than 1/10 of that of the T-type tee. In practical engineering applications, the incorporation of dovetail tees leads to a 17.58% reduction in the required elevation difference. This results in a more uniform flow field and enhanced stability in both flow rate and pressure. Such improvements contribute to heightened engineering efficiency and environmental sustainability, particularly evident in the design of LNG filling stations.

In this paper an integrated methodology for the coupling between 1D- and 3D-CFD simulation codes is presented, which has been developed to support the design and calibration of new diesel engines. The aim of the proposed methodology is to couple 1D engine models, which may be available in the early-stage engine development phases, with 3D predictive combustion simulations, in order to obtain reliable estimates of engine performance and emissions for newly designed automotive diesel engines. The coupling procedure features simulations performed in 1D-CFD by means of GT-SUITE and in 3D-CFD by means of Converge, executed within a specifically designed calculation methodology. An assessment of the coupling procedure has been performed by comparing its results with experimental data acquired on an automotive Diesel engine, considering different working points including both part load and full load conditions. Different multiple injection schedules have been evaluated for part-load operation, including pre and post injections. The proposed methodology, featuring detailed 3D chemistry modeling, was proven to be capable to properly assess pollutant formation, specifically to estimate NOx concentrations. Soot formation trend was also well-matched for most of the explored working points. The proposed procedure can therefore be considered as a suitable methodology to support the design and calibration of new Diesel engines, thanks to its ability to provide reliable engine performance and emissions estimations from the early-stage of a new engine development.

In this study, we present more than 8 years of observations of the quasi-16-day wave (Q16DW) in the mesosphere and lower thermosphere (MLT) wind at middle latitudes observed by the Mengcheng (33.4°N, 116.5°E) meteor radar. The long-term variation in amplitudes calculated from the data between April 2014 and December 2022 shows enhanced wave activity during winter and early spring (near equinox) and suppressed wave activity during the summer. The Q16DWs are relatively weak in the meridional wind. During the winter months, the Q16DWs in the zonal component exhibit a burst below 85 km, and their amplitudes reach up to 10 m/s. In the early spring, the Q16DWs strengthen above 90 km with amplitudes in excess of 12 m/s. The phase differences between the zonal and meridional components of the Q16DW are, on average, slightly smaller than 90°, suggesting the existence of orthogonal relationships between them. During strong bursts, the periods of the Q16DW in winter range between 15 and 18 d, whereas in winter, the periods tend to be more diffuse. The wintertime Q16DW is amplified, on average, when the zonal wind shear peaks, suggesting that barotropic instability may be one source of Q16DW. Q16DW amplitudes exhibit considerable interannual variability; however, a relationship between the 11-year solar cycle and the Q16DW is not found.

Molecular dynamics(MD) simulations are carried out to characterize the mechanicalproperties and failure behavior of van der Waals heterostructures composed ofgraphene and hexagonal boron nitride(hBN) single layer sheets. The graphene–hBNand hBN–graphene–hBN heterostructures simulations are carried out under tensileand shear deformation. Accordingly, stress versus strain curves of each systemare plotted and various properties of heterostructures, namely elastic modulusand shear modulus as well as failure stress and failure strain, are evaluatedand compared with one another as well as with the pristine graphene and hBNsheets. Subsequently, the failure mechanism/characterization of each sheet in theheterostructures is described. Alternatively, the elastic and shear modulus of eachheterostructure are computed by means of rule of mixture(ROM) which are in goodagreement with results that are obtained from MD simulations.

Aquaporin-3 (AQP3) is one of the aquaglyceroporins, which is expressed in the basolateral layer of the skin membrane. Studies have reported that human skin squamous cell carcinoma overexpresses AQP3 and inhibition of its function may alleviate skin tumorigenesis. In the present study, we have applied a virtual screening method that encompasses filters for physicochemical properties and molecular docking to select potential hit compounds that bind to the Aquaporin-3 protein. Based on molecular docking results, the top 20 hit compounds were analyzed for stability in the binding pocket using unconstrained molecular dynamics simulations and further evaluated for binding free energy. Furthermore, examined the ligand-unbinding pathway of the inhibitor from its bound form to explore possible routes for inhibitor approach to the ligand-binding site. With a good docking score, stability in the binding pocket, and free energy of binding, these hit compounds can be developed as Aquaporin-3 inhibitors in the near future.

A computational simulation of a PT6A gas turbine engine operating at off-design conditions is described in the present article. The model consists of a 0-dimensional thermo-fluidic description of the engine by applying the mass, linear momentum, angular momentum, and energy balances in each engine's component. The transient behavior of the engine is simulated for different blends of the original JET-A1 fuel with bio-diesel. Simulated thermodynamic variables of the air at each engine's component, as well as some performance parameters correspond to the reported experimental measurements. The numerical results also demonstrate the ability of the computational simulation to predict acceptable fuel blends, such that the efficiency of the engine is maximized and its structural integrity is maintained.

Alzheimer's disease (AD) is a progressive neurodegenerative brain disorder. One of the important therapeutic approaches of AD is the inhibition of β‐site APP cleaving enzyme‐1 (BACE1). This enzyme plays a central role in the synthesis of the pathogenic β-amyloid peptides (Aβ) in Alzheimer's disease. A group of potent BACE1 inhibitors with known x-ray structures (PDB ID 5i3X, 5i3Y, 5iE1, 5i3V, 5i3W, 4LC7, 3TPP) were studied by molecular dynamics simulation and binding energy calculation employing MM_GB(PB)SA. The calculated binding energies gave Kd values 0.139 µM, 1.39 nM, 4.39 mM, 24.3 nM, 1.39 mM, 29.13 mM and 193.07 nM, respectively. These inhibitors showed potent inhibitory activities in enzymatic and cell assays. The Kd values were compared with experimental values, the structures were discussed in view of the energy contributions to binding. Drug likeness of these inhibitors is also discussed. Accommodation of ligands in the catalytic site of BACE1 is discussed depending on the type of fragment involved in each structure. Molecular dynamics (MD) simulations and energy studies were used to explore the recognition of the selected BACE1 inhibitors by Asp 32, Asp228 and the hydrophobic flap. The results show that selective BACE1 inhibition may be due to the formation of strong electrostatic interactions with Asp32 and Asp228 and a large number of hydrogen bonds, π-π and Van der Waals interactions with the amino acid residues located inside the catalytic cavity. Interactions with the ligands show a similar binding mode with BACE1. These results help to rationalize the design of selective BACE1 inhibitors.

The SARS-CoV-2 was confirmed to cause the regional outbreak of coronavirus disease 2019 (COVID-19) in Wuhan, China. The 3C-like protease (3CL^pro), an essential enzyme for viral replication, is a valid target to compacts SARS-CoV and MERS-CoV. In this research, an integrated library consisting of 1000 compounds from Asinex Focused Covalent (AFCL) library and 16 FDA-approved protease inhibitors were screened against SARS-CoV-2 3CL^pro. Top compounds with significant docking scores and making stable interactions with catalytic dyad residues were obtained. The screening results in identification of compound 621 from AFCL library as well as Paritaprevir and Simeprevir from FDA-approved protease inhibitors as potential inhibitors of SARS-CoV-2 3CL^pro. The mechanism and dynamic stability of binding between the identified compounds and SARS-CoV-2 3CL^pro were characterized using 50 nanoseconds (ns) molecular dynamic (MD) simulation approach. The identified compounds are potential inhibitors worthy of further development as SARS-CoV-2 3CLpro inhibitors/drugs. Importantly, the identified FDA-approved therapeutics could be ready for clinical trials to treat infected patients and help to curb the COVID-19.

The recent demand for reducing pollutant and CO2 emissions from internal combustion engines has created an urgent need for the development of ultra-lean burn engines that ensure combus-tion stability and reducing knocking tendency. One of the most promising methods is the Pre-chamber Spark Ignition (PCSI) system, where a jet of high-energy reactive gases, produced by pilot combustion in a pre-chamber, ignites the main combustion event in the cylinder. Given the intricate phenomena inherent to PCSI systems, conducting 3D CFD studies is imperative for a comprehensive analysis and optimal design. Furthermore, the detailed CFD model, combined with the calibrated 0-D/1-D model, is anticipated to yield a significant amount of new data that would be difficult to obtain through experimental approaches, making it essential for advancing our understanding and optimization of these systems. However, recently published papers re-port that some state-of-the-art models developed for conventional SI operation may not be pre-dictive under the challenging conditions of TJI systems, particularly under lean conditions. This review elucidates the reasons behind the widespread adoption of CFD in the optimal design of PCSI engines. It presents significant examples and delves into the potential and challenges of employing CFD not just as a predictive tool but also as a design instrument for enhancing PCSI engine performance.

This research paper presents a comprehensive study on the gasification of wheat straw pellets in a 10-kW fixed bed gasifier through a combination of Computational Fluid Dynamics (CFD) simulation and experimental validation. The developed 2D CFD model in ANSYS meshing simulates the gasification process in ANSYS Fluent software. The investigation evaluates key parameters such as equivalence ratio, higher heating value, and temperature distribution within the gasifier to enhance syngas production efficiency. The simulated results exhibit a noteworthy agreement with experimental data obtained from gasification. The impact of the equivalence ratio on gas production and lower heating value (LHV) is systematically explored, revealing that an equivalence ratio of 0.35 is optimal for syngas production. The resulting producer gas composition at this optimum condition includes CO (~27.67%), CH4 (~3.29%), CO2 (~11.09%), H2 (~11.09%), and N2 (~51%). The study further investigates the positive influence of reactor temperature on increasing syngas quantity while considering the uneven shape of the reactor and various thermal reactions affecting temperature, static pressure, velocity, and density. The findings contribute valuable insights to improve the efficiency of fixed-bed gasifiers, offering essential information on performance parameters for sustainable and optimized syngas production.

Efficient thermal management of modern electronics requires the use of thin films with highly anisotropic thermal conductivity. Such films enable the effective dissipation of excess heat along one direction while simultaneously providing thermal insulation along the perpendicular direction. In this study, we investigate the thermal conductivity of bilayer graphene (BLG) sheets using non-equilibrium molecular dynamics, examining both in-plane and cross-plane thermal conductivities. The in-plane thermal conductivity of 10 nm × 10 nm BLG with zigzag and armchair edges at room temperature is found to be around 204 W/m.K and 124 W/m.K, respectively. The in-plane thermal conductivity of BLG increases with sheet length. For all sizes, BLG with a zigzag edge exhibits higher thermal conductivity than that of the armchair edge, with this difference becoming more pronounced as the lengths of the sheets increase. In addition, increasing temperature from 300 K to 600 K decreases the in-plane thermal conductivity of a 10 nm× 10 nm zigzag BLG by about 34%. Similarly, the application of a 12.5% tensile strain induces a 51% reduction in its thermal conductivity compared to the strain-free values. Armchair configurations exhibit similar responses to variations in temperature and strain, but with less sensitivity. Furthermore, the cross-plane thermal conductivity of BLG at 300 K is estimated to be 0.05 W/m·K, significantly lower than the in-plane results by approximately four orders of magnitude. The cross-plane thermal conductance of BLG decreases with increasing temperatures, specifically, at 600 K, its value is almost 16% of that observed at 300 K.

Objective: The stability of the flight phase in ski jumping is crucial for athletes' performance and safety. This study aims to investigate the influence of unfavorable conditions on aerodynamic characteristics and flight stability through computational fluid dynamics (CFD) numerical simulations. Methods: The ski jumper and the skis are considered as a multi-body system. A detailed three-dimensional (3D) model of this multi-body system under a commonly observed posture during flight is established. The partially averaged Navier-Stokes (PANS) turbulence model is employed, and CFD simulations are conducted to predict the aerodynamic characteristics of the multi-body system under lateral environmental wind and asymmetric postures during flight phase. The conditions of asymmetric postures include yaw rotation and roll rotation. Results: (1) Lateral environmental wind generated yaw force, yaw moment, and roll moment, which influenced the lift, drag, and pitch moment of the athlete. These forces and moments were relatively small at lower wind speeds (less than 3 m/s) and became more significant at higher wind speeds (greater than 4.5 m/s). (2) Under the influence of yaw rotation or roll rotation, the multi-body system exhibited noticeable yaw force, yaw moment, and roll moment, all showing a monotonic increasing trend. Moreover, they had a significant impact on the lift, drag, and pitch moment of the multi-body system. Conclusion: (1) The influence of unfavorable conditions is complex, resulting in significant yaw force, yaw moment, and roll moment on the multi-body system. The adverse effects of roll rotation were generally greater than those of yaw rotation. (2) The multi-body system exhibited self-stabilizing tendencies in yaw and roll. This phenomenon can provide a solution to maintain flight stability by employing appropriate yaw or (and) roll rotation angles, effectively compensating for or even eliminating the adverse effects of lateral environmental wind. (3) Understanding the mechanisms of how unfavorable conditions affect the aerodynamic characteristics and stability during flight in ski jumping can provide valuable assistance for real-time prediction and decision-making during competitions, as well as scientific guidance for training athletes stable flight control and techniques and improving their sport performance.

Nitrile butadiene rubber (NBR) and its various composites are extensively studied as matrix materials for oil-free lubricated mechanical friction surfaces. While numerous macroscopic friction experiments can compare the frictional performance of different NBR composites, the complex material preparation and low experimental efficiency pose challenges. Nanoscale molecular dynamics (MD) simulations can help develop materials with improved friction properties, but they cannot directly provide the friction coefficients of actual macroscopic friction surfaces. Therefore, it is important to integrate the advantages of macroscopic and nanoscale friction studies and perform a synergistic analysis to modify the friction properties of composite materials. In this study, a multi-scale approach is proposed to simulate the frictional characteristics of carbon nanotube (CNT)-reinforced NBR by combining the MD friction simulation， micromechanical bridging model, and macroscopic finite element analysis (FEA) methods. The results of the multi-scale friction simulation of copper (Cu)-CNT/NBR composites show that the addition of CNTs significantly improves the frictional properties of NBR, and the extent of the improvement is related to the mass fraction of CNTs. As the mass fraction of CNTs increases (0%, 1.25%, 2.5%, 5%), the coefficient of friction decreases from 0.50 to 0.38. The results are validated by ring-block friction experiments at the same scale as the simulations.

A crop-weed simulation model is presented to compare and evaluate Integrated Weed Management (IWM) strategies. Specifically, the model was parameterized for soybean crops in competition with Euphorbia davidii Subils. We used both, weed and crop demographic data surveyed in agronomic fields of the central zone of the Buenos Aires province, Argentina, throughout two crop cycles (2011/2012 and 2013/2014). The proposed model underwent a calibration process and subsequent validation with 70/30 % data split respectively (N=37). Two annual-based and one multiannual-based case studies were simulated to demonstrate the performance of the model. Different IWM strategies were compared under both, operational and tactical planning horizons through the evaluation of different model outcomes (i.e. crop yield, interspecific competition, economic return, and environmental impact). Our case studies results suggest that the inclusion of cultural management practices could reduce weed interspecific competition by 46 to 97 % and weed seed production by 40 to 89%. An increment in both expected crop yield, by 6 to 20%, and annual gross margin, by 44 to 199 US$.ha-1, were obtained in silico for similar levels of environmental impact.

Education for Sustainable Development (ESD) is considered vital to the success of the United Nations’ Sustainable Development Goals. Systems Thinking has been identified as a core competency necessary to incorporate into ESD. Systems Thinking orientated ESD learning tools, established methods of assessment of sustainability skills, and studies to demonstrate effectiveness of such learning tools, are all lacking. There is a wealth of experience in the System Dynamics field regarding the application of Systems Thinking and simulation to environmental problems, sustainability and systems education. Many System Dynamicists regard simulation as essential for teaching Systems Thinking. The substantial body of research into the design of effective simulation-based learning environments (SBLEs) can also inform ESD initiatives. This research describes a randomised controlled trial (n=106) to investigate whether an online sustainability learning tool that incorporates Systems Thinking and System Dynamics simulation increases understanding of a specific problem and supports transfer of knowledge to a second problem with a similar systemic structure. The effects of Systems Thinking and simulation were tested separately and in combination. The learning tool was designed for a single online learning session. Simulation was found to increase ESD learning outcomes significantly, and also to support transfer of skills, although less significantly.

Amorphous solid dispersions are considered a promising formulation strategy for the oral delivery of poorly soluble drugs. The limiting factor for the applicability of this approach is the physical (in)stability of the amorphous phase in solid samples. Minimizing the risk of reduced shelf life for a new drug by establishing a suitable excipient/polymer-type from first principles would be desirable to accelerate formulation development. Here we perform Molecular Dynamics simulations to determine properties of blends of eight different polymer-small molecule drug combinations for which stability data is available from a consistent set of literature data. We calculate thermodynamic factors (mixing energies) as well as mobilities (diffusion rates and roto-vibrational fluctuations). We find that either of the two factors, mobility and energetics, can determine the relative stability of the amorphous form for a given drug. Which factor is rate limiting depends on physico-chemical properties of the drug and the excipients/polymers. The methods outlined here can be readily employed for an in-silico pre-screening of different excipients for a given drug to establish a qualitative ranking of the expected relative stabilities, thereby accelerating and streamlining formulation development.

The proximal part of the colon offers opportunities to prolong the absorption window following oral administration of a drug. In this work, we used computer simulations to understand how the hydrodynamics in the proximal colon might affect the release from dosage forms designed to target the colon. For this purpose, we developed and compared three different models: a completely-filled colon, a partially-filled colon and a partially-filled colon with a gaseous phase present (gas-liquid model).The highest velocities of the liquid were found in the completely-filled model, which also shows the best mixing profile, defined by the distribution of tracking particles over time. No significant differences with regard to the mixing and velocity profiles were found between the partially-filled model and the gas-liquid model. The fastest transit time of an undissolved tablet was found in the completely-filled model. The velocities of the liquid in the gas-liquid model are slightly higher along the colon than in the partially-filled model. The filling level has an impact on the exsisting shear forces and shear rates, which are decisive factors in the development of new drugs and formulations.

Histone Lysine Specific Demethylase 1 (LSD1) is overexpressed in many cancers and become a new target for anticancer drugs. In recent years, the small molecule inhibitors with various structures targeting LSD1 have been reported. Here we report the binding interaction modes of a series of thieno[3,2-b]pyrrole-5-carboxamides LSD1 inhibitors using molecular docking, three dimensional quantitative structure-activity relationship (3D-QSAR). Comparative molecular field analysis (CoMFA q²=0.783, r²=0.944, r²_pred=0.851) and Comparative molecular similarity indices analysis (CoMSIA q²=0.728, r²=0.982, r²_pred=0.814) were used to establish 3D-QSAR models, which had good verification and prediction capabilities. Based on the contour maps and the information of molecular docking, 8 novel small molecules were designed in silico, among which compounds D4, D5 and D8 with high predictive activity were subjected to further molecular dynamics simulations (MD), and their possible binding modes were explored. It was found that Asn535 plays a crucial role in stabilizing the inhibitors. Furthermore, the ADME and bioavailability prediction for D4, D5 and D8 were carried out. The results would provide valuable guidance for designing new reversible LSD1 inhibitors in the future.

The main regulatory factors during the adaptation of cancer cells to hypoxic stress are the hypoxia-inducible factors (HIFs), which are being increasingly recognized as an interesting and challenging target for the design of new chemotherapeutic molecules. HIF2A was found to have an large internal hydrophilic cavity within its PAS-B domain, unique to this sub-unit and is suggested to be a possible ligand-binding site. Regulation of HIF2A by cellular molecules is still greatly unknown. In This paper we have employed in-silico techniques, such as molecular docking and dynamic simulation, to design new direct inhibitors against HIF-2A subunit via targeting one of its critical domains and the final top screened molecules have been tested on hypoxic cancer cells for further validation of their inhibitory potential. we targeted the hydrophilic cavity inside the PAS-B domain of the HIF2A to identify novel molecules with a high binding capacity. Virtual Screening methodology was used for molecular docking of NSC library against the target domain inside the HIF2A PAS-B domain with the top 5% compounds with significant MolDock and Re-rank scores were selected for further analysis. The NSC 106416, NSC 217021, NSC 217026, and NSC 215639 compounds were selected based on their docking scores. NSC 215639 had the minimum polar solvation energy and also had a relative strong binding energy. NSC 217026 had the strongest binding energy among other compounds.

The details of antigen-antibody interactions and the identification of epitopes are critical for the development of monoclonal antibody drugs. Ab42 is a native human-derived anti-CFH monoclonal antibody. In this study, the interaction between antigen pCFH and antibody (Ab42) was theoretically demonstrated by molecular docking and MD simulation, combined with free energy calculation and computational alanine scanning (CAS), and key amino acids and epitopes were identified. Experimental alanine scanning (EAS) was then carried out to verify the results of the calculation, and our results indicated that Ab42 antibody forms hydrogen bonds and interacts hydrophobically with pCFH through the Tyr315, Ser100, Gly33, and Tyr53 residues on its CDR, while the main pCFH epitopes are located at the six sites of Pro441, Ile442, Asp443, Asn444, Ile447, and Thr448. In conclusion, this study has explored the mechanism of antigen-antibody interaction from both theoretical and experimental aspects, and our results have important theoretical significance for the design and development of relevant antibody drugs.

A series of novel substituted isoxazolidine derivatives was synthesized through 1,3-dipolar cycloaddition reactions of α-aryl-N-methyl nitrones with various ethylene moieties, resulting in the formation of isoxazolidine derivatives. The structures of the synthesized compounds were characterized using spectroscopic methods. The [3+2] cycloaddition (32CA) reactions of α-aryl-N-methyl nitrones with diverse ethylene substituents were computed employing Density Functional Theory (DFT) at the B3LYP/6–31G(d) level, upgrading bond parameters. An investigation of the electron localization function (ELF) unveiled the zwitterionic nature of α-aryl-N-methyl nitrones, devoid of pseudoradical or carbenoid centers. Utilization of CDFT indices enabled the prediction of global electronic flux from the strongly nucleophilic α-aryl-N-methyl nitrones to the varied electrophilic ethylene functionalities. Molecular docking and molecular dynamics simulations were conducted on the isoxazolidine derivatives against the EGFR receptor (PDB: 4ZAU). In silico assessment of the synthesized isoxazolidines involved molecular docking, wherein the compound with the highest docking score was subjected to molecular dynamics simulations. Compound 11a, out of the thirty isoxazolidine derivatives, displayed the most substantial binding energy, yielding a g score of -6.57 kcal/mol. These observations highlighted the functional role of amide NH2 and NO2 in the binding process with the target protein, influencing its activity. Furthermore, prediction of ADME drug-likeness properties was performed to identify a suitable candidate.

A general procedure is described, to generate material parameter sets to simulate fire propagation in horizontal cable tray installations. Cone Calorimeter test data is processed in an inverse modelling approach. Here, parameter sets are generated procedurally and serve as input for simulations conducted with the Fire Dynamics Simulator (FDS). The simulation responses are compared with the experimental data and ranked based on their fitness. The best fitness was found for a test condition of \SI{50}{\kilo\watt\per\meter^2}. Low flux conditions \SI{25}{\kilo\watt\per\meter^2} and less exhibited difficulties to be simulated accurately. As a validation step, the best parameter sets are then utilised to simulate fire propagation within a horizontal cable tray installation and are compared with experimental data. It is important to note, the inverse modelling process is focused on the Cone Calorimeter and not aware of the actual validation step. Despite this handicap, the general features in the fire development can be reproduced, however not exact. The fire in the tray simulation extinguishes earlier and the total energy release is slightly higher as compared to the experiment. The responses of the material parameter sets are briefly compared with a selection of state of the art procedures.

This work is devoted to consideration and analysis of the application of molecular dynamics simulation (MDS) methods to the study of nanosized polymer polyvinylidene fluoride (PVDF) thin ferroelectric films (two-dimensional ferroelectrics) and their composites with graphene layers: 1) to study and calculations of the polarization switching time depending on the electric field and PVDF film thickness; 2) to study and calculations of the polarization switching time depending changes of the PVDF on PVDF-TrFE film; 3) to study the polarization switching time in PVDF under influence of graphene layers. All calculations at each MDS step were carried out using quantum semi-empirical methods PM3. A comparison and analysis of the results of these calculations and the kinetics of polarization switching within the framework of the Landau-Ginzburg-Devonshire theory for homogeneous switching in ferroelectric polymer films is carried out. The study of the composite heterostructures of the “graphene-PVDF” type and calculations of their polarization switching times were presented too. It is shown that replacing PVDF with PVDF-TrFE significantly changes the polarization switching times in these thin polymer films, and that introducing various graphene layers into the PVDF layered structure leads to both an increase and a decrease in the polarization switching time. Here everything also depends on the position and displacement of the ferroelectric coercive field depending on the system damping parameters.

In this review we summarize the recent development in understanding the role of PIP2 in cellular function and signaling. We first discuss the effect of PIP2 on actin binding proteins addressing the mechanism of the actin cytoskeletal dynamics such as polymerization or depolymerization of the filamentous network or the coupling to membrane to generate forces. Next, we outline the role of PIP2 in membrane dynamics. We summarized how the membrane organization depends upon PIP2 in the presence of ions or transmembrane proteins that are sensitive to membrane curvature. We discuss how clathrin coated pits interact with adaptor proteins during the endocytosis process, which is facilitated by PIP2. Finally, we discuss the role of PIP2 in cell signaling and diseases.

The conformational state of the activation loop (A-loop) is pivotal for the activation of most protein kinases. Hence, the characterization of the conformational dynamics of the A-loop is important to increase our understanding of the molecular processes related to diseases and to support the discovery of small molecule kinase inhibitors. Here, we carry out a combination of Molecular Dynamics (MD) and Essential Dynamics (ED) analyses to fully map the effects of phosphorylation, ADP, and conformation disrupting (CD) inhibitors (i.e., CD532 and MLN8054) on the dynamics of the A-loop of Aurora-A. MD revealed that the stability of the A-loop in an open conformation is enhanced by single phospho-Thr-288, while paradoxically, the presence of second phosphorylation at Thr-287 decreases such stability and renders the A-loop more fluctuant in time and space. Moreover, we found that such post-translational modification has a significant effect on the direction of A-loop motions. ED analysis suggests that the presence of the phosphate moiety induces the dynamics of Aurora-A to sample two distinct energy minima, instead of a single large minimum, as in unphosphorylated Aurora-A states. This suggests that the conformational distributions of Aurora-A with both single and double phospho-threonine modifications are remarkably different from the unphosphorylated state. In the closed states, binding of CD532 and MLN8054 inhibitors has the effect of increasing the distance of the N- and C-lobes of the kinase domain of Aurora-A, and the angle analysis between those two lobes during MD simulations showed that the N- and C-lobes are kept more open in presence of CD532, compared to MLN8054. As the A-loop is a common feature of Aurora protein kinases, our studies provide a general description of the conformational dynamics of this structure upon phosphorylation and different ligands binding.

Fluctuations of protein three-dimensional structures and large-scale conformational transitions are crucial for the biological function of proteins and their complexes. Experimental studies of such phenomena remain very challenging and therefore molecular modeling can be a good alternative or a valuable supporting tool for the investigation of large molecular systems and long-time events. In this mini-review, we present two alternative approaches to the coarse-grained (CG) modeling of dynamic properties of protein systems. We discuss two CG representations of polypeptide chains used for Monte Carlo dynamics simulations of protein local dynamics and conformational transitions and, on other hand, highly simplified structure-based Elastic Network Models of protein flexibility. In contrast to classical Molecular Dynamics the modeling strategies discussed here allow quite accurate modeling of much larger systems and longer time dynamic phenomena. We briefly describe the main features of these models and outline some of their applications, including modeling of near-native structure fluctuations, sampling of large regions of the protein conformational space, or possible support for the structure prediction of large proteins and their complexes.

Newton's second law, sometimes called the fundamental principle of dynamics, although considered as an irreducible axiom of mechanics based on and validated by experience, might paradoxically depend on the energetic content of our cosmos, through the existence of a dynamical form of aether appearing, in the ancient theory of Fatio de Duillier and Lesage, as an explanation of gravitational forces. In such a framework, Newton's theory is an approximation valid for small velocities as it was the case in special relativity theory.

Most works related to the identification of mathematical nonlinear systems make one suppose that such approaches can always be directly applied to any nonlinear system. This misconception produces a great deal of discouragement when the obtained results are not the expected ones. Thus, the current work hypothesizes that the most information one has about the mathematical structure of the model, the most precise the identification result should be. Therefore, a variant of the Sparse Identification of Nonlinear Dynamics (SINDY) approach is presented to obtain the full mathematical nonlinear model of a high-order system with coupled dynamics, namely, a commercial quadcopter. Furthermore, due to its high sensitivity to inputs, a control system is devised using the identified model to stabilize the quadcopter. This illustrates the effectiveness of the proposed identification method.

Molecular dynamics(MD) simulations are playing an increasingly important role in structure-based drug discovery (SBDD). Here we review the use of MD for proteins in aqueous solvation, organic/aqueous mixed solvents (MDmix) and with small ligands, to the classic SBDD problems: binding mode and binding free energy predictions. The simulation of proteins in their condensed state reveals the solvent structure and preferential interaction sites (hot spots) on the protein surface. This information is largely transferable across all classes of protein ligands (from water to drugs) and can be used very effectively to understand ligand recognition and improve the predictive capability of well-established methods such as molecular docking. MD simulations for protein and drug or drug-like compounds are now being used but are still computationally expensive and can only be applied to specific cases. On the other hand, MDmix simulations can now be used in SBDD and we will describe the latest developments and implementations. We expect to see an increase in the application of these techniques to a plethora of protein targets to identify new drug candidates with the advent of new tools and faster computers.

This study presents the complexity and sensitivity of chaotic system dynamics in the case of the double pendulum. It applied detailed numerical analyses of the double pendulum in multiple computing platforms in order to demonstrate the complexity in behavior of the system of double pendulums. The equations of motion were derived from the Euler-Lagrange formalism, in order to capture the system's dynamics, which is coupled nonlinearly. These were solved numerically using the efficient Runge-Kutta-Fehlberg method, implemented in Python, R, GNU Octave, and Julia, while runtimes and memory usage were extensively benchmarked across these environments. Time series analyses, including the calculation of Shannon entropy and the Kolmogorov-Smirnov test, quantified the system's unpredictability and sensitivity to infinitesimal perturbations of the initial conditions. Phase space diagrams illustrated the intricate trajectories and strange attractors, as further confirmation of the chaotic nature of the double pendulum. All the findings have a clear indication of the importance of accurate measurements of the initial condition in a chaotic system, contributing to an increased understanding of nonlinear dynamics. Future research directions are faster simulations using Numba and GPU computing, stochastic effects, chaotic synchronization, and applications in climate modeling. This work will be useful for understanding chaos theory and efficient computational approaches in complex systems of dynamical nature.

State transition in the multiple-levels system has the great potential applications in the quantum technology. In this article we employ a deterministic approach in complex space to analyze the dynamics of the 1s-2p electron transition in the hydrogen atom. The electron’s spin motion is embodied in the framework of quantum Hamilton mechanics that allows us to examine the transition dynamics more precisely. The transition is driven by an oscillating electric field in the z-direction. The electron’s transition process can be visualized by monitoring its motion in the complex space. The quantum potential and the total energy proposed in this paper provide new indices to observe the dynamic changes of electrons in the transition process.

Complex human behavior, including interlimb and interpersonal coordination, has been studied from a dynamical system perspective. We review the applications of a dynamical system approach to a sporting activity, which includes continuous, discrete, and switching dynamics. Continuous dynamics identified switching between in- and anti-phase synchronization, controlled by an interpersonal distance of 0.1 m during expert kendo matches, using a relative phase analysis. As discrete dynamics, return map analysis was applied to the time series of movements during kendo matches, and six coordination patterns were classified. Furthermore, state transition probabilities were calculated based on the two states, which clarified the coordination patterns and switching behavior. We introduced switching dynamics with temporal inputs to clarify the simple rules underlying the complex behavior corresponding to switching inputs in a striking action as a non-autonomous system. As a result, we determined that the time evolution of the striking action was characterized as fractal-like movement patterns generated by a simple Cantor set rule with rotation. Finally, we propose a switching hybrid dynamics to understand both court-net sports, as strongly coupled interpersonal competition, and weakly coupled sports, such as martial arts.

The aim of this study is to investigate transient dynamic flow characteristics of the fluid flow through 5-way electric coolant valve (PCCV : Penta-Control Coolant Valve). To achieve this goal, the present paper attempts the three-dimensional dynamic simulation of the fluid flow through the valve using a commercial CFD solver with moving mesh technique to consider flow inertia and dynamic flow in the opening and closing stages of the ball valve rotating motion. Firstly, dynamic flow characteristics and the thermal mixing inside the PCCV ball valve during the opening and closing stage was analyzed. It is found that the discrepancies between dynamic and steady state simulation is remarkable when fluxes with different levels of enthalpy and momentum flow into the PCCV leads to strong flow interference and flow inertia, while the discrepancies are relatively small at low rotation speed and weak flow interference. Then, the effect of dynamic flow characteristics of the valve on dynamic thermal mixing characteristics at two different ball valve rotational speeds and rotational directions were investigated. It was found that the dynamic flow and thermal mixing characteristics inside the PCCV are greatly affected by the rotation speed, rotation direction, and degree of flow interference between fluxes. It is helpful for the design of the better coolant control strategies and the improvement of the FCEV thermal management system.

We develop an action principle to construct the field equations for dissipative/resistive general relativistic two-temperature plasmas, including a neutrally charged component. The total action is a combination of four pieces: an action for a multi-fluid/plasma system with dissipation/resistivity and entrainment; the Maxwell action for the electromagnetic field; the Coulomb action with a minimal coupling of the four-potential to the charged fluxes; and the Einstein-Hilbert action for gravity (with the metric being minimally coupled to the other action pieces). We use a pull-back formalism from spacetime to abstract matter spaces to build unconstrained variations for the neutral, positively, and negatively charged fluid species and for three associated entropy flows. The full suite of field equations is recast in the so-called ``$3 + 1$'' form (suitable for numerical simulations), where spacetime is broken up into a foliation of spacelike hypersurfaces and a prescribed ``flow-of-time''. A previously constructed phenomenological model for the resistivity is updated to include the modified heat flow and the presence of a neutrally charged species. We impose baryon number and charge conservation as well as the Second Law of Thermodynamics in order to constrain the number of free parameters in the resistivity. Finally, we take the Newtonian limit of the ``$3 + 1$'' form of the field equations which can be compared to existing non-relativistic formulations. Applications include main sequence stars, neutron star interiors, accretion disks, and the early universe.

Drawing inspiration from a recent construction of a polyhedral structure associated with an icosahedrally-symmetric map on the Riemann sphere, the article shows how to build such "dynamical polyhedra" for other icosahedral maps. First, icosahedral algebra is used to determine a special family of maps with 60 periodic critical points. The topological behavior of each map is worked out and results in a geometric algorithm that constructs a system of edges---the dynamical polyhedron---in natural correspondence to a map's topology. It turns out that the maps' descriptions fall into classes the presentation of which concludes the paper.

Evolution of cooperation has traditionally been studied by assuming that individuals adopt either of two pure strategies, to cooperate or defect. Recent work have considered continuous cooperative investments, turning full cooperation and full defection into two opposing ends of a spectrum and sometimes allowing for the emergence of the traditionally-studied pure strategies through evolutionary diversification. These studies have typically assumed a well-mixed population in which individuals are encountered with equal probability, Here, we allow for the possibility of assortative interactions by assuming that, with specified probabilities, an individual interacts with one or more other individuals of the same strategy. A closely related assumption has previously been made in evolutionary game theory and has been interpreted in terms of relatedness. We systematically study the effect of relatedness and find, among other conclusions, that the scope for evolutionary branching is reduced by either higher average degree of, or higher uncertainty in, relatedness with interaction partners. We also determine how different types of non-linear dependencies of benefits and costs constrain the types of evolutionary outcomes that can occur. While our results overall corroborate the conclusions of earlier studies, that higher relatedness promotes the evolution of cooperation, our investigation gives a comprehensive picture of how relatedness affects the evolution of cooperation with continuous investments.

In this paper we introduce an ODE system to model the interaction between nature resources and human exploitation in a rich consumeristic society. In this model the rate of change of population depends on wealth per capita, and the rate of consumption has a quadratic growth with respect to population and wealth. As in our previous work \cite{BaCra_1}, we distinguish between renewable and non renewable resources, and we introduce a replenishment term for non renewable resources. We first get some information on the asymptotic behaviour of wealth and population, then we compute all the equilibria of the system and we study their stability when the parameter of exploitation of resources is small. Some numerical simulations confirm the theoretical results, and give suggestions for future research.

Artificial intelligence (AI) systems of autonomous systems such as drones, robots and self-driving cars may consume up to 50% of total power available onboard, thereby limiting the vehicle’s range of functions and considerably reducing the distance the vehicle can travel on a single charge. Next-generation onboard AI systems need an even higher power since they collect and process even larger amounts of data in real time. This problem cannot be solved using the traditional computing devices since they become more and more power-consuming. In this review article, we discuss the perspectives of development of onboard neuromorphic computers that mimic the operation of a biological brain using nonlinear-dynamical properties of natural physical environments surrounding autonomous vehicles. Previous research also demonstrated that quantum neuromorphic processors (QNPs) can conduct computations with the efficiency of a standard computer while consuming less than 1% of the onboard battery power. Since QNPs is a semi-classical technology, their technical simplicity and low, compared with quantum computers, cost make them ideally suitable for application in autonomous AI system. Providing a perspective view on the future progress in unconventional physical reservoir computing and surveying the outcomes of more than 200 interdisciplinary research works, this article will be of interest to a broad readership, including both students and experts in the fields of physics, engineering, quantum technologies and computing.

Reservoir computing (RC) systems can efficiently forecast chaotic time series using nonlinear dynamical properties of an artificial neural network of random connections. The versatility of RC systems has motivated further research on both hardware counterparts of traditional RC algorithms and more efficient RC-like schemes. Inspired by the nonlinear processes in a living biological brain and using solitary waves excited on the surface of a flowing liquid film, in this paper we experimentally validate a physical RC system that substitutes the effect of randomness for a nonlinear transformation of input data. Carrying out all operations using a microcontroller with a minimal computational power, we demonstrate that the so-designed RC system serves as a technically simple hardware counterpart to the `next-generation’ improvement of the traditional RC algorithm.

Titanium dioxide nanoparticles have risen concerns about their possible toxicity and the European Food Safety Authority recently banned the use of TiO2 nano-additive in food products. Following the intent of relating nanomaterials atomic structure with their toxicity without having to conduct large scale experiments on living organisms, we investigate the aggregation of titanium dioxide nanoparticles using a multi-scale technique: starting from ab initio Density Functional Theory to get an accurate determination of the energetics and electronic structure, we switch to classical Molecular Dynamics simulations to calculate the Potential of Mean Force for the connection of two identical nanoparticles in water; the fitting of the latter by a set of mathematical equations is the key for the upscale. Lastly, we perform Brownian Dynamics simulations where each nanoparticle is a spherical bead. This coarsening strategy allows studying the aggregation of a few thousand nanoparticles. Applying this novel procedure, we find three new molecular descriptors, namely, the aggregation free energy and two numerical parameters used to correct the observed deviation from the aggregation kinetic described by the Smoluchowski theory. Molecular descriptors can be fed into QSAR models to predict the toxicity of a material knowing its physicochemical properties, without having to conduct large scale experiments on living organisms.

Cathepsin D (CatD; EC 3.4.23.5) family peptidases of parasitic organisms are regarded as potential drug targets as they play critical roles in the physiology and pathobiology of parasites. Previously, we characterized the biochemical features of cathepsin D isozyme 2 (CatD2) in the carcinogenic liver fluke Clonorchis sinensis (CsCatD2). In this study, we performed all-atomic molecular dynamics simulations by applying different systems for the ligand-free/bound forms under neutral and acidic conditions to investigate the pH-dependent structural alterations and associated functional changes in CsCatD2. CsCatD2 showed several distinctive characteristics as follows: 1) CsCatD2-inhibitor complex formed more hydrogen bonds; 2) acidic pH caused major conformational transitions from open to closed state in this enzyme; 3) neutral pH induced displacement of the N-terminal part to hinder the accessibility of the active site and open allosteric site of this enzyme; and 4) the flap dynamics metrics, including distance (d1), TriCα angles (θ1 and θ2), and dihedral angle (ϕ), account for the asymmetrical twisting motion of the active site of this enzyme. These findings provide an in-depth understanding of the pH-dependent structural dynamics of CsCatD2 and basic information for the rational design of an inhibitor as a drug targeting CsCatD2.

The computing power of smartphones has not received considerable attention in the mainstream education system. Most of the education-oriented smartphone applications (apps) are limited to general purpose services like Massive Open Online Courses (MOOCs), language learning, and calculators (performing basic mathematical calculations). Greater potential of smartphones lies in educators and researchers developing their customized apps for learners in highly specific domains. In line with this, we present Fluid Dynamics, a highly accurate Android application for measuring flow properties in compressible flows. This app can determine properties across the stationary normal and oblique shock, moving normal shock and across Prandtl $-$ Meyer expansion fan. This app can also measure isentropic flows, Fanno flows, and Rayleigh flows. The functionality of this app is also extended to calculate properties in the atmosphere by assuming the International Standard Atmosphere (ISA) relations and also flows across the Pitot tube. Such measurements are complicated and time-consuming since the relations are implicit and hence require the use of numerical methods, which give rise to repetitive calculations. The app is an efficient semi-implicit solver for gas dynamics formulations and uses underlying numerical methods for the computations in a graphical user interface (GUI), thereby easing and quickening the learning of concerned users. The app is designed for the Android operating system, the most ubiquitous and capable surveillance platform, and its calculations are based on JAVA based code methodology. In order to check its accuracy, the app's results are validated against the existing data given in the literature.

Here, we present a general framework for computing the infrared anharmonic vibrational spectra of polyatomic molecules using the Born-Oppenheimer molecular dynamics (BOMD) with the software PyRAMD. To account for the nuclear quantum effects, we suggest using the simplified Wigner sampling (SWS) approach [\textit{Phys. Chem. Chem. Phys.}, 2023, \textbf{25}, 18406-18423] simultaneously coupled with the Andersen and Berendsen thermostats. We propose a new criterion for selecting the parameter of the SWS based on the molecules' harmonic vibrational frequencies and usage of the large-time-step blue shift correction, allowing for a decrease in computational expenses. For the Fourier transform of the dipole moment autocorrelation function, we propose to use the regularized least-squares analysis, which allows us to obtain higher frequency resolution than the direct application of fast Fourier transform. Finally, we suggest the usage of the pre-parameterized scaling factors for the IR spectra from BOMD, also providing the scaling factors for the spectra at the BLYP-D3(BJ)/6-31G, PBE-D3(BJ)/6-31G, and PBEh-3c levels of theory.

This article encapsulates an exploration of seizure dynamics through the lens of computational modeling in epilepsy. Starting with a foundational understanding of the FitzHugh-Nagumo model, asimplified representation of neuronal activity, we try to understand the intricacies of epileptic seizures. We methodically demonstrated the transition from normal neuronal activity to a seizure-like state by altering key parameters in the model, such as external current and coupling strength. This was followed by an extension of the model to a network of neurons, simulating the complex interactions and synchronization patterns indicative of seizure propagation. Numerical simulations were conducted to visualize the impact of varying coupling strengths on network dynamics, offering insights into the mechanisms of seizure initiation and spread. The study was complemented by a discussion on the implications of these findings for understanding epilepsy, highlighting the bridging of theoretical models with clinical understanding. Our approach not only illuminates the potential of computational models in epilepsy research but also underscores the significance of interdisciplinary collaboration in advancing our comprehension of neurological disorders. Through this article, we aim to provide a nuanced perspective on the modeling of epileptic seizures, offering a valuable resource for researchers and clinicians in the field.

This paper considers a nonlinear model for population dynamics with age structure. The fertility rate with respect to age is non constant and has the form proposed by . Moreover, its multiplicative structure and the multiplicative structure of mortality makes the model separable. In this setting it is shown that the number of births in unit time is given by a system of nonlinear ordinary differential equations. The steady state solution together with the equilibrium solution is found explicitly.

In previous papers we have shown how Schrödinger’s equation which includes an electromagnetic field interaction can be deduced from a fluid dynamical Lagrangian of a charged potential flow that interacts with an electromagnetic field. The quantum behaviour was derived from Fisher information terms which were added to the classical Lagrangian. It was thus shown that a quantum mechanical system is driven by information and not only electromagnetic fields. This program was applied also to Pauli’s equations by removing the restriction of potential flow and using the Clebsch formalism. Although the analysis was quite successful there were still terms that did not admit interpretation, some of them can be easily traced to the relativistic Dirac theory. Here we repeat the analysis for a relativistic flow, pointing to a new approach for deriving relativistic quantum mechanics.

A self-consistent charge density-functional tight-binding method combined with molecular dynamics simulations is employed to reveal the effect of polymorph on the thermal decomposition stability of 1,1-Diamino-2,2-Dinitroethylene (FOX-7). Two types of heating, constant temperature heating and temperature-programmed heating, are adopted. Potential evolution indicates that γ-FOX-7 possesses the lowest thermal stability, as it is closer to the decomposition state. Crystal form has an important influence on the thermal decomposition of FOX-7, resulting in different decomposition rates and initial reactions. In general, β- and γ-FOX-7 always decompose more completely than α-FOX-7. This work emphases the importance of polymorph dependent initial decay of an energetic polymorphic compound once heated in a volume constrained condition.

We study the synchronous dynamics of three diffusively coupled erbium-doped fiber lasers (EDLFs) in the unidirectional ring configuration without external pump modulation. The dynamical behavior of the system is analyzed using time series, Fourier spectra, Poincaré sections, bifurcation diagrams, and Lyapunov exponents for different values of the coupling strength. For weak coupling, we observe a well-known route to chaos from a stable equilibrium through a Hopf bifurcation and a series of torus bifurcations as the coupling strength is increased. An interesting result is found for large values of the coupling strength, where the phase locking is close to zero. This allows a significant increase in the peak energy of the EDFLs pulses, i.e., above the coupling strength the lasers switch to a Q-switching mode with large-amplitude short pulses. This result allows us to propose a new method for increasing the laser pulse energy based on the control of the bistability by the rotating wave in the array of three unidirectionally ring-coupled EDFLs as a function of the coupling strength. In our system, we were able to increase the peak laser power by almost 20 times more than a continuous single EDFL.

Global warming is one of the problems of human civilization and decarbonization policy is the main solution to this problem. In this work, we propose an alternative method of using the gravity-assist by the asteroids to increase the orbital distance of the Earth from the Sun. We can manipulate the orbit of asteroids in the asteroid belt by solar sailing and propulsion engines to guide them towards the Mars orbit and a gravitational scattering can put asteroids in a favorable direction to provide an energy loss scattering from the Earth. The result would be increasing the orbital distance of the earth and consequently cooling down the Earth’s temperature. We calculate the increase in the orbital distance of the earth for each scattering and investigate the feasibility of performing this project.

The contamination of areas around solid urban waste dumps is a global challenge for the maintenance of environmental quality in large urban centres in developing countries. This study applied geophysical methods (electrical resistivity) to identify leachate contamina-tion plumes in the subsoil and groundwater, as well as to describe their temporal (2020 and 2021) dynamics in the lithology and groundwater around the Hulene - B waste dump, Maputo, Mozambique. Geophysical methods (electrical resistivity) were applied to identify possible groundwater contamination plumes, their dynamics, mechanisms of their enrichment and dispersion. Eight 400 m electrical resistivity profiles were performed, four profiles in January 2020 and four profiles in May 2021, overlapped, and the data were inverted with RES2D software. The electrical resistivity models indicate an E - W move-ment of large contamination plumes that dilute superficially into the natural surface wa-ter receiving basin and groundwater, creating zones of resistive anomalies. The thickness of the plumes in the subsurface environment was shown to be extensive in summer for profiles 1a and 2b and we associate it with the higher leachate production and migration mechanisms, which are intense in the hot and rainy season. Profile 4b showed the prop-agation of anomalous surface and subsurface areas, which was associated with higher leachate production and migration process in the new deposition zone (west). The spatial distribution of contamination plumes at both stations reduced significantly as we moved further away from the waste deposit, revealing the attenuating effect of groundwater and lithological substrate (Profile 3 a, b, and fig.7).

We research the interaction between six representative carbon-based nanoparticles (CBNs) and 20 standard amino acids through all-atom molecular dynamics simulations. The six carbon-based nanoparticles are fullerene(C60), CNT55L3, CNT1010L3, CNT1515L3, CNT2020L3, and two-dimensional-graphene(Graphene33). Their curvatures decrease sequentially, and all of CNT are single-walled carbon nanotubes. We have observed that as the curvature of CBNs decreases, the adsorption effect of 20 amino acids with them has an increasing trend. In addition, we also used multi-dimensional clustering to analyze the adsorption effects of 20 amino acids on six carbon-based nanoparticles. We observed that the π-π interaction still plays an extremely important role in the adsorption of amino acids on carbon-based nanoparticles. Individual long-chain amino acids and “Benzene-like” Pro also have a strong adsorption effect with carbon-based nanoparticles.

The nucleus has been studied for well over 100 years, and chromatin has been the intense focus of experiments for decades. In this review, we focus on an understudied aspect of chromatin biology, namely the chromatin fiber polymer's mechanical properties. In recent years, innovative work deploying interdisciplinary approaches including computational modeling, in vitro manipulations of purified and native chromatin have resulted in deep mechanistic insights into how the mechanics of chromatin might contribute to its function. The picture that emerges is one of a nucleus that is shaped as much by external forces pressing down upon it, as internal forces pushing outwards from the chromatin. These properties may have evolved to afford the cell a dynamic and reversible force-induced communication highway which allows rapid coordination between external cues and internal genomic function.

Li₂MnO₃ is critical component in the well-studied Li-excess cathode materials xLi₂MnO₃•(1- x)LiMO₂ for achieving high lithium storage capacity. In this article, the diffusion of Li ions in Li₂MnO₃ is studied using molecular dynamics (MD) simulation with well-behaved empirical force fields obtained by fitting against the crystal structure from experiment and phonons calculated using Density Function Theory (DFT). We have found two possible tetrahedral hopping channels, 0-TM and 1-TM(Mn⁴⁺) channel, which are differentiated by the face sharing octahedral cations. Simulation results show that the 0-TM channel is active for Li hopping, while 1-TM(Mn4+) channel is inactive. During the delithiation process, the Li ions in the TM layered are firstly removed, then those in the Li layer. However, the Li ions will be trapped in the tetrahedral 0-TM channels as long as the four face sharing octahedral sites are cleared. Up to x=1.0 for Li₂-xMnO₃, almost all the Li ions are located at the tetrahedral sites, forming a regular array along a axis. The de-intercalation of tetrahedral Li ions requires a high voltage (>5.2 V vs. Li/Li+), limiting the practical capacities measured in lab. The diffusion of Mn ions into the Li layers is observed in a deeper delithiated structure (x=1.2 for Li₂-xMnO₃), indicating an initial phase transformation to a spinel-like structure. However, the Mn ions are mainly trapped in the tetrahedral sites in the Li layer, instead of the octahedral sites fin spinel-like structure. A few of Mn ions diffusing into the octahedral sites in Li layers have no face sharing tetrahedral Li ions, revealing a further Li de-intercalation is imperative for the complete phase transformation. Our model is not stable for x≥1.4 in Li₂-xMnO₃. Other charge compensation mechanism should be considered in this high delithiation stage, eg. oxygen release.

Measurements of optical properties have been used for decades to study particle distributions in the ocean. They have been found useful to constrain suspended mass concentration as well as particle-related properties such as size, composition, packing (particle porosity or density) and settling velocity. Optical properties, however, provide measurements that are biased, as certain particles (based on size, composition, shape or packing) contribute to a specific property more than others. Here we study this issue both theoretically as well as by contrasting different optical properties collected simultaneously in a bottom boundary layer, to highlight the utility of such measurements as well as the biases we are likely to encounter using different optical properties to study suspended particles. In particular, we investigate the possibility to infer settling velocity from vertical profiles of optical measurements, finding that the effects of aggregation dynamics can seldom be ignored.

Quantum Computation, in the gate array version, uses logical gates adopting convenient forms for computational algorithms based on those of classical computation. There, two-level quantum systems are the basic elements connecting the binary nature of classical computation with the settlement of quantum processing. Despite, their design depends on specific quantum systems and physical interactions involved, exacerbating the dynamics analysis. Predictable and controllable manipulation should be addressed to control the quantum states, but resources are restricted to limitations imposed by the physical settlement. This work presents a formalism to decompose the quantum information dynamics in SU(2^2d) for 2d-partite two-level systems into 2^2d-1 SU(2) quantum subsystems. Decomposition lets to set control procedures, to generate large entangled states and to design specialized dedicated quantum gates. There, easy and traditional operations proposed by quantum computation are recovered for more complex and large systems. Alternating the parameters of local and non-local interactions, the procedure states a universal exchange semantics on the generalized Bell states basis. It could be understood as a momentary splitting of the 2d information channels into 2^2d-1 pairs of 2 level quantum information subsystems and a settlement of the quantum information manipulation free of the imposed restrictions by the underlying physical system.

This article objectively assesses, the hypothesis of the streamline's shape theory and its formulated equation. The deduction of proof uses algebra rather than first-order partial differential equations to address the specific hypothesis of "Streamline's shape theory" from the fundamental perspective of applied mathematics and scientifically derives mathematical relations of the axioms and corollaries in the field of fluid dynamics. The algebraic methods employed provide progressively more distinct and precise solutions compared to first-order partial differential equations. The foremost objective of this work is to evaluate if the formulations of the streamline's shape theory can have solutions for inviscid-incompressible and viscid-compressible flows of Newtonian fluids and to identify their nature. Secondly, to understand how the topology of the body and the free-stream conditions affect these solutions with due regards to the shape and size of the body interacting with the fluid flow. Finally, to explore the possibility of this theory to develop a CFD solver for streamline simulation to reduce the experimentation in the analysis of flow-structure interactions of Newtonian fluids and also to identify its scope of applications and limitations.

Polarization in online social networks has gathered a significant amount of attention in the research community and in the public sphere due to stark disagreements with millions of participants in topics surrounding politics, climate, the economy and other areas where an agreement is required. There are multiple approaches to investigating the scenarios in which polarization occurs and given that polarization is not a new phenomenon but that its virality may be supported by the low cost and latency messaging offered by online social media platforms; an investigation into the intrinsic dynamics of online opinion evolution is presented for complete networks. Extending a model which utilizes the Binary Voter Model (BVM) to examine the effect of the degree of freedom for selecting contacts based upon homophily, simulations show that different opinions are reinforced for a period of time when users have a greater range of choice for association. The facility of discussion threads and groups formed upon common views further delays the rate in which a consensus can form between all members of the network. This can temporarily incubate members from interacting with those who can present an alternative opinion where a voter model would then proceed to produce a homogeneous opinion based upon pairwise interactions.

Modelling errors, robust stabilization/tracking problems under parameter and model uncertainties complicate the control of the flexible underactuated systems. Chattering-free sliding-mode based input-output control law realizes robustness against the structured and unstructured uncertainties in the system dynamics and avoids excitation of unmodeled dynamics. The main purpose is to propose a robust adaptive solution for stabilizing and tracking direct-drive (DD) flexible robot arms under parameter and model uncertainties, as well as external disturbances. A lightweight robot arm subject to external and internal dynamic effects was taken into consideration. The challenges are compensating actuator dynamics with the inverter switching effects and torque ripples, stabilizing the zero dynamics under parameter/model uncertainties and disturbances while precisely track the predefined reference position. The precise control of this kind of system demands an accurate system model and knowledge of all sources that excite unmodeled dynamics. For this purpose, equations of motion for a flexible robot arm were derived and formulated for the large motion via Lagrange’s method. The goals were determined to achieve high-speed, precise position control, and satisfied accuracy by compensating the unwanted torque ripple and friction that degrades performance through an adaptive robust control approach. The actuator dynamics and their effect on the torque output were investigated due to the transmitted torque to the load side. The high-performance goals, precision&robustness issues, and stability concerns were satisfied by using robust-adaptive input-output linearization-based control law combining chattering-free sliding mode control (SMC) while avoiding the excitation of unmodeled dynamics.

Our earlier work has tentatively shown that the hierarchy of fermion masses and mixing angles follows from the universal behavior of nonlinear dynamics. In this brief sequel we survey a similar scenario in which the Cabibbo angle arises from the nonlinear dynamics of charged-current interactions.

Single nucleotide polymorphisms (SNP) are associated with diseases and drug response variabilities in humans. Elucidating the damaging and disease-associated SNPs using wet-laboratory approaches can be challenging and resource-demanding due to the large number of SNPs in the human genome. Due to the growth in the field of computational biology and bioinformatics, algorithms have been developed to help screen and filter out the most deleterious SNPs that are worth considering for wet-laboratory studies. Here we review the existing in-silico based methods used to predict and characterize the effects of SNPs on protein structure and function. This cutting-edge approach will facilitate the search for novel therapeutics, help understand the etiology of diseases and fast-track the personalized medicine agenda.

In many European countries over the last decades, arable fields dominate agriculture landscapes, leading to a very intensive land-use practices. This reason seems to be the main cause of popula-tions declines for numerous farmland species, including the European hare (Lepus europaeus Pallas, 1778). The Research institute for Animal Production (National Agricultural and Food Centre, Luzianky, Slovakia) has been engaged in a long monitoring project (project currently run-ning), collecting certain indicators of hare population dynamics during hunting season since 1987 to 2023 in the Slovak Danubian Lowland. In the same macro-area (Čiližská Radvaň and Lehnice) a study was conducted on the influence of permanent semi-natural vegetation in relation to re-cruitment, population density and production. The whole monitored period was aggregated into 5-years intervals (for a total of 7 time-intervals), with the aim of analyzing the brown hare popu-lation dynamics. Spring hare density in the Danubian Lowland is currently 20.8 hares/km2, with harvests of 4.6 hares/km2. During all the monitoring period, bag’s animals have been examined following the regular hunting operations for the purpose of age determination (weight of eye lenses), sex ratio and productivity. The results of our analysis showed that the proportion of juve-nile in bag (PYB) among those shot varied from 37.0 % of the last 5-years interval (2018-2023), to a maximum of 51.0 % in interval of years 1998-2002. On total average there were 1.86 juveniles per adult female (r). The proportion of adult females in gamebag varied from 22.58 % (years in-terval 1992-1997) to 31.26 % (years interval 2018-2023). Sex-ratio (SI; males : females) among shot hares showed a value of 0.50, ranged from 0.48 in the period 2008-2012 to 0.52 in the first observed period (years 1987-1991) and in the last one (years 2018-2023). Average weight of shot hares was 4.04 kg (juveniles 3.83 kg, adults 4.27 kg, adult males 4.21 kg and females 4.32 kg). There was a large positive effect of set-aside with special mixtures, created for hares in large-scale farmed agrarian landscape, on hare density, bag and recruitment. In model hunting grounds with such set-asides increased the spring stock by 25 %, bag by 100 % and recruitment by 20 %. This study reveals that the management of European brown hare is not sustainable, and the population is decreasing. It is proved through the decline of harvest hares and by population dynamics parameters. Environmental improvements lead to the stabilization and increasing of requested parameters.

This study examines the relationship between Bitcoin market dynamics and user activity on the r/cryptocurrency subreddit. The purpose of this research is to understand how social media activity correlates with Bitcoin price and trading volume, and to explore the sentiment and topical focus of Reddit discussions. We collected data on Bitcoin’s closing price and trading volume from January 2021 to December 2022, alongside the most popular posts and comments from the subreddit during the same period. Our analysis revealed significant correlations between Bitcoin market metrics and Reddit activity, with user discussions often reacting to market changes. Additionally, user activity on Reddit may indirectly influence the market through broader social and economic factors. Sentiment analysis showed that positive comments were more prevalent during price surges, while negative comments increased during downturns. Topic modeling identified four main discussion themes, which varied over time, particularly during market dips. These findings suggest that social media activity on Reddit can provide valuable insights into market trends and investor sentiment. Overall, our study highlights the influential role of online communities in shaping cryptocurrency market dynamics, offering potential tools for market prediction and regulation.

In this work, the structural dynamics of a commercial quadrotor was investigated, which presents problems of lateral stability or sliding instead of remaining self-leveling through its autonomous control system. The possible existence of vibrations motivated the characterization of the frequency response of the arms and propellers by means of the frequency response function (FRF) using the impact hammer technique. The experimental results provided sufficient information for the future implementation of structural solutions or through reprogramming in the autonomous control algorithm that compensates or mitigates the negative effect of vibration levels due to resonance phenomenon and improves the stability in self-leveling condition of the quadrotor.

The landscape of business intelligence (BI) is marked by rapid growth, extensive research, and practical implementations, reflecting its sustained relevance in modern business strategies. This paper delves into the dynamics of BI, particularly focusing on the interplay between maturity and agility. While BI maturity emphasizes optimization and predefined goals, BI agility prioritizes adaptability and response to change. The paper highlights the contradictions between these concepts, emphasizing the need for a balanced approach in BI strategy formulation.The role of organizational culture in fostering BI agility is explored through literature review and interviews with BI professionals. Key insights include the necessity of an open culture for effective BI utilization, clear strategic vision, decision delegation, information sharing, business-IT cooperation, and a learning-oriented mindset. These cultural factors contribute significantly to BI effectiveness and the ability to navigate dynamic business landscapes. The paper proposes pillars of agile maturity supported by an open organizational culture, including efficient communication, information integration, creative problem-solving, and close collaboration between business and IT. These pillars underscore the importance of a flexible and open mindset in navigating BI challenges and ensuring sustained value. Empirical validation and further research are suggested to deepen our understanding of the impact of organizational culture on BI agility and effectiveness.

We present contrast information, a novel application of some specific cases of relative entropy measures, designed to be useful for cognitive modelling of sequential perception of continuous signals. We explain the relevance of entropy in cognitive modelling of music and language. Then, as a first step to demonstrating the utility of constrast information for that purpose, we show empirically that its discrete case correlates well with existing successful cognitive models in the literature. We explain some interesting properties of constrast information. Finally we propose future work towards a cognitive architecture that uses it.

Auxins are chemical compounds of wide interest, mostly due to their role in plant metabolism and development. Since the latter half of the XX century, synthetic auxins have been used as herbicides, presenting notable advantages, such as low toxicity in humans. As of today, extensive descriptions of syntetic and natural auxins have been made; yet studies centered on the molecular recognition process of auxins are scarce. Herein, we present a comprehensive in silico characterization of auxin receptor TIR1, using structure based methods to aid de novo design of putative ligands. In addition, we conducted binding site characterization using cosolvent molecular dynamics and enhanced sampling simulations with reference ligands. We also present a database of putative auxins and decoy compounds which can aid further studies focusing on synthetic auxin design. To the best of our knowledge, this study is the first of its kind focusing on TIR1.

Computational modeling (CM) is a versatile scientific methodology used to examine the properties and behavior of complex systems, such as polymeric materials for biomedical bioengineering. CM has emerged as a primary tool for predicting, setting up, and interpreting experimental results. Integrating in silico and in vitro experiments accelerates scientific advancements, yielding quicker results at a reduced cost. While CM is a mature discipline, its recent prominence in Bio-medical Engineering for biopolymer materials has recently gained prominence. In biopolymer biomedical engineering, CM focuses on three key research areas: A) Computer-aided design (CAD/CAM), B) Finite Element Analysis, and C) Molecular Dynamic Simulations. This review centers on Molecular Dynamics (MD) simulations in biopolymers, analyzing structural, functional, and evolutionary aspects of biomolecular systems over time. MD simulations solve Newton's equations of motion for all-atom systems, generating spatial trajectories for each atom, providing insights into properties like water absorption on biopolymer surfaces and interactions with solid surfaces, crucial for biomaterial assessment. This review offers readers a comprehensive overview of the diverse applications of Molecular Dynamics (MD) simulations on biopolymers. Furthermore, it emphasizes the flexibility, robustness, and synergistic relationship between in silico and experimental techniques.

The innate immune system is the first line of defense against pathogens. It’s composition includes barriers, mucus and other substances as well as phagocytic and other cells. The purpose of the paper is to analyze in general grounds the immune system and the body immunity to cancer. Simple ideas and the qualitative theory of differential equations are used along with general principles such as the minimization of the pathogen load and economy of resources. In the simplest linear model, the annihilation rate of pathogens in any tissue should be greater than the pathogen’s average rate of growth. When nonlinearities are added, a reference value for the number of pathogens is set, and a stability condition emerges, which relates strength of regular threats, barrier height and annihilation rate. On the other hand, in cancer immunity, the linear model leads to an expression for the lifetime risk, which accounts for both the effects of carcinogens (endogenous or external) and the immune response. The stability condition allows a comparison of immunity in different tissues. The way the tissue responds to an infection shows a correlation with the way it responds to cancer. These statements are formulated at the qualitative level, but may and deserve to be quantitatively checked.

This review presents an updated overview of research concerning Leishmania protein structures, primarily sourced from the Protein Data Bank (PDB), that play a role in the metabolic pathways of the Leishmania parasite. Furthermore, we assess the current progress in the identification and development of bioactive chemical agents aimed at addressing this substantially overlooked tropical disease. We have analyzed experimental data obtained from in vitro, in vivo and in silico sources. This data has been categorized into four main areas: a) vector taxonomy and geographic distribution; b) parasite taxonomy and geographic distribution; c) enzymatic functions of proteins engaged in parasite/host interactions throughout various developmental stages (such as oxidoreductases, transferases, hydrolases, lyases, isomerases, ligases, and cytokines); and d) established and experimental treatments employing bioactive chemical compounds. Our objective is to establish a foundational point of reference for research efforts concentrating on the elucidation of interaction mechanisms and the processes of ligand-protein activation/inactivation, specifically linked to Leishmania infections. Consequently, we emphasize enzymes recognized for their involvement in the biochemical pathways incited during Leishmania infection episodes. This review encapsulates the current understanding, offering insights to inform and direct future explorations aimed at targeting proteins and pathways to enhance the management of Leishmania-related diseases.